MWho is in ControlWho is in Control.
This study shows who is in control by showing just the Bull side, the Bear side or a combined view. This study follows the same philosophy of simplicity I try to use as much as possible in my studies. The least number of parameters and as understandable as possible.
Len : length of the period
Signal : Signal to show change of trend
Disp Bull : Display/Hide Bull Side
Disp Bear : Display/Hide Bear Side
Disp Differential : Display/Hide the differential between Bulls and Bears.
Search in scripts for "bear"
: Volume Zone Oscillator & Price Zone Oscillator LB Update JRMThis is a simple update of Lazy Bear's " Indicators: Volume Zone Indicator & Price Zone Indicator" Script. PZO plots on the same indicator. The horizontal plot lines are taken primarily from two articles by Wahalil and Steckler "In The Volume Zone" May 2011, Stocks and Commodities and "Entering The Price Zone"June 2011, Stocks and Commodities. With both indicators on the same plot it is easier to see divergences between the indicators. I did add a plot line at 80 and -80 as well because that is getting into truly extreme price/volume territory where one might contemplate a close your eyes and sell or cover particularly if confirmed at a higher time frame with the expectation of some type of corrective move..
The inputs and plot lines can be edited as per Lazy Bear's original script and follows the original format. Many thanks to Lazy Bear.
Live Market - Performance MonitorLive Market — Performance Monitor
Study material (no code) — step-by-step training guide for learners
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1) What this tool is — short overview
This indicator is a live market performance monitor designed for learning. It scans price, volume and volatility, detects order blocks and trendline events, applies filters (volume & ATR), generates trade signals (BUY/SELL), creates simple TP/SL trade management, and renders a compact dashboard summarizing market state, risk and performance metrics.
Use it to learn how multi-factor signals are constructed, how Greeks-style sensitivity is replaced by volatility/ATR reasoning, and how a live dashboard helps monitor trade quality.
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2) Quick start — how a learner uses it (step-by-step)
1. Add the indicator to a chart (any ticker / timeframe).
2. Open inputs and review the main groups: Order Block, Trendline, Signal Filters, Display.
3. Start with defaults (OB periods ≈ 7, ATR multiplier 0.5, volume threshold 1.2) and observe the dashboard on the last bar.
4. Walk the chart back in time (use the last-bar update behavior) and watch how signals, order blocks, trendlines, and the performance counters change.
5. Run the hands-on labs below to build intuition.
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3) Main configurable inputs (what you can tweak)
• Order Block Relevant Periods (default ~7): number of consecutive candles used to define an order block.
• Min. Percent Move for Valid OB (threshold): minimum percent move required for a valid order block.
• Number of OB Channels: how many past order block lines to keep visible.
• Trendline Period (tl_period): pivot lookback for detecting highs/lows used to draw trendlines.
• Use Wicks for Trendlines: whether pivot uses wicks or body.
• Extension Bars: how far trendlines are projected forward.
• Use Volume Filter + Volume Threshold Multiplier (e.g., 1.2): requires volume to be greater than multiplier × average volume.
• Use ATR Filter + ATR Multiplier: require bar range > ATR × multiplier to filter noise.
• Show Targets / Table settings / Colors for visualization.
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4) Core building blocks — what the script computes (plain language)
Price & trend:
• Spot / LTP: current close price.
• EMA 9 / 21 / 50: fast, medium, slow moving averages to define short/medium trend.
o trend_bullish: EMA9 > EMA21 > EMA50
o trend_bearish: EMA9 < EMA21 < EMA50
o trend_neutral: otherwise
Volatility & noise:
• ATR (14): average true range used for dynamic target and filter sizing.
• dynamic_zone = ATR × atr_multiplier: minimum bar range required for meaningful move.
• Annualized volatility: stdev of price changes × sqrt(252) × 100 — used to classify volatility (HIGH/MEDIUM/LOW).
Momentum & oscillators:
• RSI 14: overbought/oversold indicator (thresholds 70/30).
• MACD: EMA(12)-EMA(26) and a 9-period signal line; histogram used for momentum direction and strength.
• Momentum (ta.mom 10): raw momentum over 10 bars.
Mean reversion / band context:
• Bollinger Bands (20, 2σ): upper, mid, lower.
o price_position measures where price sits inside the band range as 0–100.
Volume metrics:
• avg_volume = SMA(volume, 20) and volume_spike = volume > avg_volume × volume_threshold
o volume_ratio = volume / avg_volume
Support & Resistance:
• support_level = lowest low over 20 bars
• resistance_level = highest high over 20 bars
• current_position = percent of price between support & resistance (0–100)
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5) Order Block detection — concept & logic
What it tries to find: a bar (the base) followed by N candles in the opposite direction (a classical order block setup), with a minimum % move to qualify. The script records the high/low of the base candle, averages them, and plots those levels as OB channels.
How learners should think about it (conceptual):
1. An order block is a signature area where institutions (theory) left liquidity — often seen as a large bar followed by a sequence of directional candles.
2. This indicator uses a configurable number of subsequent candles to confirm that the pattern exists.
3. When found, it stores and displays the base candle’s high/low area so students can see how price later reacts to those zones.
Implementation note for learners: the tool keeps a limited history of OB lines (ob_channels). When new OBs exceed the count, the oldest lines are removed — good practice to avoid clutter.
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6) Trendline detection — idea & interpretation
• The script finds pivot highs and lows using a symmetric lookback (tl_period and half that as right/left).
• It then computes a trendline slope from successive pivots and projects the line forward (extension_bars).
• Break detection: Resistance break = close crosses above the projected resistance line; Support break = close crosses below projected support.
Learning tip: trendlines here are computed from pivot points and time. Watch how changing tl_period (bigger = smoother, fewer pivots) alters the trendlines and break signals.
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7) Signal generation & filters — step-by-step
1. Primary triggers:
o Bullish trigger: order block bullish OR resistance trendline break.
o Bearish trigger: bearish order block OR support trendline break.
2. Filters applied (both must pass unless disabled):
o Volume filter: volume must be > avg_volume × volume_threshold.
o ATR filter: bar range (high-low) must exceed ATR × atr_multiplier.
o Not in an existing trade: new trades only start if trade_active is false.
3. Trend confirmation:
o The primary trigger is only confirmed if trend is bullish/neutral for buys or bearish/neutral for sells (EMA alignment).
4. Result:
o When confirmed, a long or short trade is activated with TP/SL calculated from ATR multiples.
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8) Trade management — what the tool does after a signal
• Entry management: the script marks a trade as trade_active and sets long_trade or short_trade flags.
• TP & SL rules:
o Long: TP = high + 2×ATR ; SL = low − 1×ATR
o Short: TP = low − 2×ATR ; SL = high + 1×ATR
• Monitoring & exit:
o A trade closes when price reaches TP or SL.
o When TP/SL hit, the indicator updates win_count and total_pnl using a very simple calculation (difference between TP/SL and previous close).
o Visual lines/labels are drawn for TP and updated as the trade runs.
Important learner notes:
• The script does not store a true entry price (it uses close in its P&L math), so PnL is an approximation — treat this as a learning proxy, not a position accounting system.
• There’s no sizing, slippage, or fee accounted — students must manually factor these when translating to real trades.
• This indicator is not a backtesting strategy; strategy.* functions would be needed for rigorous backtest results.
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9) Signal strength & helper utilities
• Signal strength is a composite score (0–100) made up of four signals worth 25 points each:
1. RSI extreme (overbought/oversold) → 25
2. Volume spike → 25
3. MACD histogram magnitude increasing → 25
4. Trend existence (bull or bear) → 25
• Progress bars (text glyphs) are used to visually show RSI and signal strength on the table.
Learning point: composite scoring is a way to combine orthogonal signals — study how changing weights changes outcomes.
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10) Dashboard — how to read each section (walkthrough)
The dashboard is split into sections; here's how to interpret them:
1. Market Overview
o LTP / Change%: immediate price & daily % change.
2. RSI & MACD
o RSI value plus progress bar (overbought 70 / oversold 30).
o MACD histogram sign indicates bullish/bearish momentum.
3. Volume Analysis
o Volume ratio (current / average) and whether there’s a spike.
4. Order Block Status
o Buy OB / Sell OB: the average base price of detected order blocks or “No Signal.”
5. Signal Status
o 🔼 BUY or 🔽 SELL if confirmed, or ⚪ WAIT.
o No-trade vs Active indicator summarizing market readiness.
6. Trend Analysis
o Trend direction (from EMAs), market sentiment score (composite), volatility level and band/position metrics.
7. Performance
o Win Rate = wins / signals (percentage)
o Total PnL = cumulative PnL (approximate)
o Bull / Bear Volume = accumulated volumes attributable to signals
8. Support & Resistance
o 20-bar highest/lowest — use as nearby reference points.
9. Risk & R:R
o Risk Level from ATR/price as a percent.
o R:R Ratio computed from TP/SL if a trade is active.
10. Signal Strength & Active Trade Status
• Numeric strength + progress bar and whether a trade is currently active with TP/SL display.
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11) Alerts — what will notify you
The indicator includes pre-built alert triggers for:
• Bullish confirmed signal
• Bearish confirmed signal
• TP hit (long/short)
• SL hit (long/short)
• No-trade zone
• High signal strength (score > 75%)
Training use: enable alerts during a replay session to be notified when the indicator would have signalled.
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12) Labs — hands-on exercises for learners (step-by-step)
Lab A — Order Block recognition
1. Pick a 15–30 minute timeframe on a liquid ticker.
2. Use default OB periods (7). Mark each time the dashboard shows a Buy/Sell OB.
3. Manually inspect the chart at the base candle and the following sequence — draw the OB zone by hand and watch later price reactions to it.
4. Repeat with OB periods 5 and 10; note stability vs noise.
Lab B — Trendline break confirmation
1. Increase trendline period (e.g., 20), watch trendlines form from pivots.
2. When a resistance break is flagged, compare with MACD & volume: was momentum aligned?
3. Note false breaks vs confirmed moves — change extension_bars to see projection effects.
Lab C — Filter sensitivity
1. Toggle Use Volume Filter off, and record the number and quality of signals in a 2-day window.
2. Re-enable volume filter and change threshold from 1.2 → 1.6; note how many low-quality signals are filtered out.
Lab D — Trade management simulation
1. For each signalled trade, record the time, close entry approximation, TP, SL, and eventual hit/miss.
2. Compute actual PnL if you had entered at the open of the next bar to compare with the script’s PnL math.
3. Tabulate win rate and average R:R.
Lab E — Performance review & improvement
1. Build a spreadsheet of signals over 30–90 periods with columns: Date, Signal type, Entry price (real), TP, SL, Exit, PnL, Notes.
2. Analyze which filters or indicators contributed most to winners vs losers and adjust weights.
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13) Common pitfalls, assumptions & implementation notes (things to watch)
• P&L simplification: total_pnl uses close as a proxy entry price. Real entry/exit prices and slippage are not recorded — so PnL is approximate.
• No position sizing or money management: the script doesn’t compute position size from equity or risk percent.
• Signal confirmation logic: composite "signal_strength" is a simple 4×25 point scheme — explore different weights or additional signals.
• Order block detection nuance: the script defines the base candle and checks the subsequent sequence. Be sure to verify whether the intended candle direction (base being bullish vs bearish) aligns with academic/your trading definition — read the code carefully and test.
• Trendline slope over time: slope is computed using timestamps; small differences may make lines sensitive on very short timeframes — using bar_index differences is usually more stable.
• Not a true backtester: to evaluate performance statistically you must transform the logic into a strategy script that places hypothetical orders and records exact entry/exit prices.
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14) Suggested improvements for advanced learners
• Record true entry price & timestamp for accurate PnL.
• Add position sizing: risk % per trade using SL distance and account size.
• Convert to strategy. (Pine Strategy)* to run formal backtests with equity curves, drawdowns, and metrics (Sharpe, Sortino).
• Log trades to an external spreadsheet (via alerts + webhook) for offline analysis.
• Add statistics: average win/loss, expectancy, max drawdown.
• Add additional filters: news time blackout, market session filters, multi-timeframe confirmation.
• Improve OB detection: combine wick/body, volume spike at base bar, and liquidity sweep detection.
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15) Glossary — quick definitions
• ATR (Average True Range): measure of typical range; used to size targets and stops.
• EMA (Exponential Moving Average): trend smoothing giving more weight to recent prices.
• RSI (Relative Strength Index): momentum oscillator; >70 overbought, <30 oversold.
• MACD: momentum oscillator using difference of two EMAs.
• Bollinger Bands: volatility bands around SMA.
• Order Block: a base candle area with subsequent confirmation candles; a zone of institutional interest (learning model).
• Pivot High/Low: local turning point defined by candles on both sides.
• Signal Strength: combined score from multiple indicators.
• Win Rate: proportion of signals that hit TP vs total signals.
• R:R (Risk:Reward): ratio of potential reward (TP distance) to risk (entry to SL).
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16) Limitations & assumptions (be explicit)
• This is an indicator for learning — not a trading robot or broker connection.
• No slippage, fees, commissions or tie-in to real orders are considered.
• The logic is heuristic (rule-of-thumb), not a guarantee of performance.
• Results are sensitive to timeframe, market liquidity, and parameter choices.
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17) Practical classroom / study plan (4 sessions)
• Session 1 — Foundations: Understand EMAs, ATR, RSI, MACD, Bollinger Bands. Run the indicator and watch how these numbers change on a single day.
• Session 2 — Zones & Filters: Study order blocks and trendlines. Test volume & ATR filters and note changes in false signals.
• Session 3 — Simulated trading: Manually track 20 signals, compute real PnL and compare to the dashboard.
• Session 4 — Improvement plan: Propose changes (e.g., better PnL accounting, alternative OB rule) and test their impact.
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18) Quick reference checklist for each signal
1. Was an order block or trendline break detected? (primary trigger)
2. Did volume meet threshold? (filter)
3. Did ATR filter (bar size) show a real move? (filter)
4. Was trend aligned (EMA 9/21/50)? (confirmation)
5. Signal confirmed → mark entry approximation, TP, SL.
6. Monitor dashboard (Signal Strength, Volatility, No-trade zone, R:R).
7. After exit, log real entry/exit, compute actual PnL, update spreadsheet.
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19) Educational caveat & final note
This tool is built for training and analysis: it helps you see how common technical building blocks combine into trade ideas, but it is not a trading recommendation. Use it to develop judgment, to test hypotheses, and to design robust systems with proper backtesting and risk control before risking capital.
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20) Disclaimer (must include)
Training & Educational Only — This material and the indicator are provided for educational purposes only. Nothing here is investment advice or a solicitation to buy or sell financial instruments. Past simulated or historical performance does not predict future results. Always perform full backtesting and risk management, and consider seeking advice from a qualified financial professional before trading with real capital.
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Volume Trend AnalysisStudy Material for Volume Trend Analysis Dashboard
1. Introduction
This script is a complete volume-based technical analysis dashboard designed in TradingView, created under the guidelines of TradingView and aiTrendview. It combines multiple indicators—Volume, RSI, Supertrend, Buy/Sell Pressure, and Momentum—into a single visual dashboard.
The purpose is education and market observation, not guaranteed profits. Students using this tool should focus on understanding patterns, signals, and probabilities rather than treating them as fixed rules.
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2. Core Components and Indicators
🔹 Volume Analysis
• Volume shows the number of shares/contracts traded in a specific period.
• The script compares today’s volume with historical averages (e.g., 20-day average).
• This helps identify whether trading activity is higher or lower than usual.
• Learning use: A student can track if high volume confirms a price breakout or if low volume suggests weak conviction.
• Combination:
o High price rise + High volume → Strong bullish move.
o Price rise + Low volume → Weak rally, may fail.
o Price fall + High volume → Strong selling pressure.
o Price fall + Low volume → Weak decline, may reverse.
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🔹 RSI (Relative Strength Index)
• RSI measures momentum (0–100 scale).
• Above 70 = Overbought (possible selling zone).
• Below 30 = Oversold (possible buying zone).
• Around 50 = Neutral, sideways market.
• Learning use: Combine with volume—RSI near extremes with high volume often marks turning points.
• Combination:
o RSI < 30 + High buy pressure volume = Strong bounce probability.
o RSI > 70 + High sell pressure volume = Risk of reversal downward.
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🔹 Supertrend
• Supertrend uses volatility (ATR) to show support/resistance bands.
• Price above = Bullish trend.
• Price below = Bearish trend.
• Learning use: New students can treat it as a dynamic stop-loss and trailing tool.
• Combination:
o Price > Supertrend + RSI > 50 + High buy volume = Safe bullish trend.
o Price < Supertrend + RSI < 50 + High sell volume = Safe bearish trend.
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🔹 Buy/Sell Pressure
• The indicator splits volume into buying vs. selling portions based on price action.
• Shows % of buying volume vs. selling volume.
• Learning use: Students can visualize whether bulls or bears are dominating.
• Combination:
o Buying > 65% → Bulls stronger.
o Selling > 65% → Bears stronger.
o Balanced → Market indecisive (range-bound).
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🔹 Momentum & Signal Status
• Momentum combines RSI and Supertrend to classify market as Bullish, Bearish, or Neutral.
• Buy/Sell signals are triggered on crossovers of price with Supertrend along with RSI conditions.
• Learning use: Beginners should not blindly trade these signals but track how often they succeed/fail under different market conditions.
• Combination:
o Bullish Momentum + Buy Signal + High Volume = Strong entry setup.
o Bearish Momentum + Sell Signal + High Volume = Strong short setup.
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🔹 Volume Pace
• Compares current intraday volume with expected average progress.
• Above pace = Traders active earlier than usual.
• Below pace = Weak interest in current session.
• Learning use: Beginners can track whether moves are backed by real activity or just price manipulation.
