Swing Trend AnalysisIntroducing the Swing Trend Analyzer: A Powerful Tool for Swing and Positional Trading
The Swing Trend Analyzer is a cutting-edge indicator designed to enhance your swing and positional trading by providing precise entry points based on volatility contraction patterns and other key technical signals. This versatile tool is packed with features that cater to traders of all timeframes, offering flexibility, clarity, and actionable insights.
Key Features:
1. Adaptive Moving Averages:
The Swing Trend Analyzer offers multiple moving averages tailored to the timeframe you are trading on. On the daily chart, you can select up to four different moving average lengths, while all other timeframes provide three moving averages. This flexibility allows you to fine-tune your analysis according to your trading strategy. Disabling a moving average is as simple as setting its value to zero, making it easy to customize the indicator to your needs.
2. Dynamic Moving Average Colors Based on Relative Strength:
This feature allows you to compare the performance of the current ticker against a major index or any symbol of your choice. The moving average will change color based on whether the ticker is outperforming or underperforming the selected index over the chosen period. For example, on a daily chart, if the 21-day moving average turns blue, it indicates that the ticker has outperformed the selected index over the last 21 days. This visual cue helps you quickly identify relative strength, a key factor in successful swing trading.
3. Visual Identification of Price Contractions:
The Swing Trend Analyzer changes the color of price bars to white (on a dark theme) or black (on a light theme) when a contraction in price is detected. Price contractions are highlighted when either of the following conditions is met: a) the current bar is an inside bar, or b) the price range of the current bar is less than the 14-period Average Daily Range (ADR). This feature makes it easier to spot price contractions across all timeframes, which is crucial for timing entries in swing trading.
4. Overhead Supply Detection with Automated Resistance Lines:
The indicator intelligently detects the presence of overhead supply and draws a single resistance line to avoid clutter on the chart. As price breaches the resistance line, the old line is automatically deleted, and a new resistance line is drawn at the appropriate level. This helps you focus on the most relevant resistance levels, reducing noise and improving decision-making.
5. Buyable Gap Up Marker: The indicator highlights bars in blue when a candle opens with a gap that remains unfilled. These bars are potential Buyable Gap Up (BGU) candidates, signaling opportunities for long-side entries.
6. Comprehensive Swing Trading Information Table:
The indicator includes a detailed table that provides essential data for swing trading:
a. Sector and Industry Information: Understand the sector and industry of the ticker to identify stocks within strong sectors.
b. Key Moving Averages Distances (10MA, 21MA, 50MA, 200MA): Quickly assess how far the current price is from key moving averages. The color coding indicates whether the price is near or far from these averages, offering vital visual cues.
c. Price Range Analysis: Compare the current bar's price range with the previous bar's range to spot contraction patterns.
d. ADR (20, 10, 5): Displays the Average Daily Range over the last 20, 10, and 5 periods, crucial for identifying contraction patterns. On the weekly chart, the ADR continues to provide daily chart information.
e. 52-Week High/Low Data: Shows how close the stock is to its 52-week high or low, with color coding to highlight proximity, aiding in the identification of potential breakout or breakdown candidates.
f. 3-Month Price Gain: See the price gain over the last three months, which helps identify stocks with recent momentum.
7. Pocket Pivot Detection with Visual Markers:
Pocket pivots are a powerful bullish signal, especially relevant for swing trading. Pocket pivots are crucial for swing trading and are effective across all timeframes. The indicator marks pocket pivots with circular markers below the price bar:
a. 10-Day Pocket Pivot: Identified when the volume exceeds the maximum selling volume of the last 10 days. These are marked with a blue circle.
b. 5-Day Pocket Pivot: Identified when the volume exceeds the maximum selling volume of the last 5 days. These are marked with a green circle.
The Swing Trend Analyzer is designed to provide traders with the tools they need to succeed in swing and positional trading. Whether you're looking for precise entry points, analyzing relative strength, or identifying key price contractions, this indicator has you covered. Experience the power of advanced technical analysis with the Swing Trend Analyzer and take your trading to the next level.
Search in scripts for "relative strength"
[Forex Fondamental Overview SGM]Fundamental analysis tool designed for currency trading in financial markets. The script generates a dashboard that displays key economic indicators for two selected currencies. Here is what makes this script particularly interesting for a trader:
1. Direct comparison between two currencies: The script allows you to choose two currencies (from a predefined list) and directly compare their key economic indicators such as interest rate, GDP growth, debt-to-GDP ratio, unemployment rate, inflation (CPI and PPI), and the services and manufacturing PMI indices. This gives you immediate insight into the economic strengths and weaknesses of each currency, which is crucial for making informed trading decisions.
2. Automatic data updating: Indicator values are updated automatically using security requests (request.security) that pull the most recent data available. This means you don't need to manually update data or check multiple sources; the script takes care of that for you.
3. Currency Relative Strength Calculation: The script calculates a strength index for each currency based on its economic indicators, and then it determines a relative strength index for the currency pair. This allows you to quickly see which currency is currently strongest, providing a basis for "buy strength, sell weakness" trading strategies.
4. Intuitive visualization: Results are presented in clear tables with colored indicators, making the information quickly digestible. For example, the background color changes depending on the relative strength of the currency pair, giving you an immediate visual signal of the overall trend.
5. Adaptability to different trading strategies: Whether you are a swing trader, a day trader, or a scalper, understanding the economic state of currencies can help you align your trading positions with underlying macroeconomic trends. This script gives you this information without requiring detailed economic analysis on your part.
In short, this script is a powerful tool for any Forex trader who wants to integrate fundamental analysis into their trading routine without bothering with the complexity of tracking and analyzing a multitude of economic indicators manually.
RSI, STOCHASTIC RSI AND MFI COMBOCombining the Relative Strength Index (RSI), Stochastic RSI (StochRSI), and Money Flow Index (MFI) can provide traders with a comprehensive approach to analyze market momentum, overbought/oversold conditions, and money flow. Each indicator offers unique insights, and their combination can help confirm trading signals and filter out false signals. Let's delve into each indicator and then discuss how they can be used together:
Relative Strength Index (RSI) 14: DA BLUE LINE
The RSI is a momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100 and is typically used to identify overbought (>70) and oversold (<30) conditions. A reading above 70 may indicate that an asset is overbought and could be due for a pullback, while a reading below 30 may suggest that an asset is oversold and could be due for a bounce.
Stochastic RSI (StochRSI) 14: DA RED LINE
The StochRSI is an oscillator that combines the features of both the Stochastic Oscillator and RSI. It measures the relative position of the RSI within its range over a specific period (e.g., 14 periods). Like the RSI, the StochRSI oscillates between 0 and 100 and is used to identify overbought and oversold conditions. Typically:
A StochRSI above 0.8 may suggest overbought conditions.
A StochRSI below 0.2 may indicate oversold conditions.
Money Flow Index (MFI) 14: DA PURPLE LINE
The MFI is a momentum oscillator that measures the inflow and outflow of money into an asset over a specific period (e.g., 14 periods). It oscillates between 0 and 100 and is used to identify overbought and oversold conditions based on both price and volume. Generally:
An MFI above 80 may indicate overbought conditions.
An MFI below 20 may suggest oversold conditions.
Combining RSI, StochRSI, and MFI:
When combining RSI, StochRSI, and MFI, traders can use the following approach to analyze the market:
Identify Overbought/Oversold Conditions:
Look for confluence between RSI, StochRSI, and MFI readings to identify overbought and oversold conditions.
For example, if RSI > 70, StochRSI > 0.8, and MFI > 80, it may suggest a strong overbought condition, potentially indicating a reversal or pullback.
Confirm Trend Strength:
Use the RSI, StochRSI, and MFI to confirm the strength of a trend.
A rising trend with RSI, StochRSI, and MFI above 50 may suggest strong bullish momentum, while a falling trend with readings below 50 may indicate strong bearish momentum.
Divergence Analysis:
Look for divergences between price and RSI, StochRSI, or MFI to identify potential trend reversals.
For example, if the price makes a higher high, but RSI, StochRSI, or MFI makes a lower high (bearish divergence), it may suggest weakening bullish momentum and potential downside.
Combining RSI, StochRSI, and MFI can offer traders a more holistic view of market momentum, overbought/oversold conditions, and money flow. Backtest it let me know your success.
Dashboard — Vol & PriceDashboard for traders
Indicator Description
1. Prev Day High
What it shows: the previous trading day's high.
Why it shows: a resistance level. Many traders watch to see if the price will hold above or below this level. A breakout can signal buying strength.
2. Prev Day Low
What it shows: the previous day's low.
Why it shows: a support level. If the price breaks downwards, it signals weakness and a possible continuation of the decline.
3. Today
What it shows:
The difference between the current price and yesterday's close (in absolute values and as a percentage).
Color: green for an increase, red for a decrease.
Why it shows: immediately shows how strong a gap or movement is today relative to yesterday. This is an indicator of current momentum.
