EPS Estimate Profile [SS]This is the EPS Estimate Profile indicator.
What it does
This indicator
Collects all EPS estimates over the course of a lookback and BINS them (sorts them into 10 equal sized categories).
Analyzes the returns from earnings releases based on the EPS estimate and the reaction.
Calculates the number of bullish vs bearish responses that transpired based on the EPS estimate profile.
Calculates the expected Open to High and Open to Low ATR based on the EPS estimate using regression.
Toggle to actual EPS release to compare once earnings results are released.
How to Use it
This indicator can be used to gain insight into whether an earnings release will be received bullishly or bearishly based on the company's EPS estimate.
The indicator allows you to see all historic estimates and how the market generally responded to those estimates, as well as a breakdown of how many times estimates in those ranges produced a bullish response or a bearish response to earnings.
Examples
Let's look at some examples:
Here is MSFT. MSFT's last EPS estimate was 3.672.
If we consult the table, we can see the average return associated with this estimate range is -4%.
Now let's flip to the Daily timeframe and take a look:
MSFT ended the day red and continued to sell into the coming days.
Let's look at another example:
MCDs. Last earnings estimate was 3.327, putting it at the top of the range with an average positive return of 4%.
Let's look on the daily:
We can see that the earnings had a huge, bullish effect on MCD, despite them coming in below their estimates.
If we toggle the indicator to "Actual" EPS release, to see the profile of Actual earnings releases vs response, we get this:
Since MCD under-performed, they were still at the top of the profile; but, we can see that the expected returns are more muted now, though still positive. And indeed, the reaction was still positive.
Distinguishing % Bullish/Bearish to Avg Returns
You will see the profile table displays both the average returns and the percent of bullish/bearish responses. In some cases, you will see that, despite a negative return, the profile reveals more bullish reactions than bearish.
What does this mean?
It means, despite there being more bullish responses, when bearish responses happen they tend to be more severe and profound, vs bullish responses likely are muted.
This can alert you to potential downside risk and help you manage risk accordingly should you elect to trade the earnings release.
ATR Prediction
You will notice in the bottom right corner of the screen a secondary table that lists the predicted open to high ATR and open to low ATR.
This is done using RAW EPS estimates (or raw ACTUAL estimates depending on which you select) and performing a regression to determine the expected ATR.
This is only for reference, the analysis should focus around the historic profile of return estimates and actual return values.
IMPORTANT NOTE: You MUST be on the Monthly timeframe to use this. Otherwise, you will get an error. If, on certain tickers with a huge history, such as MSFT and XOM or OXY, you get an error, you can simply reduce the lookback length to 80 and this will resolve the issue.
Conclusion
And that's the indicator!
A blend of some light math and fundamentals! A real joy honestly.
Hope you enjoy it!
Search in scripts for "bear"
Range Trading StrategyOVERVIEW
The Range Trading Strategy is a systematic trading approach that identifies price ranges
from higher timeframe candles or trading sessions, tracks pivot points, and generates
trading signals when range extremes are mitigated and confirmed by pivot levels.
CORE CONCEPT
The strategy is based on the principle that when a candle (or session) closes within the
range of the previous candle (or session), that previous candle becomes a "range" with
identifiable high and low extremes. When price breaks through these extremes, it creates
trading opportunities that are confirmed by pivot levels.
RANGE DETECTION MODES
1. HTF (Higher Timeframe) Mode:
Automatically selects a higher timeframe based on the current chart timeframe
Uses request.security() to fetch HTF candle data
Range is created when an HTF candle closes within the previous HTF candle's range
The previous HTF candle's high and low become the range extremes
2. Sessions Mode:
- Divides the trading day into 4 sessions (UTC):
* Session 1: 00:00 - 06:00 (6 hours)
* Session 2: 06:00 - 12:00 (6 hours)
* Session 3: 12:00 - 20:00 (8 hours)
* Session 4: 20:00 - 00:00 (4 hours, spans midnight)
- Tracks high, low, and close for each session
- Range is created when a session closes within the previous session's range
- The previous session's high and low become the range extremes
PIVOT DETECTION
Pivots are detected based on candle color changes (bullish/bearish transitions):
1. Pivot Low:
Created when a bullish candle appears after a bearish candle
Pivot low = minimum of the current candle's low and previous candle's low
The pivot bar is the actual bar where the low was formed (current or previous bar)
2. Pivot High:
Created when a bearish candle appears after a bullish candle
Pivot high = maximum of the current candle's high and previous candle's high
The pivot bar is the actual bar where the high was formed (current or previous bar)
IMPORTANT: There is always only ONE active pivot high and ONE active pivot low at any
given time. When a new pivot is created, it replaces the previous one.
RANGE CREATION
A range is created when:
(HTF Mode) An HTF candle closes within the previous HTF candle's range AND a new HTF
candle has just started
(Sessions Mode) A session closes within the previous session's range AND a new session
has just started
Or Range Can Be Created when the Extreme of Another Range Gets Mitigated and We Have a Pivot low Just Above the Range Low or Pivot High just Below the Range High
Range Properties:
rangeHigh: The high extreme of the range
rangeLow: The low extreme of the range
highStartTime: The timestamp when the range high was actually formed (found by looping
backwards through bars)
lowStartTime: The timestamp when the range low was actually formed (found by looping
backwards through bars)
highMitigated / lowMitigated: Flags tracking whether each extreme has been broken
isSpecial: Flag indicating if this is a "special range" (see Special Ranges section)
RANGE MITIGATION
A range extreme is considered "mitigated" when price interacts with it:
High is mitigated when: high >= rangeHigh (any interaction at or above the level)
Low is mitigated when: low <= rangeLow (any interaction at or below the level)
Mitigation can happen:
At the moment of range creation (if price is already beyond the extreme)
At any point after range creation when price touches the extreme
SIGNAL GENERATION
1. Pending Signals:
When a range extreme is mitigated, a pending signal is created:
a) BEARISH Pending Signal:
- Triggered when: rangeHigh is mitigated
- Confirmation Level: Current pivotLow
- Signal is confirmed when: close < pivotLow
- Stop Loss: Current pivotHigh (at time of confirmation)
- Entry: Short position
Signal Confirmation
b) BULLISH Pending Signal:
- Triggered when: rangeLow is mitigated
- Confirmation Level: Current pivotHigh
- Signal is confirmed when: close > pivotHigh
- Stop Loss: Current pivotLow (at time of confirmation)
- Entry: Long position
IMPORTANT: There is only ever ONE pending bearish signal and ONE pending bullish signal
at any given time. When a new pending signal is created, it replaces the previous one
of the same type.
2. Signal Confirmation:
- Bearish: Confirmed when price closes below the pivot low (confirmation level)
- Bullish: Confirmed when price closes above the pivot high (confirmation level)
- Upon confirmation, a trade is entered immediately
- The confirmation line is drawn from the pivot bar to the confirmation bar
TRADE EXECUTION
When a signal is confirmed:
1. Position Management:
- Any existing position in the opposite direction is closed first
- Then the new position is entered
2. Stop Loss:
- Bearish (Short): Stop at pivotHigh
- Bullish (Long): Stop at pivotLow
3. Take Profit:
- Calculated using Risk:Reward Ratio (default 2:1)
- Risk = Distance from entry to stop loss
- Target = Entry ± (Risk × R:R Ratio)
- Can be disabled with "Stop Loss Only" toggle
4. Trade Comments:
- "Range Bear" for short trades
- "Range Bull" for long trades
SPECIAL RANGES
Special ranges are created when:
- A range high is mitigated AND the current pivotHigh is below the range high
- A range low is mitigated AND the current pivotLow is above the range low
In these cases:
- The pivot value is stored in an array (storedPivotHighs or storedPivotLows)
- A "special range" is created with only ONE extreme:
* If pivotHigh < rangeHigh: Creates a range with rangeHigh = pivotLow, rangeLow = na
* If pivotLow > rangeLow: Creates a range with rangeLow = pivotHigh, rangeHigh = na
- Special ranges can generate signals just like normal ranges
- If a special range is mitigated on the creation bar or the next bar, it is removed
entirely without generating signals (prevents false signals)
Special Ranges
REVERSE ON STOP LOSS
When enabled, if a stop loss is hit, the strategy automatically opens a trade in the
opposite direction:
1. Long Stop Loss Hit:
- Detects when: position_size > 0 AND position_size <= 0 AND low <= longStopLoss
- Action: Opens a SHORT position
- Stop Loss: Current pivotHigh
- Trade Comment: "Reverse on Stop"
2. Short Stop Loss Hit:
- Detects when: position_size < 0 AND position_size >= 0 AND high >= shortStopLoss
- Action: Opens a LONG position
- Stop Loss: Current pivotLow
- Trade Comment: "Reverse on Stop"
The reverse trade uses the same R:R ratio and respects the "Stop Loss Only" setting.
VISUAL ELEMENTS
1. Range Lines:
- Drawn from the time when the extreme was formed to the mitigation point (or current
time if not mitigated)
- High lines: Blue (or mitigated color if mitigated)
- Low lines: Red (or mitigated color if mitigated)
- Style: SOLID
- Width: 1
2. Confirmation Lines:
- Drawn when a signal is confirmed
- Extends from the pivot bar to the confirmation bar
- Bearish: Red, solid line
- Bullish: Green, solid line
- Width: 1
- Can be toggled on/off
STRATEGY SETTINGS
1. Range Detection Mode:
- HTF: Uses higher timeframe candles
- Sessions: Uses trading session boundaries
2. Auto HTF:
- Automatically selects HTF based on current chart timeframe
- Can be disabled to use manual HTF selection
3. Risk:Reward Ratio:
- Default: 2.0 (2:1)
- Minimum: 0.5
- Step: 0.5
4. Stop Loss Only:
- When enabled: Trades only have stop loss (no take profit)
- Trades close on stop loss or when opposite signal confirms
5. Reverse on Stop Loss:
- When enabled: Hitting a stop loss opens opposite trade with stop at opposing pivot
6. Max Ranges to Display:
- Limits the number of ranges kept in memory
- Oldest ranges are purged when limit is exceeded
KEY FEATURES
1. Dynamic Pivot Tracking:
- Pivots update on every candle color change
- Always maintains one high and one low pivot
2. Range Lifecycle:
- Ranges are created when price closes within previous range
- Ranges are tracked until mitigated
- Mitigation creates pending signals
- Signals are confirmed by pivot levels
3. Signal Priority:
- Only one pending signal of each type at a time
- New signals replace old ones
- Confirmation happens on close of bar
4. Position Management:
- Closes opposite positions before entering new trades
- Tracks stop loss levels for reverse functionality
- Respects pyramiding = 1 (only one position per direction)
5. Time-Based Drawing:
- Uses time coordinates instead of bar indices for line drawing
- Prevents "too far from current bar" errors
- Lines can extend to any historical point
USAGE NOTES
- Best suited for trending and ranging markets
- Works on any timeframe, but HTF mode adapts automatically
- Sessions mode is ideal for intraday trading
- Pivot detection requires clear candle color changes
- Range detection requires price to close within previous range
- Signals are generated on bar close, not intra-bar
The strategy combines range identification, pivot tracking, and signal confirmation to
create a systematic approach to trading breakouts and reversals based on price structure, past performance does not in any way predict future performance
v2.0—Tristan's Multi-Indicator Reversal Strategy🎯 Multi-Indicator Reversal Strategy - Optimized for High Win Rates
A powerful confluence-based strategy that combines RSI, MACD, Williams %R, Bollinger Bands, and Volume analysis to identify high-probability reversal points . Designed to let winners run with no stop loss or take profit - positions close only when opposite signals occur.
Also, the 3 hour timeframe works VERY well—just a lot less trades.
📈 Proven Performance
This strategy has been backtested and optimized on multiple blue-chip stocks with 80-90%+ win rates on 1-hour timeframes from Aug 2025 through Oct 2025:
✅ V (Visa) - Payment processor
✅ MSFT (Microsoft) - Large-cap tech
✅ WMT (Walmart) - Retail leader
✅ IWM (Russell 2000 ETF) - Small-cap index
✅ NOW (ServiceNow) - Enterprise software
✅ WM (Waste Management) - Industrial services
These stocks tend to mean-revert at extremes, making them ideal candidates for this reversal-based approach. I only list these as a way to show you the performance of the script. These values and stock choices may change over time as the market shifts. Keep testing!
🔑 How to Use This Strategy Successfully
Step 1: Apply to Chart
Open your desired stock (V, MSFT, WMT, IWM, NOW, WM recommended)
Set timeframe to 1 Hour
Apply this strategy
Check that the Williams %R is set to -20 and -80, and "Flip All Signals" is OFF (can flip this for some stocks to perform better.)
Step 2: Understand the Signals
🟢 Green Triangle (BUY) Below Candle:
Multiple indicators (RSI, Williams %R, MACD, Bollinger Bands) show oversold conditions
Enter LONG position
Strategy will pyramid up to 10 entries if more buy signals occur
Hold until red triangle appears
🔴 Red Triangle (SELL) Above Candle:
Multiple indicators show overbought conditions
Enter SHORT position (or close existing long)
Strategy will pyramid up to 10 entries if more sell signals occur
Hold until green triangle appears
🟣 Purple Labels (EXIT):
Shows when positions close
Displays count if multiple entries were pyramided (e.g., "Exit Long x5")
Step 3: Let the Strategy Work
Key Success Principles:
✅ Be Patient - Signals don't occur every day, wait for quality setups
✅ Trust the Process - Don't manually close positions, let opposite signals exit
✅ Watch Pyramiding - The strategy can add up to 10 positions in the same direction
✅ No Stop Loss - Positions ride through drawdowns until reversal confirmed
✅ Session Filter - Only trades during NY session (9:30 AM - 4:00 PM ET)
⚙️ Winning Settings (Already Set as Defaults)
INDICATOR SETTINGS:
- RSI Length: 14
- RSI Overbought: 70
- RSI Oversold: 30
- MACD: 12, 26, 9 (standard)
- Williams %R Length: 14
- Williams %R Overbought: -20 ⭐ (check this! And adjust to your liking)
- Williams %R Oversold: -80 ⭐ (check this! And adjust to your liking)
- Bollinger Bands: 20, 2.0
- Volume MA: 20 periods
- Volume Multiplier: 1.5x
SIGNAL REQUIREMENTS:
- Min Indicators Aligned: 2
- Require Divergence: OFF
- Require Volume Spike: OFF
- Require Reversal Candle: OFF
- Flip All Signals: OFF ⭐
RISK MANAGEMENT:
- Use Stop Loss: OFF ⭐⭐⭐
- Use Take Profit: OFF ⭐⭐⭐
- Allow Pyramiding: ON ⭐⭐⭐
- Max Pyramid Entries: 10 ⭐⭐⭐
SESSION FILTER:
- Trade Only NY Session: ON
- NY Session: 9:30 AM - 4:00 PM ET
**⭐ = Critical settings for success**
## 🎓 Strategy Logic Explained
### **How It Works:**
1. **Multi-Indicator Confluence**: Waits for at least 2 out of 4 technical indicators to align before generating signals
2. **Oversold = Buy**: When RSI < 30, Williams %R < -80, price below lower Bollinger Band, and/or MACD turning bullish → BUY signal
3. **Overbought = Sell**: When RSI > 70, Williams %R > -20, price above upper Bollinger Band, and/or MACD turning bearish → SELL signal
4. **Pyramiding Power**: As trend continues and more signals fire in the same direction, adds up to 10 positions to maximize gains
5. **Exit Only on Reversal**: No arbitrary stops or targets - only exits when opposite signal confirms trend change
6. **Session Filter**: Only trades during liquid NY session hours to avoid overnight gaps and low-volume periods
### **Why No Stop Loss Works:**
Traditional reversal strategies fail because they:
- Get stopped out too early during normal volatility
- Miss the actual reversal that happens later
- Cut winners short with tight take profits
This strategy succeeds because it:
- ✅ Rides through temporary noise
- ✅ Captures full reversal moves
- ✅ Uses multiple indicators for confirmation
- ✅ Pyramids into winning positions
- ✅ Only exits when technical picture completely reverses
---
## 📊 Understanding the Display
**Live Indicator Counter (Top Corner / end of current candles):**
Bull: 2/4
Bear: 0/4
(STANDARD)
Shows how many indicators currently align bullish/bearish
"STANDARD" = normal reversal mode (buy oversold, sell overbought)
"FLIPPED" = momentum mode if you toggle that setting
Visual Indicators:
🔵 Blue background = NY session active (trading window)
🟡 Yellow candle tint = Volume spike detected
💎 Aqua diamond = Bullish divergence (price vs RSI)
💎 Fuchsia diamond = Bearish divergence
⚡ Advanced Tips
Optimizing for Different Stocks:
If Win Rate is Low (<50%):
Try toggling "Flip All Signals" to ON (switches to momentum mode)
Increase "Min Indicators Aligned" to 3 or 4
Turn ON "Require Divergence"
Test on different timeframe (4-hour or daily)
If Too Few Signals:
Decrease "Min Indicators Aligned" to 2
Turn OFF all requirement filters
Widen Williams %R bands to -15 and -85
If Too Many False Signals:
Increase "Min Indicators Aligned" to 3 or 4
Turn ON "Require Divergence"
Turn ON "Require Volume Spike"
Reduce Max Pyramid Entries to 5
Stock Selection Guidelines:
Best Suited For:
Large-cap stable stocks (V, MSFT, WMT)
ETFs (IWM, SPY, QQQ)
Stocks with clear support/resistance
Mean-reverting instruments
Avoid:
Ultra low-volume penny stocks
Extremely volatile crypto (try traditional settings first)
Stocks in strong one-directional trends lasting months
🔄 The "Flip All Signals" Feature
If backtesting shows poor results on a particular stock, try toggling "Flip All Signals" to ON:
STANDARD Mode (OFF):
Buy when oversold (reversal strategy)
Sell when overbought
May work best for: V, MSFT, WMT, IWM, NOW, WM
FLIPPED Mode (ON):
Buy when overbought (momentum strategy)
Sell when oversold
May work best for: Strong trending stocks, momentum plays, crypto
Test both modes on your stock to see which performs better!
📱 Alert Setup
Create alerts to notify you of signals:
📊 Performance Expectations
With optimized settings on recommended stocks:
Typical results we are looking for:
Win Rate: 70-90%
Average Winner: 3-5%
Average Loser: 1-3%
Signals Per Week: 1-3 on 1-hour timeframe
Hold Time: Several hours to days
Remember: Past performance doesn't guarantee future results. Always use proper risk management.
Tristan's Multi-Indicator Reversal StrategyMulti-Indicator Reversal Strategy - Buy Low, Sell High
A comprehensive reversal detection system that combines multiple proven technical indicators to identify high-probability entry points for catching reversals at market extremes.
📊 Strategy Overview
This strategy is designed for traders who want to buy at lows and sell at highs by detecting when stocks are overextended and ready to reverse. It works by requiring multiple technical indicators to align before generating a signal, significantly reducing false entries.
Best Used On:
Timeframe: 1-hour charts (also works on 15min, 30min, 4hour)
Session: NY Trading Session (9:30 AM - 4:00 PM ET)
Assets: Stocks, ETFs, Crypto (particularly volatile tech stocks like ZM, TSLA, AAPL)
Trading Style: Swing trading, Intraday reversals
🔧 Technical Components
The strategy combines FIVE powerful technical indicators:
1. RSI (Relative Strength Index)
2. MACD (Moving Average Convergence Divergence)
3. Williams %R
4. Bollinger Bands
5. Volume Analysis
6. Divergence Detection (Optional)
🎨 Visual Signals
Entry Signals:
🟢 Green Triangle (below candle) = BUY LONG signal
🔴 Red Triangle (above candle) = SELL SHORT signal
Exit Signals:
🟣 Purple Label = Position closed (shows "x2", "x3" if multiple entries)
Additional Indicators:
💎 Aqua Diamond = Bullish divergence detected
💎 Fuchsia Diamond = Bearish divergence detected
🔵 Blue Background = NY Session active
🟡 Yellow Bar Tint = Volume spike detected
⚪ Small Circles = Near-signal conditions (2+ indicators aligned)
Live Counter:
Top corner shows: "Bull: X/4" and "Bear: X/4"
Indicates how many indicators currently align
⚙️ How to Use This Strategy
For Beginners (More Signals):
Set "Min Indicators Aligned" to 2
Turn OFF "Require Divergence"
Turn OFF "Require Volume Spike"
Turn OFF "Require Reversal Candle Pattern"
Keep "Allow Multiple Entries" OFF
This gives you more frequent signals to learn from.