• Combination:
o Above pace + Bullish signals = Reliable rally.
o Below pace + Bullish signals = Weak rally, avoid.
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3. How to Use the Dashboard
• The dashboard consolidates all indicators into a simple table: Signals, Momentum, Position, Profit, Volume, Pressure, Levels, and Status.
• It helps beginners see different aspects of market condition at one glance.
• Instead of jumping between multiple charts, everything is available in one panel.
• Students can use this to practice observation, backtest signals, and record outcomes.
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4. Educational Guidelines
1. Paper Trade First: Always test on virtual trading accounts before real money.
2. Record Outcomes: Note how each signal works in trending vs. sideways markets.
3. Combine with Chart Reading: This is not standalone—students must learn candlestick patterns, support/resistance, and fundamentals.
4. Avoid Overtrading: Just because a dashboard flashes “BUY” doesn’t mean to enter blindly.
5. Adapt Timeframes: Learn the difference between intraday vs. daily signals. Shorter timeframes = more noise.
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5. Common Beginner Mistakes
• Blind Trading: Treating BUY/SELL signals as automatic entry/exit without analysis.
• Ignoring Volume: Not checking whether signals are backed by strong or weak volume.
• Overconfidence: Assuming 100% accuracy—no indicator is perfect.
• Misusing Alerts: Alerts help monitoring but don’t guarantee profitability.
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6. Disclaimer
This indicator is created strictly for educational and learning purposes under TradingView and aiTrendview guidelines.
• It is not financial advice and should not be treated as a guaranteed profit-making tool.
• Past performance does not guarantee future results.
• Misuse of this indicator for blind speculation can result in financial loss.
• Always use it with proper risk management and independent judgment.
• For real trading decisions, consult a certified financial advisor.
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✅ By studying this dashboard, students gain exposure to:
• How multiple indicators interact.
• How volume confirms or rejects price moves.
• How to build discipline by observing signals, not chasing them.
This makes the tool a training ground for market observation rather than a shortcut to quick profits.
Hammer, Engulfing & Star Candles aksh//@version=5
indicator("Hammer, Engulfing & Star Candles ", overlay=true, max_bars_back=500)
// ===== Inputs =====
showHammer = input.bool(true, "Show Hammer")
showShootingStar = input.bool(true, "Show Shooting Star")
showEngulfing = input.bool(true, "Show Bull/Bear Engulfing")
showMorningStar = input.bool(true, "Show Morning Star (3-candle)")
showEveningStar = input.bool(true, "Show Evening Star (3-candle)")
// Sensitivity / thresholds
wickToBodyMin = input.float(2.5, "Min Wick:Body (Hammer/Star)", minval=0.5, step=0.1)
maxOppWickToBody = input.float(0.7, "Max Opp Wick:Body (Hammer/Star)", minval=0.0, step=0.1)
closeInTopPct = input.float(0.35, "Hammer: close in top % of range", minval=0.0, maxval=1.0, step=0.05)
closeInBotPct = input.float(0.35, "Star: close in bottom % of range", minval=0.0, maxval=1.0, step=0.05)
minBodyFracRange = input.float(0.15, "Min body as % of range (avoid doji)", minval=0.0, maxval=1.0, step=0.01)
engulfRequireBodyPct = input.float(1.00, "Engulfing: body >= prev body x", minval=0.5, maxval=3.0, step=0.05)
engulfAllowWicks = input.bool(false, "Engulfing: allow wick engulf if bodies equal")
starMiddleBodyMaxPct = input.float(0.40, "Morning/Evening Star: middle body <= % of avg body", minval=0.05, maxval=1.0, step=0.05)
starCloseRetracePct = input.float(0.50, "Morning/Evening Star: final close retraces >= % of first body", minval=0.25, maxval=1.0, step=0.05)
// ===== Helpers =====
body(c,o) => math.abs(c - o)
upperWick(h,o,c) => h - math.max(o, c)
lowerWick(l,o,c) => math.min(o, c) - l
rng(h,l) => h - l
isBull(o,c) => c > o
isBear(o,c) => o > c
midpoint(h,l) => (h + l) * 0.5
b = body(close, open)
uw = upperWick(high, open, close)
lw = lowerWick(low, open, close)
rg = rng(high, low)
prev_o = open , prev_c = close , prev_h = high , prev_l = low
prev_b = body(prev_c, prev_o)
// avoid divide-by-zero
safe(val) => nz(val, 0.0000001)
// ===== Single-candle patterns =====
// Hammer: long lower wick, small/limited upper wick, decent body, close toward top of range
hammer = showHammer and rg > 0 and b/rg >= minBodyFracRange and
(lw / safe(b) >= wickToBodyMin) and (uw / safe(b) <= maxOppWickToBody) and
(close >= (low + (1.0 - closeInTopPct) * rg))
// Shooting Star: long upper wick, small/limited lower wick, close toward bottom
shootingStar = showShootingStar and rg > 0 and b/rg >= minBodyFracRange and
(uw / safe(b) >= wickToBodyMin) and (lw / safe(b) <= maxOppWickToBody) and
(close <= (low + closeInBotPct * rg))
// ===== Two-candle patterns: Engulfing =====
// Bullish engulfing: previous bearish, current bullish, current body engulfs previous body
bullEngulf = showEngulfing and isBear(prev_o, prev_c) and isBull(open, close) and
(open <= prev_c and close >= prev_o) and (b >= engulfRequireBodyPct * prev_b or (engulfAllowWicks and high >= prev_h and low <= prev_l))
// Bearish engulfing: previous bullish, current bearish, current body engulfs previous body
bearEngulf = showEngulfing and isBull(prev_o, prev_c) and isBear(open, close) and
(open >= prev_c and close <= prev_o) and (b >= engulfRequireBodyPct * prev_b or (engulfAllowWicks and high >= prev_h and low <= prev_l))
// ===== Three-candle patterns: Morning/Evening Star =====
// Morning Star: strong bearish candle, small middle candle (gap or small body), strong bullish close retracing into first body
o2 = open , c2 = close
b2 = body(c2, o2)
avgBody = ta.sma(body(close, open), 20)
smallMiddle = body(close , open ) <= starMiddleBodyMaxPct * nz(avgBody, prev_b)
firstBear = isBear(o2, c2)
lastBull = isBull(open, close)
retrBull = lastBull and (close >= (c2 + starCloseRetracePct * (o2 - c2)))
morningStar = showMorningStar and firstBear and smallMiddle and retrBull
// Evening Star: mirror
firstBull = isBull(o2, c2)
lastBear = isBear(open, close)
retrBear = lastBear and (close <= (c2 - starCloseRetracePct * (c2 - o2)))
eveningStar = showEveningStar and firstBull and smallMiddle and retrBear
// ===== Plotting =====
plotshape(hammer, title="Hammer", style=shape.labelup, location=location.belowbar, text="🔨\nHammer", size=size.tiny, color=color.new(color.lime, 0), textcolor=color.black)
plotshape(shootingStar, title="Shooting Star", style=shape.labeldown, location=location.abovebar, text="⭐\nStar", size=size.tiny, color=color.new(color.orange, 0), textcolor=color.black)
plotshape(bullEngulf, title="Bull Engulfing", style=shape.labelup, location=location.belowbar, text="🟢\nEngulf", size=size.tiny, color=color.new(color.teal, 0), textcolor=color.black)
plotshape(bearEngulf, title="Bear Engulfing", style=shape.labeldown, location=location.abovebar, text="🔴\nEngulf", size=size.tiny, color=color.new(color.red, 0), textcolor=color.white)
plotshape(morningStar, title="Morning Star", style=shape.labelup, location=location.belowbar, text="🌅\nMorning", size=size.tiny, color=color.new(color.aqua, 0), textcolor=color.black)
plotshape(eveningStar, title="Evening Star", style=shape.labeldown, location=location.abovebar, text="🌆\nEvening", size=size.tiny, color=color.new(color.purple, 0), textcolor=color.white)
// Optional: color bars when patterns occur
barcolor(hammer ? color.new(color.lime, 60) : na)
barcolor(shootingStar ? color.new(color.orange, 60) : na)
barcolor(bullEngulf ? color.new(color.teal, 70) : na)
barcolor(bearEngulf ? color.new(color.red, 70) : na)
barcolor(morningStar ? color.new(color.aqua, 70) : na)
barcolor(eveningStar ? color.new(color.purple, 70) : na)
// ===== Alerts =====
alertcondition(hammer, "Hammer", "Hammer detected")
alertcondition(shootingStar, "Shooting Star", "Shooting Star detected")
alertcondition(bullEngulf, "Bullish Engulfing","Bullish Engulfing detected")
alertcondition(bearEngulf, "Bearish Engulfing","Bearish Engulfing detected")
alertcondition(morningStar, "Morning Star", "Morning Star detected (3-candle)")
alertcondition(eveningStar, "Evening Star", "Evening Star detected (3-candle)")
// ===== Hints (toggle in the Style tab if labels feel too crowded) =====
// You can adjust thresholds to match your market/timeframe.
// Common tweaks: increase wickToBodyMin for stricter hammers/stars; increase minBodyFracRange to avoid doji;
// require stronger retrace in star patterns by raising starCloseRetracePct.
Cnagda Liquidit Trading SystemCnagda Liquidit Trading System helps spot where price is likely to trap traders and reverse, then gives simple, actionable Level to entry, place SL, and take profits with confidence. It blends imbalance zones, trend bias, order blocks, liquidity pools, high-probability fake Signal, and context-aware candle patterns into one clean workflow.
🟩🟥 Imbalance boxes: “Crowd rushed, gaps left”
What it is: Green/red boxes mark fast, one-sided moves where price “skipped” orders—think FVG-like zones that often get revisited.
Why it helps: Price frequently pulls back to “fill” these zones, creating clean retest entries with logical stops.
⏩How to use:
Green box = potential demand retest; Red box = potential supply retest. Enter on pullback into box, not on first impulse. Put stop on far side of box and aim first targets at recent swing points.
↕️ Swing bias (HH/HL vs LH/LL): “Which way is the road?”
What it is: Higher-highs/higher-lows = up-bias; Lower-highs/lower-lows = down-bias. system plots Buy/Sell OB levels aligned with that bias.
Why it helps: Trading with the broader flow reduces “hero trades” against institutions. Bias gives clearer entries and cleaner drawdowns.
⏩How to use:
Up-bias: look for long on Buy OB retests. Down-bias: look for short on Sell OB retests. Wait for a small rejection/engulfing to confirm before triggering.
🧱Order blocks: “Where big players remember”
What it is: last opposite-colored candle before an impulsive move—these zones often hold memory and reaction. system plots these as Buy/Sell OB lines.
Why it helps: Many breakouts pull back to the origin. Good entries often happen on retest, not on the breakout chase.
⏩ How to use:
Let price return into the OB, show wick rejection, and decent volume. Enter with stop beyond OB; define risk-reward before entry.
📊Volume coloring: “How Volume is move?”
What it is: Bar color reflects relative volume; inside bars are black. The dashboard also shows Volume and “Volume vs Prev.”
Why it helps: Patterns without volume often fade; volume validates strength and intent of moves.
⏩ How to use:
Favor entries where imbalance/OB/liquidity-grab coincide with higher volume. If volume is weak, reduce size or skip.
🧲 BSL/SSL liquidity pools: “Fishing for stops”
What it is: Equal highs cluster stops above (BSL); equal lows cluster stops below (SSL). system plots these and highlights the nearest one (“magnet”).
Why it helps: Price often sweeps these pools to trigger stops before reversing. This is a prime trap-reversal location.
⏩ How to use:
Watch nearest BSL/SSL. If price wicks through and closes back inside, anticipate a reversal. Trade reaction, not first poke. When price closes beyond, consider that pool mitigated and move on.
🟢🔴 Advanced liquidity grab: “Catch fakeout”
What it is: Bullish grab = makes a new low beyond a prior low but closes back above it, with a long lower wick, small body, and higher volume. Bearish is mirror. Labeled automatically.
Why it helps: It exposes trap moves (stop hunts) and often precedes true direction.
⏩ How to use:
Best when it aligns with a nearby imbalance/OB and supportive volume. Enter on reversal candle break or on retest. Stop goes beyond sweep wick.
🧠 Smart candlestick patterns (only in right place)
What it is: Engulfing, Hammer, Shooting Star, Hanging Man, Doji (with high volume), Morning/Evening Star, Piercing—but marked “effective” only if context (swing/trend/location) agrees.
Why it helps: same pattern in the wrong place is noise; in the right place, it’s signal.
⏩ How to use:
Location first (BSL/SSL/OB/imbalance), then pattern. Treat pattern as trigger/confirmation—one fresh label shows to keep chart clean.
🧭 Dashboard: “Context in a glance”
⏩ Reversal Level: current swing anchor—expect turns or reactions nearby; great for alerts and planning.
⏩ Volume vs Prev + Volume: Strength meter for signal candle—higher adds conviction.
⏩ Nearest Pool: next “magnet” area—look for sweeps/rejections there.
🧩Step-by-step trading flow (with mindset)
⏩ Set bias: HH/HL = long bias, LH/LL = short bias. Counter-trend only on clean sweeps with strong confirmation.
⏩ Find magnet: Check Nearest Pool (BSL/SSL). Focus attention there; it saves screen time.
⏩ Wait for event: Look for a sweep/grab label, or sharp rejection at pool/OB/imbalance. Avoid FOMO.
⏩ Add confluence: Stack 2–3 of these—imbalance box, OB, contextual pattern, supportive volume.
⏩Plan entry: Bullish: trigger above reversal candle high or take retest of FVG/OB. Stop below sweep wick/zone. Target at least 1:1.5–1:2.
Bearish: mirror above.
⏩Manage smartly: Take partials, move to breakeven or trail thoughtfully. Don’t drag stops inside zone out of emotion.
🎛️ Parameter tuning (to reduce human error)
⏩ swingLen: Smaller = faster but noisier; larger = cleaner but slower. Backtest first, then go live.
⏩ Tolerance (ATR or percent): ATR tolerance adapts to volatility (good for fast markets and lower TFs). Start around 0.15–0.30. In calm markets, try percent 0.05–0.15%.
⏩ minBarsGap: Start with 3–5 so equal highs/lows are truly equal—reduces false pools.
❌Common mistakes → ✅ Better habits
⏩Chasing every breakout → Wait for sweep/rejection, then confirm.
⏩Ignoring volume → Validate strength; cut size or skip on weak volume.
⏩Losing history of pools → If reviewing/backtesting, keep mitigated pools visible (dashed/faded).
⏩Over-tight tolerance/too small swingLen → Increases false signals; backtest to find balance.
📝 checklist (before entry)
⏩ Is there a nearby BSL/SSL and did a sweep/grab happen there?
⏩ Is there a close imbalance/OB that price can retest?
⏩ Do we have an effective pattern plus supportive volume?
⏩Is the stop beyond the wick/zone and RR ≥ 1:1.5?
•?((¯°·._.• 🎀 𝐻𝒶𝓅𝓅𝓎 𝒯𝓇𝒶𝒹𝒾𝓃𝑔 🎀 •._.·°¯((?•
Signal Hunter Pro - GKDXLSignal Hunter Pro - GKDXL combines four powerful technical indicators with trend strength filtering and volume confirmation to generate reliable BUY/SELL signals. This indicator is perfect for traders who want a systematic approach to market analysis without the noise of conflicting signals.
🔧 Core Features
📈 Multi-Indicator Signal System
Moving Averages: EMA 20, EMA 50, and SMA 200 for trend analysis
Bollinger Bands: Dynamic support/resistance with price momentum detection
RSI: Enhanced RSI logic with smoothing and multi-zone analysis
MACD: Traditional MACD with signal line crossovers and zero-line analysis
🎛️ Advanced Filtering System
ADX Trend Strength Filter: Only signals when trend strength exceeds threshold
Volume Confirmation: Ensures signals occur with adequate volume participation
Multi-Timeframe Logic: Works on any timeframe from 1m to 1D and beyond
🚨 Intelligent Signal Generation
Requires 3 out of 4 indicators to align for signal confirmation
Separate bullish and bearish signal conditions
Real-time signal strength scoring (1/4 to 4/4)
Built-in alert system for automated notifications
⚙️ Customizable Parameters
📊 Technical Settings
Moving Averages: Adjustable EMA and SMA periods
Bollinger Bands: Configurable length and multiplier
RSI: Customizable length, smoothing, and overbought/oversold levels
MACD: Flexible fast, slow, and signal line settings
🎯 Risk Management
Risk Percentage: Set your risk per trade (0.1% to 10%)
Reward Ratio: Configure risk-to-reward ratios (1:1 to 1:5)
ADX Threshold: Control minimum trend strength requirements
🖥️ Display Options
Indicator Visibility: Toggle individual indicators on/off
Information Table: Optional detailed status table (off by default)
Volume Analysis: Real-time volume vs. average comparison
🎨 Visual Elements
📈 Chart Indicators
EMA Lines: Blue (20) and Orange (50) exponential moving averages
SMA 200: Gray long-term trend line
Bollinger Bands: Upper/lower bands with semi-transparent fill
Clean Interface: Minimal visual clutter for clear analysis
📋 Information Table (Optional)
Real-time indicator status with ✓/✗/— symbols
Current signal strength and direction
ADX trend strength measurement
Volume confirmation status
No-signal reasons when conditions aren't met
🔔 Alert System
📢 Three Alert Types
BUY Signal: Triggered when 3+ indicators align bullishly
SELL Signal: Triggered when 3+ indicators align bearishly
General Alert: Any signal detection for broader monitoring
📱 Alert Messages
Clear, actionable alert text
Includes indicator name for easy identification
Compatible with webhook integrations
🎯 How It Works
📊 Signal Logic
Indicator Assessment: Each of the 4 indicators is evaluated as Bullish/Bearish/Neutral
Consensus Building: Counts aligned indicators (minimum 3 required)
Filter Application: Applies trend strength and volume filters
Signal Generation: Generates BUY/SELL when all conditions are met
🔍 Indicator States
Moving Averages: Price position, EMA alignment, and crossovers
Bollinger Bands: Price relative to bands and momentum shifts
RSI: Multi-zone analysis with momentum and crossover detection
MACD: Signal line crossovers and zero-line positioning
🎉 Why Choose Signal Hunter Pro?