4. ADR, % (Average Daily Range)
What it shows: Average daily range (High – Low), expressed as a percentage of the closing price, for the selected period (default 7 days).
Why it's useful: To understand the "normal" volatility of an instrument. For example, if the ADR is 3%, then a 1% move is small, while a 6% move is very large.
5. ATR (Average True Range)
What it shows: Average fluctuation range (including gaps), in absolute points, for the specified period (default 7 days).
Why it's useful: A classic volatility indicator. Useful for setting stops, calculating position sizes, and identifying "noise" movements.
6. ATR (Today), %
What it shows: How much the current movement today (from yesterday's close to the current price) represents in % of the average ATR.
Why it shows: Shows whether the instrument has "played out" its average range. If the value is already >100%, there is a high probability that the movement will begin to slow.
7. Vol (Today)
What it shows:
Current trading volume for the day (in millions/billions).
Comparison with yesterday as a percentage (for example: 77.32M (-52.78%)).
Color: green if the volume is higher than yesterday; red if lower.
Why it shows:Quickly shows whether the market is active today. Volume = fuel for price movement.
8. Avg Vol (20d)
What it shows: Average daily volume over the last 20 trading days.
Why it's useful:"normal" activity level. It's a convenient backdrop for assessing today's turnover.
9. Rel. Vol (Today), % (Relative Volume)
What it shows: Deviation of the current volume from the average (20 days).
Formula: `(today / average - 1)` * 100`.
+30% = volume 30% above average, -40% = 40% below average.
Color: green for +, red for –.
Why it's useful:A key indicator for a trader. If RelVol > 100% (green), the market is "charged," and the movement is more significant. If low, activity is weak and movements are less reliable.
10. Normalized RS (Relative Strength)
What it shows: the relative strength of a stock to a selected benchmark (e.g., SPY), normalized by the period (default 7 days).
100 = same result as the market.
> 100 = the stock is stronger than the index.
<100 = weaker than the index.
Why it's needed: filtering ideas. Strong stocks rise faster when the market rises, weak stocks fall more sharply. This helps trade in the direction of the trend and select the best candidates.
In summary:
Prev High / Low — key support and resistance levels.
Today — an instant understanding of the current momentum.
ADR and ATR — volatility and potential movement.
ATR (Today) — how much the instrument has already "run."
Vol + Rel.Vol — activity and confirmation of the movement's strength.
RS — selecting strong/weak leaders against the market.
Power RSI Segment Runner [CHE] Power RSI Segment Runner — Tracks RSI momentum across higher timeframe segments to detect directional switches for trend confirmation.
Summary
This indicator calculates a running Relative Strength Index adapted to segments defined by changes in a higher timeframe, such as daily closes, providing a smoothed view of momentum within each period. It distinguishes between completed segments, which fix the final RSI value, and ongoing ones, which update in real time with an exponential moving average filter. Directional switches between bullish and bearish momentum trigger visual alerts, including overlay lines and emojis, while a compact table displays current trend strength as a progress bar. This segmented approach reduces noise from intra-period fluctuations, offering clearer signals for trend persistence compared to standard RSI on lower timeframes.
Motivation: Why this design?
Standard RSI often generates erratic signals in choppy markets due to constant recalculation over fixed lookback periods, leading to false reversals that mislead traders during range-bound or volatile phases. By resetting the RSI accumulation at higher timeframe boundaries, this indicator aligns momentum assessment with broader market cycles, capturing sustained directional bias more reliably. It addresses the gap between short-term noise and long-term trends, helping users filter entries without over-relying on absolute overbought or oversold thresholds.
What’s different vs. standard approaches?
- Baseline Reference: Diverges from the classic Wilder RSI, which uses a fixed-length exponential moving average of gains and losses across all bars.
- Architecture Differences:
- Segments momentum resets at higher timeframe changes, isolating calculations per period instead of continuous history.
- Employs persistent sums for ups and downs within segments, with on-the-fly RSI derivation and EMA smoothing.
- Integrates switch detection logic that clears prior visuals on reversal, preventing clutter from outdated alerts.
- Adds overlay projections like horizontal price lines and dynamic percent change trackers for immediate trade context.
- Practical Effect: Charts show discrete RSI endpoints for past segments alongside a curved running trace, making momentum evolution visually intuitive. Switches appear as clean, extendable overlays, reducing alert fatigue and highlighting only confirmed directional shifts, which aids in avoiding whipsaws during minor pullbacks.
How it works (technical)
The indicator begins by detecting changes in the specified higher timeframe, such as a new daily bar, to define segment boundaries. At each boundary, it finalizes the prior segment's RSI by summing positive and negative price changes over that period and derives the value from the ratio of those sums, then applies an exponential moving average for smoothing. Within the active segment, it accumulates ongoing ups and downs from price changes relative to the source, recalculating the running RSI similarly and smoothing it with the same EMA length.
Points for the running RSI are collected into an array starting from the segment's onset, forming a curved polyline once sufficient bars accumulate. Comparisons between the running RSI and the last completed segment's value determine the current direction as long, short, or neutral, with switches triggering deletions of old visuals and creation of new ones: a label at the RSI pane, a vertical dashed line across the RSI range, an emoji positioned via ATR offset on the price chart, a solid horizontal line at the switch price, a dashed line tracking current close, and a midpoint label for percent change from the switch.
Initialization occurs on the first bar by resetting accumulators, and visualization gates behind a minimum bar count since the segment start to avoid early instability. The trend strength table builds vertically with filled cells proportional to the rounded RSI value, colored by direction. All drawing objects update or extend on subsequent bars to reflect live progress.
Parameter Guide
EMA Length — Controls the smoothing applied to the running RSI; higher values increase lag but reduce noise. Default: 10. Trade-offs: Shorter settings heighten sensitivity for fast markets but risk more false switches; longer ones suit trending conditions for stability.
Source — Selects the price data for change calculations, typically close for standard momentum. Default: close. Trade-offs: Open or high/low may emphasize gaps, altering segment intensity.
Segment Timeframe — Defines the higher timeframe for segment resets, like daily for intraday charts. Default: D. Trade-offs: Shorter frames create more frequent but shorter segments; longer ones align with major cycles but delay resets.
Overbought Level — Sets the upper threshold for potential overbought conditions (currently unused in visuals). Default: 70. Trade-offs: Adjust for asset volatility; higher values delay bearish warnings.
Oversold Level — Sets the lower threshold for potential oversold conditions (currently unused in visuals). Default: 30. Trade-offs: Lower values permit deeper dips before signaling bullish potential.
Show Completed Label — Toggles labels at segment ends displaying final RSI. Default: true. Trade-offs: Enables historical review but can crowd charts on dense timeframes.
Plot Running Segment — Enables the curved polyline for live RSI trace. Default: true. Trade-offs: Visualizes intra-segment flow; disable for cleaner panes.
Running RSI as Label — Displays current running RSI as a forward-projected label on the last bar. Default: false. Trade-offs: Useful for quick reads; may overlap in tight scales.
Show Switch Label — Activates RSI pane labels on directional switches. Default: true. Trade-offs: Provides context; omit to minimize pane clutter.
Show Switch Line (RSI) — Draws vertical dashed lines across the RSI range at switches. Default: true. Trade-offs: Marks reversal bars clearly; extends both ways for reference.
Show Solid Overlay Line — Projects a horizontal line from switch price forward. Default: true. Trade-offs: Acts as dynamic support/resistance; wider lines enhance visibility.
Show Dashed Overlay Line — Tracks a dashed line from switch to current close. Default: true. Trade-offs: Shows price deviation; thinner for subtlety.
Show Percent Change Label — Midpoint label tracking percent move from switch. Default: true. Trade-offs: Quantifies progress; centers dynamically.
Show Trend Strength Table — Displays right-side table with direction header and RSI bar. Default: true. Trade-offs: Instant strength gauge; fixed position avoids overlap.
Activate Visualization After N Bars — Delays signals until this many bars into a segment. Default: 3. Trade-offs: Filters immature readings; higher values miss early momentum.
Segment End Label — Color for completed RSI labels. Default: 7E57C2. Trade-offs: Purple tones for finality.
Running RSI — Color for polyline and running elements. Default: yellow. Trade-offs: Bright for live tracking.
Long — Color for bullish switch visuals. Default: green. Trade-offs: Standard for uptrends.
Short — Color for bearish switch visuals. Default: red. Trade-offs: Standard for downtrends.
Solid Line Width — Thickness of horizontal overlay line. Default: 2. Trade-offs: Bolder for emphasis on key levels.
Dashed Line Width — Thickness of tracking and vertical lines. Default: 1. Trade-offs: Finer to avoid dominance.
Reading & Interpretation
Completed segment RSIs appear as static points or labels in purple, indicating the fixed momentum at period close—values drifting toward the upper half suggest building strength, while lower half implies weakness. The yellow curved polyline traces the live smoothed RSI within the current segment, rising for accumulating gains and falling for losses. Directional labels and lines in green or red flag switches: green for running momentum exceeding the prior segment's, signaling potential uptrend continuation; red for the opposite.