For Advanced Traders (High Probability):
Set "Min Indicators Aligned" to 3 or 4
Turn ON "Require Divergence"
Turn ON "Require Volume Spike"
Turn ON "Require Reversal Candle Pattern"
Adjust stop loss to your risk tolerance
This filters for only the highest-quality setups.
Recommended Settings for 1-Hour Charts:
Min Indicators Aligned: 3
Stop Loss: 2.5%
Take Profit: 5.0%
RSI Length: 14
Williams %R Length: 14
Volume Multiplier: 1.5x
Session: NY only (for stocks)
BUY SIGNAL generated when:
2-4 indicators show oversold/bullish conditions:
RSI < 30 and turning up
MACD crossing bullish or histogram positive
Williams %R < -80 and turning up
Price at/below lower Bollinger Band
Optional confirmations (if enabled):
Bullish divergence detected
Volume spike present
Bullish reversal candle pattern
Session filter: Signals only during NY trading hours
SELL SIGNAL Generated When:
2-4 indicators show overbought/bearish conditions:
RSI > 70 and turning down
MACD crossing bearish or histogram negative
Williams %R > -20 and turning down
Price at/above upper Bollinger Band
Optional confirmations (if enabled):
Bearish divergence detected
Volume spike present
Bearish reversal candle pattern
🛡️ Risk Management Features
Automatic Stop Loss: Protects capital (default 2.5%)
Take Profit Target: Locks in gains (default 5.0%)
Pyramiding Control: Toggle to prevent position stacking
Session Filter: Avoids overnight risk and low-liquidity periods
Position Flipping: Automatically reverses when opposite signal appears
💡 Best Practices
✅ DO:
Wait for candle close before entering (built into strategy)
Use on volatile assets with clear trends
Combine with your own analysis and risk management
Backtest on your specific assets and timeframes
Start with paper trading to learn the signals
Adjust indicator requirements based on market conditions
❌ DON'T:
Use on very low timeframes (<5 min) without adjustment
Ignore the session filter on stocks
Use maximum leverage - these are reversal trades
Trade during major news events or earnings
Expect 100% win rate - focus on risk/reward ratio
📊 Performance Notes
This strategy prioritizes quality over quantity. With default settings, you may see:
2-5 signals per week on 1-hour charts
Higher win rate with stricter settings (3-4 indicators aligned)
Best performance during trending markets with clear reversals
Reduced performance in choppy, sideways markets
Tip: Adjust "Min Indicators Aligned" based on market conditions:
Trending markets: Use 3-4 (fewer but stronger signals)
Range-bound markets: Use 2 (more signals, but watch for false breakouts)
GTI BGTI: RSI Suite (Standard • Stochastic • Smoothed)
A three-layer momentum and trend toolkit that combines Standard RSI, Stochastic RSI, and a Smoothed/“Macro” RSI to help you read intraday swings, trend transitions, and high-probability reversal/continuation spots.
All in one pane with intuitive coloring and optional divergence markers and alerts.
Why this works
* Stochastic RSI (K/D) visualizes fast momentum swings and timing.
* Standard RSI moves more gradually, helping confirm trend transitions that may span several Stochastic cycles.
* Smoothed RSI (Average → Macro) adds a second-pass filter and slope persistence to reveal the macro direction while suppressing noise.
Used together, Stochastic guides entries/exits around local highs/lows, while the RSI layers improve confidence when a small swing is likely part of a larger turn.
What you’ll see
* Standard RSI (yellow; pink above Bull line, aqua below Bear line).
* Stochastic RSI (K/D) with contextual colors:
* Greens when RSI is weak/oversold (bearish conditions → watch for bullish reversals/continuations).
* Reds when RSI is strong/overbought (bullish conditions → watch for bearish reversals/continuations).
* Smoothed (Macro) RSI with trend color:
* Red when macro is ascending (bullish),
* Aqua when macro is descending (bearish).
* Divergences (optional markers):
* Bearish: RSI Lower High + Price Higher High (red ⬇).
* Bullish: RSI Higher Low + Price Lower Low (green ⬆).
* No repaint: pivots confirm after the chosen right-bars window.
How to use it
* Bullish Reversal
* Macro RSI is reversing at a higher low after price has been in a overall downtrend
* Stochastic RSI is switching from green to red in an overall downtrend
* Bullish Oversold
* Macro RSI is reversing from a significantly low level after price has a short but strong dip during an overall uptrend
* Stochastic RSI is switching from green to red in an overall uptrend
* Bullish Continuation
* Macro RSI is ascending with a strong slope or forming a higher low above the 50 line
* Stochastic RSI is reaching a bottom but still painted red
* Bearish Reversal
* Macro RSI is reversing at a lower high after price has been in a overall uptrend
* Stochastic RSI is switching from red to green in an overall uptrend
* Bearish Overbought
* Macro RSI is reversing from a significantly high level after price has a short but strong jump during an overall downtrend
* Stochastic RSI is switching from red to green in an overall downtrend
* Bearish Continuation
* Macro RSI is descending with a strong slope or forming a lower high below the 50 line
* Stochastic RSI is reaching a top but still painted green
* Divergences: Use as signals of exhaustion—best when aligned with Macro RSI color/slope and key levels (e.g., Bull/Bear lines, 50 midline).
*** IMPORTANT ***
* Stack confluence, don’t single-signal trade. Look for:
* 1) Macro RSI color & slope (red = ascending/bullish, aqua = descending/bearish)
* 2) Standard RSI location (above/below Bull/Bear lines or 50)
* 3) Stoch flip + direction
* 4) Price structure (HH/HL vs LH/LL)
* 5) Divergence type (regular vs hidden) at meaningful levels
* Trade with the macro
* Prioritize longs when Macro RSI is red or just flipped up
* Prioritize shorts when Macro RSI is aqua or just flipped down
* Counter-trend setups = smaller size and faster management.
* Location > signal
* The same crossover/divergence is higher quality near Bull (~60)/Bear(~40) or extremes than in the mid-range chop around 50.
* Early vs confirmed
* Use the early pivot heads-up for anticipation, but scale in only after the confirmed pivot (right-bars complete). If early signal fails to confirm, stand down.
* Define invalidation upfront
* For divergence entries, place stops beyond the pivot extreme (LL/HH). If Macro RSI flips against your trade or RSI breaks back through 50 with slope, exit or tighten.
* Multi-timeframe alignment
* Best results come when entry timeframe (e.g., 1H) aligns with higher-TF macro (e.g., 4H/D). If they disagree, treat it as mean-reversion only.
* Avoid common traps
* Skip: isolated Stochastic flips without RSI support, divergences without price HH/LL confirmation, and serial divergences when Macro RSI slope is strong against the idea.
* Parameter guidance
* Start with defaults; then tune: confirmBars 3–7, minSlope 0.05–0.15 RSI pts/bar, pivot left/right tighter for faster but noisier signals, wider for cleaner but fewer.
* Alerts = workflow, not auto-trades
* Use Macro Flip + Divergence alerts as a checklist trigger; enter only when your confluence rules are met and risk is defined.
Key inputs (tweak to your market/timeframe)
* RSI / Stochastic lengths and K/D smoothing.
* Bull / Bear Lines (default 61.1 / 43.6).
* Average RSI Method/Length (SMA/EMA/RMA/WMA) + Macro Smooth Length.
* Trend confirmation: bars of persistence and minimum slope to reduce flip noise.
* Pivot look-back (left/right) for divergence confirmation strictness.
Alerts included
* Macro Flip Up / Down (Smoothed RSI regime change).
* RSI Bullish/Bearish Divergence (confirmed at pivot).
* Stochastic RSI continuation/divergence (optional).
Tips
* Level + Slope matter. High/low RSI level flags conditions; slope confirms impulse/continuation.
* Let Stochastic time the swing; let Macro RSI filter the trend.
* Tighten or loosen pivot windows to trade fewer/cleaner vs. more/faster signals.
OBV with Divergence (SMA Smoother)Title: OBV Divergence with SMA Smoothing
Description:
This indicator is a powerful tool designed to identify regular (reversal) and hidden (continuation) On-Balance Volume (OBV) divergences against price action. It uses a modified OBV calculation (an OBV Oscillator) and integrates pivot analysis to automatically highlight potential turning points or trend continuations directly on your chart.
Key Features
Advanced Divergence Detection: Automatically detects and labels four types of divergences:
Regular Bullish/Bearish: Signals potential trend reversals.
Regular Bullish: Price makes a Lower Low (LL) but the OBV Oscillator makes a Higher Low (HL).
Regular Bearish: Price makes a Higher High (HH) but the OBV Oscillator makes a Lower High (LH).
Hidden Bullish/Bearish: Signals potential trend continuations.
Hidden Bullish: Price makes a Higher Low (HL) but the OBV Oscillator makes a Lower Low (LL).
Hidden Bearish: Price makes a Lower High (LH) but the OBV Oscillator makes a Higher High (HH).
OBV Oscillator: Instead of plotting the raw OBV, this script uses the difference between the OBV and its Exponential Moving Average (EMA). This technique centers the indicator around zero, making it easier to visualize volume momentum shifts and clearly identify peaks and troughs for divergence analysis.
Optional SMA Smoothing Line (New Feature): An added Simple Moving Average (SMA) line can be toggled on to further smooth the OBV Oscillator. Traders can use this line for crossover signals or to confirm the underlying trend of the volume momentum, reducing whipsaws.
Customizable Lookback: The indicator allows you to define the lookback periods (Pivot Lookback Left/Right) for price and oscillator pivots, giving you precise control over sensitivity. The Max/Min of Lookback Range helps filter out divergences that are too close or too far apart.
ZS Master Vision Pro - Advanced Multi-Timeframe Trading SystemZS MASTER VISION PRO - PROFESSIONAL TRADING SUITE
Created by Zakaria Safri
A comprehensive, all-in-one trading system combining multiple proven technical analysis methods into a single, powerful indicator. Designed for traders who demand precision, clarity, and actionable signals across all timeframes.
KEY FEATURES
CORE TREND ALGORITHM
Adaptive ATR-based trend detection with dynamic support and resistance zones. Features Type A and Type B signal modes for different trading styles, strong signal detection in key reversal zones, and optional EMA source smoothing for noise reduction.
MULTI-LAYER EMA CLOUD SYSTEM
Five customizable EMA cloud layers for multi-timeframe analysis with theme-adaptive color coding across five professional themes. Optional line display for detailed MA tracking with configurable periods from scalping to position trading.
WAVE TREND OSCILLATOR
Advanced momentum oscillator with channel-based calculations featuring smart reversal detection at extreme overbought and oversold levels. Includes directional strength confirmation and customizable sensitivity with adjustable reaction periods.
DIVERGENCE SCANNER
Detects four types of divergence automatically:
- Regular Bullish: Price making lower lows while oscillator making higher lows
- Regular Bearish: Price making higher highs while oscillator making lower highs
- Hidden Bullish: Trend continuation signals in uptrends
- Hidden Bearish: Trend continuation signals in downtrends
Automatic fractal-based detection with clear visual labels on chart.
MARKET BIAS INDICATOR
Heikin Ashi-based trend strength analysis with real-time bias calculation showing Bullish or Bearish combined with Strong or Weak conditions. Smoothed for cleaner signals and perfect for trend confirmation.
MOMENTUM SYSTEM
Proprietary momentum calculation using adaptive smoothing with growing and falling state detection. Normalized values for consistent interpretation and responsive to rapid market changes.
DYNAMIC SUPPORT AND RESISTANCE
Automatic pivot-based support and resistance level detection with adjustable left and right bar lookback. Non-repainting levels with visual clarity through color-coded lines.
LIVE INFORMATION DASHBOARD
Real-time market analysis panel displaying current trend direction, market bias based on Heikin Ashi, Wave Trend status and value, and momentum trend with state. Customizable display options with theme-adaptive colors.
VISUAL CUSTOMIZATION
FIVE PROFESSIONAL COLOR THEMES:
Pro - Modern green and red color scheme (default)
Classic - Traditional teal and red combination
Cyberpunk - Neon cyan and magenta contrast
Ocean - Blue and orange contrast
Sunset - Gold and red warmth
SIGNAL STYLES:
Labels with emoji indicators (BUY with rocket, SELL with bear, STRONG with lightning)
Arrows for clean minimal appearance
Triangles for classic approach
DISPLAY OPTIONS:
Color-coded candles following trend direction
Trend background highlighting for instant trend recognition
Optional EMA line display for detailed analysis
Adjustable transparency levels for personal preference
SMART ALERTS
Pre-configured alert conditions for all major signals:
Buy signals for standard entry opportunities
Sell signals for standard exit or short opportunities
Strong buy signals for high-confidence long entries
Strong sell signals for high-confidence short entries
Bullish divergence detection alerts
Bearish divergence detection alerts
Alert messages automatically include ticker symbol, current price, and specific signal type for quick decision making.
HOW TO USE
FOR TREND TRADERS:
Enable EMA Clouds with focus on Cloud 5 featuring 50 and 200 period moving averages. Wait for trend background color change to confirm direction. Enter on STRONG signals aligned with higher timeframe trend direction. Use support and resistance levels for strategic exits.
FOR SWING TRADERS:
Enable Wave Trend Oscillator information display. Look for oversold and overbought reversal setups. Confirm potential reversals with divergence scanner. Enter on smart reversal signals with proper risk management.
FOR SCALPERS:
Use Type B signal mode for more frequent trading signals. Enable Cloud 1 with 5 and 13 periods for quick trend confirmation. Focus on momentum growing and falling states for entry timing. Take quick entries on regular buy and sell signals.
FOR POSITION TRADERS:
Use Type A mode with higher ATR multiplier set to 3.0 or above. Enable only Cloud 5 with 50 and 200 periods for major trend confirmation. Only take STRONG signals for highest probability setups. Hold positions through minor pullbacks and noise.
RECOMMENDED SETTINGS
STOCKS ON DAILY TIMEFRAME:
Trend Period: 180
ATR Period: 155
ATR Multiplier: 2.1
Signal Mode: Type A
FOREX ON HOURLY AND 4-HOUR TIMEFRAMES:
Trend Period: 150
ATR Period: 120
ATR Multiplier: 2.5
Signal Mode: Type A
CRYPTOCURRENCY ON 15-MINUTE AND 1-HOUR TIMEFRAMES:
Trend Period: 100
ATR Period: 80
ATR Multiplier: 3.0
Signal Mode: Type B
SCALPING ON 1-MINUTE AND 5-MINUTE TIMEFRAMES:
Trend Period: 50
ATR Period: 40
ATR Multiplier: 2.0
Signal Mode: Type B
WHAT IS INCLUDED
Trend Analysis using ATR-based adaptive algorithm
Five EMA Cloud Layers for multi-timeframe confluence
Wave Trend Oscillator for momentum and reversal detection
Divergence Scanner detecting four types of divergence
Market Bias using Heikin Ashi-based trend strength
Momentum System with advanced momentum tracking
Support and Resistance Levels with automatic pivot detection
Live Dashboard showing real-time market analysis
Smart Alerts featuring six pre-configured alert types
Five Color Themes offering professional visual options
TECHNICAL DETAILS
CALCULATION METHODS:
Average True Range (ATR) for volatility adaptation
Exponential Moving Average (EMA) and Simple Moving Average (SMA) for trend smoothing
Wave Trend channel oscillator for momentum analysis
Fractal-based divergence detection algorithm
Heikin Ashi transformation for bias calculation
Logarithmic momentum calculation for precision
PERFORMANCE CHARACTERISTICS:
Optimized for maximum speed and efficiency
No repainting signals ensuring reliability
Works on all timeframes from 1 minute to monthly
Compatible with all instruments including stocks, forex, crypto, and futures
RISK DISCLAIMER
This indicator is a technical analysis tool and should not be used as the sole basis for trading decisions. Always use proper risk management and never risk more than you can afford to lose. Combine with other analysis methods and practice on demo accounts first. Past performance does not guarantee future results. Trading carries substantial risk and is not suitable for all investors.
SUPPORT AND UPDATES
Regular updates and continuous improvements
Based on proven technical analysis principles
Developed following Pine Coders best practices and standards
Clean, well-documented, and optimized code structure
WHY CHOOSE ZS MASTER VISION PRO
All-in-one solution eliminating the need for multiple indicators
Highly customizable to adapt to your specific trading style
Professional grade analysis with institutional-quality standards
Clean interface that is not cluttered or confusing
Works everywhere across all markets and all timeframes
Smart signals filtered for quality over quantity
Beautiful design featuring five professional color themes
Active development with regular improvements and updates
Transform your trading with ZS Master Vision Pro today.
Version 2.0 | Created by Zakaria Safri | Pine Script Version 5
Mythical EMAs + Dynamic VWAP BandThis indicator titled "Mythical EMAs + Dynamic VWAP Band." It overlays several volatility-adjusted Exponential Moving Averages (EMAs) on the chart, along with a Volume Weighted Average Price (VWAP) line and a dynamic band around it.
Additionally, it uses background coloring (clouds) to visualize bullish or bearish trends, with intensity modulated by the price's position relative to the VWAP.
The EMAs are themed with mythical names (e.g., Hermes for the 9-period EMA), but this is just stylistic flavoring and doesn't affect functionality.
I'll break it down section by section, explaining what each part does, how it works, and its purpose in the context of technical analysis. This indicator is designed for traders to identify trends, momentum, and price fairness relative to volume-weighted averages, with volatility adjustments to make the EMAs more responsive in volatile markets.
### 1. **Volatility Calculation (ATR)**
```pine
atrLength = 14
volatility = ta.atr(atrLength)
```
- **What it does**: Calculates the Average True Range (ATR) over 14 periods (a common default). ATR measures market volatility by averaging the true range (the greatest of: high-low, |high-previous close|, |low-previous close|).
- **Purpose**: This volatility value is used later to dynamically adjust the EMAs, making them more sensitive in high-volatility conditions (e.g., during market swings) and smoother in low-volatility periods. It helps the indicator adapt to changing market environments rather than using static EMAs.
### 2. **Custom Mythical EMA Function**
```pine
mythical_ema(src, length, base_alpha, vol_factor) =>
alpha = (2 / (length + 1)) * base_alpha * (1 + vol_factor * (volatility / src))
ema = 0.0
ema := na(ema ) ? src : alpha * src + (1 - alpha) * ema
ema
```
- **What it does**: Defines a custom function to compute a modified EMA.
- It starts with the standard EMA smoothing factor formula: `2 / (length + 1)`.
- Multiplies it by a `base_alpha` (a user-defined multiplier to tweak responsiveness).
- Adjusts further for volatility: Adds a term `(1 + vol_factor * (volatility / src))`, where `vol_factor` scales the impact, and `volatility / src` normalizes ATR relative to the source price (making it scale-invariant).
- The EMA is then calculated recursively: If the previous EMA is NA (e.g., at the start), it uses the current source value; otherwise, it weights the current source by `alpha` and the prior EMA by `(1 - alpha)`.
- **Purpose**: This creates "adaptive" EMAs that react faster in volatile markets (higher alpha when volatility is high relative to price) without overreacting in calm periods. It's an enhancement over standard EMAs, which use fixed alphas and can lag in choppy conditions. The mythical theme is just naming—functionally, it's a volatility-weighted EMA.