✅ Multi-Indicator Confirmation reduces false signals
✅ Trend Strength Filtering improves win rate
✅ Volume Confirmation ensures market participation
✅ Customizable Parameters adapt to any trading style
✅ Clean Visual Design doesn't clutter your charts
✅ Professional Alert System for automated trading
✅ No Repainting - reliable historical signals
✅ Works on All Timeframes from scalping to investing
Inside Candle DivergenceStudy Material: Inside Candle Divergence Indicator (aiTrendview)
1. Introduction
The Inside Candle Divergence Indicator is a custom tool built on TradingView using Pine Script. It is designed to help traders identify potential reversal points or trend continuations using a mix of candlestick analysis, RSI (Relative Strength Index), VWAP (Volume Weighted Average Price), Pivot Points, and Volume analytics. The tool also provides a dashboard table on the chart, summarizing all key values in a single glance for traders and analysts.
This indicator is not just a signal generator but also an educational framework—explaining how different concepts in technical analysis combine to build a systematic approach for market entries and exits.
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2. Core Concepts Behind the Tool
A. Inside Candle Pattern
An Inside Candle forms when the current candle’s high is lower than or equal to the previous candle’s high, and the low is higher than or equal to the previous candle’s low.
• This means the entire price action of the current candle is "inside" the range of the previous candle.
• A bullish inside candle occurs when the close is higher than the open.
• A bearish inside candle occurs when the close is lower than the open.
This pattern shows market indecision but also sets up potential breakouts or trend reversals.
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B. RSI (Relative Strength Index)
The indicator calculates RSI using the formula from the ta.rsi() function in TradingView. RSI helps measure momentum in the market.
• A low RSI (below 25) signals an oversold zone → possible buy.
• A high RSI (above 75) signals an overbought zone → possible sell.
By combining RSI with the Inside Candle, the indicator ensures that signals are triggered only when momentum and price patterns confirm each other.
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C. Buy & Sell Signals
• Buy Signal: Triggered when RSI < Buy Level (default 25) and a bullish inside candle forms.
• Sell Signal: Triggered when RSI > Sell Level (default 75) and a bearish inside candle forms.
When triggered, the chart displays a BUY (green label below candle) or SELL (red label above candle) marker. The indicator also saves the entry price and signal bar for future reference inside the dashboard.
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D. VWAP (Volume Weighted Average Price)
VWAP is calculated using the typical price (H+L+C)/3 and weighting it by volume.
• VWAP shows the average trading price weighted by volume, widely used by institutions.
• The tool calculates the distance of price from VWAP in % terms.
• If price is far above VWAP, the market may be overheated (overbought). If far below, it may be undervalued (oversold).
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E. Volume Analysis
The tool splits volume into Buy Volume and Sell Volume:
• Buy Volume: If close > open.
• Sell Volume: If close ≤ open.
• Cumulative totals are maintained, and percentages are calculated to show what proportion of total market volume is bullish vs bearish.
• A progress bar style visual (using blocks █) shows the dominance of buyers or sellers.
This allows traders to quickly measure whether buyers or sellers are controlling the market trend.
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F. Daily Pivot Points
Pivot Points are calculated using the previous day’s high, low, and close:
• Pivot = (High + Low + Close) / 3
• R1, S1, R2, S2, R3, S3 levels are derived from this pivot.
• These levels act as support and resistance zones.
The script plots Pivot, R1, and S1 lines on the chart for easy reference.
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G. Trend Direction
The indicator checks where the price is compared to R1 and S1:
• If price > R1 → Bullish Trend
• If price < S1 → Bearish Trend
• Otherwise → Neutral Trend
The trend direction is displayed in the dashboard with arrows (↑, ↓, →).
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H. Price Change Calculation
The tool calculates:
• Price Change = Current Close – Previous Close
• Percentage Change = (Change / Previous Close) × 100
• Displays ▲ (green upward) or ▼ (red downward) with the exact percentage.
This gives traders a quick snapshot of intraday price movement.
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I. Dashboard Table
One of the most powerful features is the real-time dashboard table shown on the chart. It contains:
1. Symbol & Price Info (Current ticker, price, change %)
2. RSI Reading (with color coding: green for oversold, red for overbought)
3. VWAP and Distance from VWAP
4. Volume Analysis with Progress Bar (Buy vs Sell %)
5. Pivot Levels (Pivot, R1, S1)
6. Trend Direction (Bullish, Bearish, Neutral)
7. Signal Status (Last Buy/Sell signal with entry price)
This reduces the need for multiple indicators and gives traders a command-center view directly on the chart.
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J. Alerts
The tool generates alerts whenever a Buy or Sell condition is met. Traders can set up TradingView alerts to be notified instantly when:
• Buy Signal Alert → RSI oversold + Bullish inside candle
• Sell Signal Alert → RSI overbought + Bearish inside candle
This ensures no opportunity is missed even if you’re not actively monitoring the chart.
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K. Background Highlights
The chart background also changes faintly (light green or light red) when a Buy or Sell condition is triggered. This gives traders visual confirmation along with signals and alerts.
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3. Practical Use of This Tool
• Scalpers & Intraday Traders can use it for quick momentum-based entries.
• Swing Traders can use the RSI + Inside Candle + Pivot Points to find medium-term reversals.
• Analysts can use the dashboard for real-time summaries in reports.
• Volume Analysis helps understand institutional activity.
Remember: This is not a standalone holy grail. It must be used with proper risk management and confirmation from higher timeframes.
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4. Strict Disclaimer (aiTrendview)
⚠️ Disclaimer from aiTrendview:
This indicator is designed for educational and analytical purposes only. It is not financial advice or a guaranteed trading strategy. Markets are inherently risky and unpredictable; past performance of indicators does not ensure future results. Trading involves risk of financial loss, and traders must use proper risk management, stop-loss, and independent judgment.
aiTrendview strictly follows TradingView.com rules and compliance guidelines.
Any misuse of this tool, its code, or analytical features for unauthorized commercial purposes, false promises, or misleading activities is strictly discouraged. The creators of this script and aiTrendview will not be responsible for any losses, damages, or misuse arising from its application. Always trade responsibly and only with money you can afford to lose.
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Trendlines Oscillator [LuxAlgo]The Trendlines Oscillator helps traders identify trends and momentum based on the normalized distances between the current price and the most recently detected bullish and bearish trend lines.
The indicator features bullish and bearish momentum, a signal line with crossings, and multiple smoothing options.
🔶 USAGE
The indicator displays three lines: two for momentum and one for the signal. When one of the momentum lines (bullish or bearish) crosses the signal line, the tool displays a dot to indicate which momentum is gaining strength.
As a general rule, when the green bullish momentum line is above the red bearish momentum line, it indicates buyer strength. This means that the actual prices are farther from the support trend lines than the resistance trend lines. The opposite is true for seller strength.
To calculate bullish momentum, the tool first identifies bullish trend lines acting as support below the price. Then, it measures the delta between the price and those trend lines and normalizes the reading into the displayed momentum values.
The same process is used for bearish momentum, but with bearish trendlines acting as resistance above the price.
🔹 Length & Memory
Modifying the Length and Memory values will cause the tool to display different momentum values.
Traders can adjust the length to detect larger trendlines and adjust the memory to indicate how many trendlines the tool should consider.
As the chart above shows, smaller values make the tool more responsive, while larger values are useful for detecting larger trends.
🔹 Smoothing
By default, the data is not smoothed, and the signal uses a triangular moving average with a length of 10. Traders can smooth both the data and the signal line.
Traders can choose from up to ten different methods, or none. Some examples are shown on the chart above.
🔶 DETAILS
The steps for the calculations are as follows:
1. Gather the pivots, highs, and lows.
ph = fixnan(ta.pivothigh(lengthInput, lengthInput))
pl = fixnan(ta.pivotlow(lengthInput, lengthInput))
2. Calculate the slope and y-intercept for each trendline between contiguous lower highs (resistance) or higher lows (support).
if ph < ph
slope = (ph - ph )/(n-lengthInput - phx1)
res.unshift(l.new(ph - slope * phx1, slope))
if pl > pl
slope = (pl - pl )/(n-lengthInput - plx1)
sup.unshift(l.new(pl - slope * plx1, slope))
3. Calculate the value of each trendline on the current bar, then calculate the difference with the current price (delta). To calculate the relative sum of deltas, only consider trendlines below the price for support or above the price for resistance.
method get_point(l id, x)=>
id.slope * x + id.intercept
for element in sup
point = element.get_point(n)
if sourceInput > point
sup_sum += sourceInput - point
sup_den += math.abs(sourceInput - point)
for element in res
point = element.get_point(n)
if sourceInput < point
res_sum += point - sourceInput
res_den += math.abs(point - sourceInput)
4. Normalize the value from 0 to 100 by taking the sum of the relative values of the deltas divided by the sum of the absolute values of the deltas.
float supportLine = sup_sum / sup_den * 100
float resistanceLine = res_sum / res_den * 100
5. Smooth both values, then calculate the signal line as the difference between them.
float smoothSupport = smooth(supportLine,dataSmoothingInput,dataSmoothingLengthInput)
float smoothResistance = smooth(resistanceLine,dataSmoothingInput,dataSmoothingLengthInput)
float signal = math.abs(smoothSupport - smoothResistance)
float signalLine = smooth(signal,smoothingInput,smoothingLengthInput)
6. Calculate the crossing signals against the signal line, using only the first signal from each series of bullish or bearish crossings.
bullSignal = smoothSupport > signalLine and smoothSupport < signalLine
bearSignal = smoothResistance > signalLine and smoothResistance < signalLine
lastSignal := bullSignal and lastSignal == BEAR ? BULL : bearSignal and lastSignal == BULL ? BEAR : lastSignal
firstBull = ta.change(lastSignal) > 0
firstBear = ta.change(lastSignal) < 0
🔶 SETTINGS
Length: The size of the market structure used for trendline detection.
Memory: The number of trendlines used in calculations.
Source: The source for the calculations is closing prices by default.
🔹 Smoothing
Data Smoothing: Choose the smoothing method and length
Signal Smoothing: Choose the smoothing method and length
Tide Tracker ZonesTide Tracker Zones – Advanced Trend & Pullback Visualizer
Overview
Tide Tracker Zones is a sophisticated trading tool designed for traders who require clarity, precision, and actionable insights in real time. The indicator converts price action into dynamic trend zones, allowing users to instantly recognize market direction, potential reversals, and low-risk entry opportunities. By visualizing the market in this way, traders can focus on execution rather than deciphering complex charts.
Unlike static indicators, Tide Tracker Zones adapts to market volatility, providing a clear picture of bullish and bearish pressure across multiple timeframes. Its visual design, including color-coded trend zones, a prominent guide line, and carefully placed signals, ensures that market behavior is easy to interpret, making it suitable for scalping, swing trading, and longer-term strategies alike.
How It Works
The indicator relies on dynamic upper and lower bands derived from recent price ranges and a configurable multiplier. These bands expand during volatile periods and contract when price action stabilizes, creating flexible zones that reflect the dominant market tide.
A guide line tracks the active band, serving as a continuous reference for trend direction. Unlike traditional moving averages, the guide line does not clutter the chart but instead provides a subtle, intuitive indication of whether the market is in a bullish or bearish phase. Background shading reinforces this trend visually, highlighting bullish zones in one color and bearish zones in another, so the prevailing market flow is immediately clear.
The system continuously evaluates price relative to the bands to determine trend direction and detect potential reversals. When price crosses a band and flips the trend, the guide line updates, and signals are generated, providing traders with actionable information without overwhelming the chart.
Signals and Pullbacks
Tide Tracker Zones offers visual cues that make entry points more obvious and less speculative. Trend reversal arrows are plotted when the market changes direction: BUY arrows indicate a shift from bearish to bullish, and SELL arrows indicate a shift from bullish to bearish.
The indicator also highlights first pullbacks within an active trend. These pullback dots mark low-risk opportunities to enter a trend in progress, filtered to ensure that only the most relevant signals are displayed. The system uses ATR-based spacing to place arrows and dots vertically on the chart, preventing visual clutter and ensuring readability even during periods of high volatility.
Color-coded zones enhance situational awareness. Bullish zones are displayed in a customizable orange, while bearish zones are shown in green. Transparency is dynamically adjusted to maintain chart clarity while still providing a clear indication of trend strength.
Strategy Integration
Tide Tracker Zones can be used effectively for both trend-following and pullback strategies. Traders may enter positions in the direction of the guide line and colored zone, using trend reversal arrows for confirmation. First pullback dots offer tactical entries with reduced risk, allowing traders to enter a trend after a brief retracement.
Stop-loss levels can be placed just beyond the opposing trend zone, while take-profit targets may be determined using the width of the bands to account for market volatility. The indicator adapts seamlessly across multiple timeframes. Higher timeframes provide context and filter noise, while lower timeframes allow traders to refine entry timing. This makes it a versatile tool for scalping, swing trading, or longer-term positions.
Advanced Techniques
For traders seeking greater precision, Tide Tracker Zones can be combined with volume or momentum indicators to validate signals. Observing the sequence of trend arrows and pullback dots allows users to develop a systematic approach to entries and exits. Monitoring the width and behavior of the bands over time can also provide insights into periods of expanding or contracting volatility, helping traders anticipate market shifts.
Adjustments to the spread length and multiplier allow the indicator to be tuned for different assets and market conditions. By understanding the interaction between the guide line, trend zones, and pullback signals, traders can create a robust framework for decision-making, reducing guesswork and improving consistency.
Why Use Tide Tracker Zones
Tide Tracker Zones provides instant clarity and actionable insight in any market. Its dynamic zones and guide line give a clear visual understanding of trend direction, while trend reversal arrows and pullback dots highlight potential entry points. Unlike traditional indicators, it adapts to volatility and changing conditions, making it reliable across multiple asset classes and timeframes.
By combining trend detection, pullback analysis, and intuitive visual guidance, Tide Tracker Zones equips traders with a complete framework for disciplined, confident trading, transforming complex price action into a visual map of opportunity.
SmartPlusSmartPlus
Overview
The SmartPlus indicator is a complete framework for intraday traders. It combines key market reference points (VWAP, moving averages, and the first 15-minute high/low range) with predictive levels based on historical daily moves. Together, these elements allow traders to build directional bias, spot breakouts, and manage risk throughout the session.
Key Features
1. VWAP (Volume-Weighted Average Price)
- Plots the intraday VWAP in real time.
- VWAP acts as a central “fair value” reference point for institutional order flow.
- Price trading above VWAP generally suggests bullish bias, while below VWAP leans bearish.
2. Exponential Moving Averages (EMAs)
- Two configurable EMAs are included:
- Fast EMA (default: 21 periods)
- Slow EMA (default: 34 periods)
- Each EMA is plotted with a single, user-selectable color for clarity.
- Crossovers or alignment between price, VWAP, and EMAs help define market structure.
3. Smart Bar Coloring
- Candles automatically change color when conditions align:
- Bull Zone: Price above VWAP, Fast EMA, and Slow EMA.
- Bear Zone: Price below VWAP, Fast EMA, and Slow EMA.
- Fluorescent bar coloring helps highlight momentum zones visually without additional analysis.
4. First 15-Minute High/Low/Mid (Automatic)
- Automatically detects the first 15 minutes of each new trading day (no manual input required).
- Plots horizontal lines for:
- First 15-Minute High (green)
- First 15-Minute Low (red)
- Midpoint of that range (gray)
- Once the initial 15-minute window ends, these levels remain projected throughout the session as breakout or support/resistance zones.
- Alerts trigger when price breaks above the high or below the low after the window.
5. Daily Support/Resistance Forecast
- Uses a rolling lookback of recent daily ranges (default: 126 days).
- Tracks average up moves and down moves from the daily open.
- Optionally incorporates standard deviation for wider confidence bands.
- Plots forecast levels above/below the current day’s open for reference.
Trading Logic (How to Use)
- Bullish Bias:
- Price is above VWAP, above both EMAs, and ideally above the first 15-minute high.
- This setup suggests trend continuation or breakout opportunities on the long side.
- Bearish Bias:
- Price is below VWAP, below both EMAs, and ideally below the first 15-minute low.
- This setup suggests downward pressure or breakout opportunities on the short side.
- Neutral / Caution Zone:
- Price caught between VWAP, EMAs, or inside the 15-minute range often signals indecision.
- Best to wait for confirmation or breakout before committing to trades.
Expectations After Using It
- The script provides context and structure, not trading signals.
- It highlights where price is relative to meaningful market levels so traders can act with greater confidence.
- Combining VWAP, EMAs, and the 15-minute breakout framework helps traders stay aligned with the market’s natural rhythm.
Disclaimer
This script is a tool for market analysis and educational purposes only.
It does not constitute financial advice, trading recommendations, or guaranteed profitability.
Markets are inherently risky, and past patterns do not ensure future results.
Always combine this tool with sound risk management, personal research, and professional guidance before making any trading decisions.
Volatility Zones (VStop + Bands) — Fixed (v2)📝 What this indicator is
This script is called “Volatility Zones (VStop + Bands)”.
It is an ATR-based volatility indicator that combines dynamic volatility bands, a Volatility Stop line (VStop), and volatility spike detection into a single tool.
Unlike moving average–based indicators, this tool does not rely on averages of price direction. Instead, it measures the market’s true volatility and reacts to expansions or contractions in price ranges.