The right table's header colors green for long, red for short, or gray for neutral/wait, with filled purple bars scaling from bottom (low RSI) to top (high), topped by the numeric value. Overlay elements project from switch bars: the solid green/red line as a price anchor, dashed tracker showing pullback extent, and percent label quantifying deviation—positive for alignment with direction, negative for counter-moves. Emojis (up arrow for long, down for short) float above/below price via ATR spacing for quick chart scans.
Practical Workflows & Combinations
- Trend Following: Enter long on green switch confirmation after a higher high in structure; filter with table strength above midpoint for conviction. Pair with volume surge for added weight.
- Exits/Stops: Trail stops to the solid overlay line on pullbacks; exit if percent change reverses beyond 2 percent against direction. Use wait bars to confirm without chasing.
- Multi-Asset/Multi-TF: Defaults suit forex/stocks on 1H-4H with daily segments; for crypto, shorten EMA to 5 for volatility. Scale segment TF to weekly for daily charts across indices.
- Combinations: Overlay on EMA clouds for confluence—switch aligning with cloud break strengthens signal. Add volatility filters like ATR bands to debounce in low-volume regimes.
Behavior, Constraints & Performance
Signals confirm on bar close within segments, with running polyline updating live but gated by minimum bars to prevent flicker. Higher timeframe changes may introduce minor repaints on timeframe switches, mitigated by relying on confirmed HTF closes rather than intrabar peeks. Resource limits cap at 500 labels/lines and 50 polylines, pruning old objects on switches to stay efficient; no explicit loops, but array growth ties to segment length—suitable for up to 500-bar histories without lag.
Known limits include delayed visualization in short segments and insensitivity to overbought/oversold levels, as thresholds are inputted but not actively visualized. Gaps in source data reset accumulators prematurely, potentially skewing early RSI.
Sensible Defaults & Quick Tuning
Start with EMA length 10, daily segments, and 3-bar wait for balanced responsiveness on hourly charts. For excessive switches in ranging markets, increase wait bars to 5 or EMA to 14 to dampen noise. If signals lag in trends, drop EMA to 5 and use 1H segments. For stable assets like indices, widen to weekly segments; tune colors for dark/light themes without altering logic.
What this indicator is—and isn’t
This tool serves as a momentum visualization and switch detector layered over price action, aiding trend identification and confirmation in segmented contexts. It is not a standalone trading system, predictive model, or risk calculator—always integrate with broader analysis, position sizing, and stop-loss discipline. View it as an enhancement for discretionary setups, not automated alerts without validation.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
SECTOR ROTATION Sector Rotation Indicator with Auto Chart Symbol
This indicator helps traders track relative performance across multiple indices/sectors simultaneously, making it easy to identify sector rotation and market leadership.
Key Features:
✅ 21 Symbols Tracking: Monitor 20 customizable symbols + your current chart symbol automatically(DIVIDEND SYMBOL)
✅ Percentage Performance: All moving averages show percentage gain/loss from 1 timeframe period ago
✅ Color-Coded Visualization: Heat map coloring (red to green) based on relative performance ranking
✅ Flexible Timeframes: Works on any timeframe from 1-minute to 12-month charts
✅ Performance Table: Quick-view table showing candle performance with inside/outside bar detection
✅ Indian Market Ready: Pre-configured with NSE indices (NIFTY, BANKNIFTY, and sectoral indices)
Default Symbols (Customizable):
NIFTY, CNXSMALLCAP, CNXMIDCAP, BANKNIFTY
Sector indices: IT, AUTO, PHARMA, METAL, ENERGY, FMCG, etc.
Plus your current chart symbol (automatically added)
How It Works:
Select your preferred timeframe (1D, 1W, 1M, etc.)
The indicator calculates percentage performance from given period ago
Moving averages show smoothed performance trends
Colors indicate relative strength: Green = outperformers, Red = underperformers
Perfect For:
Sector rotation analysis
Relative strength comparison
Market breadth assessment
Index/ETF traders
Swing and position traders
Settings:
Adjustable MA length (default: 20)
Customizable colors and table position
Show/hide percentage labels
Horizontal or vertical table layout
This is not any buy or sell signal or recommendation, consult with your advisor first.
Enhanced Holt-Winters RSI [BOSWaves]Enhanced Holt-Winters RSI – Next-Level Momentum Smoothing & Signal Precision
Overview
The Enhanced Holt-Winters RSI transforms the classic Relative Strength Index into a robust, lag-minimized momentum oscillator through Holt-Winters triple exponential smoothing. By modeling the level, trend, and cyclical behavior of the RSI series, this indicator delivers smoother, more responsive signals that highlight overbought/oversold conditions, momentum shifts, and high-conviction trading setups without cluttering the chart with noise.
Unlike traditional RSI, which reacts to historical data and produces frequent whipsaws, the Enhanced Holt-Winters RSI filters transient price fluctuations, enabling traders to detect emerging momentum and potential reversal zones earlier.
Theoretical Foundation
The traditional RSI measures relative strength by comparing average gains and losses, but suffers from:
Lag in trend recognition : Signals often arrive after momentum has shifted.
Noise sensitivity : High-frequency price movements generate unreliable crossovers.
Limited insight into structural market shifts : Standard RSI cannot contextualize cyclical or momentum patterns.
The Enhanced Holt-Winters RSI addresses these limitations by applying triple exponential smoothing directly to the RSI series. This decomposes the series into:
Level (Lₜ) : Represents the smoothed central tendency of RSI.
Trend (Tₜ) : Captures rate-of-change in smoothed momentum.
Seasonal Component (Sₜ) : Models short-term cyclical deviations in momentum.
By incorporating these elements, the oscillator produces smoothed RSI values that react faster to emerging trends while suppressing erratic noise. Its internal forecast is mathematical, influencing the smoothed RSI output and signals, rather than being directly plotted.
How It Works
The Enhanced Holt-Winters RSI builds its signal framework through several layers:
1. Base RSI Calculation
Computes standard RSI over the selected period as the primary momentum input.
2. Triple Exponential Smoothing (Holt-Winters)
The RSI is smoothed recursively to extract underlying momentum structure:
Level, trend, and seasonal components are combined to produce a smoothed RSI.
This internal smoothing reduces lag and enhances signal reliability.
3. Momentum Analysis
Short-term momentum shifts are tracked via a moving average of the smoothed RSI, highlighting acceleration or deceleration in directional strength.
4. Volume Confirmation (Optional)
Buy/sell signals can be filtered through a configurable volume threshold, ensuring only high-conviction moves trigger alerts.
5. Visual Output
Colored Candles : Represent overbought (red), oversold (green), or neutral (yellow) conditions.
Oscillator Panel : Plots the smoothed RSI with dynamic color coding for immediate trend context.
Signals : Triangular markers indicate bullish or bearish setups, with stronger signals flagged in extreme zones.
Interpretation
The Enhanced Holt-Winters RSI provides a multi-dimensional perspective on price action:
Trend Strength : Smoothed RSI slope and color coding reflect the direction and momentum intensity.
Momentum Shifts : Rapid changes in the smoothed RSI indicate emerging strength or weakness.
Overbought/Oversold Zones : Highlight areas where price is stretched relative to recent momentum.
High-Conviction Signals : Combined with volume filtering, markers indicate optimal entries/exits.
Cycle Awareness : Smoothing reveals structural patterns, helping traders avoid reacting to noise.
By combining these elements, traders gain early insight into market structure and momentum without relying on raw, lag-prone RSI data.
Strategy Integration
The Enhanced Holt-Winters RSI can be applied across trading styles:
Trend Following
Enter when RSI is aligned with price momentum and color-coded signals confirm trend direction.
Strong slope in the smoothed RSI signals trend continuation.
Reversal Trading
Look for RSI extremes with momentum shifts and strong signal markers.
Compression in oscillator values often precedes reversal setups.
Breakout Detection
Oscillator flattening in neutral zones followed by directional expansion indicates potential breakout conditions.
Multi-Timeframe Confluence
Higher timeframes provide directional bias; lower timeframes refine entry timing using smoothed RSI dynamics.
Technical Implementation Details
Input Source : Close, open, high, low, or price.
Smoothing : Holt-Winters triple exponential smoothing applied to RSI.
Parameters :
Level (α) : Controls smoothing of RSI.
Trend (β) : Adjusts responsiveness to momentum changes.
Seasonal Length : Defines cycles for short-term adjustments.
Delta Smoothing : Reduces choppiness in smoothed RSI difference.
Outputs :
Smoothed RSI
Colored candles and oscillator panel
Buy/Sell signal markers (with optional strength filtering)
Volume Filtering : Optional threshold to confirm signals.