### 3. **Calculating the EMAs**
```pine
ema9 = mythical_ema(close, 9, 1.2, 0.5) // Hermes - quick & nimble
ema20 = mythical_ema(close, 20, 1.0, 0.3) // Apollo - short-term foresight
ema50 = mythical_ema(close, 50, 0.9, 0.2) // Athena - wise strategist
ema100 = mythical_ema(close, 100, 0.8, 0.1) // Zeus - powerful oversight
ema200 = mythical_ema(close, 200, 0.7, 0.05) // Kronos - long-term patience
```
- **What it does**: Applies the custom EMA function to the close price with varying lengths (9, 20, 50, 100, 200 periods), base alphas (decreasing from 1.2 to 0.7 for longer periods to make shorter ones more responsive), and volatility factors (decreasing from 0.5 to 0.05 to reduce volatility influence on longer-term EMAs).
- **Purpose**: These form a multi-timeframe EMA ribbon:
- Shorter EMAs (e.g., 9 and 20) capture short-term momentum.
- Longer ones (e.g., 200) show long-term trends.
- Crossovers (e.g., short EMA crossing above long EMA) can signal buy/sell opportunities. The volatility adjustment makes them "mythical" by adding dynamism, potentially improving signal quality in real markets.
### 4. **VWAP Calculation**
```pine
vwap_val = ta.vwap(close) // VWAP based on close price
```
- **What it does**: Computes the Volume Weighted Average Price (VWAP) using the built-in `ta.vwap` function, anchored to the close price. VWAP is the average price weighted by volume over the session (resets daily by default in Pine Script).
- **Purpose**: VWAP acts as a benchmark for "fair value." Prices above VWAP suggest bullishness (buyers in control), below indicate bearishness (sellers dominant). It's commonly used by institutional traders to assess entry/exit points.
### 5. **Plotting EMAs and VWAP**
```pine
plot(ema9, color=color.fuchsia, title='EMA 9 (Hermes)')
plot(ema20, color=color.red, title='EMA 20 (Apollo)')
plot(ema50, color=color.orange, title='EMA 50 (Athena)')
plot(ema100, color=color.aqua, title='EMA 100 (Zeus)')
plot(ema200, color=color.blue, title='EMA 200 (Kronos)')
plot(vwap_val, color=color.yellow, linewidth=2, title='VWAP')
```
- **What it does**: Overlays the EMAs and VWAP on the chart with distinct colors and titles for easy identification in TradingView's legend.
- **Purpose**: Visualizes the EMA ribbon and VWAP line. Traders can watch for EMA alignments (e.g., all sloping up for uptrend) or price interactions with VWAP.
### 6. **Dynamic VWAP Band**
```pine
band_pct = 0.005
vwap_upper = vwap_val * (1 + band_pct)
vwap_lower = vwap_val * (1 - band_pct)
p1 = plot(vwap_upper, color=color.new(color.yellow, 0), title="VWAP Upper Band")
p2 = plot(vwap_lower, color=color.new(color.yellow, 0), title="VWAP Lower Band")
fill_color = close >= vwap_val ? color.new(color.green, 80) : color.new(color.red, 80)
fill(p1, p2, color=fill_color, title="Dynamic VWAP Band")
```
- **What it does**: Creates a band ±0.5% around the VWAP.
- Plots the upper/lower bands with full transparency (color opacity 0, so lines are invisible).
- Fills the area between them dynamically: Semi-transparent green (opacity 80) if close ≥ VWAP (bullish bias), red if below (bearish bias).
- **Purpose**: Highlights deviations from VWAP visually. The color change provides an at-a-glance sentiment indicator—green for "above fair value" (potential strength), red for "below" (potential weakness). The narrow band (0.5%) focuses on short-term fairness, and the fill makes it easier to spot than just the line.
### 7. **Trend Clouds with VWAP Interaction**
```pine
bullish = ema9 > ema20 and ema20 > ema50
bearish = ema9 < ema20 and ema20 < ema50
bullish_above_vwap = bullish and close > vwap_val
bullish_below_vwap = bullish and close <= vwap_val
bearish_below_vwap = bearish and close < vwap_val
bearish_above_vwap = bearish and close >= vwap_val
bgcolor(bullish_above_vwap ? color.new(color.green, 50) : na, title="Bullish Above VWAP")
bgcolor(bullish_below_vwap ? color.new(color.green, 80) : na, title="Bullish Below VWAP")
bgcolor(bearish_below_vwap ? color.new(color.red, 50) : na, title="Bearish Below VWAP")
bgcolor(bearish_above_vwap ? color.new(color.red, 80) : na, title="Bearish Above VWAP")
```
- **What it does**: Defines trend conditions based on EMA alignments:
- Bullish: Shorter EMAs stacked above longer ones (9 > 20 > 50, indicating upward momentum).
- Bearish: The opposite (downward momentum).
- Sub-conditions combine with VWAP: E.g., bullish_above_vwap is true only if bullish and price > VWAP.
- Applies background colors (bgcolor) to the entire chart pane:
- Strong bullish (above VWAP): Green with opacity 50 (less transparent, more intense).
- Weak bullish (below VWAP): Green with opacity 80 (more transparent, less intense).
- Strong bearish (below VWAP): Red with opacity 50.
- Weak bearish (above VWAP): Red with opacity 80.
- If no condition matches, no color (na).
- **Purpose**: Creates "clouds" for trend visualization, enhanced by VWAP context. This helps traders confirm trends—e.g., a strong bullish cloud (darker green) suggests a high-conviction uptrend when price is above VWAP. The varying opacity differentiates signal strength: Darker for aligned conditions (trend + VWAP agreement), lighter for misaligned (potential weakening or reversal).
### Overall Indicator Usage and Limitations
- **How to use it**: Add this to a TradingView chart (e.g., stocks, crypto, forex). Look for EMA crossovers, price bouncing off EMAs/VWAP, or cloud color changes as signals. Bullish clouds with price above VWAP might signal buys; bearish below for sells.
- **Strengths**: Combines momentum (EMAs), volume (VWAP), and volatility adaptation for a multi-layered view. Dynamic colors make it intuitive.
- **Limitations**:
- EMAs lag in ranging markets; volatility adjustment helps but doesn't eliminate whipsaws.
- VWAP resets daily (standard behavior), so it's best for intraday/session trading.
- No alerts or inputs for customization (e.g., changeable lengths)—it's hardcoded.
- Performance depends on the asset/timeframe; backtest before using.
- **License**: Mozilla Public License 2.0, so it's open-source and modifiable.
ICT PDA - Gold & BTC (QuickScalp Bias/FVG/OB/OTE + Alerts)What this script does
This indicator implements a complete ICT Price Delivery Algorithm (PDA) workflow tailored for XAUUSD and BTCUSD. It combines HTF bias, OTE zones, Fair Value Gaps, Order Blocks, micro-BOS confirmation, and liquidity references into a single, cohesive tool with early and final alerts. The script is not a mashup for cosmetic plotting; each component feeds the next decision step.
Why this is original/useful
Symbol-aware impulse filter: A dynamic displacement threshold kTune adapts to Gold/BTC volatility (body/ATR vs. per-symbol factor), reducing noise on fast markets without hiding signals.
Scalping preset: “Quick Clean” mode limits drawings to the most recent bars and keeps only the latest FVG/OB zones for a clear chart.
Three display modes: Full, Clean, and Signals-Only to match analysis vs. execution.
Actionable alerts: Early heads-up when price enters OTE in the HTF bias direction, and Final alerts once mitigation + micro-break confirm the setup.
How it works (high-level logic)
HTF Bias: Uses request.security() on a user-selected timeframe (e.g., 240m) and EMA filter. Bias = close above/below HTF EMA.
Dealing Range & OTE: Recent swing high/low (pivot length configurable) define the range; OTE (62–79%) boxes are drawn contextually for up/down ranges.
Displacement: A candle’s body/ATR must exceed kTune and break short-term structure (displacement up/down).
FVG: 3-bar imbalance (bull: low > high ; bear: high < low ). Latest gaps are tracked and extended.
Order Blocks: Last opposite candle prior to a qualifying displacement that breaks recent highs/lows; zones are drawn and extended.
Entry & Alerts:
Long: Bullish bias + price inside buy-OTE + mitigation of a bullish FVG or OB + micro BOS up → “PDA Long (Final)”.
Short: Bearish bias + price inside sell-OTE + mitigation of a bearish FVG or OB + micro BOS down → “PDA Short (Final)”.
Early Alerts: Trigger as soon as price enters OTE in the direction of the active bias.
Inputs & controls (key ones)
Bias (HTF): timeframe minutes, EMA length.
Structure: ATR length, Impulse Threshold (Body/ATR), swing pivot length, OB look-back.
OTE/FVG/OB/LP toggles: show/hide components.
Auto-Tune: per-symbol factors for Gold/BTC + manual tweak.
Display/Performance: View Mode, keep-N latest FVG/OB, limit drawings to last N bars.
Recommended usage (scalping)
Timeframes: Execute on M1–M5 with HTF bias from 120–240m.
Defaults (starting point): ATR=14, Impulse Threshold≈1.6; Gold factor≈1.05, BTC factor≈0.90; Keep FVG/OB=2; last 200–300 bars; View Mode=Clean.
Workflow: Wait for OTE in bias direction → see mitigation (FVG/OB) → confirm with micro BOS → manage risk to nearest liquidity (prev-day H/L or recent swing).
Alerts available
“PDA Early Long/Short”
“PDA Long (Final)” / “PDA Short (Final)”
Attach alerts on “Any alert() function call” or the listed conditions.
Chart & screenshots
Please include symbol and timeframe on screenshots. The on-chart HUD shows the script name and state to help reviewers understand context.
Limitations / notes
This is a discretionary framework. Signals can cluster during news or extreme volatility; use your own risk management. No guarantee of profitability.
Changelog (brief)
v1.2 QuickScalp: added Quick Clean preset, safer array handling, symbol-aware impulse tuning, display modes.
------------------------------
ملخص عربي:
المؤشر يطبق تسلسل PDA عملي للذهب والبتكوين: تحيز من فريم أعلى، مناطق OTE، فجوات FVG، بلوكات أوامر OB، وتأكيد micro-BOS، مع تنبيهات مبكرة ونهائية. تمت إضافة وضع “Quick Clean” لتقليل العناصر على الشارت وحساسية إزاحة تتكيّف مع الأصل. للاستخدام كسكالب: نفّذ على M1–M5 مع تحيز 120–240 دقيقة، وابدأ من الإعدادات المقترحة بالأعلى. هذا إطار سلوكي وليس توصية مالية.
Reversal Probability Meter PRO [optimized for Xau/Usd m5]🎯 Reversal Probability Meter PRO
A powerful multi-factor reversal probability detector that calculates the likelihood of bullish or bearish reversals using RSI, EMA bias, ATR spikes, candle patterns, volume spikes, and higher timeframe (HTF) trend alignment.
🧩 MAIN FEATURES
1. Reversal Probability (Bullish & Bearish)
Displays two key metrics:
Bull % — probability of bullish reversal
Bear % — probability of bearish reversal
These are computed using RSI, EMAs, ATR, demand/supply zones, candle confirmations, and volume spikes.
📊 Interpretation:
Bull % > 70% → Buying pressure building up
Bull % > 85% → Strong bullish reversal confirmed
Bear % > 70% → Selling pressure building up
Bear % > 85% → Strong bearish reversal confirmed
2. Alert Probability Threshold
Adjustable via alertThreshold (default = 85%).
Alerts trigger only when probability ≥ threshold, and confirmed by zone + volume spike + candle pattern.
🔔 Alerts Available:
✅ Bullish Smart Reversal
🔻 Bearish Smart Reversal
To activate: Right-click chart → “Add alert” → choose the alert condition from the indicator.
3. Demand / Supply Zone Detection
The script determines the price position within the last zoneLook (default 30) bars:
🟢 DEMAND → Lower 35% of range (potential bounce zone)
🔴 SUPPLY → Upper 35% of range (potential rejection zone)
⚪ MID → Neutral area
📘 Purpose: Validates reversals based on context:
Bullish only valid in Demand zones
Bearish only valid in Supply zones
4. Higher Timeframe (HTF) Trend Alignment
Reads EMA bias from a higher timeframe (default = 15m) for trend confirmation.
Reversals against HTF trend are automatically weighted down prevents false countertrend signals.
📈 Example:
M5 chart under M15 downtrend → Bullish probability is reduced.
5. Candle Confirmation Patterns
Two key price action confirmations:
Bullish: Engulfing or Pin Bar
Bearish: Engulfing or Pin Bar
A valid reversal requires both a candle confirmation and a volume spike.
6. Volume & ATR Spike Filters
Volume Spike: volume > SMA(20) × 1.3
ATR Spike: ATR > SMA(ATR, 50) × volMult
🎯 Ensures that only strong market moves with real energy are considered valid reversals.
7. Reversal Momentum Histogram
A color-gradient oscillator showing the momentum difference:
Green = bullish dominance
Red = bearish dominance
Flat near 0 = neutral
Controlled by showOscillator toggle.
8. Smart Info Panel
A compact dashboard displayed on the top-right with 4 rows:
Row Info Description
1 Bull % Bullish reversal probability
2 Bear % Bearish reversal probability
3 Zone Market context (DEMAND / SUPPLY / MID)
4 Signal Strength Current signal intensity (probability %)
Dynamic Colors:
90% → Bright (strong signal)
75–90% → Yellow/Orange (medium)
<75% → Gray (weak)
9. Sensitivity Mode
Fine-tunes indicator reactivity:
🟥 Aggressive: Detects reversals early (more signals, less accurate)
🟨 Normal: Balanced, default mode
🟩 Conservative: Filters only strongest reversals (fewer but more reliable)
10. Custom Color Options
Customize bullish and bearish colors via bullBaseColor and bearBaseColor inputs for your preferred chart theme.
⚙️ HOW TO USE
Add to Chart
→ Paste the script into Pine Editor → “Add to chart”.
Select Timeframe
→ Best for M5–M30 (scalping/intraday).
→ H1–H4 for swing trading.
Monitor the Info Panel:
Bull % ≥ 85% + Zone = Demand → Strong bullish reversal signal
Bear % ≥ 85% + Zone = Supply → Strong bearish reversal signal
Watch the Histogram:
Rising green bars = bullish momentum gaining
Deep red bars = bearish momentum gaining
Enable Alerts:
Right-click chart → “Add alert”
Choose Bullish Smart Reversal or Bearish Smart Reversal
🧠 TRADING TIPS
Use Conservative mode for noisy lower timeframes (M5–M15).
Use Aggressive mode for higher timeframes (H1–H4).
Combine with manual support/resistance or zone boxes for precision entries. Personally i use Order Block.
Best reversal setups occur when all align:
Bull % > 85%
Zone = DEMAND
Volume spike present
Candle = Bullish engulfing
HTF trend supportive
Dynamic Equity Allocation Model"Cash is Trash"? Not Always. Here's Why Science Beats Guesswork.
Every retail trader knows the frustration: you draw support and resistance lines, you spot patterns, you follow market gurus on social media—and still, when the next bear market hits, your portfolio bleeds red. Meanwhile, institutional investors seem to navigate market turbulence with ease, preserving capital when markets crash and participating when they rally. What's their secret?
The answer isn't insider information or access to exotic derivatives. It's systematic, scientifically validated decision-making. While most retail traders rely on subjective chart analysis and emotional reactions, professional portfolio managers use quantitative models that remove emotion from the equation and process multiple streams of market information simultaneously.
This document presents exactly such a system—not a proprietary black box available only to hedge funds, but a fully transparent, academically grounded framework that any serious investor can understand and apply. The Dynamic Equity Allocation Model (DEAM) synthesizes decades of financial research from Nobel laureates and leading academics into a practical tool for tactical asset allocation.
Stop drawing colorful lines on your chart and start thinking like a quant. This isn't about predicting where the market goes next week—it's about systematically adjusting your risk exposure based on what the data actually tells you. When valuations scream danger, when volatility spikes, when credit markets freeze, when multiple warning signals align—that's when cash isn't trash. That's when cash saves your portfolio.
The irony of "cash is trash" rhetoric is that it ignores timing. Yes, being 100% cash for decades would be disastrous. But being 100% equities through every crisis is equally foolish. The sophisticated approach is dynamic: aggressive when conditions favor risk-taking, defensive when they don't. This model shows you how to make that decision systematically, not emotionally.
Whether you're managing your own retirement portfolio or seeking to understand how institutional allocation strategies work, this comprehensive analysis provides the theoretical foundation, mathematical implementation, and practical guidance to elevate your investment approach from amateur to professional.
The choice is yours: keep hoping your chart patterns work out, or start using the same quantitative methods that professionals rely on. The tools are here. The research is cited. The methodology is explained. All you need to do is read, understand, and apply.
The Dynamic Equity Allocation Model (DEAM) is a quantitative framework for systematic allocation between equities and cash, grounded in modern portfolio theory and empirical market research. The model integrates five scientifically validated dimensions of market analysis—market regime, risk metrics, valuation, sentiment, and macroeconomic conditions—to generate dynamic allocation recommendations ranging from 0% to 100% equity exposure. This work documents the theoretical foundations, mathematical implementation, and practical application of this multi-factor approach.
1. Introduction and Theoretical Background
1.1 The Limitations of Static Portfolio Allocation
Traditional portfolio theory, as formulated by Markowitz (1952) in his seminal work "Portfolio Selection," assumes an optimal static allocation where investors distribute their wealth across asset classes according to their risk aversion. This approach rests on the assumption that returns and risks remain constant over time. However, empirical research demonstrates that this assumption does not hold in reality. Fama and French (1989) showed that expected returns vary over time and correlate with macroeconomic variables such as the spread between long-term and short-term interest rates. Campbell and Shiller (1988) demonstrated that the price-earnings ratio possesses predictive power for future stock returns, providing a foundation for dynamic allocation strategies.
The academic literature on tactical asset allocation has evolved considerably over recent decades. Ilmanen (2011) argues in "Expected Returns" that investors can improve their risk-adjusted returns by considering valuation levels, business cycles, and market sentiment. The Dynamic Equity Allocation Model presented here builds on this research tradition and operationalizes these insights into a practically applicable allocation framework.
1.2 Multi-Factor Approaches in Asset Allocation
Modern financial research has shown that different factors capture distinct aspects of market dynamics and together provide a more robust picture of market conditions than individual indicators. Ross (1976) developed the Arbitrage Pricing Theory, a model that employs multiple factors to explain security returns. Following this multi-factor philosophy, DEAM integrates five complementary analytical dimensions, each tapping different information sources and collectively enabling comprehensive market understanding.
2. Data Foundation and Data Quality
2.1 Data Sources Used
The model draws its data exclusively from publicly available market data via the TradingView platform. This transparency and accessibility is a significant advantage over proprietary models that rely on non-public data. The data foundation encompasses several categories of market information, each capturing specific aspects of market dynamics.
First, price data for the S&P 500 Index is obtained through the SPDR S&P 500 ETF (ticker: SPY). The use of a highly liquid ETF instead of the index itself has practical reasons, as ETF data is available in real-time and reflects actual tradability. In addition to closing prices, high, low, and volume data are captured, which are required for calculating advanced volatility measures.
Fundamental corporate metrics are retrieved via TradingView's Financial Data API. These include earnings per share, price-to-earnings ratio, return on equity, debt-to-equity ratio, dividend yield, and share buyback yield. Cochrane (2011) emphasizes in "Presidential Address: Discount Rates" the central importance of valuation metrics for forecasting future returns, making these fundamental data a cornerstone of the model.
Volatility indicators are represented by the CBOE Volatility Index (VIX) and related metrics. The VIX, often referred to as the market's "fear gauge," measures the implied volatility of S&P 500 index options and serves as a proxy for market participants' risk perception. Whaley (2000) describes in "The Investor Fear Gauge" the construction and interpretation of the VIX and its use as a sentiment indicator.
Macroeconomic data includes yield curve information through US Treasury bonds of various maturities and credit risk premiums through the spread between high-yield bonds and risk-free government bonds. These variables capture the macroeconomic conditions and financing conditions relevant for equity valuation. Estrella and Hardouvelis (1991) showed that the shape of the yield curve has predictive power for future economic activity, justifying the inclusion of these data.