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⚙️ How it is built
The indicator uses several volatility-based components:
1. Average True Range (ATR)
o ATR is calculated over a user-defined length.
o It measures how much price typically moves in a given number of bars, making it the foundation of this indicator.
2. Volatility Bands
o Upper band = close + ATR × factor
o Lower band = close - ATR × factor
o The area between them is shaded.
o This gives traders an immediate visual sense of market volatility width — wide bands = high volatility, narrow bands = quiet market.
3. Volatility Stop (VStop)
o A stateful trailing stop based on ATR.
o It tracks the highest (or lowest) price in the current trend and places a stop offset by ATR × multiplier.
o When price crosses this stop, the indicator flips trend direction.
o This creates a dynamic stop-and-reverse mechanism that adapts to volatility.
4. Trend Zones
o When the trend is bullish, the stop is green and the chart background is shaded softly green.
o When bearish, the stop is red and the background is shaded softly red.
o This makes the market’s directional bias visually clear at all times.
5. Flip Signals (Buy/Sell Arrows)
o Whenever the VStop flips, arrows appear:
Green BUY arrows below price when the trend turns bullish.
Red SELL arrows above price when the trend turns bearish.
o These are also tied to built-in alerts for automation.
6. Volatility Spike Detection
o The script compares current ATR to its recent average.
o If ATR suddenly expands above a threshold, a small yellow “VOL” marker appears at the top of the chart.
o This highlights potential breakout phases or unusual volatility events.
7. Stop Labels
o At every trend flip, a small label appears at the bar, showing the exact stop level.
o This makes it easy to use the stop as a reference for risk management.
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📊 How it works in practice
• When price is above the VStop line, the market is considered in an uptrend.
• When price is below the VStop line, the market is in a downtrend.
• The bands expand/contract with volatility, helping traders gauge risk and position sizing.
• Flip arrows signal when trend direction changes.
• Volatility spikes warn traders that the market is entering a higher-risk phase, often before strong moves.
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🎯 How it may help traders
• Trend following → Helps traders identify whether the market is trending up or down.
• Stop placement → Provides a dynamic stop level that adjusts to volatility.
• Volatility awareness → Shaded bands and spike markers show when the market is likely to become unstable.
• Trade timing → Flip arrows and labels help identify potential entry or exit points.
• Risk management → Wide bands indicate higher risk; narrow bands suggest safer, tighter ranges.
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🌍 In what markets it is useful
Because the indicator is based purely on volatility, it works across all asset classes and timeframes:
• Stocks & ETFs → Helps identify breakouts and long-term trends.
• Forex → Very useful in spot FX where volatility shifts frequently.
• Crypto → ATR reacts strongly to high volatility, helping traders adapt stops dynamically.
• Futures & Commodities → Great for tracking trending commodities and managing risk.
Scalpers, swing traders, and position traders can all benefit by adjusting the ATR length and multipliers to suit their trading style.
________________________________________
💡 Originality of this script
This is not just a mashup of existing indicators. It integrates:
• ATR-based Volatility Bands for context,
• A stateful Volatility Stop (adapted and rewritten cleanly),
• Flip arrows and labels for actionable trading signals,
• Volatility spike detection to highlight regime shifts.
The result is a comprehensive volatility-aware trading tool that goes beyond just plotting ATR or trend stops.
________________________________________
🔔 Alerts
• Buy Flip → triggers when the trend changes bullish.
• Sell Flip → triggers when the trend changes bearish.
Traders can connect these alerts to automated strategies, bots, or notification systems.
Volume Profile Grid [Alpha Extract]A sophisticated volume distribution analysis system that transforms market activity into institutional-grade visual profiles, revealing hidden support/resistance zones and market participant behavior. Utilizing advanced price level segmentation, bullish/bearish volume separation, and dynamic range analysis, the Volume Profile Grid delivers comprehensive market structure insights with Point of Control (POC) identification, Value Area boundaries, and volume delta analysis. The system features intelligent visualization modes, real-time sentiment analysis, and flexible range selection to provide traders with clear, actionable volume-based market context.
🔶 Dynamic Range Analysis Engine
Implements dual-mode range selection with visible chart analysis and fixed period lookback, automatically adjusting to current market view or analyzing specified historical periods. The system intelligently calculates optimal bar counts while maintaining performance through configurable maximum limits, ensuring responsive profile generation across all timeframes with institutional-grade precision.
// Dynamic period calculation with intelligent caching
get_analysis_period() =>
if i_use_visible_range
chart_start_time = chart.left_visible_bar_time
current_time = last_bar_time
time_span = current_time - chart_start_time
tf_seconds = timeframe.in_seconds()
estimated_bars = time_span / (tf_seconds * 1000)
range_bars = math.floor(estimated_bars)
final_bars = math.min(range_bars, i_max_visible_bars)
math.max(final_bars, 50) // Minimum threshold
else
math.max(i_periods, 50)
🔶 Advanced Bull/Bear Volume Separation
Employs sophisticated candle classification algorithms to separate bullish and bearish volume at each price level, with weighted distribution based on bar intersection ratios. The system analyzes open/close relationships to determine volume direction, applying proportional allocation for doji patterns and ensuring accurate representation of buying versus selling pressure across the entire price spectrum.
🔶 Multi-Mode Volume Visualization
Features three distinct display modes for bull/bear volume representation: Split mode creates mirrored profiles from a central axis, Side by Side mode displays sequential bull/bear segments, and Stacked mode separates volumes vertically. Each mode offers unique insights into market participant behavior with customizable width, thickness, and color parameters for optimal visual clarity.
// Bull/Bear volume calculation with weighted distribution
for bar_offset = 0 to actual_periods - 1
bar_high = high
bar_low = low
bar_volume = volume
// Calculate intersection weight
weight = math.min(bar_high, next_level) - math.max(bar_low, current_level)
weight := weight / (bar_high - bar_low)
weighted_volume = bar_volume * weight
// Classify volume direction
if bar_close > bar_open
level_bull_volume += weighted_volume
else if bar_close < bar_open
level_bear_volume += weighted_volume
else // Doji handling
level_bull_volume += weighted_volume * 0.5
level_bear_volume += weighted_volume * 0.5
🔶 Point of Control & Value Area Detection
Implements institutional-standard POC identification by locating the price level with maximum volume accumulation, providing critical support/resistance zones. The Value Area calculation uses sophisticated sorting algorithms to identify the price range containing 70% of trading volume, revealing the market's accepted value zone where institutional participants concentrate their activity.
🔶 Volume Delta Analysis System
Incorporates real-time volume delta calculation with configurable dominance thresholds to identify significant bull/bear imbalances. The system visually highlights price levels where buying or selling pressure exceeds threshold percentages, providing immediate insight into directional volume flow and potential reversal zones through color-coded delta indicators.
// Value Area calculation using 70% volume accumulation
total_volume_sum = array.sum(total_volumes)
target_volume = total_volume_sum * 0.70
// Sort volumes to find highest activity zones
for i = 0 to array.size(sorted_volumes) - 2
for j = i + 1 to array.size(sorted_volumes) - 1
if array.get(sorted_volumes, j) > array.get(sorted_volumes, i)
// Swap and track indices for value area boundaries
// Accumulate until 70% threshold reached
for i = 0 to array.size(sorted_indices) - 1
accumulated_volume += vol
array.push(va_levels, array.get(volume_levels, idx))
if accumulated_volume >= target_volume
break
❓How It Works
🔶 Weighted Volume Distribution
Implements proportional volume allocation based on the percentage of each bar that intersects with price levels. When a bar spans multiple levels, volume is distributed proportionally based on the intersection ratio, ensuring precise representation of trading activity across the entire price spectrum without double-counting or volume loss.
🔶 Real-Time Profile Generation
Profiles regenerate on each bar close when in visible range mode, automatically adapting to chart zoom and scroll actions. The system maintains optimal performance through intelligent caching mechanisms and selective line updates, ensuring smooth operation even with maximum resolution settings and extended analysis periods.
🔶 Market Sentiment Analysis
Features comprehensive volume analysis table displaying total volume metrics, bullish/bearish percentages, and overall market sentiment classification. The system calculates volume dominance ratios in real-time, providing immediate insight into whether buyers or sellers control the current price structure with percentage-based sentiment thresholds.
🔶 Visual Profile Mapping
Provides multi-layered visual feedback through colored volume bars, POC line highlighting, Value Area boundaries, and optional delta indicators. The system supports profile mirroring for alternative perspectives, line extension for future reference, and customizable label positioning with detailed price information at critical levels.
Why Choose Volume Profile Grid
The Volume Profile Grid represents the evolution of volume analysis tools, combining traditional volume profile concepts with modern visualization techniques and intelligent analysis algorithms. By integrating dynamic range selection, sophisticated bull/bear separation, and multi-mode visualization with POC/Value Area detection, it provides traders with institutional-quality market structure analysis that adapts to any trading style. The comprehensive delta analysis and sentiment monitoring system eliminates guesswork while the flexible visualization options ensure optimal clarity across all market conditions, making it an essential tool for traders seeking to understand true market dynamics through volume-based price discovery.
Chart-Only Scanner — Pro Table v2.5.1Chart-Only Scanner — Pro Table v2.5
User Manual (Pine Script v6)
What this tool does (in one line)
A compact, on-chart table that scores the current chart symbol (or an optional override) using momentum, volume, trend, volatility, and pattern checks—so you can quickly decide UP, DOWN, or WAIT.
Quick Start (90 seconds)
Add the indicator to any chart and timeframe (1m…1M).
Leave “Override chart symbol” = OFF to auto-use the chart’s symbol.
Choose your layout:
Row (wide horizontal strip), or Grid (title + labeled cells).
Pick a size preset (Micro, Small, Medium, Large, Mobile).
Optional: turn on “Use Higher TF (EMA 20/50)” and set HTF Multiplier (e.g., 4 ⇒ if chart is 15m, HTF is 60m).
Watch the table:
DIR (↑/↓/→), ROC%, MOM, VOL, EMA stack, HTF, REV, SCORE, ACT.
Add an alert if you want: the script fires when |SCORE| ≥ Action threshold.
What to expect
A small table appears on the chart corner you choose, updating each bar (or only at bar close if you keep default smart-update).
The ACT cell shows 🔥 (strong), 👀 (medium), or ⏳ (weak).
Panels & Settings (every option explained)
Core
Momentum Period: Lookback for rate-of-change (ROC%). Shorter = more reactive; longer = smoother.
ROC% Threshold: Minimum absolute ROC% to call direction UP (↑) or DOWN (↓); otherwise →.
Require Volume Confirmation: If ON and VOL ≤ 1.0, the SCORE is forced to 0 (prevents low-volume false positives).
Override chart symbol + Custom symbol: By default, the indicator uses the chart’s symbol. Turn this ON to lock to a specific ticker (e.g., a perpetual).
Higher TF
Use Higher TF (EMA 20/50): Compares EMA20 vs EMA50 on a higher timeframe.
HTF Multiplier: Higher TF = (chart TF × multiplier).
Example: on 3H chart with multiplier 2 ⇒ HTF = 6H.
Volatility & Oscillators
ATR Length: Used to show ATR% (ATR relative to price).
RSI Length: Standard RSI; colors: green ≤30 (oversold), red ≥70 (overbought).
Stoch %K Length: With %D = SMA(%K, 3).
MACD Fast/Slow/Signal: Standard MACD values; we display Line, Signal, Histogram (L/S/H).
ADX Length (Wilder): Wilder’s smoothing (internal derivation); also shows +DI / −DI if you enable the ADX column.
EMAs / Trend
EMA Fast/Mid/Slow: We compute EMA(20/50/200) by default (editable).
EMA Stack: Bull if Fast > Mid > Slow; Bear if Fast < Mid < Slow; Flat otherwise.
Benchmark (optional, OFF by default)
Show Relative Strength vs Benchmark: Displays RS% = ROC(symbol) − ROC(benchmark) over the Momentum Period.
Benchmark Symbol: Ticker used for comparison (e.g., BTCUSDT as a market proxy).
Columns (show/hide)
Toggle which fields appear in the table. Hiding unused fields keeps the layout clean (especially on mobile).
Display
Layout Mode:
Row = a single two-row strip; each column is a metric.
Grid = a title row plus labeled pairs (label/value) arranged in rows.
Size Preset: Micro, Small, Medium, Large, Mobile change text size and the grid density.
Table Corner: Where the panel sits (e.g., Top Right).
Opaque Table Background: ON = dark card; OFF = transparent(ish).
Update Every Bar: ON = update intra-bar; OFF = smart update (last bar / real-time / confirmed history).
Action threshold (|score|): The cutoff for 🔥 and alert firing (default 70).
How to read each field
CHART: The active symbol name (or your custom override).
DIR: ↑ (ROC% > threshold), ↓ (ROC% < −threshold), → otherwise.
ROC%: Rate of change over Momentum Period.
Formula: (Close − Close ) / Close × 100.
MOM: A scaled momentum score: min(100, |ROC%| × 10).
VOL: Volume ratio vs 20-bar SMA: Volume / SMA(Volume,20).
1.5 highlights as yellow (significant participation).
ATR%: (ATR / Close) × 100 (volatility relative to price).
RSI: Colored for extremes: ≤30 green, ≥70 red.
Stoch K/D: %K and %D numbers.
MACD L/S/H: Line, Signal, Histogram. Histogram color reflects sign (green > 0, red < 0).
ADX, +DI, −DI: Trend strength and directional components (Wilder). ADX ≥ 25 is highlighted.
EMA 20/50/200: Current EMA values (editable lengths).
STACK: Bull/Bear/Flat as defined above.
VWAP%: (Close − VWAP) / Close × 100 (premium/discount to VWAP).
HTF: ▲ if HTF EMA20 > EMA50; ▼ if <; · if flat/off.
RS%: Symbol’s ROC% − Benchmark ROC% (positive = outperforming).
REV (reversal):
🟢 Eng/Pin = bullish engulfing or bullish pin detected,
🔴 Eng/Pin = bearish engulfing or bearish pin,
· = none.
SCORE (absolute shown as a number; sign shown via DIR and ACT):
Components:
base = MOM × 0.4
volBonus = VOL > 1.5 ? 20 : VOL × 13.33
htfBonus = use_mtf ? (HTF == DIR ? 30 : HTF == 0 ? 15 : 0) : 0
trendBonus = (STACK == DIR) ? 10 : 0
macdBonus = 0 (placeholder for future versions)
scoreRaw = base + volBonus + htfBonus + trendBonus + macdBonus
SCORE = DIR ≥ 0 ? scoreRaw : −scoreRaw
If Require Volume Confirmation and VOL ≤ 1.0 ⇒ SCORE = 0.
ACT:
🔥 if |SCORE| ≥ threshold
👀 if 50 < |SCORE| < threshold
⏳ otherwise
Practical examples
Strong long (trend + participation)
DIR = ↑, ROC% = +3.2, MOM ≈ 32, VOL = 1.9, STACK = Bull, HTF = ▲, REV = 🟢
SCORE: base(12.8) + volBonus(20) + htfBonus(30) + trend(10) ≈ 73 → ACT = 🔥
Action idea: look for longs on pullbacks; confirm risk with ATR%.
Weak long (no volume)
DIR = ↑, ROC% = +1.0, but VOL = 0.8 and Require Volume Confirmation = ON
SCORE forced to 0 → ACT = ⏳
Action: wait for volume > 1.0 or turn off confirmation knowingly.
Bearish reversal warning
DIR = →, REV = 🔴 (bearish engulfing), RSI = 68, HTF = ▼
SCORE may be mid-range; ACT = 👀
Action: watch for breakdown and rising VOL.
Alerts (how to use)
The script calls alert() whenever |SCORE| ≥ Action threshold.
To receive pop-ups, sounds, or emails: click “⏰ Alerts” in TradingView, choose this indicator, and pick “Any alert() function call.”
The alert message includes: symbol, |SCORE|, DIR.
Layout, Size, and Corner tips
Row is best when you want a compact status ribbon across the top.
Grid is clearer on big screens or when you enable many columns.
Size:
Mobile = one pair per row (tall, readable)
Micro/Small = dense; good for many fields
Large = presentation/screenshots
Corner: If the table overlaps price, change the corner or set Opaque Background = OFF.
Repaint & timeframe behavior
Default smart update prefers stability (last bar / live / confirmed history).
For a stricter, “close-only” behavior (less repaint): turn Update Every Bar = OFF and avoid Heikin Ashi when you want raw market OHLC (HA modifies price inputs).
HTF logic is derived from a clean, integer multiple of your chart timeframe (via multiplier). It works with 3H/4H and any TF.
Performance notes
The script analyzes one symbol (chart or override) with multiple metrics using efficient tuple requests.
If you later want a multi-symbol grid, do it with pages (10–15 per page + rotate) to stay within platform limits (recommended future add-on).
Troubleshooting
No table visible
Ensure the indicator is added and not hidden.
Try toggling Opaque Background or switch Corner (it might be behind other drawings).
Keep Columns count reasonable for the chosen Size.
If you turned ON Override, verify the Custom symbol exists on your data provider.
Numbers look different on HA candles
Heikin Ashi modifies OHLC; switch to regular candles if you need raw price metrics.
3H/4H issues
Use integer HTF Multiplier (e.g., 2, 4). The tool builds the correct string internally; no manual timeframe strings needed.
Power user tips
Volume gating: keeping Require Volume Confirmation = ON filters most fake moves; if you’re a scalper, reduce strictness or turn it off.
Action threshold: 60–80 is typical. Higher = fewer but stronger signals.
Benchmark RS%: great for spotting leaders/laggards; positive RS% = outperformance vs benchmark.
Change policy & safety
This version doesn’t alter your historical logic you tested (no radical changes).