Optimal Application Parameters
Asset-Specific Guidance:
Forex : Use moderate smoothing (α, β) to capture medium-term momentum swings while filtering minor price noise. Works best when combined with volume or volatility filters.
Equities : Balance responsiveness and smoothness to identify sustained sector momentum or rotational shifts; ideal for capturing clean directional transitions.
Cryptocurrency : Increase smoothing parameters slightly to stabilize RSI during extreme volatility; optional volume confirmation can help filter false signals.
Futures/Indices : Lower smoothing sensitivity emphasizes macro momentum and structural trend durability over short-term fluctuations.
Timeframe Optimization:
Scalping (1-5m) : Use higher sensitivity (lower smoothing factors) to react quickly to micro-momentum reversals.
Intraday (15m-1h) : Balance smoothing and responsiveness for detecting short-term acceleration and exhaustion zones.
Swing (4h-Daily) : Apply moderate smoothing to reveal underlying directional persistence and cyclical reversals.
Position (Daily-Weekly) : Use stronger smoothing to isolate dominant momentum trends and filter temporary pullbacks.
Integration Guidelines
Combine with trend filters (EMAs, SuperSmoother MA, ATR-based tools) for confirmation.
Use volume and signal strength markers to filter low-conviction trades.
Slope, color, and signal alignment can guide entry, stop placement, and scaling.
Disclaimer
The Enhanced Holt-Winters RSI is a technical analysis tool, not a guaranteed profit system. Effectiveness depends on proper settings, market structure, and disciplined risk management. Always backtest before live trading.
BB + OBV + RSI Strategy (Enhanced + Daily Table) Script Brief – *BB + OBV + RSI Strategy (Enhanced + Daily Table)*
This TradingView Pine Script combines **Bollinger Bands (BB)**, **On-Balance Volume (OBV)**, **Relative Strength Index (RSI)**, and **Exponential Moving Average (EMA)** to help traders identify potential trend conditions and market strength.
**Key Features:**
* **Bollinger Bands** (20-period SMA ± 2 Std Dev by default) to track volatility and price extremes.
* **OBV & OBV Moving Average** to confirm buying or selling pressure.
* **RSI** to highlight overbought and oversold zones.
* **200 EMA** as a long-term trend filter.
* **Daily Comparison Table** (top-right corner):
* Displays today’s vs. yesterday’s values for Close, RSI, OBV vs MA, BB Position, and EMA Trend.
* Helps quickly assess whether momentum and trend conditions are strengthening or weakening.
**Usage:**
* The chart shows **BB lines and EMA** for real-time analysis on any timeframe.
* The **table provides higher-timeframe context** (daily values), making it easier to confirm signals across multiple timeframes.
* Best applied with backtesting and proper risk management.
RSI ADX Bollinger Analysis High-level purpose and design philosophy
This indicator — RSI-ADX-Bollinger Analysis — is a compact, educational market-analysis toolkit that blends momentum (RSI), trend strength (ADX), volatility structure (Bollinger Bands) and simple volumetrics to provide traders a snapshot of market condition and trade idea quality. The design philosophy is explicit and layered: use each component to answer a different question about price action (momentum, conviction, volatility, participation), then combine answers to form a more robust, explainable signal. The mashup is intended for analysis and learning, not automatic execution: it surfaces the why behind signals so traders can test, learn and apply rules with risk management.
________________________________________
What each indicator contributes (component-by-component)
RSI (Relative Strength Index) — role and behavior: RSI measures short-term momentum by comparing recent gains to recent losses. A high RSI (near or above the overbought threshold) indicates strong recent buying pressure and potential exhaustion if price is extended. A low RSI (near or below the oversold threshold) indicates strong recent selling pressure and potential exhaustion or a value area for mean-reversion. In this dashboard RSI is used as the primary momentum trigger: it helps identify whether price is locally over-extended on the buy or sell side.
ADX (Average Directional Index) — role and behavior: ADX measures trend strength independently of direction. When ADX rises above a chosen threshold (e.g., 25), it signals that the market is trending with conviction; ADX below the threshold suggests range or weak trend. Because patterns and momentum signals perform differently in trending vs. ranging markets, ADX is used here as a filter: only when ADX indicates sufficient directional strength does the system treat RSI+BB breakouts as meaningful trade candidates.
Bollinger Bands — role and behavior: Bollinger Bands (20-period basis ± N standard deviations) show volatility envelope and relative price position vs. a volatility-adjusted mean. Price outside the upper band suggests pronounced extension relative to recent volatility; price outside the lower band suggests extended weakness. A band expansion (increasing width) signals volatility breakout potential; contraction signals range-bound conditions and potential squeeze. In this dashboard, Bollinger Bands provide the volatility/structural context: RSI extremes plus price beyond the band imply a stronger, volatility-backed move.
Volume split & basic MA trend — role and behavior: Buy-like and sell-like volume (simple heuristic using close>open or closeopen) or sell-like (close1.2 for validation and compare win rate and expectancy.
4. TF alignment: Accept signals only when higher timeframe (e.g., 4h) trend agrees — compare results.
5. Parameter sensitivity: Vary RSI threshold (70/30 vs 80/20), Bollinger stddev (2 vs 2.5), and ADX threshold (25 vs 30) and measure stability of results.
These exercises teach both statistical thinking and the specific failure modes of the mashup.
________________________________________
Limitations, failure modes and caveats (explicit & teachable)
• ADX and Bollinger measures lag during fast-moving news events — signals can be late or wrong during earnings, macro shocks, or illiquid sessions.
• Volume classification by open/close is a heuristic; it does not equal TAPEDATA, footprint or signed volume. Use it as supportive evidence, not definitive proof.
• RSI can remain overbought or oversold for extended stretches in persistent trends — relying solely on RSI extremes without ADX or BB context invites large drawdowns.
• Small-cap or low-liquidity instruments yield noisy band behavior and unreliable volume ratios.
Being explicit about these limitations is a strong point in a TradingView description — it demonstrates transparency and educational intent.
________________________________________
Originality & mashup justification (text you can paste)
This script intentionally combines classical momentum (RSI), volatility envelope (Bollinger Bands) and trend-strength (ADX) because each indicator answers a different and complementary question: RSI answers is price locally extreme?, Bollinger answers is price outside normal volatility?, and ADX answers is the market moving with conviction?. Volume participation then acts as a practical check for real market involvement. This combination is not a simple “indicator mashup”; it is a designed ensemble where each element reduces the others’ failure modes and together produce a teachable, testable signal framework. The script’s purpose is educational and analytical — to show traders how to interpret the interplay of momentum, volatility, and trend strength.
________________________________________
TradingView publication guidance & compliance checklist
To satisfy TradingView rules about mashups and descriptions, include the following items in your script description (without exposing source code):
1. Purpose statement: One or two lines describing the script’s objective (educational multi-indicator market overview and idea filter).
2. Component list: Name the major modules (RSI, Bollinger Bands, ADX, volume heuristic, SMA trend checks, signal tracking) and one-sentence reason for each.
3. How they interact: A succinct non-code explanation: “RSI finds momentum extremes; Bollinger confirms volatility expansion; ADX confirms trend strength; all three must align for a BUY/SELL.”
4. Inputs: List adjustable inputs (RSI length and thresholds, BB length & stddev, ADX threshold & smoothing, volume MA, table position/size).
5. Usage instructions: Short workflow (check TF alignment → confirm participation → define stop & R:R → backtest).
6. Limitations & assumptions: Explicitly state volume is approximated, ADX has lag, and avoid promising guaranteed profits.
7. Non-promotional language: No external contact info, ads, claims of exclusivity or guaranteed outcomes.
8. Trademark clause: If you used trademark symbols, remove or provide registration proof.
9. Risk disclaimer: Add the copy-ready disclaimer below.
This matches TradingView’s request for meaningful descriptions that explain originality and inter-component reasoning.
________________________________________
Copy-ready short publication description (paste into TradingView)
Advanced RSI-ADX-Bollinger Market Overview — educational multi-indicator dashboard. This script combines RSI (momentum extremes), Bollinger Bands (volatility envelope and band expansion), ADX (trend strength), simple SMA trend bias and a basic buy/sell volume heuristic to surface high-quality idea candidates. Signals require alignment of momentum, volatility expansion and rising ADX; volume participation is displayed to support signal confidence. Inputs are configurable (RSI length/levels, BB length/stddev, ADX length/threshold, volume MA, display options). This tool is intended for analysis and learning — not for automated execution. Users should back test and apply robust risk management. Limitations: volume classification here is a heuristic (close>open), ADX and BB measures lag in fast news events, and results vary by instrument liquidity.
________________________________________
Copy-ready risk & misuse disclaimer (paste into description or help file)
This script is provided for educational and analytical purposes only and does not constitute financial or investment advice. It does not guarantee profits. Indicators are heuristics and may give false or late signals; always back test and paper-trade before using real capital. The author is not responsible for trading losses resulting from the use or misuse of this indicator. Use proper position sizing and risk controls.