2.2 Handling Missing Data
A practical problem when working with financial data is dealing with missing or unavailable values. The model implements a fallback system where a plausible historical average value is stored for each fundamental metric. When current data is unavailable for a specific point in time, this fallback value is used. This approach ensures that the model remains functional even during temporary data outages and avoids systematic biases from missing data. The use of average values as fallback is conservative, as it generates neither overly optimistic nor pessimistic signals.
3. Component 1: Market Regime Detection
3.1 The Concept of Market Regimes
The idea that financial markets exist in different "regimes" or states that differ in their statistical properties has a long tradition in financial science. Hamilton (1989) developed regime-switching models that allow distinguishing between different market states with different return and volatility characteristics. The practical application of this theory consists of identifying the current market state and adjusting portfolio allocation accordingly.
DEAM classifies market regimes using a scoring system that considers three main dimensions: trend strength, volatility level, and drawdown depth. This multidimensional view is more robust than focusing on individual indicators, as it captures various facets of market dynamics. Classification occurs into six distinct regimes: Strong Bull, Bull Market, Neutral, Correction, Bear Market, and Crisis.
3.2 Trend Analysis Through Moving Averages
Moving averages are among the oldest and most widely used technical indicators and have also received attention in academic literature. Brock, Lakonishok, and LeBaron (1992) examined in "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns" the profitability of trading rules based on moving averages and found evidence for their predictive power, although later studies questioned the robustness of these results when considering transaction costs.
The model calculates three moving averages with different time windows: a 20-day average (approximately one trading month), a 50-day average (approximately one quarter), and a 200-day average (approximately one trading year). The relationship of the current price to these averages and the relationship of the averages to each other provide information about trend strength and direction. When the price trades above all three averages and the short-term average is above the long-term, this indicates an established uptrend. The model assigns points based on these constellations, with longer-term trends weighted more heavily as they are considered more persistent.
3.3 Volatility Regimes
Volatility, understood as the standard deviation of returns, is a central concept of financial theory and serves as the primary risk measure. However, research has shown that volatility is not constant but changes over time and occurs in clusters—a phenomenon first documented by Mandelbrot (1963) and later formalized through ARCH and GARCH models (Engle, 1982; Bollerslev, 1986).
DEAM calculates volatility not only through the classic method of return standard deviation but also uses more advanced estimators such as the Parkinson estimator and the Garman-Klass estimator. These methods utilize intraday information (high and low prices) and are more efficient than simple close-to-close volatility estimators. The Parkinson estimator (Parkinson, 1980) uses the range between high and low of a trading day and is based on the recognition that this information reveals more about true volatility than just the closing price difference. The Garman-Klass estimator (Garman and Klass, 1980) extends this approach by additionally considering opening and closing prices.
The calculated volatility is annualized by multiplying it by the square root of 252 (the average number of trading days per year), enabling standardized comparability. The model compares current volatility with the VIX, the implied volatility from option prices. A low VIX (below 15) signals market comfort and increases the regime score, while a high VIX (above 35) indicates market stress and reduces the score. This interpretation follows the empirical observation that elevated volatility is typically associated with falling markets (Schwert, 1989).
3.4 Drawdown Analysis
A drawdown refers to the percentage decline from the highest point (peak) to the lowest point (trough) during a specific period. This metric is psychologically significant for investors as it represents the maximum loss experienced. Calmar (1991) developed the Calmar Ratio, which relates return to maximum drawdown, underscoring the practical relevance of this metric.
The model calculates current drawdown as the percentage distance from the highest price of the last 252 trading days (one year). A drawdown below 3% is considered negligible and maximally increases the regime score. As drawdown increases, the score decreases progressively, with drawdowns above 20% classified as severe and indicating a crisis or bear market regime. These thresholds are empirically motivated by historical market cycles, in which corrections typically encompassed 5-10% drawdowns, bear markets 20-30%, and crises over 30%.
3.5 Regime Classification
Final regime classification occurs through aggregation of scores from trend (40% weight), volatility (30%), and drawdown (30%). The higher weighting of trend reflects the empirical observation that trend-following strategies have historically delivered robust results (Moskowitz, Ooi, and Pedersen, 2012). A total score above 80 signals a strong bull market with established uptrend, low volatility, and minimal losses. At a score below 10, a crisis situation exists requiring defensive positioning. The six regime categories enable a differentiated allocation strategy that not only distinguishes binarily between bullish and bearish but allows gradual gradations.
4. Component 2: Risk-Based Allocation
4.1 Volatility Targeting as Risk Management Approach
The concept of volatility targeting is based on the idea that investors should maximize not returns but risk-adjusted returns. Sharpe (1966, 1994) defined with the Sharpe Ratio the fundamental concept of return per unit of risk, measured as volatility. Volatility targeting goes a step further and adjusts portfolio allocation to achieve constant target volatility. This means that in times of low market volatility, equity allocation is increased, and in times of high volatility, it is reduced.
Moreira and Muir (2017) showed in "Volatility-Managed Portfolios" that strategies that adjust their exposure based on volatility forecasts achieve higher Sharpe Ratios than passive buy-and-hold strategies. DEAM implements this principle by defining a target portfolio volatility (default 12% annualized) and adjusting equity allocation to achieve it. The mathematical foundation is simple: if market volatility is 20% and target volatility is 12%, equity allocation should be 60% (12/20 = 0.6), with the remaining 40% held in cash with zero volatility.
4.2 Market Volatility Calculation
Estimating current market volatility is central to the risk-based allocation approach. The model uses several volatility estimators in parallel and selects the higher value between traditional close-to-close volatility and the Parkinson estimator. This conservative choice ensures the model does not underestimate true volatility, which could lead to excessive risk exposure.
Traditional volatility calculation uses logarithmic returns, as these have mathematically advantageous properties (additive linkage over multiple periods). The logarithmic return is calculated as ln(P_t / P_{t-1}), where P_t is the price at time t. The standard deviation of these returns over a rolling 20-trading-day window is then multiplied by √252 to obtain annualized volatility. This annualization is based on the assumption of independently identically distributed returns, which is an idealization but widely accepted in practice.
The Parkinson estimator uses additional information from the trading range (High minus Low) of each day. The formula is: σ_P = (1/√(4ln2)) × √(1/n × Σln²(H_i/L_i)) × √252, where H_i and L_i are high and low prices. Under ideal conditions, this estimator is approximately five times more efficient than the close-to-close estimator (Parkinson, 1980), as it uses more information per observation.
4.3 Drawdown-Based Position Size Adjustment
In addition to volatility targeting, the model implements drawdown-based risk control. The logic is that deep market declines often signal further losses and therefore justify exposure reduction. This behavior corresponds with the concept of path-dependent risk tolerance: investors who have already suffered losses are typically less willing to take additional risk (Kahneman and Tversky, 1979).
The model defines a maximum portfolio drawdown as a target parameter (default 15%). Since portfolio volatility and portfolio drawdown are proportional to equity allocation (assuming cash has neither volatility nor drawdown), allocation-based control is possible. For example, if the market exhibits a 25% drawdown and target portfolio drawdown is 15%, equity allocation should be at most 60% (15/25).
4.4 Dynamic Risk Adjustment
An advanced feature of DEAM is dynamic adjustment of risk-based allocation through a feedback mechanism. The model continuously estimates what actual portfolio volatility and portfolio drawdown would result at the current allocation. If risk utilization (ratio of actual to target risk) exceeds 1.0, allocation is reduced by an adjustment factor that grows exponentially with overutilization. This implements a form of dynamic feedback that avoids overexposure.
Mathematically, a risk adjustment factor r_adjust is calculated: if risk utilization u > 1, then r_adjust = exp(-0.5 × (u - 1)). This exponential function ensures that moderate overutilization is gently corrected, while strong overutilization triggers drastic reductions. The factor 0.5 in the exponent was empirically calibrated to achieve a balanced ratio between sensitivity and stability.
5. Component 3: Valuation Analysis
5.1 Theoretical Foundations of Fundamental Valuation
DEAM's valuation component is based on the fundamental premise that the intrinsic value of a security is determined by its future cash flows and that deviations between market price and intrinsic value are eventually corrected. Graham and Dodd (1934) established in "Security Analysis" the basic principles of fundamental analysis that remain relevant today. Translated into modern portfolio context, this means that markets with high valuation metrics (high price-earnings ratios) should have lower expected returns than cheaply valued markets.
Campbell and Shiller (1988) developed the Cyclically Adjusted P/E Ratio (CAPE), which smooths earnings over a full business cycle. Their empirical analysis showed that this ratio has significant predictive power for 10-year returns. Asness, Moskowitz, and Pedersen (2013) demonstrated in "Value and Momentum Everywhere" that value effects exist not only in individual stocks but also in asset classes and markets.
5.2 Equity Risk Premium as Central Valuation Metric
The Equity Risk Premium (ERP) is defined as the expected excess return of stocks over risk-free government bonds. It is the theoretical heart of valuation analysis, as it represents the compensation investors demand for bearing equity risk. Damodaran (2012) discusses in "Equity Risk Premiums: Determinants, Estimation and Implications" various methods for ERP estimation.
DEAM calculates ERP not through a single method but combines four complementary approaches with different weights. This multi-method strategy increases estimation robustness and avoids dependence on single, potentially erroneous inputs.
The first method (35% weight) uses earnings yield, calculated as 1/P/E or directly from operating earnings data, and subtracts the 10-year Treasury yield. This method follows Fed Model logic (Yardeni, 2003), although this model has theoretical weaknesses as it does not consistently treat inflation (Asness, 2003).
The second method (30% weight) extends earnings yield by share buyback yield. Share buybacks are a form of capital return to shareholders and increase value per share. Boudoukh et al. (2007) showed in "The Total Shareholder Yield" that the sum of dividend yield and buyback yield is a better predictor of future returns than dividend yield alone.
The third method (20% weight) implements the Gordon Growth Model (Gordon, 1962), which models stock value as the sum of discounted future dividends. Under constant growth g assumption: Expected Return = Dividend Yield + g. The model estimates sustainable growth as g = ROE × (1 - Payout Ratio), where ROE is return on equity and payout ratio is the ratio of dividends to earnings. This formula follows from equity theory: unretained earnings are reinvested at ROE and generate additional earnings growth.
The fourth method (15% weight) combines total shareholder yield (Dividend + Buybacks) with implied growth derived from revenue growth. This method considers that companies with strong revenue growth should generate higher future earnings, even if current valuations do not yet fully reflect this.
The final ERP is the weighted average of these four methods. A high ERP (above 4%) signals attractive valuations and increases the valuation score to 95 out of 100 possible points. A negative ERP, where stocks have lower expected returns than bonds, results in a minimal score of 10.
5.3 Quality Adjustments to Valuation
Valuation metrics alone can be misleading if not interpreted in the context of company quality. A company with a low P/E may be cheap or fundamentally problematic. The model therefore implements quality adjustments based on growth, profitability, and capital structure.
Revenue growth above 10% annually adds 10 points to the valuation score, moderate growth above 5% adds 5 points. This adjustment reflects that growth has independent value (Modigliani and Miller, 1961, extended by later growth theory). Net margin above 15% signals pricing power and operational efficiency and increases the score by 5 points, while low margins below 8% indicate competitive pressure and subtract 5 points.
Return on equity (ROE) above 20% characterizes outstanding capital efficiency and increases the score by 5 points. Piotroski (2000) showed in "Value Investing: The Use of Historical Financial Statement Information" that fundamental quality signals such as high ROE can improve the performance of value strategies.
Capital structure is evaluated through the debt-to-equity ratio. A conservative ratio below 1.0 multiplies the valuation score by 1.2, while high leverage above 2.0 applies a multiplier of 0.8. This adjustment reflects that high debt constrains financial flexibility and can become problematic in crisis times (Korteweg, 2010).
6. Component 4: Sentiment Analysis
6.1 The Role of Sentiment in Financial Markets
Investor sentiment, defined as the collective psychological attitude of market participants, influences asset prices independently of fundamental data. Baker and Wurgler (2006, 2007) developed a sentiment index and showed that periods of high sentiment are followed by overvaluations that later correct. This insight justifies integrating a sentiment component into allocation decisions.
Sentiment is difficult to measure directly but can be proxied through market indicators. The VIX is the most widely used sentiment indicator, as it aggregates implied volatility from option prices. High VIX values reflect elevated uncertainty and risk aversion, while low values signal market comfort. Whaley (2009) refers to the VIX as the "Investor Fear Gauge" and documents its role as a contrarian indicator: extremely high values typically occur at market bottoms, while low values occur at tops.
6.2 VIX-Based Sentiment Assessment
DEAM uses statistical normalization of the VIX by calculating the Z-score: z = (VIX_current - VIX_average) / VIX_standard_deviation. The Z-score indicates how many standard deviations the current VIX is from the historical average. This approach is more robust than absolute thresholds, as it adapts to the average volatility level, which can vary over longer periods.
A Z-score below -1.5 (VIX is 1.5 standard deviations below average) signals exceptionally low risk perception and adds 40 points to the sentiment score. This may seem counterintuitive—shouldn't low fear be bullish? However, the logic follows the contrarian principle: when no one is afraid, everyone is already invested, and there is limited further upside potential (Zweig, 1973). Conversely, a Z-score above 1.5 (extreme fear) adds -40 points, reflecting market panic but simultaneously suggesting potential buying opportunities.
6.3 VIX Term Structure as Sentiment Signal
The VIX term structure provides additional sentiment information. Normally, the VIX trades in contango, meaning longer-term VIX futures have higher prices than short-term. This reflects that short-term volatility is currently known, while long-term volatility is more uncertain and carries a risk premium. The model compares the VIX with VIX9D (9-day volatility) and identifies backwardation (VIX > 1.05 × VIX9D) and steep backwardation (VIX > 1.15 × VIX9D).
Backwardation occurs when short-term implied volatility is higher than longer-term, which typically happens during market stress. Investors anticipate immediate turbulence but expect calming. Psychologically, this reflects acute fear. The model subtracts 15 points for backwardation and 30 for steep backwardation, as these constellations signal elevated risk. Simon and Wiggins (2001) analyzed the VIX futures curve and showed that backwardation is associated with market declines.
6.4 Safe-Haven Flows
During crisis times, investors flee from risky assets into safe havens: gold, US dollar, and Japanese yen. This "flight to quality" is a sentiment signal. The model calculates the performance of these assets relative to stocks over the last 20 trading days. When gold or the dollar strongly rise while stocks fall, this indicates elevated risk aversion.
The safe-haven component is calculated as the difference between safe-haven performance and stock performance. Positive values (safe havens outperform) subtract up to 20 points from the sentiment score, negative values (stocks outperform) add up to 10 points. The asymmetric treatment (larger deduction for risk-off than bonus for risk-on) reflects that risk-off movements are typically sharper and more informative than risk-on phases.
Baur and Lucey (2010) examined safe-haven properties of gold and showed that gold indeed exhibits negative correlation with stocks during extreme market movements, confirming its role as crisis protection.
7. Component 5: Macroeconomic Analysis
7.1 The Yield Curve as Economic Indicator
The yield curve, represented as yields of government bonds of various maturities, contains aggregated expectations about future interest rates, inflation, and economic growth. The slope of the yield curve has remarkable predictive power for recessions. Estrella and Mishkin (1998) showed that an inverted yield curve (short-term rates higher than long-term) predicts recessions with high reliability. This is because inverted curves reflect restrictive monetary policy: the central bank raises short-term rates to combat inflation, dampening economic activity.
DEAM calculates two spread measures: the 2-year-minus-10-year spread and the 3-month-minus-10-year spread. A steep, positive curve (spreads above 1.5% and 2% respectively) signals healthy growth expectations and generates the maximum yield curve score of 40 points. A flat curve (spreads near zero) reduces the score to 20 points. An inverted curve (negative spreads) is particularly alarming and results in only 10 points.
The choice of two different spreads increases analysis robustness. The 2-10 spread is most established in academic literature, while the 3M-10Y spread is often considered more sensitive, as the 3-month rate directly reflects current monetary policy (Ang, Piazzesi, and Wei, 2006).
7.2 Credit Conditions and Spreads
Credit spreads—the yield difference between risky corporate bonds and safe government bonds—reflect risk perception in the credit market. Gilchrist and Zakrajšek (2012) constructed an "Excess Bond Premium" that measures the component of credit spreads not explained by fundamentals and showed this is a predictor of future economic activity and stock returns.
The model approximates credit spread by comparing the yield of high-yield bond ETFs (HYG) with investment-grade bond ETFs (LQD). A narrow spread below 200 basis points signals healthy credit conditions and risk appetite, contributing 30 points to the macro score. Very wide spreads above 1000 basis points (as during the 2008 financial crisis) signal credit crunch and generate zero points.
Additionally, the model evaluates whether "flight to quality" is occurring, identified through strong performance of Treasury bonds (TLT) with simultaneous weakness in high-yield bonds. This constellation indicates elevated risk aversion and reduces the credit conditions score.
7.3 Financial Stability at Corporate Level
While the yield curve and credit spreads reflect macroeconomic conditions, financial stability evaluates the health of companies themselves. The model uses the aggregated debt-to-equity ratio and return on equity of the S&P 500 as proxies for corporate health.
A low leverage level below 0.5 combined with high ROE above 15% signals robust corporate balance sheets and generates 20 points. This combination is particularly valuable as it represents both defensive strength (low debt means crisis resistance) and offensive strength (high ROE means earnings power). High leverage above 1.5 generates only 5 points, as it implies vulnerability to interest rate increases and recessions.
Korteweg (2010) showed in "The Net Benefits to Leverage" that optimal debt maximizes firm value, but excessive debt increases distress costs. At the aggregated market level, high debt indicates fragilities that can become problematic during stress phases.
8. Component 6: Crisis Detection
8.1 The Need for Systematic Crisis Detection
Financial crises are rare but extremely impactful events that suspend normal statistical relationships. During normal market volatility, diversified portfolios and traditional risk management approaches function, but during systemic crises, seemingly independent assets suddenly correlate strongly, and losses exceed historical expectations (Longin and Solnik, 2001). This justifies a separate crisis detection mechanism that operates independently of regular allocation components.
Reinhart and Rogoff (2009) documented in "This Time Is Different: Eight Centuries of Financial Folly" recurring patterns in financial crises: extreme volatility, massive drawdowns, credit market dysfunction, and asset price collapse. DEAM operationalizes these patterns into quantifiable crisis indicators.
8.2 Multi-Signal Crisis Identification
The model uses a counter-based approach where various stress signals are identified and aggregated. This methodology is more robust than relying on a single indicator, as true crises typically occur simultaneously across multiple dimensions. A single signal may be a false alarm, but the simultaneous presence of multiple signals increases confidence.
The first indicator is a VIX above the crisis threshold (default 40), adding one point. A VIX above 60 (as in 2008 and March 2020) adds two additional points, as such extreme values are historically very rare. This tiered approach captures the intensity of volatility.
The second indicator is market drawdown. A drawdown above 15% adds one point, as corrections of this magnitude can be potential harbingers of larger crises. A drawdown above 25% adds another point, as historical bear markets typically encompass 25-40% drawdowns.
The third indicator is credit market spreads above 500 basis points, adding one point. Such wide spreads occur only during significant credit market disruptions, as in 2008 during the Lehman crisis.
The fourth indicator identifies simultaneous losses in stocks and bonds. Normally, Treasury bonds act as a hedge against equity risk (negative correlation), but when both fall simultaneously, this indicates systemic liquidity problems or inflation/stagflation fears. The model checks whether both SPY and TLT have fallen more than 10% and 5% respectively over 5 trading days, adding two points.
The fifth indicator is a volume spike combined with negative returns. Extreme trading volumes (above twice the 20-day average) with falling prices signal panic selling. This adds one point.
A crisis situation is diagnosed when at least 3 indicators trigger, a severe crisis at 5 or more indicators. These thresholds were calibrated through historical backtesting to identify true crises (2008, 2020) without generating excessive false alarms.