Any future “radical” change (score weights, HTF logic, UI hiding data) will ship with a toggle and an Impact Statement so you can keep old behavior if you prefer.
Glossary (quick)
ROC%: Percent change over N bars.
MOM: Scaled momentum (0–100).
VOL ratio: Volume vs 20-bar average.
ATR%: ATR as % of price.
ADX/DI: Trend strength / direction components (Wilder).
EMA stack: Relationship between EMAs (bullish/bearish/flat).
VWAP%: Premium/discount to VWAP.
RS%: Relative strength vs benchmark.
Markov Chain [3D] | FractalystWhat exactly is a Markov Chain?
This indicator uses a Markov Chain model to analyze, quantify, and visualize the transitions between market regimes (Bull, Bear, Neutral) on your chart. It dynamically detects these regimes in real-time, calculates transition probabilities, and displays them as animated 3D spheres and arrows, giving traders intuitive insight into current and future market conditions.
How does a Markov Chain work, and how should I read this spheres-and-arrows diagram?
Think of three weather modes: Sunny, Rainy, Cloudy.
Each sphere is one mode. The loop on a sphere means “stay the same next step” (e.g., Sunny again tomorrow).
The arrows leaving a sphere show where things usually go next if they change (e.g., Sunny moving to Cloudy).
Some paths matter more than others. A more prominent loop means the current mode tends to persist. A more prominent outgoing arrow means a change to that destination is the usual next step.
Direction isn’t symmetric: moving Sunny→Cloudy can behave differently than Cloudy→Sunny.
Now relabel the spheres to markets: Bull, Bear, Neutral.
Spheres: market regimes (uptrend, downtrend, range).
Self‑loop: tendency for the current regime to continue on the next bar.
Arrows: the most common next regime if a switch happens.
How to read: Start at the sphere that matches current bar state. If the loop stands out, expect continuation. If one outgoing path stands out, that switch is the typical next step. Opposite directions can differ (Bear→Neutral doesn’t have to match Neutral→Bear).
What states and transitions are shown?
The three market states visualized are:
Bullish (Bull): Upward or strong-market regime.
Bearish (Bear): Downward or weak-market regime.
Neutral: Sideways or range-bound regime.
Bidirectional animated arrows and probability labels show how likely the market is to move from one regime to another (e.g., Bull → Bear or Neutral → Bull).
How does the regime detection system work?
You can use either built-in price returns (based on adaptive Z-score normalization) or supply three custom indicators (such as volume, oscillators, etc.).
Values are statistically normalized (Z-scored) over a configurable lookback period.
The normalized outputs are classified into Bull, Bear, or Neutral zones.
If using three indicators, their regime signals are averaged and smoothed for robustness.
How are transition probabilities calculated?
On every confirmed bar, the algorithm tracks the sequence of detected market states, then builds a rolling window of transitions.
The code maintains a transition count matrix for all regime pairs (e.g., Bull → Bear).
Transition probabilities are extracted for each possible state change using Laplace smoothing for numerical stability, and frequently updated in real-time.
What is unique about the visualization?
3D animated spheres represent each regime and change visually when active.
Animated, bidirectional arrows reveal transition probabilities and allow you to see both dominant and less likely regime flows.
Particles (moving dots) animate along the arrows, enhancing the perception of regime flow direction and speed.
All elements dynamically update with each new price bar, providing a live market map in an intuitive, engaging format.
Can I use custom indicators for regime classification?
Yes! Enable the "Custom Indicators" switch and select any three chart series as inputs. These will be normalized and combined (each with equal weight), broadening the regime classification beyond just price-based movement.
What does the “Lookback Period” control?
Lookback Period (default: 100) sets how much historical data builds the probability matrix. Shorter periods adapt faster to regime changes but may be noisier. Longer periods are more stable but slower to adapt.
How is this different from a Hidden Markov Model (HMM)?
It sets the window for both regime detection and probability calculations. Lower values make the system more reactive, but potentially noisier. Higher values smooth estimates and make the system more robust.
How is this Markov Chain different from a Hidden Markov Model (HMM)?
Markov Chain (as here): All market regimes (Bull, Bear, Neutral) are directly observable on the chart. The transition matrix is built from actual detected regimes, keeping the model simple and interpretable.
Hidden Markov Model: The actual regimes are unobservable ("hidden") and must be inferred from market output or indicator "emissions" using statistical learning algorithms. HMMs are more complex, can capture more subtle structure, but are harder to visualize and require additional machine learning steps for training.
A standard Markov Chain models transitions between observable states using a simple transition matrix, while a Hidden Markov Model assumes the true states are hidden (latent) and must be inferred from observable “emissions” like price or volume data. In practical terms, a Markov Chain is transparent and easier to implement and interpret; an HMM is more expressive but requires statistical inference to estimate hidden states from data.
Markov Chain: states are observable; you directly count or estimate transition probabilities between visible states. This makes it simpler, faster, and easier to validate and tune.
HMM: states are hidden; you only observe emissions generated by those latent states. Learning involves machine learning/statistical algorithms (commonly Baum–Welch/EM for training and Viterbi for decoding) to infer both the transition dynamics and the most likely hidden state sequence from data.
How does the indicator avoid “repainting” or look-ahead bias?
All regime changes and matrix updates happen only on confirmed (closed) bars, so no future data is leaked, ensuring reliable real-time operation.
Are there practical tuning tips?
Tune the Lookback Period for your asset/timeframe: shorter for fast markets, longer for stability.
Use custom indicators if your asset has unique regime drivers.
Watch for rapid changes in transition probabilities as early warning of a possible regime shift.
Who is this indicator for?
Quants and quantitative researchers exploring probabilistic market modeling, especially those interested in regime-switching dynamics and Markov models.
Programmers and system developers who need a probabilistic regime filter for systematic and algorithmic backtesting:
The Markov Chain indicator is ideally suited for programmatic integration via its bias output (1 = Bull, 0 = Neutral, -1 = Bear).
Although the visualization is engaging, the core output is designed for automated, rules-based workflows—not for discretionary/manual trading decisions.
Developers can connect the indicator’s output directly to their Pine Script logic (using input.source()), allowing rapid and robust backtesting of regime-based strategies.
It acts as a plug-and-play regime filter: simply plug the bias output into your entry/exit logic, and you have a scientifically robust, probabilistically-derived signal for filtering, timing, position sizing, or risk regimes.
The MC's output is intentionally "trinary" (1/0/-1), focusing on clear regime states for unambiguous decision-making in code. If you require nuanced, multi-probability or soft-label state vectors, consider expanding the indicator or stacking it with a probability-weighted logic layer in your scripting.
Because it avoids subjectivity, this approach is optimal for systematic quants, algo developers building backtested, repeatable strategies based on probabilistic regime analysis.
What's the mathematical foundation behind this?
The mathematical foundation behind this Markov Chain indicator—and probabilistic regime detection in finance—draws from two principal models: the (standard) Markov Chain and the Hidden Markov Model (HMM).
How to use this indicator programmatically?
The Markov Chain indicator automatically exports a bias value (+1 for Bullish, -1 for Bearish, 0 for Neutral) as a plot visible in the Data Window. This allows you to integrate its regime signal into your own scripts and strategies for backtesting, automation, or live trading.
Step-by-Step Integration with Pine Script (input.source)
Add the Markov Chain indicator to your chart.
This must be done first, since your custom script will "pull" the bias signal from the indicator's plot.
In your strategy, create an input using input.source()
Example:
//@version=5
strategy("MC Bias Strategy Example")
mcBias = input.source(close, "MC Bias Source")
After saving, go to your script’s settings. For the “MC Bias Source” input, select the plot/output of the Markov Chain indicator (typically its bias plot).
Use the bias in your trading logic
Example (long only on Bull, flat otherwise):
if mcBias == 1
strategy.entry("Long", strategy.long)
else
strategy.close("Long")
For more advanced workflows, combine mcBias with additional filters or trailing stops.
How does this work behind-the-scenes?
TradingView’s input.source() lets you use any plot from another indicator as a real-time, “live” data feed in your own script (source).
The selected bias signal is available to your Pine code as a variable, enabling logical decisions based on regime (trend-following, mean-reversion, etc.).
This enables powerful strategy modularity : decouple regime detection from entry/exit logic, allowing fast experimentation without rewriting core signal code.
Integrating 45+ Indicators with Your Markov Chain — How & Why
The Enhanced Custom Indicators Export script exports a massive suite of over 45 technical indicators—ranging from classic momentum (RSI, MACD, Stochastic, etc.) to trend, volume, volatility, and oscillator tools—all pre-calculated, centered/scaled, and available as plots.
// Enhanced Custom Indicators Export - 45 Technical Indicators
// Comprehensive technical analysis suite for advanced market regime detection
//@version=6
indicator('Enhanced Custom Indicators Export | Fractalyst', shorttitle='Enhanced CI Export', overlay=false, scale=scale.right, max_labels_count=500, max_lines_count=500)
// |----- Input Parameters -----| //
momentum_group = "Momentum Indicators"
trend_group = "Trend Indicators"
volume_group = "Volume Indicators"
volatility_group = "Volatility Indicators"
oscillator_group = "Oscillator Indicators"
display_group = "Display Settings"
// Common lengths
length_14 = input.int(14, "Standard Length (14)", minval=1, maxval=100, group=momentum_group)
length_20 = input.int(20, "Medium Length (20)", minval=1, maxval=200, group=trend_group)
length_50 = input.int(50, "Long Length (50)", minval=1, maxval=200, group=trend_group)
// Display options
show_table = input.bool(true, "Show Values Table", group=display_group)
table_size = input.string("Small", "Table Size", options= , group=display_group)
// |----- MOMENTUM INDICATORS (15 indicators) -----| //
// 1. RSI (Relative Strength Index)
rsi_14 = ta.rsi(close, length_14)
rsi_centered = rsi_14 - 50
// 2. Stochastic Oscillator
stoch_k = ta.stoch(close, high, low, length_14)
stoch_d = ta.sma(stoch_k, 3)
stoch_centered = stoch_k - 50
// 3. Williams %R
williams_r = ta.stoch(close, high, low, length_14) - 100
// 4. MACD (Moving Average Convergence Divergence)
= ta.macd(close, 12, 26, 9)
// 5. Momentum (Rate of Change)
momentum = ta.mom(close, length_14)
momentum_pct = (momentum / close ) * 100
// 6. Rate of Change (ROC)
roc = ta.roc(close, length_14)
// 7. Commodity Channel Index (CCI)
cci = ta.cci(close, length_20)
// 8. Money Flow Index (MFI)
mfi = ta.mfi(close, length_14)
mfi_centered = mfi - 50
// 9. Awesome Oscillator (AO)
ao = ta.sma(hl2, 5) - ta.sma(hl2, 34)
// 10. Accelerator Oscillator (AC)
ac = ao - ta.sma(ao, 5)
// 11. Chande Momentum Oscillator (CMO)
cmo = ta.cmo(close, length_14)
// 12. Detrended Price Oscillator (DPO)
dpo = close - ta.sma(close, length_20)
// 13. Price Oscillator (PPO)
ppo = ta.sma(close, 12) - ta.sma(close, 26)
ppo_pct = (ppo / ta.sma(close, 26)) * 100
// 14. TRIX
trix_ema1 = ta.ema(close, length_14)
trix_ema2 = ta.ema(trix_ema1, length_14)
trix_ema3 = ta.ema(trix_ema2, length_14)
trix = ta.roc(trix_ema3, 1) * 10000
// 15. Klinger Oscillator
klinger = ta.ema(volume * (high + low + close) / 3, 34) - ta.ema(volume * (high + low + close) / 3, 55)
// 16. Fisher Transform
fisher_hl2 = 0.5 * (hl2 - ta.lowest(hl2, 10)) / (ta.highest(hl2, 10) - ta.lowest(hl2, 10)) - 0.25
fisher = 0.5 * math.log((1 + fisher_hl2) / (1 - fisher_hl2))
// 17. Stochastic RSI
stoch_rsi = ta.stoch(rsi_14, rsi_14, rsi_14, length_14)
stoch_rsi_centered = stoch_rsi - 50
// 18. Relative Vigor Index (RVI)
rvi_num = ta.swma(close - open)
rvi_den = ta.swma(high - low)
rvi = rvi_den != 0 ? rvi_num / rvi_den : 0
// 19. Balance of Power (BOP)
bop = (close - open) / (high - low)
// |----- TREND INDICATORS (10 indicators) -----| //
// 20. Simple Moving Average Momentum
sma_20 = ta.sma(close, length_20)
sma_momentum = ((close - sma_20) / sma_20) * 100
// 21. Exponential Moving Average Momentum
ema_20 = ta.ema(close, length_20)
ema_momentum = ((close - ema_20) / ema_20) * 100
// 22. Parabolic SAR
sar = ta.sar(0.02, 0.02, 0.2)
sar_trend = close > sar ? 1 : -1
// 23. Linear Regression Slope
lr_slope = ta.linreg(close, length_20, 0) - ta.linreg(close, length_20, 1)
// 24. Moving Average Convergence (MAC)
mac = ta.sma(close, 10) - ta.sma(close, 30)
// 25. Trend Intensity Index (TII)
tii_sum = 0.0
for i = 1 to length_20
tii_sum += close > close ? 1 : 0
tii = (tii_sum / length_20) * 100
// 26. Ichimoku Cloud Components
ichimoku_tenkan = (ta.highest(high, 9) + ta.lowest(low, 9)) / 2
ichimoku_kijun = (ta.highest(high, 26) + ta.lowest(low, 26)) / 2
ichimoku_signal = ichimoku_tenkan > ichimoku_kijun ? 1 : -1
// 27. MESA Adaptive Moving Average (MAMA)
mama_alpha = 2.0 / (length_20 + 1)
mama = ta.ema(close, length_20)
mama_momentum = ((close - mama) / mama) * 100
// 28. Zero Lag Exponential Moving Average (ZLEMA)
zlema_lag = math.round((length_20 - 1) / 2)
zlema_data = close + (close - close )
zlema = ta.ema(zlema_data, length_20)
zlema_momentum = ((close - zlema) / zlema) * 100
// |----- VOLUME INDICATORS (6 indicators) -----| //
// 29. On-Balance Volume (OBV)
obv = ta.obv
// 30. Volume Rate of Change (VROC)
vroc = ta.roc(volume, length_14)
// 31. Price Volume Trend (PVT)
pvt = ta.pvt
// 32. Negative Volume Index (NVI)
nvi = 0.0
nvi := volume < volume ? nvi + ((close - close ) / close ) * nvi : nvi
// 33. Positive Volume Index (PVI)
pvi = 0.0
pvi := volume > volume ? pvi + ((close - close ) / close ) * pvi : pvi
// 34. Volume Oscillator
vol_osc = ta.sma(volume, 5) - ta.sma(volume, 10)
// 35. Ease of Movement (EOM)
eom_distance = high - low
eom_box_height = volume / 1000000
eom = eom_box_height != 0 ? eom_distance / eom_box_height : 0
eom_sma = ta.sma(eom, length_14)
// 36. Force Index
force_index = volume * (close - close )
force_index_sma = ta.sma(force_index, length_14)
// |----- VOLATILITY INDICATORS (10 indicators) -----| //
// 37. Average True Range (ATR)
atr = ta.atr(length_14)
atr_pct = (atr / close) * 100
// 38. Bollinger Bands Position
bb_basis = ta.sma(close, length_20)
bb_dev = 2.0 * ta.stdev(close, length_20)
bb_upper = bb_basis + bb_dev
bb_lower = bb_basis - bb_dev
bb_position = bb_dev != 0 ? (close - bb_basis) / bb_dev : 0
bb_width = bb_dev != 0 ? (bb_upper - bb_lower) / bb_basis * 100 : 0
// 39. Keltner Channels Position
kc_basis = ta.ema(close, length_20)
kc_range = ta.ema(ta.tr, length_20)
kc_upper = kc_basis + (2.0 * kc_range)
kc_lower = kc_basis - (2.0 * kc_range)
kc_position = kc_range != 0 ? (close - kc_basis) / kc_range : 0
// 40. Donchian Channels Position
dc_upper = ta.highest(high, length_20)
dc_lower = ta.lowest(low, length_20)
dc_basis = (dc_upper + dc_lower) / 2
dc_position = (dc_upper - dc_lower) != 0 ? (close - dc_basis) / (dc_upper - dc_lower) : 0
// 41. Standard Deviation
std_dev = ta.stdev(close, length_20)
std_dev_pct = (std_dev / close) * 100
// 42. Relative Volatility Index (RVI)
rvi_up = ta.stdev(close > close ? close : 0, length_14)
rvi_down = ta.stdev(close < close ? close : 0, length_14)
rvi_total = rvi_up + rvi_down
rvi_volatility = rvi_total != 0 ? (rvi_up / rvi_total) * 100 : 50
// 43. Historical Volatility
hv_returns = math.log(close / close )
hv = ta.stdev(hv_returns, length_20) * math.sqrt(252) * 100
// 44. Garman-Klass Volatility
gk_vol = math.log(high/low) * math.log(high/low) - (2*math.log(2)-1) * math.log(close/open) * math.log(close/open)
gk_volatility = math.sqrt(ta.sma(gk_vol, length_20)) * 100
// 45. Parkinson Volatility
park_vol = math.log(high/low) * math.log(high/low)
parkinson = math.sqrt(ta.sma(park_vol, length_20) / (4 * math.log(2))) * 100
// 46. Rogers-Satchell Volatility
rs_vol = math.log(high/close) * math.log(high/open) + math.log(low/close) * math.log(low/open)
rogers_satchell = math.sqrt(ta.sma(rs_vol, length_20)) * 100
// |----- OSCILLATOR INDICATORS (5 indicators) -----| //
// 47. Elder Ray Index
elder_bull = high - ta.ema(close, 13)