________________________________________
Risk Disclaimer: This tool is provided for education and analysis only. It is not financial advice and does not guarantee returns. Users assume all risk for trades made based on this script. Back test thoroughly and use proper risk management.
Currency Strength v3.0Currency Strength v3.0
Summary
The Currency Strength indicator is a powerful tool designed to gauge the relative strength of major and emerging market currencies. By plotting the True Strength Index (TSI) of various currency indices, it provides a clear visual representation of which currencies are gaining momentum and which are losing it. This indicator automatically detects the currency pair on your chart and highlights the corresponding strength lines, simplifying analysis and helping you quickly identify potential trading opportunities based on currency dynamics.
Key Features
Comprehensive Currency Analysis: Tracks the strength of 19 currencies, including major pairs and several emerging market currencies.
Automatic Pair Detection: Intelligently identifies the base and quote currency of the active chart, automatically highlighting the relevant strength lines.
Dynamic Coloring: The base currency is consistently colored blue, and the quote currency is colored gold, making it easy to distinguish between the two at a glance.
Non-Repainting TSI Calculation: Uses the True Strength Index (TSI) for smooth and reliable momentum readings that do not repaint.
Customizable Settings: Allows for adjustment of the fast and slow periods for the TSI calculation to fit your specific trading style.
Clean Interface: Features a minimalist legend table that only displays the currencies relevant to your current chart, keeping your workspace uncluttered.
How It Works
The indicator pulls data from major currency indices (like DXY for the US Dollar and EXY for the Euro). For currencies that don't have a dedicated index, it uses their USD pair (e.g., USDCNY) and inverts the calculation to derive the currency's strength relative to the dollar. It then applies the True Strength Index (TSI) to this data. The TSI is a momentum oscillator that is less volatile than other oscillators, providing a more reliable measure of strength. The resulting values are plotted on the chart, allowing you to see how different currencies are performing against each other in real-time.
How to Use
Trend Confirmation: When the base currency's line is rising and above the zero line, and the quote currency's line is falling, it can confirm a bullish trend for the pair. The opposite would suggest a bearish trend.
Identifying Divergences: Look for divergences between the currency strength lines and the price action of the pair. For example, if the price is making higher highs but the base currency's strength is making lower highs, it could signal a potential reversal.
Crossovers: A crossover of the base and quote currency lines can signal a shift in momentum. A bullish signal occurs when the base currency line crosses above the quote currency line. A bearish signal occurs when it crosses below.
Overbought/Oversold Levels: The horizontal dashed lines at 0.5 and -0.5 can be used as general guides for overbought and oversold conditions, respectively. Strength moving beyond these levels may indicate an unsustainable move that is due for a correction.
Settings
Fast Period: The short-term period for the TSI calculation. Default is 7.
Slow Period: The long-term period for the TSI calculation. Default is 15.
Index Source: The price source used for the calculations (e.g., Close, Open). Default is Close.
Base Currency Color: The color for the base currency line. Default is Royal Blue.
Quote Currency Color: The color for the quote currency line. Default is Goldenrod.
Disclaimer
This indicator is intended for educational and analytical purposes only. It is not financial advice. Trading involves substantial risk, and past performance is not indicative of future results. Always conduct your own research and risk management before making any trading decisions.
Bear Market Probability Model# Bear Market Probability Model: A Multi-Factor Risk Assessment Framework
The Bear Market Probability Model represents a comprehensive quantitative framework for assessing systemic market risk through the integration of 13 distinct risk factors across four analytical categories: macroeconomic indicators, technical analysis factors, market sentiment measures, and market breadth metrics. This indicator synthesizes established financial research methodologies to provide real-time probabilistic assessments of impending bear market conditions, offering institutional-grade risk management capabilities to retail and professional traders alike.
## Theoretical Foundation
### Historical Context of Bear Market Prediction
Bear market prediction has been a central focus of financial research since the seminal work of Dow (1901) and the subsequent development of technical analysis theory. The challenge of predicting market downturns gained renewed academic attention following the market crashes of 1929, 1987, 2000, and 2008, leading to the development of sophisticated multi-factor models.
Fama and French (1989) demonstrated that certain financial variables possess predictive power for stock returns, particularly during market stress periods. Their three-factor model laid the groundwork for multi-dimensional risk assessment, which this indicator extends through the incorporation of real-time market microstructure data.
### Methodological Framework
The model employs a weighted composite scoring methodology based on the theoretical framework established by Campbell and Shiller (1998) for market valuation assessment, extended through the incorporation of high-frequency sentiment and technical indicators as proposed by Baker and Wurgler (2006) in their seminal work on investor sentiment.
The mathematical foundation follows the general form:
Bear Market Probability = Σ(Wi × Ci) / ΣWi × 100
Where:
- Wi = Category weight (i = 1,2,3,4)
- Ci = Normalized category score
- Categories: Macroeconomic, Technical, Sentiment, Breadth
## Component Analysis
### 1. Macroeconomic Risk Factors
#### Yield Curve Analysis
The inclusion of yield curve inversion as a primary predictor follows extensive research by Estrella and Mishkin (1998), who demonstrated that the term spread between 3-month and 10-year Treasury securities has historically preceded all major recessions since 1969. The model incorporates both the 2Y-10Y and 3M-10Y spreads to capture different aspects of monetary policy expectations.
Implementation:
- 2Y-10Y Spread: Captures market expectations of monetary policy trajectory
- 3M-10Y Spread: Traditional recession predictor with 12-18 month lead time
Scientific Basis: Harvey (1988) and subsequent research by Ang, Piazzesi, and Wei (2006) established the theoretical foundation linking yield curve inversions to economic contractions through the expectations hypothesis of the term structure.
#### Credit Risk Premium Assessment
High-yield credit spreads serve as a real-time gauge of systemic risk, following the methodology established by Gilchrist and Zakrajšek (2012) in their excess bond premium research. The model incorporates the ICE BofA High Yield Master II Option-Adjusted Spread as a proxy for credit market stress.
Threshold Calibration:
- Normal conditions: < 350 basis points
- Elevated risk: 350-500 basis points
- Severe stress: > 500 basis points
#### Currency and Commodity Stress Indicators
The US Dollar Index (DXY) momentum serves as a risk-off indicator, while the Gold-to-Oil ratio captures commodity market stress dynamics. This approach follows the methodology of Akram (2009) and Beckmann, Berger, and Czudaj (2015) in analyzing commodity-currency relationships during market stress.
### 2. Technical Analysis Factors
#### Multi-Timeframe Moving Average Analysis
The technical component incorporates the well-established moving average convergence methodology, drawing from the work of Brock, Lakonishok, and LeBaron (1992), who provided empirical evidence for the profitability of technical trading rules.
Implementation:
- Price relative to 50-day and 200-day simple moving averages
- Moving average convergence/divergence analysis
- Multi-timeframe MACD assessment (daily and weekly)
#### Momentum and Volatility Analysis
The model integrates Relative Strength Index (RSI) analysis following Wilder's (1978) original methodology, combined with maximum drawdown analysis based on the work of Magdon-Ismail and Atiya (2004) on optimal drawdown measurement.
### 3. Market Sentiment Factors
#### Volatility Index Analysis
The VIX component follows the established research of Whaley (2009) and subsequent work by Bekaert and Hoerova (2014) on VIX as a predictor of market stress. The model incorporates both absolute VIX levels and relative VIX spikes compared to the 20-day moving average.
Calibration:
- Low volatility: VIX < 20
- Elevated concern: VIX 20-25
- High fear: VIX > 25
- Panic conditions: VIX > 30
#### Put-Call Ratio Analysis
Options flow analysis through put-call ratios provides insight into sophisticated investor positioning, following the methodology established by Pan and Poteshman (2006) in their analysis of informed trading in options markets.
### 4. Market Breadth Factors
#### Advance-Decline Analysis
Market breadth assessment follows the classic work of Fosback (1976) and subsequent research by Brown and Cliff (2004) on market breadth as a predictor of future returns.
Components:
- Daily advance-decline ratio
- Advance-decline line momentum
- McClellan Oscillator (Ema19 - Ema39 of A-D difference)
#### New Highs-New Lows Analysis
The new highs-new lows ratio serves as a market leadership indicator, based on the research of Zweig (1986) and validated in academic literature by Zarowin (1990).
## Dynamic Threshold Methodology
The model incorporates adaptive thresholds based on rolling volatility and trend analysis, following the methodology established by Pagan and Sossounov (2003) for business cycle dating. This approach allows the model to adjust sensitivity based on prevailing market conditions.