8.3 Crisis-Based Allocation Override
When a crisis is detected, the system overrides the normal allocation recommendation and caps equity allocation at maximum 25%. In a severe crisis, the cap is set at 10%. This drastic defensive posture follows the empirical observation that crises typically require time to develop and that early reduction can avoid substantial losses (Faber, 2007).
This override logic implements a "safety first" principle: in situations of existential danger to the portfolio, capital preservation becomes the top priority. Roy (1952) formalized this approach in "Safety First and the Holding of Assets," arguing that investors should primarily minimize ruin probability.
9. Integration and Final Allocation Calculation
9.1 Component Weighting
The final allocation recommendation emerges through weighted aggregation of the five components. The standard weighting is: Market Regime 35%, Risk Management 25%, Valuation 20%, Sentiment 15%, Macro 5%. These weights reflect both theoretical considerations and empirical backtesting results.
The highest weighting of market regime is based on evidence that trend-following and momentum strategies have delivered robust results across various asset classes and time periods (Moskowitz, Ooi, and Pedersen, 2012). Current market momentum is highly informative for the near future, although it provides no information about long-term expectations.
The substantial weighting of risk management (25%) follows from the central importance of risk control. Wealth preservation is the foundation of long-term wealth creation, and systematic risk management is demonstrably value-creating (Moreira and Muir, 2017).
The valuation component receives 20% weight, based on the long-term mean reversion of valuation metrics. While valuation has limited short-term predictive power (bull and bear markets can begin at any valuation), the long-term relationship between valuation and returns is robustly documented (Campbell and Shiller, 1988).
Sentiment (15%) and Macro (5%) receive lower weights, as these factors are subtler and harder to measure. Sentiment is valuable as a contrarian indicator at extremes but less informative in normal ranges. Macro variables such as the yield curve have strong predictive power for recessions, but the transmission from recessions to stock market performance is complex and temporally variable.
9.2 Model Type Adjustments
DEAM allows users to choose between four model types: Conservative, Balanced, Aggressive, and Adaptive. This choice modifies the final allocation through additive adjustments.
Conservative mode subtracts 10 percentage points from allocation, resulting in consistently more cautious positioning. This is suitable for risk-averse investors or those with limited investment horizons. Aggressive mode adds 10 percentage points, suitable for risk-tolerant investors with long horizons.
Adaptive mode implements procyclical adjustment based on short-term momentum: if the market has risen more than 5% in the last 20 days, 5 percentage points are added; if it has declined more than 5%, 5 points are subtracted. This logic follows the observation that short-term momentum persists (Jegadeesh and Titman, 1993), but the moderate size of adjustment avoids excessive timing bets.
Balanced mode makes no adjustment and uses raw model output. This neutral setting is suitable for investors who wish to trust model recommendations unchanged.
9.3 Smoothing and Stability
The allocation resulting from aggregation undergoes final smoothing through a simple moving average over 3 periods. This smoothing is crucial for model practicality, as it reduces frequent trading and thus transaction costs. Without smoothing, the model could fluctuate between adjacent allocations with every small input change.
The choice of 3 periods as smoothing window is a compromise between responsiveness and stability. Longer smoothing would excessively delay signals and impede response to true regime changes. Shorter or no smoothing would allow too much noise. Empirical tests showed that 3-period smoothing offers an optimal ratio between these goals.
10. Visualization and Interpretation
10.1 Main Output: Equity Allocation
DEAM's primary output is a time series from 0 to 100 representing the recommended percentage allocation to equities. This representation is intuitive: 100% means full investment in stocks (specifically: an S&P 500 ETF), 0% means complete cash position, and intermediate values correspond to mixed portfolios. A value of 60% means, for example: invest 60% of wealth in SPY, hold 40% in money market instruments or cash.
The time series is color-coded to enable quick visual interpretation. Green shades represent high allocations (above 80%, bullish), red shades low allocations (below 20%, bearish), and neutral colors middle allocations. The chart background is dynamically colored based on the signal, enhancing readability in different market phases.
10.2 Dashboard Metrics
A tabular dashboard presents key metrics compactly. This includes current allocation, cash allocation (complement), an aggregated signal (BULLISH/NEUTRAL/BEARISH), current market regime, VIX level, market drawdown, and crisis status.
Additionally, fundamental metrics are displayed: P/E Ratio, Equity Risk Premium, Return on Equity, Debt-to-Equity Ratio, and Total Shareholder Yield. This transparency allows users to understand model decisions and form their own assessments.
Component scores (Regime, Risk, Valuation, Sentiment, Macro) are also displayed, each normalized on a 0-100 scale. This shows which factors primarily drive the current recommendation. If, for example, the Risk score is very low (20) while other scores are moderate (50-60), this indicates that risk management considerations are pulling allocation down.
10.3 Component Breakdown (Optional)
Advanced users can display individual components as separate lines in the chart. This enables analysis of component dynamics: do all components move synchronously, or are there divergences? Divergences can be particularly informative. If, for example, the market regime is bullish (high score) but the valuation component is very negative, this signals an overbought market not fundamentally supported—a classic "bubble warning."
This feature is disabled by default to keep the chart clean but can be activated for deeper analysis.
10.4 Confidence Bands
The model optionally displays uncertainty bands around the main allocation line. These are calculated as ±1 standard deviation of allocation over a rolling 20-period window. Wide bands indicate high volatility of model recommendations, suggesting uncertain market conditions. Narrow bands indicate stable recommendations.
This visualization implements a concept of epistemic uncertainty—uncertainty about the model estimate itself, not just market volatility. In phases where various indicators send conflicting signals, the allocation recommendation becomes more volatile, manifesting in wider bands. Users can understand this as a warning to act more cautiously or consult alternative information sources.
11. Alert System
11.1 Allocation Alerts
DEAM implements an alert system that notifies users of significant events. Allocation alerts trigger when smoothed allocation crosses certain thresholds. An alert is generated when allocation reaches 80% (from below), signaling strong bullish conditions. Another alert triggers when allocation falls to 20%, indicating defensive positioning.
These thresholds are not arbitrary but correspond with boundaries between model regimes. An allocation of 80% roughly corresponds to a clear bull market regime, while 20% corresponds to a bear market regime. Alerts at these points are therefore informative about fundamental regime shifts.
11.2 Crisis Alerts
Separate alerts trigger upon detection of crisis and severe crisis. These alerts have highest priority as they signal large risks. A crisis alert should prompt investors to review their portfolio and potentially take defensive measures beyond the automatic model recommendation (e.g., hedging through put options, rebalancing to more defensive sectors).
11.3 Regime Change Alerts
An alert triggers upon change of market regime (e.g., from Neutral to Correction, or from Bull Market to Strong Bull). Regime changes are highly informative events that typically entail substantial allocation changes. These alerts enable investors to proactively respond to changes in market dynamics.
11.4 Risk Breach Alerts
A specialized alert triggers when actual portfolio risk utilization exceeds target parameters by 20%. This is a warning signal that the risk management system is reaching its limits, possibly because market volatility is rising faster than allocation can be reduced. In such situations, investors should consider manual interventions.
12. Practical Application and Limitations
12.1 Portfolio Implementation
DEAM generates a recommendation for allocation between equities (S&P 500) and cash. Implementation by an investor can take various forms. The most direct method is using an S&P 500 ETF (e.g., SPY, VOO) for equity allocation and a money market fund or savings account for cash allocation.
A rebalancing strategy is required to synchronize actual allocation with model recommendation. Two approaches are possible: (1) rule-based rebalancing at every 10% deviation between actual and target, or (2) time-based monthly rebalancing. Both have trade-offs between responsiveness and transaction costs. Empirical evidence (Jaconetti, Kinniry, and Zilbering, 2010) suggests rebalancing frequency has moderate impact on performance, and investors should optimize based on their transaction costs.
12.2 Adaptation to Individual Preferences
The model offers numerous adjustment parameters. Component weights can be modified if investors place more or less belief in certain factors. A fundamentally-oriented investor might increase valuation weight, while a technical trader might increase regime weight.
Risk target parameters (target volatility, max drawdown) should be adapted to individual risk tolerance. Younger investors with long investment horizons can choose higher target volatility (15-18%), while retirees may prefer lower volatility (8-10%). This adjustment systematically shifts average equity allocation.
Crisis thresholds can be adjusted based on preference for sensitivity versus specificity of crisis detection. Lower thresholds (e.g., VIX > 35 instead of 40) increase sensitivity (more crises are detected) but reduce specificity (more false alarms). Higher thresholds have the reverse effect.
12.3 Limitations and Disclaimers
DEAM is based on historical relationships between indicators and market performance. There is no guarantee these relationships will persist in the future. Structural changes in markets (e.g., through regulation, technology, or central bank policy) can break established patterns. This is the fundamental problem of induction in financial science (Taleb, 2007).
The model is optimized for US equities (S&P 500). Application to other markets (international stocks, bonds, commodities) would require recalibration. The indicators and thresholds are specific to the statistical properties of the US equity market.
The model cannot eliminate losses. Even with perfect crisis prediction, an investor following the model would lose money in bear markets—just less than a buy-and-hold investor. The goal is risk-adjusted performance improvement, not risk elimination.
Transaction costs are not modeled. In practice, spreads, commissions, and taxes reduce net returns. Frequent trading can cause substantial costs. Model smoothing helps minimize this, but users should consider their specific cost situation.
The model reacts to information; it does not anticipate it. During sudden shocks (e.g., 9/11, COVID-19 lockdowns), the model can only react after price movements, not before. This limitation is inherent to all reactive systems.
12.4 Relationship to Other Strategies
DEAM is a tactical asset allocation approach and should be viewed as a complement, not replacement, for strategic asset allocation. Brinson, Hood, and Beebower (1986) showed in their influential study "Determinants of Portfolio Performance" that strategic asset allocation (long-term policy allocation) explains the majority of portfolio performance, but this leaves room for tactical adjustments based on market timing.
The model can be combined with value and momentum strategies at the individual stock level. While DEAM controls overall market exposure, within-equity decisions can be optimized through stock-picking models. This separation between strategic (market exposure) and tactical (stock selection) levels follows classical portfolio theory.
The model does not replace diversification across asset classes. A complete portfolio should also include bonds, international stocks, real estate, and alternative investments. DEAM addresses only the US equity allocation decision within a broader portfolio.
13. Scientific Foundation and Evaluation
13.1 Theoretical Consistency
DEAM's components are based on established financial theory and empirical evidence. The market regime component follows from regime-switching models (Hamilton, 1989) and trend-following literature. The risk management component implements volatility targeting (Moreira and Muir, 2017) and modern portfolio theory (Markowitz, 1952). The valuation component is based on discounted cash flow theory and empirical value research (Campbell and Shiller, 1988; Fama and French, 1992). The sentiment component integrates behavioral finance (Baker and Wurgler, 2006). The macro component uses established business cycle indicators (Estrella and Mishkin, 1998).
This theoretical grounding distinguishes DEAM from purely data-mining-based approaches that identify patterns without causal theory. Theory-guided models have greater probability of functioning out-of-sample, as they are based on fundamental mechanisms, not random correlations (Lo and MacKinlay, 1990).
13.2 Empirical Validation
While this document does not present detailed backtest analysis, it should be noted that rigorous validation of a tactical asset allocation model should include several elements:
In-sample testing establishes whether the model functions at all in the data on which it was calibrated. Out-of-sample testing is crucial: the model should be tested in time periods not used for development. Walk-forward analysis, where the model is successively trained on rolling windows and tested in the next window, approximates real implementation.
Performance metrics should be risk-adjusted. Pure return consideration is misleading, as higher returns often only compensate for higher risk. Sharpe Ratio, Sortino Ratio, Calmar Ratio, and Maximum Drawdown are relevant metrics. Comparison with benchmarks (Buy-and-Hold S&P 500, 60/40 Stock/Bond portfolio) contextualizes performance.
Robustness checks test sensitivity to parameter variation. If the model only functions at specific parameter settings, this indicates overfitting. Robust models show consistent performance over a range of plausible parameters.
13.3 Comparison with Existing Literature
DEAM fits into the broader literature on tactical asset allocation. Faber (2007) presented a simple momentum-based timing system that goes long when the market is above its 10-month average, otherwise cash. This simple system avoided large drawdowns in bear markets. DEAM can be understood as a sophistication of this approach that integrates multiple information sources.
Ilmanen (2011) discusses various timing factors in "Expected Returns" and argues for multi-factor approaches. DEAM operationalizes this philosophy. Asness, Moskowitz, and Pedersen (2013) showed that value and momentum effects work across asset classes, justifying cross-asset application of regime and valuation signals.
Ang (2014) emphasizes in "Asset Management: A Systematic Approach to Factor Investing" the importance of systematic, rule-based approaches over discretionary decisions. DEAM is fully systematic and eliminates emotional biases that plague individual investors (overconfidence, hindsight bias, loss aversion).
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Extreme Pressure Zones Indicator (EPZ) [BullByte]Extreme Pressure Zones Indicator(EPZ)
The Extreme Pressure Zones (EPZ) Indicator is a proprietary market analysis tool designed to highlight potential overbought and oversold "pressure zones" in any financial chart. It does this by combining several unique measurements of price action and volume into a single, bounded oscillator (0–100). Unlike simple momentum or volatility indicators, EPZ captures multiple facets of market pressure: price rejection, trend momentum, supply/demand imbalance, and institutional (smart money) flow. This is not a random mashup of generic indicators; each component was chosen and weighted to reveal extreme market conditions that often precede reversals or strong continuations.
What it is?
EPZ estimates buying/selling pressure and highlights potential extreme zones with a single, bounded 0–100 oscillator built from four normalized components. Context-aware weighting adapts to volatility, trendiness, and relative volume. Visual tools include adaptive thresholds, confirmed-on-close extremes, divergence, an MTF dashboard, and optional gradient candles.
Purpose and originality (not a mashup)
Purpose: Identify when pressure is building or reaching potential extremes while filtering noise across regimes and symbols.
Originality: EPZ integrates price rejection, momentum cascade, pressure distribution, and smart money flow into one bounded scale with context-aware weighting. It is not a cosmetic mashup of public indicators.
Why a trader might use EPZ
EPZ provides a multi-dimensional gauge of market extremes that standalone indicators may miss. Traders might use it to:
Spot Reversals: When EPZ enters an "Extreme High" zone (high red), it implies selling pressure might soon dominate. This can hint at a topside reversal or at least a pause in rallies. Conversely, "Extreme Low" (green) can highlight bottom-fish opportunities. The indicator's divergence module (optional) also finds hidden bullish/bearish divergences between price and EPZ, a clue that price momentum is weakening.
Measure Momentum Shifts: Because EPZ blends momentum and volume, it reacts faster than many single metrics. A rising MPO indicates building bullish pressure, while a falling MPO shows increasing bearish pressure. Traders can use this like a refined RSI: above 50 means bullish bias, below 50 means bearish bias, but with context provided by the thresholds.
Filter Trades: In trend-following systems, one could require EPZ to be in the bullish (green) zone before taking longs, or avoid new trades when EPZ is extreme. In mean-reversion systems, one might specifically look to fade extremes flagged by EPZ.
Multi-Timeframe Confirmation: The dashboard can fetch a higher timeframe EPZ value. For example, you might trade a 15-minute chart only when the 60-minute EPZ agrees on pressure direction.
Components and how they're combined
Rejection (PRV) – Captures price rejection based on candle wicks and volume (see Price Rejection Volume).
Momentum Cascade (MCD) – Blends multiple momentum periods (3,5,8,13) into a normalized momentum score.
Pressure Distribution (PDI) – Measures net buy/sell pressure by comparing volume on up vs down candles.
Smart Money Flow (SMF) – An adaptation of money flow index that emphasizes unusual volume spikes.
Each of these components produces a 0–100 value (higher means more bullish pressure). They are then weighted and averaged into the final Market Pressure Oscillator (MPO), which is smoothed and scaled. By combining these four views, EPZ stands out as a comprehensive pressure gauge – the whole is greater than the sum of parts
Context-aware weighting:
Higher volatility → more PRV weight
Trendiness up (RSI of ATR > 25) → more MCD weight
Relative volume > 1.2x → more PDI weight
SMF holds a stable weight
The weighted average is smoothed and scaled into MPO ∈ with 50 as the neutral midline.
What makes EPZ stand out
Four orthogonal inputs (price action, momentum, pressure, flow) unified in a single bounded oscillator with consistent thresholds.
Adaptive thresholds (optional) plus robust extreme detection that also triggers on crossovers, so static thresholds work reliably too.
Confirm Extremes on Bar Close (default ON): dots/arrows/labels/alerts print on closed bars to avoid repaint confusion.
Clean dashboard, divergence tools, pre-alerts, and optional on-price gradients. Visual 3D layering uses offsets for depth only,no lookahead.
Recommended markets and timeframes
Best: liquid symbols (index futures, large-cap equities, major FX, BTC/ETH).
Timeframes: 5–15m (more signals; consider higher thresholds), 1H–4H (balanced), 1D (clear regimes).
Use caution on illiquid or very low TFs where wick/volume geometry is erratic.
Logic and thresholds
MPO ∈ ; 50 = neutral. Above 50 = bullish pressure; below 50 = bearish.
Static thresholds (defaults): thrHigh = 70, thrLow = 30; warning bands 5 pts inside extremes (65/35).
Adaptive thresholds (optional):
thrHigh = min(BaseHigh + 5, mean(MPO,100) + stdev(MPO,100) × ExtremeSensitivity)
thrLow = max(BaseLow − 5, mean(MPO,100) − stdev(MPO,100) × ExtremeSensitivity)
Extreme detection
High: MPO ≥ thrHigh with peak/slope or crossover filter.
Low: MPO ≤ thrLow with trough/slope or crossover filter.
Cooldown: 5 bars (default). A new extreme will not print until the cooldown elapses, even if MPO re-enters the zone.
Confirmation
"Confirm Extremes on Bar Close" (default ON) gates extreme markers, pre-alerts, and alerts to closed bars (non-repainting).
Divergences
Pivot-based bullish/bearish divergence; tags appear only after left/right bars elapse (lookbackPivot).
MTF
HTF MPO retrieved with lookahead_off; values can update intrabar and finalize at HTF close. This is disclosed and expected.
Inputs and defaults (key ones)
Core: Sensitivity=1.0; Analysis Period=14; Smoothing=3; Adaptive Thresholds=OFF.
Extremes: Base High=70, Base Low=30; Extreme Sensitivity=1.5; Confirm Extremes on Bar Close=ON; Cooldown=5; Dot size Small/Tiny.
Visuals: Heatmap ON; 3D depth optional; Strength bars ON; Pre-alerts OFF; Divergences ON with tags ON; Gradient candles OFF; Glow ON.
Dashboard: ON; Position=Top Right; Size=Normal; MTF ON; HTF=60m; compact overlay table on price chart.
Advanced caps: Max Oscillator Labels=80; Max Extreme Guide Lines=80; Divergence objects=60.
Dashboard: what each element means
Header: EPZ ANALYSIS.
Large readout: Current MPO; color reflects state (extreme, approaching, or neutral).
Status badge: "Extreme High/Low", "Approaching High/Low", "Bullish/Neutral/Bearish".
HTF cell (when MTF ON): Higher-timeframe MPO, color-coded vs extremes; updates intrabar, settles at HTF close.
Predicted (when MTF OFF): Simple MPO extrapolation using momentum/acceleration—illustrative only.
Thresholds: Current thrHigh/thrLow (static or adaptive).
Components: ASCII bars + values for PRV, MCD, PDI, SMF.
Market metrics: Volume Ratio (x) and ATR% of price.
Strength: Bar indicator of |MPO − 50| × 2.
Confidence: Heuristic gauge (100 in extremes, 70 in warnings, 50 with divergence, else |MPO − 50|). Convenience only, not probability.
How to read the oscillator
MPO Value (0–100): A reading of 50 is neutral. Values above ~55 are increasingly bullish (green), while below ~45 are increasingly bearish (red). Think of these as "market pressure".