elder_bear = low - ta.ema(close, 13)
elder_power = elder_bull + elder_bear
// 48. Schaff Trend Cycle (STC)
stc_macd = ta.ema(close, 23) - ta.ema(close, 50)
stc_k = ta.stoch(stc_macd, stc_macd, stc_macd, 10)
stc_d = ta.ema(stc_k, 3)
stc = ta.stoch(stc_d, stc_d, stc_d, 10)
// 49. Coppock Curve
coppock_roc1 = ta.roc(close, 14)
coppock_roc2 = ta.roc(close, 11)
coppock = ta.wma(coppock_roc1 + coppock_roc2, 10)
// 50. Know Sure Thing (KST)
kst_roc1 = ta.roc(close, 10)
kst_roc2 = ta.roc(close, 15)
kst_roc3 = ta.roc(close, 20)
kst_roc4 = ta.roc(close, 30)
kst = ta.sma(kst_roc1, 10) + 2*ta.sma(kst_roc2, 10) + 3*ta.sma(kst_roc3, 10) + 4*ta.sma(kst_roc4, 15)
// 51. Percentage Price Oscillator (PPO)
ppo_line = ((ta.ema(close, 12) - ta.ema(close, 26)) / ta.ema(close, 26)) * 100
ppo_signal = ta.ema(ppo_line, 9)
ppo_histogram = ppo_line - ppo_signal
// |----- PLOT MAIN INDICATORS -----| //
// Plot key momentum indicators
plot(rsi_centered, title="01_RSI_Centered", color=color.purple, linewidth=1)
plot(stoch_centered, title="02_Stoch_Centered", color=color.blue, linewidth=1)
plot(williams_r, title="03_Williams_R", color=color.red, linewidth=1)
plot(macd_histogram, title="04_MACD_Histogram", color=color.orange, linewidth=1)
plot(cci, title="05_CCI", color=color.green, linewidth=1)
// Plot trend indicators
plot(sma_momentum, title="06_SMA_Momentum", color=color.navy, linewidth=1)
plot(ema_momentum, title="07_EMA_Momentum", color=color.maroon, linewidth=1)
plot(sar_trend, title="08_SAR_Trend", color=color.teal, linewidth=1)
plot(lr_slope, title="09_LR_Slope", color=color.lime, linewidth=1)
plot(mac, title="10_MAC", color=color.fuchsia, linewidth=1)
// Plot volatility indicators
plot(atr_pct, title="11_ATR_Pct", color=color.yellow, linewidth=1)
plot(bb_position, title="12_BB_Position", color=color.aqua, linewidth=1)
plot(kc_position, title="13_KC_Position", color=color.olive, linewidth=1)
plot(std_dev_pct, title="14_StdDev_Pct", color=color.silver, linewidth=1)
plot(bb_width, title="15_BB_Width", color=color.gray, linewidth=1)
// Plot volume indicators
plot(vroc, title="16_VROC", color=color.blue, linewidth=1)
plot(eom_sma, title="17_EOM", color=color.red, linewidth=1)
plot(vol_osc, title="18_Vol_Osc", color=color.green, linewidth=1)
plot(force_index_sma, title="19_Force_Index", color=color.orange, linewidth=1)
plot(obv, title="20_OBV", color=color.purple, linewidth=1)
// Plot additional oscillators
plot(ao, title="21_Awesome_Osc", color=color.navy, linewidth=1)
plot(cmo, title="22_CMO", color=color.maroon, linewidth=1)
plot(dpo, title="23_DPO", color=color.teal, linewidth=1)
plot(trix, title="24_TRIX", color=color.lime, linewidth=1)
plot(fisher, title="25_Fisher", color=color.fuchsia, linewidth=1)
// Plot more momentum indicators
plot(mfi_centered, title="26_MFI_Centered", color=color.yellow, linewidth=1)
plot(ac, title="27_AC", color=color.aqua, linewidth=1)
plot(ppo_pct, title="28_PPO_Pct", color=color.olive, linewidth=1)
plot(stoch_rsi_centered, title="29_StochRSI_Centered", color=color.silver, linewidth=1)
plot(klinger, title="30_Klinger", color=color.gray, linewidth=1)
// Plot trend continuation
plot(tii, title="31_TII", color=color.blue, linewidth=1)
plot(ichimoku_signal, title="32_Ichimoku_Signal", color=color.red, linewidth=1)
plot(mama_momentum, title="33_MAMA_Momentum", color=color.green, linewidth=1)
plot(zlema_momentum, title="34_ZLEMA_Momentum", color=color.orange, linewidth=1)
plot(bop, title="35_BOP", color=color.purple, linewidth=1)
// Plot volume continuation
plot(nvi, title="36_NVI", color=color.navy, linewidth=1)
plot(pvi, title="37_PVI", color=color.maroon, linewidth=1)
plot(momentum_pct, title="38_Momentum_Pct", color=color.teal, linewidth=1)
plot(roc, title="39_ROC", color=color.lime, linewidth=1)
plot(rvi, title="40_RVI", color=color.fuchsia, linewidth=1)
// Plot volatility continuation
plot(dc_position, title="41_DC_Position", color=color.yellow, linewidth=1)
plot(rvi_volatility, title="42_RVI_Volatility", color=color.aqua, linewidth=1)
plot(hv, title="43_Historical_Vol", color=color.olive, linewidth=1)
plot(gk_volatility, title="44_GK_Volatility", color=color.silver, linewidth=1)
plot(parkinson, title="45_Parkinson_Vol", color=color.gray, linewidth=1)
// Plot final oscillators
plot(rogers_satchell, title="46_RS_Volatility", color=color.blue, linewidth=1)
plot(elder_power, title="47_Elder_Power", color=color.red, linewidth=1)
plot(stc, title="48_STC", color=color.green, linewidth=1)
plot(coppock, title="49_Coppock", color=color.orange, linewidth=1)
plot(kst, title="50_KST", color=color.purple, linewidth=1)
// Plot final indicators
plot(ppo_histogram, title="51_PPO_Histogram", color=color.navy, linewidth=1)
plot(pvt, title="52_PVT", color=color.maroon, linewidth=1)
// |----- Reference Lines -----| //
hline(0, "Zero Line", color=color.gray, linestyle=hline.style_dashed, linewidth=1)
hline(50, "Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-50, "Lower Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(25, "Upper Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-25, "Lower Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
// |----- Enhanced Information Table -----| //
if show_table and barstate.islast
table_position = position.top_right
table_text_size = table_size == "Tiny" ? size.tiny : table_size == "Small" ? size.small : size.normal
var table info_table = table.new(table_position, 3, 18, bgcolor=color.new(color.white, 85), border_width=1, border_color=color.gray)
// Headers
table.cell(info_table, 0, 0, 'Category', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 1, 0, 'Indicator', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 2, 0, 'Value', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
// Key Momentum Indicators
table.cell(info_table, 0, 1, 'MOMENTUM', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 1, 'RSI Centered', text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 2, 1, str.tostring(rsi_centered, '0.00'), text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 0, 2, '', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 1, 2, 'Stoch Centered', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 2, str.tostring(stoch_centered, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 3, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 3, 'Williams %R', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 3, str.tostring(williams_r, '0.00'), text_color=color.red, text_size=table_text_size)
table.cell(info_table, 0, 4, '', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 1, 4, 'MACD Histogram', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 2, 4, str.tostring(macd_histogram, '0.000'), text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 0, 5, '', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 1, 5, 'CCI', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 2, 5, str.tostring(cci, '0.00'), text_color=color.green, text_size=table_text_size)
// Key Trend Indicators
table.cell(info_table, 0, 6, 'TREND', text_color=color.navy, text_size=table_text_size, bgcolor=color.new(color.navy, 90))
table.cell(info_table, 1, 6, 'SMA Momentum %', text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 2, 6, str.tostring(sma_momentum, '0.00'), text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 0, 7, '', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 1, 7, 'EMA Momentum %', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 2, 7, str.tostring(ema_momentum, '0.00'), text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 0, 8, '', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 1, 8, 'SAR Trend', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 2, 8, str.tostring(sar_trend, '0'), text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 0, 9, '', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 1, 9, 'Linear Regression', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 2, 9, str.tostring(lr_slope, '0.000'), text_color=color.lime, text_size=table_text_size)
// Key Volatility Indicators
table.cell(info_table, 0, 10, 'VOLATILITY', text_color=color.yellow, text_size=table_text_size, bgcolor=color.new(color.yellow, 90))
table.cell(info_table, 1, 10, 'ATR %', text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 2, 10, str.tostring(atr_pct, '0.00'), text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 0, 11, '', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 1, 11, 'BB Position', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 2, 11, str.tostring(bb_position, '0.00'), text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 0, 12, '', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 1, 12, 'KC Position', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 2, 12, str.tostring(kc_position, '0.00'), text_color=color.olive, text_size=table_text_size)
// Key Volume Indicators
table.cell(info_table, 0, 13, 'VOLUME', text_color=color.blue, text_size=table_text_size, bgcolor=color.new(color.blue, 90))
table.cell(info_table, 1, 13, 'Volume ROC', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 13, str.tostring(vroc, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 14, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 14, 'EOM', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 14, str.tostring(eom_sma, '0.000'), text_color=color.red, text_size=table_text_size)
// Key Oscillators
table.cell(info_table, 0, 15, 'OSCILLATORS', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 15, 'Awesome Osc', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 15, str.tostring(ao, '0.000'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 16, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 16, 'Fisher Transform', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 16, str.tostring(fisher, '0.000'), text_color=color.red, text_size=table_text_size)
// Summary Statistics
table.cell(info_table, 0, 17, 'SUMMARY', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.gray, 70))
table.cell(info_table, 1, 17, 'Total Indicators: 52', text_color=color.black, text_size=table_text_size)
regime_color = rsi_centered > 10 ? color.green : rsi_centered < -10 ? color.red : color.gray
regime_text = rsi_centered > 10 ? "BULLISH" : rsi_centered < -10 ? "BEARISH" : "NEUTRAL"
table.cell(info_table, 2, 17, regime_text, text_color=regime_color, text_size=table_text_size)
This makes it the perfect “indicator backbone” for quantitative and systematic traders who want to prototype, combine, and test new regime detection models—especially in combination with the Markov Chain indicator.
How to use this script with the Markov Chain for research and backtesting:
Add the Enhanced Indicator Export to your chart.
Every calculated indicator is available as an individual data stream.
Connect the indicator(s) you want as custom input(s) to the Markov Chain’s “Custom Indicators” option.
In the Markov Chain indicator’s settings, turn ON the custom indicator mode.
For each of the three custom indicator inputs, select the exported plot from the Enhanced Export script—the menu lists all 45+ signals by name.
This creates a powerful, modular regime-detection engine where you can mix-and-match momentum, trend, volume, or custom combinations for advanced filtering.
Backtest regime logic directly.
Once you’ve connected your chosen indicators, the Markov Chain script performs regime detection (Bull/Neutral/Bear) based on your selected features—not just price returns.
The regime detection is robust, automatically normalized (using Z-score), and outputs bias (1, -1, 0) for plug-and-play integration.
Export the regime bias for programmatic use.
As described above, use input.source() in your Pine Script strategy or system and link the bias output.
You can now filter signals, control trade direction/size, or design pairs-trading that respect true, indicator-driven market regimes.
With this framework, you’re not limited to static or simplistic regime filters. You can rigorously define, test, and refine what “market regime” means for your strategies—using the technical features that matter most to you.
Optimize your signal generation by backtesting across a universe of meaningful indicator blends.
Enhance risk management with objective, real-time regime boundaries.
Accelerate your research: iterate quickly, swap indicator components, and see results with minimal code changes.
Automate multi-asset or pairs-trading by integrating regime context directly into strategy logic.
Add both scripts to your chart, connect your preferred features, and start investigating your best regime-based trades—entirely within the TradingView ecosystem.
References & Further Reading
Ang, A., & Bekaert, G. (2002). “Regime Switches in Interest Rates.” Journal of Business & Economic Statistics, 20(2), 163–182.
Hamilton, J. D. (1989). “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle.” Econometrica, 57(2), 357–384.
Markov, A. A. (1906). "Extension of the Limit Theorems of Probability Theory to a Sum of Variables Connected in a Chain." The Notes of the Imperial Academy of Sciences of St. Petersburg.
Guidolin, M., & Timmermann, A. (2007). “Asset Allocation under Multivariate Regime Switching.” Journal of Economic Dynamics and Control, 31(11), 3503–3544.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). “Simple Technical Trading Rules and the Stochastic Properties of Stock Returns.” Journal of Finance, 47(5), 1731–1764.
Zucchini, W., MacDonald, I. L., & Langrock, R. (2017). Hidden Markov Models for Time Series: An Introduction Using R (2nd ed.). Chapman and Hall/CRC.
On Quantitative Finance and Markov Models:
Lo, A. W., & Hasanhodzic, J. (2009). The Heretics of Finance: Conversations with Leading Practitioners of Technical Analysis. Bloomberg Press.
Patterson, S. (2016). The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution. Penguin Press.
TradingView Pine Script Documentation: www.tradingview.com
TradingView Blog: “Use an Input From Another Indicator With Your Strategy” www.tradingview.com
GeeksforGeeks: “What is the Difference Between Markov Chains and Hidden Markov Models?” www.geeksforgeeks.org
What makes this indicator original and unique?
- On‑chart, real‑time Markov. The chain is drawn directly on your chart. You see the current regime, its tendency to stay (self‑loop), and the usual next step (arrows) as bars confirm.
- Source‑agnostic by design. The engine runs on any series you select via input.source() — price, your own oscillator, a composite score, anything you compute in the script.
- Automatic normalization + regime mapping. Different inputs live on different scales. The script standardizes your chosen source and maps it into clear regimes (e.g., Bull / Bear / Neutral) without you micromanaging thresholds each time.
- Rolling, bar‑by‑bar learning. Transition tendencies are computed from a rolling window of confirmed bars. What you see is exactly what the market did in that window.
- Fast experimentation. Switch the source, adjust the window, and the Markov view updates instantly. It’s a rapid way to test ideas and feel regime persistence/switch behavior.
Integrate your own signals (using input.source())
- In settings, choose the Source . This is powered by input.source() .
- Feed it price, an indicator you compute inside the script, or a custom composite series.
- The script will automatically normalize that series and process it through the Markov engine, mapping it to regimes and updating the on‑chart spheres/arrows in real time.
Credits:
Deep gratitude to @RicardoSantos for both the foundational Markov chain processing engine and inspiring open-source contributions, which made advanced probabilistic market modeling accessible to the TradingView community.
Special thanks to @Alien_Algorithms for the innovative and visually stunning 3D sphere logic that powers the indicator’s animated, regime-based visualization.
Disclaimer
This tool summarizes recent behavior. It is not financial advice and not a guarantee of future results.
Coin Jin Multi SMA+ BB+ SMA forecast Ver 2.0Coin Jin Multi SMA + BB + SMA Forecast 2.0
개요
여러 개의 단순이동평균(SMA: 5/20/60/112/224/448/896 + 사용자 정의 X1/X2), 볼린저 밴드(BB), 그리고 접선 기반 곡선 예측선을 한 번에 표시합니다. 예측선은 선형회귀 기울기와 그 변화율(가속도)을 EMA로 스무딩해 곡선 외삽으로 앞으로 그려지며, 어떤 줌에서도 깔끔하게 보이도록 점선(dotted) 스타일을 강제할 수 있습니다.
스택 마커(정배열/역배열) 안내
조건: 이동평균이 정배열(5>20>60>112>224>448>(896)) 또는 역배열(5<20<60<112<224<448<(896))로 새로 전환되는 순간 삼각형 마커가 생성됩니다.
896일선 포함(with 896): SOLID 마커로 표시, Bull = 초록색, Bear = 빨간색.
896일선 미포함(no 896): HOLLOW(윤곽) 마커로 표시, 시선을 덜 끌도록 투명도 70 적용(Bull = 연두, Bear = 빨강 동일색).
방향: Bull = ▼(위, abovebar) / Bear = ▲(아래, belowbar) 로 배치됩니다.
주요 기능
SMA 7종 기본 + 사용자 정의 SMA 2개(X1/X2) 추가(기본 꺼짐, 길이/색/두께/타입 자유).
BB: 길이/배수/선두께/밴드 채움(기본 90% 투명) 지원.
예측선: Forward bars(1–100, 기본 30), 기울기 산출 길이, 스무딩 강도, 세그먼트 개수, 점/대시 스타일 선택 및 도트 강제.
스택(정/역배열) 전환 마커: with 896=SOLID, no 896=HOLLOW(투명도 70).
처음 사용하는 분들을 위한 팁 (중요)
가격 스케일을 ‘우측’으로 고정하세요.
방법 ① 차트 우측 축을 사용(기본).
방법 ② 지표 레전드의 ‘⋯’ 메뉴 → Move to → Right scale.
예측선이 본선과 어긋나 보이면 스케일이 좌측/양측으로 되어 있거나 자동 합침된 경우이니 Right scale로 맞춰주세요.
입력 요약
MA Source, 각 SMA on/off·길이·색·두께·타입
BB length/mult/width/fill/opacity(기본 90)
Forecast bars ahead(1–100), slope lookback, smoothing, segments, style/opacity, 적용 대상 선택(SMA별)
주의/면책
예측선은 가격 예언 도구가 아니라 시각적 외삽 보조지표입니다. 단독 매매 판단에 사용하지 마세요.
공개 스크린샷은 본 지표만 보이도록 깔끔하게 캡처해 주세요(다른 지표/드로잉 혼합 금지).
변경사항(v2.0)
곡선 예측선 안정화 및 도트 강제 개선.
스택 마커 no 896 상태 HOLLOW 투명도 70 적용(가독성 향상).