Dynamic Threshold Calculation:
- Warning Level: Base threshold ± (Volatility × 1.0)
- Danger Level: Base threshold ± (Volatility × 1.5)
- Bounds: ±10-20 points from base threshold
## Professional Implementation
### Institutional Usage Patterns
Professional risk managers typically employ multi-factor bear market models in several contexts:
#### 1. Portfolio Risk Management
- Tactical Asset Allocation: Reducing equity exposure when probability exceeds 60-70%
- Hedging Strategies: Implementing protective puts or VIX calls when warning thresholds are breached
- Sector Rotation: Shifting from growth to defensive sectors during elevated risk periods
#### 2. Risk Budgeting
- Value-at-Risk Adjustment: Incorporating bear market probability into VaR calculations
- Stress Testing: Using probability levels to calibrate stress test scenarios
- Capital Requirements: Adjusting regulatory capital based on systemic risk assessment
#### 3. Client Communication
- Risk Reporting: Quantifying market risk for client presentations
- Investment Committee Decisions: Providing objective risk metrics for strategic decisions
- Performance Attribution: Explaining defensive positioning during market stress
### Implementation Framework
Professional traders typically implement such models through:
#### Signal Hierarchy:
1. Probability < 30%: Normal risk positioning
2. Probability 30-50%: Increased hedging, reduced leverage
3. Probability 50-70%: Defensive positioning, cash building
4. Probability > 70%: Maximum defensive posture, short exposure consideration
#### Risk Management Integration:
- Position Sizing: Inverse relationship between probability and position size
- Stop-Loss Adjustment: Tighter stops during elevated risk periods
- Correlation Monitoring: Increased attention to cross-asset correlations
## Strengths and Advantages
### 1. Comprehensive Coverage
The model's primary strength lies in its multi-dimensional approach, avoiding the single-factor bias that has historically plagued market timing models. By incorporating macroeconomic, technical, sentiment, and breadth factors, the model provides robust risk assessment across different market regimes.
### 2. Dynamic Adaptability
The adaptive threshold mechanism allows the model to adjust sensitivity based on prevailing volatility conditions, reducing false signals during low-volatility periods and maintaining sensitivity during high-volatility regimes.
### 3. Real-Time Processing
Unlike traditional academic models that rely on monthly or quarterly data, this indicator processes daily market data, providing timely risk assessment for active portfolio management.
### 4. Transparency and Interpretability
The component-based structure allows users to understand which factors are driving risk assessment, enabling informed decision-making about model signals.
### 5. Historical Validation
Each component has been validated in academic literature, providing theoretical foundation for the model's predictive power.
## Limitations and Weaknesses
### 1. Data Dependencies
The model's effectiveness depends heavily on the availability and quality of real-time economic data. Federal Reserve Economic Data (FRED) updates may have lags that could impact model responsiveness during rapidly evolving market conditions.
### 2. Regime Change Sensitivity
Like most quantitative models, the indicator may struggle during unprecedented market conditions or structural regime changes where historical relationships break down (Taleb, 2007).
### 3. False Signal Risk
Multi-factor models inherently face the challenge of balancing sensitivity with specificity. The model may generate false positive signals during normal market volatility periods.
### 4. Currency and Geographic Bias
The model focuses primarily on US market indicators, potentially limiting its effectiveness for global portfolio management or non-USD denominated assets.
### 5. Correlation Breakdown
During extreme market stress, correlations between risk factors may increase dramatically, reducing the model's diversification benefits (Forbes and Rigobon, 2002).
## References
Akram, Q. F. (2009). Commodity prices, interest rates and the dollar. Energy Economics, 31(6), 838-851.
Ang, A., Piazzesi, M., & Wei, M. (2006). What does the yield curve tell us about GDP growth? Journal of Econometrics, 131(1-2), 359-403.
Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The Journal of Finance, 61(4), 1645-1680.
Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593-1636.
Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. The Quarterly Journal of Economics, 116(1), 261-292.
Beckmann, J., Berger, T., & Czudaj, R. (2015). Does gold act as a hedge or a safe haven for stocks? A smooth transition approach. Economic Modelling, 48, 16-24.
Bekaert, G., & Hoerova, M. (2014). The VIX, the variance premium and stock market volatility. Journal of Econometrics, 183(2), 181-192.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764.
Brown, G. W., & Cliff, M. T. (2004). Investor sentiment and the near-term stock market. Journal of Empirical Finance, 11(1), 1-27.
Campbell, J. Y., & Shiller, R. J. (1998). Valuation ratios and the long-run stock market outlook. The Journal of Portfolio Management, 24(2), 11-26.
Dow, C. H. (1901). Scientific stock speculation. The Magazine of Wall Street.
Estrella, A., & Mishkin, F. S. (1998). Predicting US recessions: Financial variables as leading indicators. Review of Economics and Statistics, 80(1), 45-61.
Fama, E. F., & French, K. R. (1989). Business conditions and expected returns on stocks and bonds. Journal of Financial Economics, 25(1), 23-49.
Forbes, K. J., & Rigobon, R. (2002). No contagion, only interdependence: measuring stock market comovements. The Journal of Finance, 57(5), 2223-2261.
Fosback, N. G. (1976). Stock market logic: A sophisticated approach to profits on Wall Street. The Institute for Econometric Research.
Gilchrist, S., & Zakrajšek, E. (2012). Credit spreads and business cycle fluctuations. American Economic Review, 102(4), 1692-1720.
Harvey, C. R. (1988). The real term structure and consumption growth. Journal of Financial Economics, 22(2), 305-333.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.
Magdon-Ismail, M., & Atiya, A. F. (2004). Maximum drawdown. Risk, 17(10), 99-102.
Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175-220.
Pagan, A. R., & Sossounov, K. A. (2003). A simple framework for analysing bull and bear markets. Journal of Applied Econometrics, 18(1), 23-46.
Pan, J., & Poteshman, A. M. (2006). The information in option volume for future stock prices. The Review of Financial Studies, 19(3), 871-908.
Taleb, N. N. (2007). The black swan: The impact of the highly improbable. Random House.
Whaley, R. E. (2009). Understanding the VIX. The Journal of Portfolio Management, 35(3), 98-105.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
Zarowin, P. (1990). Size, seasonality, and stock market overreaction. Journal of Financial and Quantitative Analysis, 25(1), 113-125.
Zweig, M. E. (1986). Winning on Wall Street. Warner Books.
Uptrick: Dynamic Z-Score DeviationOverview
Uptrick: Dynamic Z‑Score Deviation is a trading indicator built in Pine Script that combines statistical filters and adaptive smoothing to highlight potential reversal points in price action. It combines a hybrid moving average, dual Z‑Score analysis on both price and RSI, and visual enhancements like slope‑based coloring, ATR‑based shadow bands, and dynamically scaled reversal signals.
Introduction
Statistical indicators like Z‑Scores measure how far a value deviates from its average relative to the typical variation (standard deviation). Standard deviation quantifies how dispersed a set of values is around its mean. A Z‑Score of +2 indicates a value two standard deviations above the mean, while -2 is two below. Traders use Z‑Scores to spot unusually high or low readings that may signal overbought or oversold conditions.
Moving averages smooth out price data to reveal trends. The Arnaud Legoux Moving Average (ALMA) reduces lag and noise through weighted averaging. A Zero‑Lag EMA (approximated here using a time‑shifted EMA) seeks to further minimize delay in following price. The RSI (Relative Strength Index) is a momentum oscillator that measures recent gains against losses over a set period.
ATR (Average True Range) gauges market volatility by averaging the range between high and low over a lookback period. Shadow bands built using ATR give a visual mood of volatility around a central trend line. Together, these tools inform a dynamic but statistically grounded view of market extremes.
Purpose
The main goal of this indicator is to help traders spot short‑term reversal opportunities on lower timeframes. By requiring both price and momentum (RSI) to exhibit statistically significant deviations from their norms, it filters out weak setups and focuses on higher‑probability mean‑reversion zones. Reversal signals appear when price deviates far enough from its hybrid moving average and RSI deviates similarly in the same direction. This makes it suitable for discretionary traders seeking clean entry cues in volatile environments.
Originality and Uniqueness
Uptrick: Dynamic Z‑Score Deviation distinguishes itself from standard reversal or mean‑reversion tools by combining several elements into a single framework:
A composite moving average (ALMA + Zero‑Lag EMA) for a smooth yet responsive baseline
Dual Z‑Score filters on price and RSI rather than relying on a single measure
Adaptive visual elements, including slope‑aware coloring, multi‑layer ATR shadows, and signal sizing based on combined Z‑Score magnitude
Most indicators focus on one aspect—price envelopes or RSI thresholds—whereas Uptrick: Dynamic Z‑Score Deviation requires both layers to align before signaling. Its visual design aids quick interpretation without overwhelming the chart.
Why these indicators were merged
Every component in Uptrick: Dynamic Z‑Score Deviation has a purpose:
• ALMA: provides a smooth moving average with reduced lag and fewer false crossovers than a simple SMA or EMA.
• Zero‑Lag EMA (ZLMA approximation): further reduces the delay relative to price by applying a time shift to EMA inputs. This keeps the composite MA closer to current price action.