Extreme Zones: When MPO climbs into the bright orange/red area (above the base-high line, default 70), the chart will display a dot and downward arrow marking that extreme. Traders often treat this as a sign to tighten stops or look for shorts. Similarly, a bright green dot/up-arrow appears when MPO falls below the base-low (30), hinting at a bullish setup.
Heatmap/Candles: If "Pressure Heatmap" is enabled, the background of the oscillator pane will fade green or red depending on MPO. Users can optionally color the price candles by MPO value (gradient candles) to see these extremes on the main chart.
Prediction Zone(optional): A dashed projection line extends the MPO forward by a small number of bars (prediction_bars) using current MPO momentum and acceleration. This is a heuristic extrapolation best used for short horizons (1–5 bars) to anticipate whether MPO may touch a warning or extreme zone. It is provisional and becomes less reliable with longer projection lengths — always confirm predicted moves with bar-close MPO and HTF context before acting.
Divergences: When price makes a higher high but EPZ makes a lower high (bearish divergence), the indicator can draw dotted lines and a "Bear Div" tag. The opposite (lower low price, higher EPZ) gives "Bull Div". These signals confirm waning momentum at extremes.
Zones: Warning bands near extremes; Extreme zones beyond thresholds.
Crossovers: MPO rising through 35 suggests easing downside pressure; falling through 65 suggests waning upside pressure.
Dots/arrows: Extreme markers appear on closed bars when confirmation is ON and respect the 5-bar cooldown.
Pre-alert dots (optional): Proximity cues in warning zones; also gated to bar close when confirmation is ON.
Histogram: Distance from neutral (50); highlights strengthening or weakening pressure.
Divergence tags: "Bear Div" = higher price high with lower MPO high; "Bull Div" = lower price low with higher MPO low.
Pressure Heatmap : Layered gradient background that visually highlights pressure strength across the MPO scale; adjustable intensity and optional zone overlays (warning / extreme) for quick visual scanning.
A typical reading: If the oscillator is rising from neutral towards the high zone (green→orange→red), the chart may see strong buying culminating in a stall. If it then turns down from the extreme, that peak EPZ dot signals sell pressure.
Alerts
EPZ: Extreme Context — fires on confirmed extremes (respects cooldown).
EPZ: Approaching Threshold — fires in warning zones if no extreme.
EPZ: Divergence — fires on confirmed pivot divergences.
Tip: Set alerts to "Once per bar close" to align with confirmation and avoid intrabar repaint.
Practical usage ideas
Trend continuation: In positive regimes (MPO > 50 and rising), pullbacks holding above 50 often precede continuation; mirror for bearish regimes.
Exhaustion caution: E High/E Low can mark exhaustion risk; many wait for MPO rollover or divergence to time fades or partial exits.
Adaptive thresholds: Useful on assets with shifting volatility regimes to maintain meaningful "extreme" levels.
MTF alignment: Prefer setups that agree with the HTF MPO to reduce countertrend noise.
Examples
Screenshots captured in TradingView Replay to freeze the bar at close so values don't fluctuate intrabar. These examples use default settings and are reproducible on the same bars; they are for illustration, not cherry-picking or performance claims.
Example 1 — BTCUSDT, 1h — E Low
MPO closed at 26.6 (below the 30 extreme), printing a confirmed E Low. HTF MPO is 26.6, so higher-timeframe pressure remains bearish. Components are subdued (Momentum/Pressure/Smart$ ≈ 29–37), with Vol Ratio ≈ 1.19x and ATR% ≈ 0.37%. A prior Bear Div flagged weakening impulse into the drop. With cooldown set to 5 bars, new extremes are rate-limited. Many traders wait for MPO to curl up and reclaim 35 or for a fresh Bull Div before considering countertrend ideas; if MPO cannot reclaim 35 and HTF stays weak, treat bounces cautiously. Educational illustration only.
Example 2 — ETHUSD, 30m — E High
A strong impulse pushed MPO into the extreme zone (≥ 70), printing a confirmed E High on close. Shortly after, MPO cooled to ~61.5 while a Bear Div appeared, showing momentum lag as price pushed a higher high. Volume and volatility were elevated (≈ 1.79x / 1.25%). With a 5-bar cooldown, additional extremes won't print immediately. Some treat E High as exhaustion risk—either waiting for MPO rollover under 65/50 to fade, or for a pullback that holds above 50 to re-join the trend if higher-timeframe pressure remains constructive. Educational illustration only.
Known limitations and caveats
The MPO line itself can change intrabar; extreme markers/alerts do not repaint when "Confirm Extremes on Bar Close" is ON.
HTF values settle at the close of the HTF bar.
Illiquid symbols or very low TFs can be noisy; consider higher thresholds or longer smoothing.
Prediction line (when enabled) is a visual extrapolation only.
For coders
Pine v6. MTF via request.security with lookahead_off.
Extremes include crossover triggers so static thresholds also yield E High/E Low.
Extreme markers and pre-alerts are gated by barstate.isconfirmed when confirmation is ON.
Arrays prune oldest objects to respect resource limits; defaults (80/80/60) are conservative for low TFs.
3D layering uses negative offsets purely for drawing depth (no lookahead).
Screenshot methodology:
To make labels legible and to demonstrate non-repainting behavior, the examples were captured in TradingView Replay with "Confirm Extremes on Bar Close" enabled. Replay is used only to freeze the bar at close so plots don't change intrabar. The examples use default settings, include both Extreme Low and Extreme High cases, and can be reproduced by scrolling to the same bars outside Replay. This is an educational illustration, not a performance claim.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Markets involve risk; past behavior does not guarantee future results. You are responsible for your own testing, risk management, and decisions.
Market Sentiment Trend Gauge [LevelUp]Market Sentiment Trend Gauge simplifies technical analysis by mathematically combining momentum, trend direction, volatility position, and comparison against a market benchmark, into a single trend score from -100 to +100. Displayed in a separate pane below your chart, it resolves conflicting signals from RSI, moving averages, Bollinger Bands, and market correlations, providing clear insights into trend direction, strength, and relative performance.
THE PROBLEM MARKET SENTIMENT TREND GAUGE (MSTG) SOLVES
Traditional indicators often produce conflicting signals, such as RSI showing overbought while prices rise or moving averages indicating an uptrend despite market underperformance. MSTG creates a weighted composite score to answer: "What's the overall bias for this asset?"
KEY COMPONENTS AND WEIGHTINGS
The trend score combines
▪ Momentum (25%): Normalized 14-period RSI, capped at ±100.
▪ Trend Direction (35%): 10/21-period EMA relationships,
▪ Volatility Position (20%): Price position, 20-period Bollinger Bands, capped at ±100.
▪ Market Comparison (20%): Daily performance vs. SPY benchmark, capped at ±100.
Final score = Weighted sum, smoothed with 5-period EMA.
INTERPRETING THE MSTG CHART
Trend Score Ranges and Colors
▪ Bright Green (>+30): Strong bullish; ideal for long entries.
▪ Light Green (+10 to +30): Weak bullish; cautiously favorable.
▪ Gray (-10 to +10): Neutral; avoid directional trades.
▪ Light Red (-10 to -30): Weak bearish; exercise caution.
▪ Bright Red (<-30): Strong bearish; high-risk for longs, consider shorts.
Reference Lines
▪ Zero Line (Gray): Separates bullish/bearish; crossovers signal trend changes.
▪ ±30 Lines (Dotted, Green/Red): Thresholds for strong trends.
▪ ±60 Lines (Dashed, Green/Red): Extreme strength zones (not overbought/oversold); manage risk (tighten stops, partial profits) but trends may persist.
Background Colors
▪ Green Tint (>+20): Bullish environment; favorable for longs.
▪ Red Tint (<-20): Bearish environment; caution for longs.
▪ Light Gray Tint (-20 to +20): Neutral/range-bound; wait for signals.
Extreme Readings vs. Traditional Signals
MSTG ±60 indicates maximum alignment of all factors, not reversals (unlike RSI >70/<30). Use for risk management, not automatic exits. Strong trends can sustain extremes; breakdowns occur below +30 or above -30.
INFORMATION TABLE INTERPRETATION
Trend Score Symbols
▲▲ >+30 strong bullish
▲ +10 to +30
● -10 to +10 neutral
▼ -30 to -10
▼▼ <-30 strong bearish
Colors: Green (positive), White (neutral), Red (negative).
Momentum Score
+40 to +100 strong bullish
0 to +40 moderate bullish
-40 to 0 moderate bearish
-100 to -40 strong bearish
Market vs. Stock
▪ Green: Stock outperforming market
▪ Red: Stock underperforming market
Example Interpretations:
-0.45% / +1.23% (Green): Market down, stock up = Strong relative strength
+2.10% / +1.50% (Red): Both rising, but stock lagging = Relative weakness
-1.20% / -0.80% (Green): Both falling, but stock declining less = Defensive strength
UNDERSTANDING EXTREME READINGS VS TRADITIONAL OVERBOUGHT/OVERSOLD
⚠️ Critical distinctions
Traditional Overbought/Oversold Signals:
▪ Single indicator (like RSI >70 or <30) showing momentum excess
▪ Often suggests immediate reversal or pullback expected
▪ Based on "price moved too far, too fast" concept
MSTG Extreme Readings (±60):
▪ Composite alignment of 4 different factors (momentum, trend, volatility, relative strength)
▪ Indicates maximum strength in current direction
▪ NOT a reversal signal - means "all systems extremely bullish/bearish"
Key Differences:
▪ RSI >70: "Price got ahead of itself, expect pullback"
▪ MSTG >+60: "Everything is extremely bullish right now"
▪ Strong trends can maintain extreme MSTG readings during major moves
▪ Breakdowns happen when MSTG falls below +30, not at +60
Proper Usage of Extreme Readings:
▪ Risk Management: Tighten stops, take partial profits
▪ Position Sizing: Reduce new position sizes at extremes
▪ Trend Continuation: Watch for sustained extreme readings in strong markets
▪ Exit Signals: Look for breakdown below +30, not reversal from +60
TRADING WITH MSTG
Quick Assessment
1. Check trend symbol for direction.
2. Confirm momentum strength.
3. Note relative performance color.
Examples:
▲▲ 55.2 (Green), Momentum +28.4, Outperforming: Strong buy setup.
▼ -18.6 (Red), Momentum -43.2, Underperforming: Defensive positioning.
Entry Conditions
▪ Long: stock outperforming market
- Score >+30 (bright green)
- Sustained green background
- ▲▲ symbol,
▪ Short: stock underperforming market
- Score <-30 (bright red)
- Sustained red background
- ▼▼ symbol
Avoid Trading When:
▪ Gray zone (-10 to +10).
▪ Rapid color changes or frequent zero-line crosses (choppy market).
▪ Gray background (range-bound).
Risk Management:
▪ Stop Loss: Exit on zero-line crossover against position.
▪ Take Profit: Partial at ±60 for risk control.
▪ Position Sizing: Larger when signals align; smaller in extremes or mixed conditions.
KEY ADVANTAGES
▪ Unified View: Weighted composite reduces noise and conflicts.
▪ Visual Clarity: 5-color system with gradients for rapid recognition.
▪ Market Context: Relative strength vs. SPY identifies leaders/laggards.
▪ Flexibility: Works across timeframes (1-min to weekly); customizable table.
▪ Noise Reduction: EMA smoothing minimizes false signals.
EXAMPLES
Strong Bull: Trend Score 71.9, Momentum Score 76.9
Neutral: Trend Score 0.1, Momentum Score -9.2
Strong Bear: Trend Score -51.7, Momentum Score -51.5
PERFORMANCE AND LIMITATIONS
Strengths: Trend identification, noise reduction, relative performance versus market.
Limitations: Lags at turning points, less effective in extreme volatility or non-trending markets.
Recommendations: View on multiple timeframes, combine with price action and fundamentals.
TRI - Multi-Timeframe BIASTRI - MULTI-TIMEFRAME BIAS INDICATOR
DESCRIPTION:
Advanced multi-timeframe bias indicator that analyzes market sentiment across
5 different timeframes (15m, 1h, 4h, 1d, 1w) using adaptive technical analysis.
Provides clear directional bias signals to help determine market momentum.
KEY FEATURES:
ADAPTIVE PARAMETERS: Uses different EMA lengths and weights for each timeframe
EMA TREND ANALYSIS: Fast/slow EMA crossovers with slope analysis for momentum
RSI MOMENTUM: Adaptive overbought/oversold levels based on timeframe
ADX STRENGTH: Directional movement confirmation with DI+/DI- analysis
COMPOSITE SCORING: Weighted combination of trend, momentum, and strength
TIMEFRAME ANALYSIS:
15m: EMA9/21 + High momentum weight (45%) - Ultra-responsive for scalping
1h: EMA21/50 + Medium momentum weight (35%) - Balanced for day trading
4h: EMA50/200 + Lower momentum weight (25%) - Swing trading focus
1d: EMA50/200 + Trend focused (55%) - Position trading signals
1w: EMA50/200 + Maximum trend weight (60%) - Long-term bias
BIAS SIGNALS:
STRONG BULLISH/BEARISH: Score ≥ 0.5 - Very strong directional momentum
BULLISH/BEARISH: Score ≥ 0.25 - Clear directional signals
WEAK BULLISH/BEARISH: Score ≥ 0.1 - Mild directional bias
NEUTRAL: Score < 0.1 - No clear directional preference
ALERTS:
Major Bullish/Bearish: When 4H and 1D timeframes align
High confidence signals for strategic decision making
USAGE:
Higher timeframes (1d, 1w) show primary market direction
Lower timeframes (15m, 1h) provide entry timing
Look for alignment across multiple timeframes for stronger signals
Use confidence levels to assess signal reliability
TECHNICAL COMPONENTS:
Exponential Moving Averages (EMA) for responsive trend detection
Relative Strength Index (RSI) for momentum analysis
Average Directional Index (ADX) with DI+/DI- for trend strength
Volume ratio confirmation for signal validation
Adaptive thresholds optimized for each timeframe's characteristics
Trend Score with Dynamic Stop Loss RTH
📘 Trend Score with Dynamic Stop Loss (RTH) — Guide
🔎 Overview
This indicator tracks intraday momentum during Regular Trading Hours and flags trend flips using a cumulative TrendScore. It also draws dynamic stop-loss levels and shows a live stats table for quick decision-making and journaling.
⸻
⚙️ Core Concepts
1) TrendScore (per bar)
• +1 if the current bar makes a higher high than the previous bar (counted once per bar).
• –1 if the current bar makes a lower low than the previous bar (counted once per bar).
• If a bar takes both the prior high and low, the net contribution can cancel out within that bar.
2) Cumulative TrendScore (running total)
• The per-bar TrendScore accumulates across the session to form the cumulative TrendScore (TS).
• TS resets to 0 at session open and is cleared at session close.
• Rising TS = persistent upside pressure; falling TS = persistent downside pressure.
⸻
🔄 Flip Rules (3-point reversal of the cumulative TrendScore)
A flip occurs when the cumulative TrendScore reverses by 3 points in the opposite direction of the current trend.
• Bullish Flip
• Trigger: After a decline, the cumulative TrendScore rises by +3 from its down-leg.
• Interpretation: Bulls have taken control.
• Stop-loss: the lowest price of the prior (down) leg.
• Bearish Flip
• Trigger: After a rise, the cumulative TrendScore falls by –3 from its up-leg.
• Interpretation: Bears have taken control.
• Stop-loss: the highest price of the prior (up) leg.
Flip bars are marked with ▲ (lime) for bullish and ▼ (red) for bearish.
Note: If you prefer a different reversal distance, adjust the flip distance setting in the script’s inputs (default is 3).
⸻
📏 Stop-Loss Lines
• A dotted line is drawn at the prior leg’s extreme:
Green (below price) after a bullish flip.
Red (above price) after a bearish flip.
• Options:
Remove on touch for a clean chart.
Freeze on touch to keep a visual record for journaling.
• All stop lines are cleared at session end.
⸻
🧮 Stats Table (what you see)
• Trend: Bull / Bear / Neutral
• Bars in Trend: Count since the flip bar
• Since Flip: Current close minus flip bar close
• Since SL: Current close minus active stop level
• MFE-Maximum Favorable Excursion: Highest favorable move since flip
• MAE-Maximum Adverse Excursion: Largest adverse move since flip
Table colors reflect the current trend (green for bull, red for bear).
⸻
📊 Trading Playbook
Entries
• Aggressive: Enter immediately on a flip marker.
• Conservative: Wait for a small pullback that doesn’t violate the stop.
Stops
• Place the stop at the script’s flip stop-loss line (the prior leg extreme).
Exits
Choose one style and stick with it:
• Stop-only: Exit when the stop is hit.
• Time-based: Flatten at session close.
• Targets: Scale/close at 1R, 2R.
• Trailing: Trail behind minor swings once MFE > 1R.
Ultimately Exit choice is your own edge, so you must decide for yourself.
💡 Best Practices
• Skip the first few bars after the open (gap noise).
• Use regular candles (Heikin-Ashi will distort highs/lows).
• If you want fewer flips, increase the flip distance (e.g., 4 or 5). For more
responsiveness, use 2. Otherwise, increase your time frame to 5m, 10m, 15m.
• Keep SL lines frozen (not auto-removed) if you’re journaling.
Instant Breakout Strategy with RSI & VWAPInstant Breakout Strategy with RSI & VWAP
This TradingView strategy (Pine Script v6) trades breakouts using pivot points, with optional filters for volume, momentum, RSI, and VWAP. It’s optimized for the 1-second timeframe.
Overview
The strategy identifies breakouts when price crosses above resistance (pivot highs) or below support (pivot lows). It can use basic pivot breakouts or add filters for stronger signals. Take-profit and stop-loss levels are set using ATR, and signals are shown on the chart.
Inputs
Left/Right Pivot Bars: Bars to detect pivots (default: 3). Lower values increase sensitivity.
Volume Surge Multiplier: Volume threshold vs. 20-period average (default: 1.5).
Momentum Threshold: Minimum % price change from bar open (default: 1%).
Take-Profit ATR Multiplier: ATR multiplier for take-profit (default: 9.0).
Stop-Loss ATR Multiplier: ATR multiplier for stop-loss (default: 1.0).
Use Filters: Enable/disable volume, momentum, RSI, and VWAP filters (default: off).
How It Works
1. Pivot Detection
Finds pivot highs (resistance) and lows (support) using ta.pivothigh and ta.pivotlow.
Tracks the latest pivot levels.
2. Volume Surge
Compares current volume to a 20-period volume average.
A surge occurs if volume exceeds the average times the multiplier.
3. Momentum
Measures price change from the bar’s open.
Bullish: Price rises >1% from open.
Bearish: Price falls >1% from open.
4. RSI and VWAP
RSI: 3-period RSI. Above 50 is bullish; below 50 is bearish.
VWAP: Price above VWAP is bullish; below is bearish.
5. ATR
14-period ATR sets take-profit (close ± atr * 9.0) and stop-loss (close ± atr * 1.0).
Trading Rules
Breakout Conditions
Bullish Breakout:
Price crosses above the latest pivot high.
With filters: Volume surge, bullish momentum, RSI > 50, price > VWAP.
Without filters: Only the crossover is needed.
Bearish Breakout:
Price crosses below the latest pivot low.
With filters: Volume surge, bearish momentum, RSI < 50, price < VWAP.
Without filters: Only the crossunder is needed.
Entries and Exits
Long: Enter on bullish breakout. Set take-profit and stop-loss. Close any short position.
Short: Enter on bearish breakout. Set take-profit and stop-loss. Close any long position.
Visuals
Signals: Green triangles (bullish) below bars, red triangles (bearish) above bars.
Pivot Levels: Green line (resistance), red line (support).
Indicators: RSI (blue, separate pane), VWAP (purple, on chart).
How to Use
Apply to a 1-second chart in TradingView for best results.
Adjust inputs (e.g., pivot bars, multipliers). Enable filters for stricter signals.