사용자 정의 SMA X1/X2 추가(기본 OFF).
Coin Jin Multi SMA + BB + SMA Forecast 2.0 (English)
Overview
This indicator plots multiple Simple Moving Averages (SMA: 5/20/60/112/224/448/896 + two user-defined X1/X2), Bollinger Bands, and a tangent-based curved forecast in one overlay. The forecast extrapolates forward using the linear-regression slope and its rate of change (acceleration) smoothed by EMA, and you can force a dotted look so it stays clean at any zoom level.
Stack Markers (Bullish/Bearish alignment)
Markers appear only when a full bullish stack (5>20>60>112>224>448>(896)) or bearish stack (5<20<60<112<224<448<(896)) is newly formed.
With 896 included: shown as SOLID triangles — Bull = green, Bear = red.
Without 896: shown as HOLLOW (outline) with 70 transparency to reduce visual weight — Bull = lime, Bear = red (same hue).
Orientation: Bull = ▼ abovebar, Bear = ▲ belowbar.
Features
7 standard SMAs + two custom SMAs (X1/X2) (default OFF; fully configurable length/color/width/style).
BB with length/multiplier/width/fill (default fill opacity 90%).
Forecast controls: forward bars (1–100, default 30), slope window, smoothing, segment count, style/opacity, force dotted option.
Stack markers: with 896 = SOLID, without 896 = HOLLOW (70 transparency).
First-time setup (Important)
Pin the indicator to the Right price scale.
Option A: Use the right price axis.
Option B: Indicator legend “⋯” → Move to → Right scale.
If the forecast appears detached from the MA, your series is likely on the left/both scales; switch to Right scale.
Inputs
MA source; per-SMA on/off, length, color, width, style
BB length/multiplier/width/fill/opacity (default 90)
Forecast bars ahead (1–100), slope lookback, smoothing, segments, style/opacity, per-SMA apply switches
Disclaimer
The forecast is a visual extrapolation, not a price prediction. Do not use it alone to make trading decisions.
For publication, please use a clean screenshot that shows only this indicator (no mixed overlays).
What’s new in v2.0
More robust curved forecast with improved “force dotted” rendering.
HOLLOW (no 896) markers now use 70 transparency for better readability.
Added two user-defined SMAs (X1/X2), OFF by default.
Volume Stack with Dollar Volume ScoreThis script is designed to analyze candles for buy/sell pressure, volume flows, and generate intuitive emoji-based signals. Its core function is to help traders visually and quantitatively interpret price and volume behavior for potential bullish, bearish, or neutral market states.
Key Features and Logic
Price Range Analysis: Calculates the candle's price range and determines the proportion of volume attributed to buyers and sellers using buy_percent and sell_percent.
Market State Classification:
Bullish/Bearish/Neutral: Based on buy/sell percentage comparisons.
Strong Signals: Flags when buy/sell pressure exceeds defined thresholds (≥0.75).
Transitions: Detects when states shift sharply (e.g., from bull to strong bear).
Visual Cue System:
Uses different emojis (📈, 📉, 🚀, 🔥, 💎, 💀, ❌) to mark normal, strong, transition, and neutral signals for easy chart interpretation.
Dollar Volume Calculation: Multiplies close price by volume to derive "dollar volume" per bar. Normalizes this with a moving average for context-sensitive spike detection.
Scoring Mechanism:
Dollar Volume Score: Evaluates the normalized change in dollar volume, assigning scores for strong (±2), mild (±1), or neutral (0) changes.
Buy/Sell Pressure Score: Calculates a simple pressure score based on buy/sell proportions for each candle.
Composite Score: Combines both scores to define the overall bullish/bearish/neutral state.
State & Emoji Plotting:
Plots respective emojis at the chart bottom depending on composite score and state (bullish, bearish, strong moves, transitions, neutral).
Alerts:
Sends alerts for key transitions (like bull-to-strong-bear), strong moves, and neutral states, aiding automated signal handling and decision-making.
What This Script Helps You Achieve
Quick Visual Insights: Instantly see important market states and transitions with chart emojis.
Volume Context Awareness: Incorporates both price action and normalized volume changes for more reliable signals.
Automated Alerts: Supports smart trading decisions via pop-up notifications on major shifts or important conditions.
This script provides a layered analysis approach for volume and price action, blending quantifiable scores with intuitive chart markers and automated alerts, making it highly suited for traders who rely on both visual and quantitative cues in their strategy.
Engulfing Pattern[SpeculationLab]Overview
This script detects two types of engulfing / outer bar patterns and marks them directly on the chart:
Body Engulfing – The current candle’s body range (open–close) completely covers the entire range (high–low) of the previous candle.
Range Engulfing – The current candle’s full range (high–low, including wicks) completely covers the entire range (high–low) of the previous candle.
Direction logic:
Bull – The previous candle is bearish and the selected engulfing rule is met.
Bear – The previous candle is bullish and the selected engulfing rule is met.
Optional: Require the current candle to have the opposite color of the previous one.
This is an open-source pattern recognition tool for learning, backtesting, and chart review. It is not financial advice.
Key Features
Two detection modes:
body – Body engulfs previous entire range
range – Wicks engulf previous entire range
Direction detection based on the previous candle’s color, with optional opposite-color confirmation
Chart markers: “BULL” /“BEAR” above bars
Alert-ready: built-in conditions for bullish and bearish engulfing patterns
Parameters
Engulfing Type: body / range
body: Current body must fully cover the previous candle’s high–low range
range: Current full range (high–low) must fully cover the previous candle’s high–low range
Require Opposite Previous Candle (default: off):
When enabled, the engulfing pattern must also have the opposite color from the previous candle to trigger
Usage Tips
Engulfing patterns are price action structures; combine with trend, key levels, and volume for context
Signals confirm on bar close (barstate.isconfirmed) to reduce repainting
Can be used with personal risk management rules (stop-loss, take-profit, filters)
Disclaimer
For educational and research purposes only – not financial advice
Past performance of patterns does not guarantee future results
Trading involves risk; always manage it responsibly
This script is open-source – feel free to learn from or modify it, but credit the original source and author (SpeculationLab)
脚本简介
本脚本用于识别两类包裹/外包形态，并在图表上以标记提示：
Body（实体包裹）：当前K线的实体区间（开—收）完全覆盖上一根K线的整个区间（上一根的高—低）。
Range（影线外包）：当前K线的影线区间（高—低）完全覆盖上一根K线的整个区间（上一根的高—低）。
方向判定：
Bull（多）：上一根为阴线且满足所选包裹规则；
Bear（空）：上一根为阳线且满足所选包裹规则；
可选项：要求“当前K线颜色与上一根相反”后再确认（见参数）。
本脚本为开源形态识别工具，适合技术分析学习、回测与复盘，不构成任何投资建议。
主要功能
两种识别模式：body（实体包裹上一根整段） / range（影线包裹上一根整段）。
方向识别：按上一根K线颜色判断多空；可选“当前颜色与上一根相反”的二次确认。
图表提示：plotshape 在K线上方标注 “BULL / BEAR”。
提醒支持：内置 Bullish Engulf / Bearish Engulf 提醒条件。
参数说明
Engulfing Type：body / range
body：当前实体须完全覆盖上一根的高—低整段；
range：当前高—低须完全覆盖上一根的高—低整段。
Require Opposite Previous Candle（默认关闭）：
开启后，除满足包裹规则外，还需当前K线颜色与上一根相反才触发标记。
使用建议
包裹/外包是价格行为结构，建议结合趋势、关键价位、成交量等因素综合判断。
信号在收盘时确认（barstate.isconfirmed），以减少重绘干扰。
可与个人风格的风险控制规则（止损、止盈、过滤条件）配合使用。
合规与免责声明
本脚本仅用于技术研究与学习，不构成任何形式的投资建议或收益承诺。
历史形态并不代表未来结果，交易有风险，请自行评估并承担责任。
本脚本开源，欢迎学习与二次开发；转载或改用请注明来源与作者（SpeculationLab / 投机实验室）。
Ichimoku Cloud Signals [sgbpulse] Ichimoku Cloud Signals – Your Advanced Trading Tool
Meet Ichimoku Cloud Signals, the enhanced and interactive version of the classic Ichimoku Cloud indicator, designed specifically for TradingView traders seeking precision and flexibility in their trading decisions. This indicator allows you to maximize the Ichimoku's potential by customizing trend criteria, receiving clear visual signals for entering and exiting positions, and getting alerts to keep you informed.
Introduction to the Ichimoku Cloud
The Ichimoku Cloud, also known as Ichimoku Kinko Hyo, is a comprehensive technical analysis tool developed in Japan. It provides a broad view of the market: trend direction, momentum, and support and resistance levels. "Ichimoku Cloud Signals" takes this power and amplifies it with advanced features.
Key Components of the Ichimoku Cloud
The indicator displays all five familiar Ichimoku lines, along with the "Cloud" (Kumo):
Tenkan-sen (Conversion Line): Calculated as the average of the highest high and lowest low over the past 9 periods. A fast, short-term indicator used as a measure of immediate momentum.
Kijun-sen (Base Line): Calculated as the average of the highest high and lowest low over the past 26 periods. A medium-term reference line serving as a significant support/resistance level.
Senkou Span A (Leading Span A): The average of the Tenkan-sen and Kijun-sen, shifted 26 periods forward into the future.
Senkou Span B (Leading Span B): The average of the highest high and lowest low over the past 52 periods, also shifted 26 periods forward into the future.
Kumo (Cloud): The area between Senkou Span A and Senkou Span B. Its color changes: green for an uptrend (when Senkou Span A is above Senkou Span B) and red for a downtrend (when Senkou Span B is above Senkou Span A). The Cloud serves as a dynamic area of support/resistance and a tool for forecasting future trends.
Chikou Span (Lagging Span): The current closing price, shifted 26 periods backward into the past. It serves as a powerful trend confirmation tool.
How the Ichimoku Cloud Works and How to Interpret It
Trend Identification :
- Uptrend (Bullish): The price is above the Cloud. The higher the price is above the Cloud, the stronger the trend.
- Downtrend (Bearish): The price is below the Cloud. The lower the price is below the Cloud, the stronger the trend.
- Range/Consolidation: The price is within the Cloud. This indicates a market without a clear direction or one that is consolidating.
Support and Resistance:
- The Cloud itself acts as a dynamic area of support and resistance. In an uptrend, the Cloud serves as support. In a downtrend, it serves as resistance.
- A thick Cloud indicates stronger support/resistance levels, while a thin Cloud indicates weaker levels.
The Cloud as a Predictive Indicator:
The uniqueness of the Kumo (Cloud) lies in its ability to be shifted 26 periods forward. This part of the Cloud provides forecasts for future support and resistance levels and even suggests expected trend changes (like a "Kumo Twist" – a change in Cloud color), giving you a planning advantage.
Unique Advantages of Ichimoku Cloud Signals:
Ichimoku Cloud Signals takes the classic Ichimoku principles and gives you unprecedented control:
Focused Trend Selection:
Choose whether you want to analyze a bullish (uptrend) or bearish (downtrend) trend. The indicator will focus on the relevant criteria for your selection.
Customizable Trend Confirmation Criteria (8 Criteria):
The indicator relies on 8 key criteria for clear trend confirmation. You can enable or disable each criterion individually based on your trading strategy and desired risk level. Each criterion plays a vital role in confirming the strength of the trend:
- Price position relative to the Cloud (Kumo) (Default: true): Determines the main trend direction and whether it's bullish or bearish.
- Price position relative to Kijun-sen (Base Line) (Default: true): Indicates the medium-term trend and acts as a critical equilibrium level.
- Price position relative to Tenkan-sen (Conversion Line) (Default: false): Provides quick confirmation of current momentum and short-term market changes.
- Tenkan-sen (Conversion Line) / Kijun-sen (Base Line) Crossover (Default: true): A classic signal for momentum change, crucial for identifying entry points.
- Current Cloud trend (Kumo) (Default: false): Cloud color confirms the main trend direction in real-time.
- Projected Future Cloud trend (Kumo) (Default: true): Indicates an expected future change in the Cloud's trend, providing strong visual insight.
- Chikou Span (Lagging Span) position relative to the Cloud (Kumo) (Default: true): Confirms the current trend strength by comparing the price to the Ichimoku 26 periods ago.
- Chikou Span (Lagging Span) position relative to the Price (Default: false): Additional confirmation of trend strength, indicating buyer/seller dominance.
Full Customization of Ichimoku Parameters:
You can change the period lengths for each Ichimoku component, depending on your strategy:
- Conversion Line Length (Default: 9)
- Base Line Length (Default: 26)
- Leading Span Length (Default: 52)
- Cloud Lagging Length (Default: 26)
- Lagging Span Length (Default: 26)
Visual Criteria Table on the Chart:
Get immediate and clear feedback! A visual table is placed on the chart, showing in real-time which of the 8 criteria you have defined are met for your chosen trend. Criteria you have enabled will be highlighted with a blue color and a "➤" symbol, while disabled criteria will appear in a subtle gray shade. For each criterion, the table shows its real-time status with a "✔" symbol if the condition is met and an "✘" symbol if it is not met. This powerful visual tool provides a quick assessment, helps with learning, and allows for strategy optimization at the click of a button.
Precise Criteria Details in the Data Window:
Beyond the visual table, the indicator provides an additional critical layer of detail: for any point on the chart, you can hover over a candle and see in TradingView's Data Window the precise status and values of all eight criteria. For each criterion, you'll see a clear numerical value (1 or 0) indicating whether it's fully met (1) or not met (0). Additionally, you can inspect the exact numerical values of the Ichimoku lines (Tenkan-sen, Kijun-sen, etc.) at that specific moment. This comprehensive data supports in-depth analysis, strategy debugging, and long-term optimization, providing complete transparency regarding every component of the signal.
Smart and Customizable Alerts:
Ichimoku Cloud Signals provides a powerful alert system to keep you informed of key market movements, so you never miss an opportunity. There are eight unique alerts you can enable in TradingView's alert panel:
Uptrend Entry Alert: Triggers when all of your selected criteria for an uptrend are met on a new candle.
Uptrend Exit Alert: Triggers when one of your selected uptrend criteria is no longer met, signaling a potential exit point.
Downtrend Entry Alert: Triggers when all of your selected criteria for a downtrend are met on a new candle.
Downtrend Exit Alert: Triggers when one of your selected downtrend criteria is no longer met, signaling a potential exit point.
Bullish Crossover Alert: Triggers when the Conversion Line (Tenkan-sen) crosses above the Base Line (Kijun-sen), a classic signal for an upward momentum shift.
Bearish Crossover Alert: Triggers when the Conversion Line (Tenkan-sen) crosses below the Base Line (Kijun-sen), signaling a potential shift to downward momentum.
Bullish Cloud Breakout Alert: Triggers when the price closes above the Ichimoku Cloud (Kumo), indicating a strong bullish trend.
Bearish Cloud Breakout Alert: Triggers when the price closes below the Ichimoku Cloud (Kumo), indicating a strong bearish trend.
Each alert can be independently configured in TradingView's alert panel, allowing you to tailor your notifications to fit your exact trading strategy and risk management preferences.
Summary:
Ichimoku Cloud Signals is an essential tool for TradingView traders seeking control, clarity, and precision. It combines the power of the classic Ichimoku Cloud indicator with advanced customization capabilities, a convenient visual table, and clear signals, empowering you to make informed trading decisions and stay focused on managing your positions.
Important Note: Trading Risk
This indicator is intended for educational and informational purposes only and does not constitute investment advice or a recommendation for trading in any form whatsoever.
Trading in financial markets involves significant risk of capital loss. It is important to remember that past performance is not indicative of future results. All trading decisions are your sole responsibility. Never trade with money you cannot afford to lose.
ABS NR — Fail-Safe Confirm (v4.2.2)
# ABS NR — Fail-Safe Confirm (v4.2.2)
## What it is (quick take)
**ABS NR FS** is a **non-repainting “arm → confirm” entry framework** for intraday and swing execution. It blends:
* **Regime** (EMA stack + 60-min slope),
* **Location** (Keltner basis/edges),
* **Stretch** (session-anchored **VWAP Z-score**),
* **Momentum gating** (TSI cross/slope),
* **Guards** (session window, minimum ATR%, gap filter, optional market alignment).
You’ll see a **small dot** when a setup is **armed** (candidate) and a **triangle** when that setup **confirms** within a user-defined number of bars. A **gray “X”** marks a timeout (candidate canceled).
> Tip: This entry tool works best when paired with a trend context filter and a dedicated exit tool.
---
## How to use it (operational workflow)
1. **Read the regime**
* **Bull trend**: fast > slow > long EMA **and** 60-min slope up.
* **Bear trend**: fast < slow < long EMA **and** 60-min slope down.
* **Range**: neither bull nor bear.
2. **Wait for a candidate (dot)**
Two families:
* **Reclaim (trend-following):** price crosses the **KC basis** with acceptable |Z| (not overstretched) and passes the TSI gate.
* **Fade (range-revert):** price **pokes a KC band**, prints a **reversal wick**, |Z| is stretched, and TSI gate agrees.
3. **Trade the confirmation (triangle)**
The confirm must occur **within N bars** and follow your chosen **Confirm mode** logic (see Inputs). If confirmation doesn’t arrive in time, an **X** cancels the candidate.
4. **Use guards to avoid junk**
Session windows (US focus), minimum ATR%, gap guard, and optional **market alignment** (e.g., SPY above EMA20 for longs).
5. **Manage the position**
* Entries: take **triangles** in the direction of your playbook (reclaims with trend; fades in clean ranges).
* Filters and exits: use your own process or pair with a trend/exit companion.
---
## Visual semantics & alerts
* **Candidate L / S (dot)** → a setup armed on this bar.
* **CONFIRM L / S (triangle)** → actionable signal that met confirm rules within your time window.