• RSI and its EMA filter: RSI measures momentum. Applying an EMA filter on RSI smooths out false spikes and confirms genuine overbought or oversold momentum.
• Dual Z‑Scores: computing Z‑Scores on both the distance between price and the composite MA, and on smoothed RSI, ensures that signals only fire when both price and momentum are unusually stretched.
• ATR bands: using ATR‑based shadow layers visualizes volatility around the MA, guiding traders on potential support and resistance zones.
At the end, these pieces merge into a single indicator that detects statistically significant mean reversions while staying adaptive to real‑time volatility and momentum.
Calculations
1. Compute ALMA over the chosen MA length, offset, and sigma.
2. Approximate ZLMA by applying EMA to twice the price minus the price shifted by the MA length.
3. Calculate the composite moving average as the average of ALMA and ZLMA.
4. Compute raw RSI and smooth it with ALMA. Apply an EMA filter to raw RSI to reduce noise.
5. For both price and smoothed RSI, calculate the mean and standard deviation over the Z‑Score lookback period.
6. Compute Z‑Scores:
• z_price = (current price − composite MA mean) / standard deviation of price deviations
• z_rsi = (smoothed RSI − mean RSI) / standard deviation of RSI
7. Determine reversal conditions: both Z‑Scores exceed their thresholds in the same direction, RSI EMA is in oversold/overbought zones (below 40 or above 60), and price movement confirms directionality.
8. Compute signal strength as the sum of the absolute Z‑Scores, then classify into weak, medium, or strong.
9. Calculate ATR over the chosen period and multiply by layer multipliers to form shadow widths.
10.Derive slope over the chosen slope length and color the MA line and bars based on direction, optionally smoothing color transitions via EMA on RGB channels.
How this indicator actually works
1. The script begins by smoothing price data with ALMA and approximating a zero‑lag EMA, then averaging them for the main MA.
2. RSI is calculated, then smoothed and filtered.
3. Using a rolling window, the script computes statistical measures for both price deviations and RSI.
4. Z‑Scores tell how far current values lie from their recent norms.
5. When both Z‑Scores cross configured thresholds and momentum conditions align, reversal signals are flagged.
6. Signals are drawn with size and color reflecting strength.
7. The MA is plotted with dynamic coloring; ATR shadows are layered beneath to show volatility envelopes.
8. Bars can be colored to match MA slope, reinforcing trend context.
9. Alert conditions allow automated notifications when signals occur.
Inputs
Main Length: Main MA Length. Sets the period for ALMA and ZLMA.
RSI Length: RSI Length. Determines the lookback for momentum calculations.
Z-Score Lookback: Z‑Score Lookback. Window for mean and standard deviation computations.
Price Z-Score Threshold: Price Z‑Score Threshold. Minimum deviation required for price.
RSI Z-Score threshold: RSI Z‑Score Threshold. Minimum deviation required for momentum.
RSI EMA Filter Length: RSI EMA Filter Length. Smooths raw RSI readings.
ALMA Offset: Controls ALMA’s focal point in the window.
ALMA Sigma: Adjusts ALMA’s smoothing strength.
Show Reversal Signals : Toggle to display reversal signal markers.
Slope Sensitivity: Length for slope calculation. Higher values smooth slope changes.
Use Bar Coloring: Enables coloring of price bars based on MA slope.
Show MA Shadow: Toggle for ATR‑based shadow bands.
Shadow Layer Count: Number of shadow layers (1–4).
Base Shadow ATR Multiplier: Multiplier for ATR when sizing the first band.
Smooth Color Transitions (boolean): Smooths RGB transitions for line and shadows, if enabled.
ATR Length for Shadow: ATR Period for computing volatility bands.
Use Dynamic Signal Size: Toggles dynamic scaling of reversal symbols.
Features
Moving average smoothing: a hybrid of ALMA and Zero‑Lag EMA that balances responsiveness and noise reduction.
Slope coloring: MA line and optionally price bars change color based on trend direction; color transitions can be smoothed for visual continuity.
ATR shadow layers: translucent bands around the MA show volatility envelopes; up to four concentric layers help gauge distance from normal price swings.
Dual Z‑Score filters: price and momentum must both deviate beyond thresholds to trigger signals, reducing false positives.
Dynamic signal sizing: reversal markers scale in size based on the combined Z‑Score magnitude, making stronger signals more prominent.
Adaptive visuals: optional smoothing of color channels creates gradient effects on lines and fills for a polished look.
Alert conditions: built‑in buy and sell alerts notify traders when reversal setups emerge.
Conclusion
Uptrick: Dynamic Z‑Score Deviation delivers a structured way to identify short‑term reversal opportunities by fusing statistical rigor with adaptive smoothing and clear visual cues. It guides traders through multiple confirmation layers—hybrid moving average, dual Z‑Score analysis, momentum filtering, and volatility envelopes—while keeping the chart clean and informative.
Disclaimer
This indicator is provided for informational and educational purposes only and does not constitute financial advice. Trading carries risk and may not be suitable for all participants. Past performance is not indicative of future results. Always do your own analysis and risk management before making trading decisions.
Compare Strength with SLOPE Description
This indicator compares the relative strength between the current asset and a benchmark (e.g., BTC vs. ETH or AAPL vs. SPY) using a linear regression slope of their ratio over time.
The ratio is calculated as: close / benchmark
A linear regression slope is computed over a user-defined window
The slope represents trend strength: if it’s rising, the current asset is outperforming the benchmark
Plots
Gray Line: The raw ratio between the asset and benchmark
Orange Line: The slope of the ratio (shows momentum)
Background Color :
Green: The asset is significantly stronger than the benchmark
Red: The asset is significantly weaker than the benchmark
No color: No clear trend
Settings
Slope Window Length: Number of candles used in the regression (default = 10)
Slope Threshold: Sensitivity of trend detection. Smaller values detect weaker trends.
Example Use Cases
Style Rotation Strategy: Use the slope to determine whether "Growth" or "Value" style is leading.
Pair Trading / Relative Performance: Track which asset is leading in a pair (e.g., BTC vs ETH).
Factor Timing: Serve as a timing model to allocate between different sectors or factors.
Happy trading!
[blackcat] L3 Dark Horse OscillatorOVERVIEW
The L3 Dark Horse Oscillator is a sophisticated technical indicator meticulously crafted to offer traders deep insights into market momentum. By leveraging advanced calculations involving Relative Strength Value (RSV) and proprietary oscillatory techniques, this script provides clear and actionable signals for identifying potential buying and selling opportunities. Its distinctive feature—a vibrant gradient color scheme—enhances readability and makes it easier to visualize trends and reversals on the chart 📈↗️.
FEATURES
Advanced Calculation Methods: Utilizes complex algorithms to compute the Relative Strength Value (RSV) over specific periods, providing a nuanced view of price movements.
Default Period: 27 bars for initial RSV calculation.
Additional Period: 36 bars for extended RSV analysis.
Dual-Oscillator Components:
Component A: Derived using multiple layers of Simple Moving Averages (SMAs) applied to the RSV, offering a smoothed representation of short-term momentum.
Component B: Employs a unique averaging method tailored to capture medium-term trends effectively.
Dynamic Gradient Color Scheme: Enhances visualization through a spectrum of colors that change dynamically based on the calculated values, making trend identification intuitive and engaging 🌈.
Customizable Horizontal Reference Lines: Key levels are marked at 0, 10, 50, and 90 to serve as benchmarks for assessing the oscillator's readings, helping traders make informed decisions quickly.
Comprehensive Visual Representation: Combines the strengths of both components into a single, gradient-colored candlestick plot, providing a holistic view of market sentiment and momentum shifts 📊.
HOW TO USE
Adding the Indicator: Start by adding the L3 Dark Horse Oscillator to your TradingView chart via the indicators menu. This will overlay the necessary plots directly onto your price chart.
Interpreting the Components: Familiarize yourself with the two primary components represented by yellow and fuchsia lines. These lines indicate the underlying momentum derived from the RSV calculations.
Monitoring Momentum Shifts: Pay close attention to the gradient-colored candlesticks, which reflect the combined strength of both components. Notice how these candles transition through various shades, signaling changes in market dynamics.
Utilizing Reference Levels: Leverage the horizontal lines at 0, 10, 50, and 90 as critical thresholds. For instance, values above 50 might suggest bullish conditions, while those below could hint at bearish tendencies.
Combining with Other Tools: To enhance reliability, integrate this indicator with complementary technical analyses such as moving averages, volume profiles, or other oscillators like RSI or MACD.
LIMITATIONS
Market Volatility: In extremely volatile or sideways-trending markets, the indicator might produce false signals due to erratic price movements. Always cross-reference with broader market contexts.
Testing Required: Before deploying the indicator in real-time trading, conduct thorough backtesting across diverse assets and timeframes to understand its performance characteristics fully.
Asset-Specific Performance: The efficacy of the L3 Dark Horse Oscillator can differ significantly across various financial instruments and market conditions. Tailor your strategies accordingly.