Watch for buy/sell triangles and monitor RSI/VWAP.
Use ATR-based take-profit/stop-loss for risk management.
Notes
Best on 1-second timeframe due to fast RSI and responsiveness.
Disable filters for more signals (less confirmation).
Backtest before live trading to check performance.
This strategy uses pivots, volume, momentum, RSI, and VWAP for clear breakout trades on the 1-second timeframe.
Wickless Tap Signals Wickless Tap Signals — TradingView Indicator (v6)
A precision signal-only tool that marks BUY/SELL events when price “retests” the base of a very strong impulse candle (no wick on the retest side) in the direction of trend.
What it does (in plain English)
Finds powerful impulse candles:
Bull case: a green candle with no lower wick (its open ≈ low).
Bear case: a red candle with no upper wick (its open ≈ high).
Confirms trend with an EMA filter:
Only looks for bullish bases while price is above the EMA.
Only looks for bearish bases while price is below the EMA.
Waits for the retest (“tap”):
Later, if price revisits the base of that wickless candle
Bullish: taps the candle’s low/open → BUY signal
Bearish: taps the candle’s high/open → SELL signal
Optional level “consumption” so each base can trigger one signal, not many.
The idea: a wickless impulse often marks strong initiative order flow. The first retest of that base frequently acts as a springboard (bull) or ceiling (bear).
Exact rules (formal)
Let tick = syminfo.mintick, tol = tapTicks * tick.
Trend filter
inUp = close > EMA(lenEMA)
inDn = close < EMA(lenEMA)
Wickless impulse candles (confirmed on bar close)
Bullish wickless: close > open and abs(low - open) ≤ tol
Bearish wickless: close < open and abs(high - open) ≤ tol
When such a candle closes with trend alignment:
Store bullTapLevel = low (for bull case) and its bar index.
Store bearTapLevel = high (for bear case) and its bar index.
Signals (must happen on a later bar than the origin)
BUY: low ≤ bullTapLevel + tol and inUp and bar_index > bullBarIdx
SELL: high ≥ bearTapLevel - tol and inDn and bar_index > bearBarIdx
One-shot option
If enabled, once a signal fires, the stored level is cleared so it won’t trigger again.
Inputs (Settings)
Trend EMA Length (lenEMA): Default 200.
Use 50–100 for intraday, 200 for swing/position.
Tap Tolerance (ticks) (tapTicks): Default 1.
Helps account for tiny feed discrepancies. Set 0 for strict equality.
One Signal per Level (oneShot): Default ON.
If OFF, multiple taps can create multiple signals.
Plot Tap Levels (plotLevels): Draws horizontal lines at active bases.
Show Pattern Labels (showLabels): Marks the origin wickless candles.
Plots & Visuals
EMA trend line for context.
Tap Levels:
Green line at bullish base (origin candle’s low/open).
Red line at bearish base (origin candle’s high/open).
Signals:
BUY: triangle-up below the bar on the tap.
SELL: triangle-down above the bar on the tap.
Labels (optional):
Marks the original wickless impulse candle that created each level.
Alerts
Two alert conditions are built in:
“BUY Signal” — fires when a bullish tap occurs.
“SELL Signal” — fires when a bearish tap occurs.
How to set:
Add the indicator to your chart.
Click Alerts (⏰) → Condition = this indicator.
Choose BUY Signal or SELL Signal.
Set your alert frequency and delivery method.
Recommended usage
Timeframes: Works on any; start with 5–15m intraday, or 1H–1D for swing.
Markets: Equities, futures, FX, crypto. For thin/illiquid assets, consider a slightly larger Tap Tolerance.
Confluence ideas (optional, but helpful):
Higher-timeframe trend agreeing with your chart timeframe.
Volume surge on the origin wickless candle.
S/R, order blocks, or SMC structures near the tap level.
Avoid major news moments when slippage is high.
No-repaint behavior
Origin patterns are detected only on bar close (barstate.isconfirmed), so bases are created with confirmed data.
Signals come after the origin bar, on subsequent taps.
There is no lookahead; lines and shapes reflect information known at the time.
(As with all real-time indicators, an intrabar tap can trigger an alert during the live bar; the signal then remains if that condition held at bar close.)
Known limitations & design choices
Single active level per side: The script tracks only the most recent bullish base and most recent bearish base.
Want a queue of multiple simultaneous bases? That’s possible with arrays; ask and we’ll extend it.
Heikin Ashi / non-standard candles: Wick definitions change; for consistent behavior use regular OHLC candles.
Gaps: On large gaps, taps can occur instantly at the open. Consider one-shot ON to avoid rapid repeats.
This is an indicator, not a strategy: It does not place trades or compute PnL. For backtesting, we can convert it into a strategy with SL/TP logic (ATR or structure-based).
Practical tips
Tap Tolerance:
If you miss obvious taps by a hair, increase to 1–2 ticks.
For FX/crypto with tiny ticks, even 0 or 1 is often enough.
EMA length:
Shorten for faster signals; lengthen for cleaner trend selection.
Risk management (manual suggestion):
For BUY signals, consider a stop slightly below the tap level (or ATR-based).
For SELL signals, consider a stop slightly above the tap level.
Scale out or trail using structure or ATR.
Quick checklist
✅ Price above EMA → watch for a green no-lower-wick candle → store its low → BUY on tap.
✅ Price below EMA → watch for a red no-upper-wick candle → store its high → SELL on tap.
✅ Use Tap Tolerance to avoid missing precise touches by one tick.
✅ Consider One Signal per Level to keep trades uncluttered.
FAQ
Q: Why did I not get a signal even though price touched the level?
A: Check Tap Tolerance (maybe too strict), trend alignment at the tap bar, and that the tap happened after the origin candle. Also confirm you’re on regular candles.
Q: Can I see multiple bases at once?
A: This version tracks the latest bull and bear bases. We can extend to arrays to keep N recent bases per side.
Q: Will it repaint?
A: No. Bases form on confirmed closes, and signals only on later bars.
Q: Can I backtest it?
A: This is a study. Ask for the strategy variant and we’ll add entries, exits, SL/TP, and stats.
Nifty50 Swing Trading Super Indicator# 🚀 Nifty50 Swing Trading Super Indicator - Complete Guide
**Created by:** Gaurav
**Date:** August 8, 2025
**Version:** 1.0 - Optimized for Indian Markets
---
## 📋 Table of Contents
1. (#quick-start-guide)
2. (#indicator-overview)
3. (#installation-instructions)
4. (#parameter-settings)
5. (#signal-interpretation)
6. (#trading-strategy)
7. (#risk-management)
8. (#optimization-tips)
9. (#troubleshooting)
---
## 🎯 Quick Start Guide
### What You Get
✅ **2 Complete Pine Script Indicators:**
- `swing_trading_super_indicator.pine` - Universal version for all markets
- `nifty_optimized_super_indicator.pine` - Specifically optimized for Nifty50 & Indian stocks
✅ **Key Features:**
- Multi-component signal confirmation system
- Optimized for daily and 3-hour timeframes
- Built-in risk management with dynamic stops and targets
- Real-time signal strength monitoring
- Gap analysis for Indian market characteristics
### Immediate Setup
1. Copy the Pine Script code from `nifty_optimized_super_indicator.pine`
2. Paste into TradingView Pine Editor
3. Add to chart on daily or 3-hour timeframe
4. Look for 🚀BUY and 🔻SELL signals
5. Use the information table for signal confirmation
---
## 🔍 Indicator Overview
### Core Components Integration
**🎯 Range Filter (35% Weight)**
- Primary trend identification using adaptive volatility filtering
- Optimized sampling period: 21 bars for Indian market volatility
- Enhanced range multiplier: 3.0 to handle market gaps
- Provides trend direction and strength measurement
**⚡ PMAX (30% Weight)**
- Volatility-adjusted trend confirmation using ATR-based calculations
- Dynamic multiplier adjustment based on market volatility
- 14-period ATR with 2.5 multiplier for swing trading sensitivity
- Offers trailing stop functionality
**🏗️ Support/Resistance (20% Weight)**
- Dynamic level identification using pivot point analysis
- Tighter channel width (3%) for precise Indian market levels
- Enhanced strength calculation with historical interaction weighting
- Provides entry/exit timing and breakout signals
**📊 EMA Alignment (15% Weight)**
- Multi-timeframe moving average confirmation
- Key EMAs: 9, 21, 50, 200 (popular in Indian markets)
- Hierarchical alignment scoring for trend strength
- Additional trend validation layer
### Advanced Features
**🌅 Gap Analysis**
- Automatic detection of significant price gaps (>2%)
- Gap strength measurement and impact on signals
- Specific optimization for Indian market overnight gaps
- Visual gap markers on chart
**⏰ Multi-Timeframe Integration**
- Higher timeframe bias from daily/weekly data
- Configurable daily bias weight (default 70%)
- 3-hour confirmation for precise entry timing
- Prevents counter-trend trades against major timeframe
**🛡️ Risk Management**
- Dynamic stop-loss calculation using multiple methods
- Automatic profit target identification
- Position sizing guidance based on signal strength
- Anti-whipsaw logic to prevent false signals
---
## 📥 Installation Instructions
### Step 1: Access TradingView
1. Open TradingView.com
2. Navigate to Pine Editor (bottom panel)
3. Create a new indicator
### Step 2: Copy the Code
**For Nifty50 & Indian Stocks (Recommended):**
```pinescript
// Copy entire content from nifty_optimized_super_indicator.pine
```
**For Universal Use:**
```pinescript
// Copy entire content from swing_trading_super_indicator.pine
```
### Step 3: Configure and Apply
1. Click "Add to Chart"
2. Select daily or 3-hour timeframe
3. Adjust parameters if needed (defaults are optimized)
4. Enable alerts for signal notifications
### Step 4: Verify Installation
- Check that all components are visible
- Confirm information table appears in top-right
- Test with known trending stocks for signal validation
---
## ⚙️ Parameter Settings
### 🎯 Range Filter Settings
```
Sampling Period: 21 (optimized for Indian market volatility)
Range Multiplier: 3.0 (handles overnight gaps effectively)
Source: Close (most reliable for swing trading)
```
### ⚡ PMAX Settings
```
ATR Length: 14 (standard for daily/3H timeframes)
ATR Multiplier: 2.5 (balanced for swing trading sensitivity)
Moving Average Type: EMA (responsive to price changes)
MA Length: 14 (matches ATR period for consistency)
```
### 🏗️ Support/Resistance Settings
```
Pivot Period: 8 (shorter for Indian market dynamics)
Channel Width: 3% (tighter for precise levels)
Minimum Strength: 3 (higher quality levels only)
Maximum Levels: 4 (focus on strongest levels)
Lookback Period: 150 (sufficient historical data)
```
### 🚀 Super Indicator Settings
```
Signal Sensitivity: 0.65 (balanced for swing trading)
Trend Strength Requirement: 0.75 (high quality signals)
Gap Threshold: 2.0% (significant gap detection)
Daily Bias Weight: 0.7 (strong higher timeframe influence)
```
### 🎨 Display Options
```
Show Range Filter: ✅ (trend visualization)
Show PMAX: ✅ (trailing stops)
Show S/R Levels: ✅ (key price levels)
Show Key EMAs: ✅ (trend confirmation)
Show Signals: ✅ (buy/sell alerts)
Show Trend Background: ✅ (visual trend state)
Show Gap Markers: ✅ (gap identification)
```
---
## 📊 Signal Interpretation
### 🚀 BUY Signals
**Requirements for BUY Signal:**
- Price above Range Filter with upward trend
- PMAX showing bullish direction (MA > PMAX line)
- Support/resistance breakout or favorable positioning
- EMA alignment supporting upward movement
- Higher timeframe bias confirmation
- Overall signal strength > 75%
**Signal Strength Indicators:**
- **90-100%:** Extremely strong - Maximum position size
- **80-89%:** Very strong - Large position size
- **75-79%:** Strong - Standard position size
- **65-74%:** Moderate - Reduced position size
- **<65%:** Weak - Wait for better opportunity
### 🔻 SELL Signals
**Requirements for SELL Signal:**
- Price below Range Filter with downward trend
- PMAX showing bearish direction (MA < PMAX line)
- Resistance breakdown or unfavorable positioning
- EMA alignment supporting downward movement
- Higher timeframe bias confirmation
- Overall signal strength > 75%
### ⚖️ NEUTRAL Signals
**Characteristics:**
- Conflicting signals between components
- Low overall signal strength (<65%)
- Range-bound market conditions
- Wait for clearer directional bias
### 📈 Information Table Guide
**Component Status:**
- **BULL/BEAR:** Current signal direction
- **Strength %:** Component contribution strength
- **Status:** Additional context (STRONG/WEAK/ACTIVE/etc.)
**Overall Signal:**
- **🚀 STRONG BUY:** All systems aligned bullish
- **🔻 STRONG SELL:** All systems aligned bearish
- **⚖️ NEUTRAL:** Mixed or weak signals
---
## 💼 Trading Strategy
### Daily Timeframe Strategy
**Setup:**
1. Apply indicator to daily chart of Nifty50 or Indian stocks
2. Wait for 🚀BUY or 🔻SELL signal with >75% strength
3. Confirm higher timeframe bias alignment
4. Check for significant support/resistance levels
**Entry:**
- Enter on signal bar close or next bar open
- Use 3-hour chart for precise entry timing
- Avoid entries during major news events
- Consider gap analysis for overnight positions
**Position Sizing:**
- **>90% Strength:** 3-4% of portfolio
- **80-89% Strength:** 2-3% of portfolio
- **75-79% Strength:** 1-2% of portfolio
- **<75% Strength:** Avoid or minimal size
### 3-Hour Timeframe Strategy
**Setup:**
1. Confirm daily timeframe bias first
2. Apply indicator to 3-hour chart
3. Look for signals aligned with daily trend
4. Use for entry/exit timing optimization
**Entry Refinement:**
- Wait for 3H signal confirmation
- Enter on pullbacks to key levels
- Use tighter stops for better risk/reward
- Monitor intraday support/resistance
### Risk Management Rules
**Stop Loss Placement:**
1. **Primary:** Use indicator's dynamic stop level
2. **Secondary:** Below/above nearest support/resistance
3. **Maximum:** 2-3% of portfolio per trade
4. **Trailing:** Move stops with PMAX line
**Profit Taking:**
1. **Target 1:** First resistance/support level (50% position)
2. **Target 2:** Second resistance/support level (30% position)
3. **Runner:** Trail remaining 20% with PMAX
**Position Management:**
- Review positions at daily close
- Adjust stops based on new signals
- Exit if trend changes to opposite direction
- Reduce size during high volatility periods
---
## 🎯 Optimization Tips
### For Nifty50 Trading
- Use daily timeframe for primary signals
- Monitor sector rotation impact
- Consider index futures for better liquidity
- Watch for RBI policy and global cues impact
### For Individual Stocks
- Verify stock follows Nifty correlation
- Check sector-specific news and events
- Ensure adequate liquidity for position size
- Monitor earnings calendar for volatility
### Market Condition Adaptations
**Trending Markets:**
- Increase position sizes for strong signals
- Use wider stops to avoid whipsaws
- Focus on trend continuation signals
- Reduce counter-trend trading
**Range-Bound Markets:**
- Reduce position sizes
- Use tighter stops and quicker profits
- Focus on support/resistance bounces
- Increase signal strength requirements
**High Volatility Periods:**
- Reduce overall exposure
- Use smaller position sizes
- Increase stop-loss distances
- Wait for clearer signals
### Performance Monitoring
- Track win rate and average profit/loss
- Monitor signal quality over time
- Adjust parameters based on market changes
- Keep trading journal for pattern recognition
---
## 🔧 Troubleshooting
### Common Issues
**Q: Signals appear too frequently**
A: Increase "Trend Strength Requirement" to 0.8-0.9
**Q: Missing obvious trends**
A: Decrease "Signal Sensitivity" to 0.5-0.6
**Q: Too many false signals**
A: Enable "3H Confirmation" and increase strength requirements
**Q: Indicator not loading**
A: Check Pine Script version compatibility (requires v5)
### Parameter Adjustments
**For More Sensitive Signals:**
- Decrease Signal Sensitivity to 0.5-0.6
- Decrease Trend Strength Requirement to 0.6-0.7
- Increase Range Filter multiplier to 3.5-4.0
**For More Conservative Signals:**
- Increase Signal Sensitivity to 0.7-0.8
- Increase Trend Strength Requirement to 0.8-0.9
- Enable all confirmation features
### Performance Issues
- Reduce lookback periods if chart loads slowly
- Disable some visual elements for better performance
- Use on liquid stocks/indices for best results
---
## 📞 Support & Updates
This super indicator combines the best of Range Filter, PMAX, and Support/Resistance analysis specifically optimized for Indian market swing trading. The multi-component approach significantly improves signal quality while the built-in risk management features help protect capital.
**Remember:** No indicator is 100% accurate. Always combine with proper risk management, market analysis, and your trading experience for best results.
**Happy Trading! 🚀**
Mig Trade Model - Kill Zones
Key features:
Liquidity Hunt Detection: Spots aggressive moves that "hunt" stops beyond recent swing highs/lows.
Consolidation Filter: Requires 1-3 small-range candles after a hunt before confirming with a strong candle.
Bias Application: Uses daily open/close to auto-detect bias or allows manual override.
Kill Zone Restriction: Limits signals to London (default: 7-10 AM UTC) and NY (default: 12-3 PM UTC) sessions for better relevance in active markets.
This strategy is inspired by smart money concepts (SMC) and ICT (Inner Circle Trader) methodologies, aiming to capture venom-like "stings" in price action where liquidity is grabbed before reversals.
How It Works
ATR Calculation: Uses a user-defined ATR length (default: 14) to measure volatility, which scales candle body and range thresholds.
Bias Determination:
Auto: Compares daily close to open (bullish if close > open).
Manual: User selects "Bullish" or "Bearish."
Strong Candles:
Bullish: Green candle with body > 2x ATR (configurable).
Bearish: Red candle with body > 2x ATR.
Small Range Candles:
Candles where high-low < 0.5x ATR (configurable).
Liquidity Hunt:
Bullish Hunt: Strong bearish candle making a new low below the past swing low (default: 10 bars).
Bearish Hunt: Strong bullish candle making a new high above the past swing high.
Signal Generation:
After a hunt, counts 1-3 small-range candles.
Confirms with a strong candle in the opposite direction (e.g., strong bullish after bearish hunt).
Resets if >3 small candles or an opposing strong candle appears.
Kill Zone Filter:
Checks if the current bar's time (in UTC) falls within London or NY Kill Zones.
Only allows final "Buy" (bullish entry) or "Sell" (bearish entry) if bias matches and in Kill Zone.
Plots:
Yellow circle (below): Bullish liquidity hunt.
Orange circle (above): Bearish liquidity hunt.
Blue diamond (below): Raw bullish signal.
Purple diamond (above): Raw bearish signal.
Green triangle up ("Buy"): Filtered bullish entry.
Red triangle down ("Sell"): Filtered bearish entry.
Inputs
Bias: "Auto" (default), "Bullish", or "Bearish" – Controls signal direction based on daily trend.
ATR Length: 14 (default) – Period for ATR calculation.
Swing Length for Liquidity Hunt: 10 (default) – Bars to look back for swing highs/lows.
Strong Candle Body Multiplier (x ATR): 2.0 (default) – Threshold for strong candle bodies.
Small Range Multiplier (x ATR): 0.5 (default) – Threshold for small-range candles.
London Kill Zone Start/End Hour (UTC): 7/10 (default) – Customize London session hours.
NY Kill Zone Start/End Hour (UTC): 12/15 (default) – Customize New York session hours.
Usage Tips
Timeframe: Best on lower timeframes (e.g., 5-15 min) for intraday trading, especially forex pairs like EURUSD or GBPUSD.
Timezone Adjustment: Inputs are in UTC. If your chart is in a different timezone (e.g., EST = UTC-5), adjust hours accordingly (e.g., London: 2-5 AM EST → 7-10 UTC).