* **Cancel L / S (X)** → candidate expired without confirmation; ignore the dot.
**Alerts (stable names for automation):**
* **ABS FS — Confirmed** → fires on confirmed long or short.
* **ABS FS — Candidate Armed** → fires as a candidate arms.
---
## Non-repainting behavior (why signals don’t repaint)
* All HTF requests use **lookahead\_off**.
* With **Strict NR = true**, the 60-min slope uses the **prior completed** 60-min bar and arming/confirming only occurs on confirmed bars.
* Confirmation triangles finalize on bar close.
* If you disable strictness, signals may appear slightly earlier but with more intrabar sensitivity.
---
## Inputs reference (what each control does and the trade-offs)
### A) Behavior / Modes
**Mode** (`Turbo / Aggressive / Balanced / Conservative`)
Changes multiple internal thresholds:
* **Turbo** → most signals; relaxes prior-bar break & VWAP-side checks and time/vol/gap guards. Highest frequency, highest noise.
* **Aggressive** → more signals than Balanced, fewer than Turbo.
* **Balanced** → default; steady trade-off of frequency vs. quality.
* **Conservative** → tightens |Z| and other checks; fewest but cleanest signals.
**Strict NR (bar close + prior HTF 60m)**
* **true** = safer: uses prior 60-min slope; arms/confirms on confirmed bars → **fewer/cleaner** signals.
* **false** = earlier and more reactive; slightly noisier.
---
### B) Keltner Channel (location engine)
* **KC EMA Length (`kcLen`)**
Higher → smoother basis (fewer basis crosses). Lower → snappier basis (more crosses).
* **ATR Length (`atrLen`)**
Higher → steadier band width; Lower → more reactive band width.
* **KC ATR Mult (`kcMult`)**
Higher → wider bands (fewer edge pokes → fewer fades). Lower → narrower (more fades).
---
### C) Trend & HTF slope
* **Trend EMA Fast/Slow/Long (`emaFastLen / emaSlowLen / emaLongLen`)**
Larger = slower regime flips (fewer reclaims); smaller = faster flips (more reclaims).
* **HTF EMA Len (60m) (`htfLen`)**
Larger = steadier HTF slope (fewer signals); smaller = more sensitive (more signals).
---
### D) VWAP Z-Score (stretch / mean-revert logic)
* **VWAP Z-Length (`zLen`)**
Window for Z over session-anchored VWAP distance. Larger = smoother |Z| (fewer fades/re-entries). Smaller = more reactive (more).
* **Range Fade |Z| (base) (`zFadeBase`)**
Minimum |Z| to allow **fades** in ranges. Raise to demand more stretch (fewer fades). Lower to take more fades.
* **Max |Z| Trend Re-entry (base) (`maxZTrendBase`)**
Caps how stretched price can be and still permit **reclaims** with trend. Lower = stricter (avoid chases). Higher = will chase further.
---
### E) TSI Momentum Gate
* **TSI Long/Short/Signal (`tsiLong / tsiShort / tsiSig`)**
Larger = smoother/laggier momentum; smaller = snappier.
* **TSI gate (`CrossOnly / CrossOrSlope / Off`)**
* **CrossOnly**: require TSI cross of its signal (strict).
* **CrossOrSlope**: cross *or* favorable slope (balanced default).
* **Off**: no momentum gate (most signals, most noise).
---
### F) Guards (filters to avoid low-quality tape)
* **US focus 09:35–10:30 & 14:00–15:45 (base) (`useTimeBase`)**
`true` limits to high-quality windows. `false` trades all session.
* **Skip N bars after 09:30 ET (`skipFirst`)**
Skips the open scramble. Larger = skip longer.
* **Min volatility ATR% (base)** = `useVolMinBase` + `atrPctMinBase`
Requires `ATR(10)/Close*100 ≥ atrPctMinBase`. Raise threshold to avoid dead tape; lower to accept quieter sessions.
* **Gap guard (base)** = `gapGuardBase` + `gapMul`
Blocks signals when the opening gap exceeds `gapMul * ATR`. Increase `gapMul` to allow more gapped opens; decrease to be stricter.
---
### G) Visuals & Sides
* **Plot Keltner (`plotKC`)** → show/hide basis & bands.
* **Show Longs / Show Shorts** → enable/disable each side.
---
### H) Fail-Safe Confirmation
* **Confirm mode (`BreakHighOnly / BreakHigh+Hold / TwoBarImpulse`)**
* **BreakHighOnly**: confirm by taking out the armed bar’s extreme. Fastest, most frequent.
* **BreakHigh+Hold**: must **break**, have **body ≥ X·ATR**, **and** hold above/below the basis → higher quality, fewer signals.
* **TwoBarImpulse**: decisive follow-through vs. prior bar with **body ≥ X·ATR** → momentum-biased confirmations.
* **Confirm within N bars (`confirmBars`)**
Confirmation window size. Smaller = faster validation; larger = more patience (can be later).
* **Impulse body ≥ X·ATR (`impulseBodyATR`)**
Raise for stronger confirmations (fewer weak triangles). Lower to accept lighter pushes.
* **Require market alignment (`needMarket`) + `marketTicker`**
When enabled: Longs require **market > EMA20 (5m)**; Shorts require **market < EMA20 (5m)**.
* **Diagnostics: Show debug letters (`debug`)**
Tiny “B/C” audit marks for base/confirm while tuning.
---
## Tuning recipes (quick, practical)
* **If you’re getting chopped:**
* Set **Mode = Conservative**
* **Confirm mode = BreakHigh+Hold**
* Raise **impulseBodyATR** (e.g., 0.45)
* Keep **needMarket = true**
* Keep **Strict NR = true**
* **If you need more signals:**
* **Mode = Aggressive** (or Turbo if you accept more noise)
* **Confirm mode = BreakHighOnly**
* Lower **impulseBodyATR** (0.25–0.30)
* Increase **confirmBars** to 3
* **Range-day focus (fades):**
* Keep session guard on
* Raise **zFadeBase** to demand real stretch
* Keep **maxZTrendBase** moderate (don’t chase)
* **Trend-day focus (reclaims):**
* Slightly **lower `maxZTrendBase`** (avoid chasing excessive stretch)
* Use **CrossOrSlope** TSI gating
* Consider turning **needMarket** on
---
## Best practices & notes
* **Instrument specificity:** Tune Z, TSI, and guards per symbol and timeframe.
* **Session awareness:** Session filter uses **exchange-local** time; adjust for non-US markets.
* **Automation:** Use the two provided alert names; they’re stable.
* **Risk management:** Confirmation improves quality but doesn’t remove risk. Always pre-define stop/size logic.
---
## Suggested starting point (balanced profile)
* **Mode = balanced**
* **Strict NR = true**
* **Confirm mode = BreakHigh+Hold**
* **confirmBars = 2**
* **impulseBodyATR ≈ 0.35**
* **needMarket = off** (turn on for extra confluence)
* Leave Keltner/TSI defaults; then nudge `zFadeBase` and `maxZTrendBase` to match your symbol.
---
*This tool is a signal generator, not a broker or strategy. Validate on your markets/timeframes and integrate with your risk plan.*
RSI Momentum Divergence Zones [ChartPrime]⯁ OVERVIEW
RSI Momentum Divergence Zones is a hybrid oscillator and chart overlay tool that detects RSI-based momentum divergences and projects them as key zones on the chart. By combining RSI divergence logic with horizontal level plotting, this indicator reveals high-probability support and resistance areas where price has historically reacted to hidden or classic divergences.
⯁ KEY FEATURES
Momentum-Based RSI Source:
Instead of the classic RSI input, this tool uses the momentum of price as the RSI source:
rsiSrc = ta.mom(close, 10)
This emphasizes acceleration and deceleration of price moves, sharpening divergence signals and making them more responsive to early shifts in momentum.
Automatic Divergence Detection (Optional):
When enabled, the indicator continuously scans for:
— Bullish Divergence : Price makes a Lower Low while RSI forms a Higher Low
— Bearish Divergence : Price makes a Higher High while RSI forms a Lower High
It ensures divergence is valid by checking the spacing between pivots (min 5, max 50 bars).
Divergence Labels & Markers (RSI Pane + Chart):
When a valid divergence is detected:
— On RSI pane:
Labels appear at HL/LH points (“Bull” / “Bear”)
Colored lines show pivot structures
— On price chart:
Labels (“▲ Bull” / “Bear ▼”) mark price pivot that triggered the divergence
Lines highlight the exact price level at the divergence origin
Divergence Zones / Levels (Toggleable):
The indicator projects horizontal zones across the chart based on confirmed divergence points.
These levels dynamically extend as long as price respects them, and auto-expire once broken.
They act as S/R levels created by market imbalance caused by divergence reactions.
Dynamic Zone Extension Logic:
Once plotted, divergence levels will extend to the right:
— If price respects the level, the zone keeps growing
— If broken in the opposite direction, the level stops extending and turns dashed (visually showing break)
Zone Layering and Limit Control:
You can limit the number of simultaneous zones shown on the chart (e.g., 10 most recent).
Old zones automatically expire and are removed to keep the chart clean and focused.
Color Customization and Intensity:
Different colors for bullish and bearish zones let you easily distinguish trend direction.
Background fill, line width, and transparency are all adjustable.
Clean Zone Management with Arrays:
Behind the scenes, the script uses custom divLevel type arrays to manage plotted levels, ensuring they stay up-to-date, extend correctly, and delete once invalidated.
⯁ USAGE
Use bullish divergence zones as potential demand areas and bearish ones as supply zones.
Combine RSI pane labels with price-level zones to confirm strength of reversal.
Watch for price approaching a divergence level to anticipate reactions or breakouts.
Use divergence levels as trade triggers, stop-loss guides, or take-profit markers.
Limit signal count using the “Qty Divergence Zones” setting to reduce chart clutter.
Enable divergence detection only when you want to focus on key structural zones — ideal for swing or positional setups.
⯁ CONCLUSION
RSI Momentum Divergence Zones blends oscillator divergence logic with price action structure to uncover hidden strength or weakness in the market. With flexible zone plotting and clean visual signals, this tool empowers traders to identify where momentum turns into structure — turning hidden signals into tradable edges.
Market Regime Matrix [Alpha Extract]A sophisticated market regime classification system that combines multiple technical analysis components into an intelligent scoring framework to identify and track dominant market conditions. Utilizing advanced ADX-based trend detection, EMA directional analysis, volatility assessment, and crash protection protocols, the Market Regime Matrix delivers institutional-grade regime classification with BULL, BEAR, and CHOP states. The system features intelligent scoring with smoothing algorithms, duration filters for stability, and structure-based conviction adjustments to provide traders with clear, actionable market context.
🔶 Multi-Component Regime Engine Integrates five core analytical components: ADX trend strength detection, EMA-200 directional bias, ROC momentum analysis, Bollinger Band volatility measurement, and zig-zag structure verification. Each component contributes to a sophisticated scoring system that evaluates market conditions across multiple dimensions, ensuring comprehensive regime assessment with institutional precision.
// Gate Keeper: ADX determines market type
is_trending = adx_value > adx_trend_threshold
is_ranging = adx_value <= adx_trend_threshold
is_maximum_chop = adx_value <= adx_chop_threshold
// BULL CONDITIONS with Structure Veto
if price_above_ema and di_bullish
if use_structure_filter and isBullStructure
raw_bullScore := 5.0 // MAXIMUM CONVICTION: Strong signals + Bull structure
else if use_structure_filter and not isBullStructure
raw_bullScore := 3.0 // REDUCED: Strong signals but broken structure
🔶 Intelligent Scoring System Employs a dynamic 0-5 scale scoring mechanism for each regime type (BULL/BEAR/CHOP) with adaptive conviction levels. The system automatically adjusts scores based on signal alignment, market structure confirmation, and volatility conditions. Features decision margin requirements to prevent false regime changes and includes maximum conviction thresholds for high-probability setups.
🔶 Advanced Structure Filter Implements zig-zag based market structure analysis using configurable deviation thresholds to identify significant pivot points. The system tracks Higher Highs/Higher Lows (HH/HL) for bullish structure and Lower Lows/Lower Highs (LL/LH) for bearish structure, applying structure veto logic that reduces conviction when price action contradicts the underlying trend framework.
// Define Market Structure (Bull = HH/HL, Bear = LL/LH)
isBullStructure = not na(last_significant_high) and not na(prev_significant_high) and
not na(last_significant_low) and not na(prev_significant_low) and
last_significant_high > prev_significant_high and last_significant_low > prev_significant_low
isBearStructure = not na(last_significant_high) and not na(prev_significant_high) and
not na(last_significant_low) and not na(prev_significant_low) and
last_significant_low < prev_significant_low and last_significant_high < prev_significant_high
🔶 Superior Engine Components Features dual-layer regime stabilization through score smoothing and duration filtering. The score smoothing component reduces noise by averaging raw scores over configurable periods, while the duration filter requires minimum regime persistence before confirming changes. This eliminates whipsaws and ensures regime transitions represent genuine market shifts rather than temporary fluctuations.
🔶 Crash Detection & Active Penalties Incorporates sophisticated crash detection using Rate of Change (ROC) analysis with severity classification. When crash conditions are detected, the system applies active penalties (-5.0) to BULL and CHOP scores while boosting BEAR conviction based on crash severity. This ensures immediate regime response to major market dislocations and drawdown events.
// === CRASH OVERRIDE (Active Penalties) ===
is_crash = roc_value < crash_threshold
if is_crash
// Calculate crash severity
crash_severity = math.abs(roc_value / crash_threshold)
crash_bonus = 4.0 + (crash_severity - 1.0) * 2.0
// ACTIVE PENALTIES: Force bear dominance
raw_bearScore := math.max(raw_bearScore, crash_bonus)
raw_bullScore := -5.0 // ACTIVE PENALTY
raw_chopScore := -5.0 // ACTIVE PENALTY
❓How It Works
🔶 ADX-Based Market Classification The Market Regime Matrix uses ADX (Average Directional Index) as the primary gatekeeper to distinguish between trending and ranging market conditions. When ADX exceeds the trend threshold, the system activates BULL/BEAR regime logic using DI+/DI- crossovers and EMA positioning. When ADX falls below the ranging threshold, CHOP regime logic takes precedence, with maximum conviction assigned during ultra-low ADX periods.
🔶 Dynamic Conviction Scaling Each regime receives conviction ratings from UNCERTAIN to MAXIMUM based on signal alignment and score magnitude. MAXIMUM conviction (5.0 score) requires perfect signal alignment plus favorable market structure. The system progressively reduces conviction when signals conflict or structure breaks, ensuring traders understand the reliability of each regime classification.
🔶 Regime Transition Management Implements decision margin requirements where new regimes must exceed existing regimes by configurable thresholds before transitions occur. Combined with duration filtering, this prevents premature regime changes and maintains stability during consolidation periods. The system tracks both raw regime signals and final regime output for complete transparency.
🔶 Visual Regime Mapping Provides comprehensive visual feedback through colored candle overlays, background regime highlighting, and real-time information tables. The system displays regime history, conviction levels, structure status, and key metrics in an organized dashboard format. Regime changes trigger immediate visual alerts with detailed transition information.
🔶 Performance Optimization Features efficient array management for zig-zag calculations, smart variable updating to prevent recomputation, and configurable debug modes for strategy development. The system maintains optimal performance across all timeframes while providing institutional-grade analytical depth.
Why Choose Market Regime Matrix ?
The Market Regime Matrix represents the evolution of market regime analysis, combining traditional technical indicators with modern algorithmic decision-making frameworks. By integrating multiple analytical dimensions with intelligent scoring, structure verification, and crash protection, it provides traders with institutional-quality market context that adapts to changing conditions. The sophisticated filtering system eliminates noise while preserving responsiveness, making it an essential tool for traders seeking to align their strategies with dominant market regimes and avoid adverse market environments.
Institutional Momentum Zones (ADX+ROC+DI+MACD+Filters)Institutional Momentum Zones (ADX + ROC + DI + MACD + Filters)
This indicator is designed to help traders visually identify Bullish, Neutral, and Bearish momentum zones on Nifty, indices, or any liquid asset, using a rules-based, institutional-style approach.
It combines multiple professional-grade momentum and trend filters into a single framework:
ADX (Average Directional Index) – Measures trend strength, filters out choppy conditions.
Directional Indicators (+DI / –DI) – Confirms whether bulls or bears are in control.
ROC (Rate of Change) – Quantifies momentum speed and direction.
MACD (optional) – Adds confirmation by checking multi-timeframe momentum alignment.
EMA Filters (optional) – Ensures price is in alignment with long-term trend bias.
Supertrend (optional) – Can be enabled for additional trend confirmation.
How it works:
Bullish Zone (Green) → Strong trend (ADX > threshold) + upward momentum (ROC > 0, +DI > –DI) + optional EMA/MACD/Supertrend confirmation.
Bearish Zone (Red) → Strong trend (ADX > threshold) + downward momentum (ROC < 0, –DI > +DI) + optional EMA/MACD/Supertrend confirmation.
Neutral Zone (Yellow) → Low trend strength (ADX < threshold) or mixed momentum signals.
Features:
Automatic background coloring for zone detection.
On-chart labels marking new zone changes.
EMA50 / EMA200 and Supertrend overlay options.
Signal markers for bullish/bearish entries.
Info panel with live ADX, ROC, DI values, and MACD histogram.
Alert conditions for zone changes (Bull, Bear, Neutral).
Best used for:
Index momentum tracking (e.g., Nifty, Bank Nifty, Dow, S&P500)
Swing trading & positional trading strategies
Filtering trades to avoid entering during low-momentum chop
Tip: For Nifty positional trading, use Daily or 4H charts with EMA & MACD filters enabled for cleaner, high-confidence signals.