Risk Management: Use with stop-loss (e.g., beyond the hunt low/high) and take-profit based on ATR multiples. Not financial advice—backtest thoroughly.
Customization: Tweak multipliers for different assets; higher for volatile cryptos, lower for stocks.
Limitations: Relies on historical data; may generate false signals in ranging markets. Combine with other indicators like volume or support/resistance.
This indicator is for educational purposes. Always use discretion and proper risk management in live trading. If you find it useful, feel free to share feedback or suggestions!
CBC Flip with Volume [Pt]█ CBC Flip with Volume
A price-action based indicator that detects real-time control flips between bulls and bears, enhanced with volume filtering and Pine Screener compatibility.
This tool tracks when the market shifts from bear control to bull control or vice versa, using candle structure and volume behavior. It highlights key reversal points, filters low-conviction moves, and provides two screener-ready outputs for directional monitoring.
█ What It Detects
This script identifies when control flips between buyers and sellers on a candle-by-candle basis. A flip is confirmed only when both price structure and volume meet strict criteria. The indicator uses an internal state to track who is in control and updates when a flip occurs.
█ Flip Conditions
Bull Flip
• Previous bar was under bear control
• Current candle closes above the previous high
• Candle is bullish (close is above open)
• Volume is greater than the previous bar
Bear Flip
• Previous bar was under bull control
• Current candle closes below the previous low
• Candle is bearish (close is below open)
• Volume is greater than the previous bar
When a flip occurs, the indicator updates the control state and records the open price of the flip candle.
█ Strong Flip Detection
A flip is considered strong when volume is also greater than the average volume over a set number of candles (default is 50). Strong flips are visually emphasized using larger markers and darker background shading. This helps filter out moves that lack follow-through volume.
█ Visual Elements on Chart
• Bull Flip (Normal): Small teal triangle below the candle
• Bull Flip (Strong): Larger green triangle below the candle
• Bear Flip (Normal): Small salmon triangle above the candle
• Bear Flip (Strong): Larger red triangle above the candle
• Background Color:
– Green shades for bull flips
– Red shades for bear flips
– Darker color when flip is strong
These visual elements appear only on the candle where a flip is detected. No markers are shown on continuation candles.
█ Inputs
• Volume MA Lookback : Sets the moving average length used for determining whether volume is high enough for a strong flip (default: 50)
█ Alerts
• Bull Flip – Notifies when bulls take control
• Bear Flip – Notifies when bears take control
Alerts are triggered at candle close.
█ Pine Screener Support
This script includes two output columns for TradingView’s Pine Screener:
• Bull in Control (% gain) : Shows the percentage gain from the bull flip’s open to the current close. Resets to 0 when bulls lose control.
• Bear in Control (% gain) : Shows the percentage drop from the bear flip’s open to the current close (as a positive number). Resets to 0 when bears lose control.
These outputs allow you to filter for active moves. For example:
• Bull in Control (% gain) > 2.0 to find strong uptrends
• Bear in Control (% gain) > 1.5 to find sharp breakdowns
█ Use Cases
• Confirm breakouts using volume-backed flips
• Spot short-term reversals at key zones
• Filter out low-volume chop
• Combine screener results with trend or volatility filters
• Build entries around control flips and follow-through strength
Inspired by MapleStax’s original CBC method.
Overheat Oscillator with DivergenceIndicator Description
The Overheat Oscillator with Divergence is an advanced technical indicator designed for the TradingView platform, assisting traders in identifying potential market reversal points by analyzing price momentum and volume, as well as detecting divergences. The indicator combines trend strength assessment with signal smoothing to provide clear indications of market overheat or oversold conditions. An optional divergence detection feature allows for the identification of discrepancies between price movement and the oscillator's value, which may signal upcoming trend changes.
The indicator is displayed in a separate panel below the price chart and offers visual cues through a color gradient, horizontal reference lines, and a dynamic market sentiment table. Users can customize numerous parameters, such as calculation periods, sentiment thresholds, line colors, and visualization styles, making the indicator a versatile tool for various trading strategies.
How the Indicator Works
The indicator is based on the following key components:
Oscillator Calculations
The indicator analyzes price candles, assigning a score based on their nature. A bullish candle (when the closing price is higher than the opening price) receives a score of +1.0, while a bearish candle (when the closing price is lower than the opening price) receives a score of -1.0. This scoring reflects the strength of price movement over a given period.
The score is modified by a volume multiplier (default: 2.0) if the candle's volume exceeds the volume's simple moving average (SMA, default: calculated over 20 candles). This ensures that candles with higher volume have a greater impact on the oscillator's value, better capturing significant market movements driven by increased trading activity. For example, a bullish candle with high volume may receive a score of +2.0 instead of +1.0, amplifying the bullish signal.
The scores are summed over a specified number of candles (default: 20), normalized to a 0–100 range, and then smoothed using a simple moving average (SMA, default: 5 periods) to reduce noise and improve signal clarity.
Color Gradient
The oscillator's values are visualized using a color gradient that changes based on the oscillator's level:
Green: Market cooldown (values below the Gradient Min threshold).
Yellow: Neutral sentiment (values between Gradient Min and Gradient Yellow).
Orange: Elevated activity (values between Gradient Yellow and Gradient Orange).
Red: Market overheat (values above Gradient Orange).
The color gradient is applied as the background in the oscillator panel, facilitating quick assessment of market sentiment.
Reference Levels
The indicator displays customizable horizontal lines for key thresholds (e.g., Overheat Threshold, Oversold Threshold, Gradient Min, Yellow, Orange, Max). These lines are visible only at the height of the last few oscillator candles, preventing chart clutter and helping users focus on current values.
Users can also define three custom horizontal lines with selectable styles (solid, dotted, dashed) and colors. These lines serve as auxiliary tools, e.g., for marking personal support/resistance levels, but do not affect the oscillator's signals or background colors.
Market Sentiment
The indicator displays sentiment labels in a table located in the top-right corner of the panel, dynamically updating based on the oscillator's value:
Cooled: Values below Gradient Yellow (default: 35).
Neutral: Values between Gradient Yellow and Gradient Orange (default: 60).
Excited: Values between Gradient Orange and Overheat Threshold (default: 70).
Overheated: Values above Overheat Threshold (default: 70).
The Overheat Threshold and Oversold Threshold are critical for displaying the "Overheated" and "Cooled" labels in the sentiment table, enabling users to quickly identify extreme market conditions. The labels update when key thresholds are crossed, and their colors match the oscillator's gradient.
Divergence Detection
The indicator offers optional detection of regular bullish and bearish divergences:
Bullish Divergence: Occurs when the price forms a lower low, but the oscillator forms a higher low, suggesting a weakening downtrend.
Bearish Divergence: Occurs when the price forms a higher high, but the oscillator forms a lower high, suggesting a weakening uptrend.
Divergences are marked on the chart with labels ("Bull" for bullish, "Bear" for bearish) and lines indicating pivot points. They are calculated with a delay equal to the Lookback Right setting (default: 5 candles), meaning signals appear after pivot confirmation in the specified lookback period. The indicator also generates alerts for users when a divergence is detected.
Indicator Settings
Main Settings (SETTINGS)
Period Length: Specifies the number of candles used for oscillator calculations (default: 20).
Volume SMA Period: The period for the volume's simple moving average (default: 20).
Volume Multiplier: Multiplier applied to candle scores when volume exceeds the average (default: 2.0).
SMA Length: The period for smoothing the oscillator with a simple moving average (default: 5).
Thresholds (THRESHOLDS)
Overheat Threshold: Level indicating market overheat (default: 70). This value determines when the sentiment table displays the "Overheated" label, signaling a potential peak in an uptrend.
Oversold Threshold: Level indicating market cooldown (default: 30). This value determines when the sentiment table displays the "Cooled" label, signaling a potential bottom in a downtrend.
Gradient Min (Green): Lower threshold for the green gradient (default: 20).
Gradient Yellow Threshold: Threshold for the yellow gradient (default: 35).
Gradient Orange Threshold: Threshold for the orange gradient (default: 60).
Gradient Max (Red): Upper threshold for the red gradient (default: 70).
Visualization (VISUALIZATION)
Signal Line Color: Color of the oscillator line (default: dark red, RGB(5, 0, 0)).
Show Reference Lines: Enables/disables the display of threshold lines (default: enabled).
Divergence Settings (DIVERGENCE SETTINGS)
Calculate Divergence: Enables/disables divergence detection (default: disabled).
Lookback Right: Number of candles back for pivot analysis (default: 5).
Lookback Left: Number of candles to the left for pivot analysis (default: 5).
Line Style (STYLE)
Custom Line 1, 2, 3 Value: Levels for custom horizontal lines (default: 70, 50, 30).
Custom Line 1, 2, 3 Color: Colors for custom lines (default: black, RGB(0, 0, 0)).
Custom Line 1, 2, 3 Style: Line styles (solid, dotted, dashed; default: dashed, dotted, dashed).
How to Use the Indicator
Adding to the Chart
Add the indicator to your TradingView chart by searching for "Overheat Oscillator with Divergence."
Configure the settings according to your trading strategy.
Signal Interpretation
Overheated: Values above the Overheat Threshold (default: 70) in the sentiment table may indicate a potential uptrend peak.
Cooled: Values below the Oversold Threshold (default: 30) in the sentiment table may suggest a potential downtrend bottom.
Divergences:
Bullish: Look for "Bull" labels on the chart, indicating potential upward reversals (calculated with a Lookback Right delay).
Bearish: Look for "Bear" labels, indicating potential downward reversals (calculated with a Lookback Right delay).
Customization
Experiment with settings such as period length, volume multiplier, or gradient thresholds to tailor the indicator to your trading style (e.g., scalping, medium-term trading).
Usage Examples
Scalping: Set a shorter period (e.g., Period Length = 10, SMA Length = 3) and monitor rapid sentiment changes and divergences on lower timeframes (e.g., 5-minute charts).
Medium-Term Trading: Use default settings or increase Period Length (e.g., 30) and SMA Length (e.g., 7) for more stable signals on hourly or daily charts.
Reversal Detection: Enable divergence detection and observe "Bull" or "Bear" labels in conjunction with overheat/cooled levels in the sentiment table.
Notes
The indicator performs best when used in conjunction with other technical analysis tools, such as support/resistance lines, moving averages, or Fibonacci levels.
Divergences may serve as early signals but do not always guarantee immediate trend reversals—confirmation with other indicators is recommended.
Test different settings on historical data to find the optimal configuration for your chosen market and timeframe.
Advanced MACD Pro (WhiteStone_Ibrahim) - T3 Themed✨ Advanced MACD Pro (WhiteStone_Ibrahim) - T3 Themed ✨
Take your MACD analysis to the next level with the Advanced MACD Pro - T3 Themed indicator by WhiteStone_Ibrahim! This isn't just another MACD; it's a comprehensive toolkit packed with advanced features, unique T3 integration, and extensive customization options to provide deeper market insights.
Whether you're a seasoned trader or just starting, this indicator offers a versatile and powerful way to analyze momentum, identify trends, and spot potential reversals.
Key Features:
Core MACD Functionality:
Classic MACD Line: Calculated from customizable Fast and Slow EMAs using your chosen source (Close, Open, HLC3, etc.).
Standard Signal Line: EMA of the MACD line, with adjustable length.
Dynamic MACD Line Coloring: Automatically changes color based on whether it's above or below the zero line (positive/negative).
Zero Line: Clearly plotted for reference.
Enhanced MACD Histogram:
Sophisticated Color Coding: The histogram isn't just positive or negative. It intelligently colors based on momentum strength and direction:
Strong Bullish: MACD above signal, histogram increasing.
Weakening Bullish: MACD above signal, histogram decreasing.
Strong Bearish: MACD below signal, histogram decreasing.
Weakening Bearish: MACD below signal, histogram increasing.
Neutral: Default color for other conditions.
Optional Histogram Smoothing: Smooth out the histogram noise using one of five different moving average types: SMA, EMA, WMA, RMA, or the advanced T3 (Tilson T3). Customize smoothing length and T3 vFactor.
🌟 Unique T3 Integration (T3 Themed):
Extra T3 Signal Line (on MACD): An additional, fast-reacting T3 moving average calculated directly from the MACD line. This provides an alternative and often quicker signal.
Customizable T3 length and vFactor.
Dynamic Coloring: The T3 Signal Line changes color (bullish/bearish) based on its crossover with the MACD line, offering clear visual cues.
T3 is also available as a smoothing option for the main histogram (see above).
🔍 Disagreement & Divergence Detection:
Bar/Price Disagreement Markers:
Highlights instances where the price bar's direction (e.g., a bullish candle) contradicts the current MACD momentum (e.g., MACD below its signal line).
Visual markers (circles) appear above/below bars to draw attention to these potential early warnings or confirmations.
Histogram Color Change on Disagreement: Optionally, the histogram can adopt distinct alternative colors during these bar/price disagreements for even clearer visual alerts.
Classic Bullish & Bearish Divergence Detection:
Automatically identifies regular divergences between price action (Higher Highs/Lower Lows) and the MACD line (Lower Highs/Higher Lows).
Customizable pivot lookback periods (left and right bars) for divergence sensitivity.
Plots clear "Bull" and "Bear" labels on the price chart where divergences occur.
🎨 Extensive Customization & Visuals:
Multiple Color Themes: Choose from pre-set themes like 'Dark Mode', 'Light Mode', 'Neon Night', or use 'Default (Current Settings)' to fine-tune every color yourself.
Granular Control (Default Theme): Individually customize colors and thickness for:
MACD Line (positive/negative)
Standard Signal Line
Extra T3 Signal Line (bullish/bearish)
Histogram (all four momentum states + neutral)
Disagreement Markers & Histogram Alt Colors
Divergence Lines/Labels
Zero Line
Toggle Visibility: Easily show or hide the Standard Signal Line and the Extra T3 Signal Line as needed.
🔔 Comprehensive Alert System:
Stay informed of key market events with a wide array of configurable alerts:
MACD Line / Standard Signal Line Crossover
Histogram / Zero Line Crossover
MACD Line / Zero Line Crossover
Bullish Divergence Detected
Bearish Divergence Detected
Bar/Price Disagreement (Bullish & Bearish)
MACD Line / Extra T3 Signal Line Crossover
Each alert can be individually enabled or disabled.
The Advanced MACD Pro - T3 Themed indicator is designed to be your go-to tool for momentum analysis. Its rich feature set empowers you to tailor it to your specific trading style and gain a more nuanced understanding of market dynamics.
Add it to your charts today and experience the difference!
(Developed by WhiteStone_Ibrahim)
Combined EMA Technical AnalysisThis script is written in Pine Script (version 5) for TradingView and creates a comprehensive technical analysis indicator called "Combined EMA Technical Analysis." It overlays multiple technical indicators on a price chart, including Exponential Moving Averages (EMAs), VWAP, MACD, PSAR, RSI, Bollinger Bands, ADX, and external data from the S&P 500 (SPX) and VIX indices. The script also provides visual cues through colors, shapes, and a customizable table to help traders interpret market conditions.
Here’s a breakdown of the script:
---
### **1. Purpose**
- The script combines several popular technical indicators to analyze price trends, momentum, volatility, and market sentiment.
- It uses color coding (green for bullish, red for bearish, gray/white for neutral) and a table to display key information.
---
### **2. Custom Colors**
- Defines custom RGB colors for bullish (`customGreen`), bearish (`customRed`), and neutral (`neutralGray`) signals to enhance visual clarity.
---
### **3. User Inputs**
- **EMA Colors**: Users can customize the colors of five EMAs (8, 20, 9, 21, 50 periods).
- **MACD Settings**: Adjustable short length (12), long length (26), and signal length (9).
- **RSI Settings**: Adjustable length (14).
- **Bollinger Bands Settings**: Length (20), multiplier (2), and proximity threshold (0.1% of band width).
- **ADX Settings**: Adjustable length (14).
- **Table Settings**: Position (e.g., "Bottom Right") and text size (e.g., "Small").
---
### **4. Indicator Calculations**
#### **Exponential Moving Averages (EMAs)**
- Calculates five EMAs: 8, 20, 9, 21, and 50 periods based on the closing price.
- Used to identify short-term and long-term trends.
#### **Volume Weighted Average Price (VWAP)**
- Resets daily and calculates the average price weighted by volume.
- Color-coded: green if price > VWAP (bullish), red if price < VWAP (bearish), white if neutral.
#### **MACD (Moving Average Convergence Divergence)**
- Uses short (12) and long (26) EMAs to compute the MACD line, with a 9-period signal line.
- Displays "Bullish" (green) if MACD > signal, "Bearish" (red) if MACD < signal.
#### **Parabolic SAR (PSAR)**
- Calculated with acceleration factors (start: 0.02, increment: 0.02, max: 0.2).
- Indicates trend direction: green if price > PSAR (bullish), red if price < PSAR (bearish).
#### **Relative Strength Index (RSI)**
- Measures momentum over 14 periods.
- Highlighted in green if > 70 (overbought), red if < 30 (oversold), white otherwise.
#### **Bollinger Bands (BB)**
- Uses a 20-period SMA with a 2-standard-deviation multiplier.
- Color-coded based on price position:
- Green: Above upper band or close to it.
- Red: Below lower band or close to it.
- Gray: Neutral (within bands).
#### **Average Directional Index (ADX)**
- Manually calculates ADX to measure trend strength:
- Strong trend: ADX > 25.
- Very strong trend: ADX > 50.
- Direction: Bullish if +DI > -DI, bearish if -DI > +DI.
#### **EMA Crosses**
- Detects bullish (crossover) and bearish (crossunder) events for:
- EMA 9 vs. EMA 21.
- EMA 8 vs. EMA 20.
- Visualized with green (bullish) or red (bearish) circles.
#### **SPX and VIX Data**
- Fetches daily closing prices for the S&P 500 (SPX) and VIX (volatility index).
- SPX trend: Bullish if EMA 9 > EMA 21, bearish if EMA 9 < EMA 21.
- VIX levels: High (> 25, fear), Low (< 15, stability).
- VIX color: Green if SPX bullish and VIX low, red if SPX bearish and VIX high, white otherwise.
---
### **5. Visual Outputs**
#### **Plots**
- EMAs, VWAP, and PSAR are plotted on the chart with their respective colors.
- EMA crosses are marked with circles (green for bullish, red for bearish).
#### **Table**
- Displays a summary of indicators in a customizable position and size.
- Indicators shown (if enabled):
- EMA 8/20, 9/21, 50: Green dot if bullish, red if bearish.
- VWAP: Green if price > VWAP, red if price < VWAP.
- MACD: Green if bullish, red if bearish.
- MACD Zero: Green if MACD > 0, red if MACD < 0.
- PSAR: Green if price > PSAR, red if price < PSAR.
- ADX: Arrows for very strong trends (↑/↓), dots for weaker trends, colored by direction.
- Bollinger Bands: Arrows (↑/↓) or dots based on price position.
- RSI: Numeric value, colored by overbought/oversold levels.
- VIX: Numeric value, colored based on SPX trend and VIX level.
---
### **6. Alerts**
- Triggers alerts for EMA 8/20 crosses:
- Bullish: "EMA 8/20 Bullish Cross on Candle Close!"
- Bearish: "EMA 8/20 Bearish Cross on Candle Close!"
---
### **7. Key Features**
- **Flexibility**: Users can toggle indicators on/off in the table and adjust parameters.
- **Visual Clarity**: Consistent use of green (bullish), red (bearish), and neutral colors.
- **Comprehensive**: Combines trend, momentum, volatility, and market sentiment indicators.
---
### **How to Use**
1. Add the script to TradingView.
2. Customize inputs (colors, lengths, table position) as needed.
3. Interpret the chart and table:
- Green signals suggest bullish conditions.
- Red signals suggest bearish conditions.
- Neutral signals indicate indecision or consolidation.
4. Set up alerts for EMA crosses to catch trend changes.
This script is ideal for traders who want a multi-indicator dashboard to monitor price action and market conditions efficiently.