NOTES
Historical Data: Ensure ample historical data availability to facilitate precise calculations and avoid inaccuracies stemming from insufficient data points.
Parameter Adjustments: Experiment with adjusting the default periods (27 and 36 bars) if you find them unsuitable for your specific trading style or market conditions.
Visual Customization: Modify the appearance settings, including line styles and gradient colors, to better suit personal preferences without compromising functionality.
Risk Management: While the indicator offers valuable insights, always adhere to robust risk management practices to safeguard against unexpected market fluctuations.
EXAMPLE STRATEGIES
Trend Following: Use the oscillator to confirm existing trends. When Component A crosses above Component B, consider entering long positions; conversely, look for short entries during downward crossovers.
Mean Reversion: Identify extreme readings near the upper (90) or lower (10) bands where prices might revert to mean levels, presenting potential reversal opportunities.
Divergence Analysis: Compare the oscillator's behavior with price action to spot divergences, which often precede trend reversals. Bullish divergence occurs when prices make lower lows but the oscillator shows higher lows, suggesting upward momentum.
RSI and CCICombined RSI and CCI Indicator for MetaTrader
The Combined RSI and CCI Indicator is a powerful hybrid momentum oscillator designed to merge the strengths of two popular indicators—the Relative Strength Index (RSI) and the Commodity Channel Index (CCI)—into a single, visually intuitive chart window. This tool enhances traders’ ability to identify overbought and oversold conditions, divergences, trend strength, and potential reversal zones with improved precision.
Purpose
By integrating RSI and CCI, this indicator helps filter out false signals that often occur when using each tool independently. It is especially useful for swing trading, trend confirmation, and spotting high-probability entry/exit zones. This dual-oscillator approach combines RSI’s relative momentum insights with CCI’s deviation-based analysis to produce a more reliable signal structure.
Key Features
Dual Oscillator Display: Plots both RSI and CCI on the same subwindow for easy comparison and correlation analysis.
Customizable Parameters:
RSI Period and Level (default: 14)
CCI Period and Typical Price Type (default: 20, TP)
Overbought/Oversold Levels for both indicators
Color-Coded Zones:
Background highlights when both RSI and CCI enter overbought/oversold territory, signaling high potential reversal zones.
Combined Signal Logic (Optional Feature):
Buy Signal: RSI < 30 and CCI < -100
Sell Signal: RSI > 70 and CCI > 100
These can be visualized as arrows or plotted as signal markers.
Trend Filter Overlay (Optional):
Can be combined with a moving average or price action filter to confirm trend direction before accepting signals.
Divergence Detection (Advanced Option):
Optional plotting of bullish or bearish divergence where both indicators diverge from price action.
Multi-Timeframe Compatibility:
Allows the use of higher timeframe RSI/CCI values to confirm signals on lower timeframes.
Benefits
Improved Signal Accuracy: Using both RSI and CCI together helps avoid false breakouts and whipsaws.
More Informed Decision-Making: Correlating momentum (RSI) with deviation (CCI) provides a well-rounded picture of market behavior.
Efficient Charting: Saves screen space and cognitive load by combining two indicators into one clean panel.
Scalable Strategy Integration: Can be used in discretionary trading or coded into automated strategies/alerts.
Use Case Example
In a ranging market, the indicator highlights zones where both RSI and CCI are oversold, alerting traders to potential bounce opportunities.
In trending markets, it confirms trend strength when RSI and CCI are both aligned with trend direction.
When RSI is diverging from price but CCI isn’t, it can be a clue of weakening momentum, helping traders scale out or avoid traps.
This combined indicator offers a versatile, high-performance toolset for traders looking to elevate their technical analysis by leveraging multiple momentum perspectives simultaneously.
Trend Strength MeterThe Trend Strength Meter (TSM) is a powerful and versatile indicator designed to help traders identify market trends, measure their strength, and detect potential reversals with ease. This indicator combines the power of moving averages, divergence detection, and a clean, customizable dashboard to provide actionable insights for traders of all levels.
How It Works
Trend Strength Calculation:
1. The TSM calculates the trend strength using the difference between two Exponential Moving Averages (EMAs): a fast EMA (default: 20) and a slow EMA (default: 50).
2. The difference is expressed as a percentage of the slow EMA, providing a clear measure of the trend's strength and direction.
Histogram Visualization:
1. A color-coded histogram visually represents the trend strength:
Green: Bullish trend
Red: Bearish trend
Gray: Neutral or no significant trend
2. A smoothed trend strength line (SMA of the trend strength) is also plotted for better clarity.
Divergence Detection:
1. The indicator detects bullish and bearish divergences using the RSI (Relative Strength Index) and price action.
2. Bullish Divergence: Price makes a lower low, but RSI makes a higher low, signaling potential upward momentum.
3. Bearish Divergence: Price makes a higher high, but RSI makes a lower high, signaling potential downward momentum.
=> Divergences are marked with arrows on the chart:
Green Arrow: Bullish divergence
Red Arrow: Bearish divergence
Dashboard:
1. A clean and informative dashboard displays key information:
Trend Strength Value: The current strength of the trend
Trend Direction: Bullish, Bearish, or Neutral
Last Signal: Buy, Sell, or None (based on divergence signals)
The dashboard is fully customizable and can be positioned anywhere on the chart (e.g., top-right, bottom-left, center, etc.).
Key Features
1. Trend Strength Measurement: Quickly identify the strength and direction of the trend.
2. Divergence Detection: Spot potential reversals before they occur with bullish and bearish divergence signals.
3. Customizable Dashboard: Move the dashboard to your preferred location on the chart for better visibility.
4. User-Friendly Design: Clean visuals and intuitive color coding make it easy to interpret market conditions.
5. Actionable Signals: Provides clear Buy/Sell signals based on divergence, helping traders make informed decisions.
How to Use
1. Trend Confirmation:
Use the histogram and trend strength value to confirm the current market trend.
Green bars indicate a bullish trend, while red bars indicate a bearish trend.
2. Divergence Signals:
Look for divergence arrows (green for bullish, red for bearish) to anticipate potential reversals.
Combine divergence signals with other technical analysis tools for higher accuracy.
3. Dashboard Insights:
Monitor the dashboard for real-time updates on trend strength, direction, and the latest signal.
Use the "Last Signal" (Buy/Sell) to validate your trading decisions.
4. Custom Settings:
Adjust the EMA lengths and divergence lookback period to suit your trading style and timeframe.
Position the dashboard anywhere on the chart for convenience.
Best Practices
1. Use the TSM in conjunction with other indicators or price action analysis for confirmation.
2. Test the indicator on different timeframes to find the one that works best for your strategy.
3. Always practice proper risk management when trading.
Disclaimer
This indicator is a tool to assist in technical analysis and should not be used as a standalone trading strategy. Past performance is not indicative of future results. Always conduct your own research and consult with a financial advisor before making trading decisions.
alphaJohnny Dynamic RSI IndicatorAlphaJohnny Dynamic RSI Indicator (Dyn RSI)
The Dynamic RSI Indicator (Dyn RSI) is a custom Pine Script tool designed for TradingView that aggregates Relative Strength Index (RSI) signals from multiple timeframes to provide a comprehensive view of market momentum. It combines RSI data from Weekly, Daily, 4-hour, 1-hour, and 30-minute intervals, offering traders a flexible and customizable way to analyze trends across different periods.
Key Features:
Multi-Timeframe RSI Aggregation: Combines RSI signals from user-selected timeframes for a holistic momentum assessment.
Dynamic or Equal Weighting: Choose between correlation-based dynamic weights (adjusting based on each timeframe’s correlation with price changes) or equal weights for simplicity.
Smoothed Momentum Line: A visually intuitive line that reflects the strength of the aggregate signal, smoothed for clarity.
Color-Coded Signal Strength:
Dark Green: Strong buy signal
Light Green: Weak buy signal
Yellow: Neutral
Light Red: Weak sell signal
Dark Red: Strong sell signal
Visual Markers: Large green triangles at the bottom for strong buy signals and red triangles at the top for strong sell signals.
How to Use:
Apply to Chart: Add the indicator to your TradingView chart (it will appear in a separate pane).
Customize Settings: Adjust inputs like RSI period, signal thresholds, included timeframes, weighting method, and smoothing period to fit your trading style.
Interpret Signals:
Momentum Line: Watch for color changes to gauge market conditions.
Triangles: Green at the bottom for strong buy opportunities, red at the top for strong sell opportunities.
Notes:
The indicator is designed for a separate pane (overlay=false), with triangles positioned relative to the pane’s range.
Fine-tune thresholds and weights based on your strategy and the asset being analyzed.
The source code is open for modification to suit your needs.
This indicator is ideal for traders seeking a multi-timeframe perspective on RSI to identify potential trend reversals and momentum shifts.
Mswing HommaThe Mswing is a momentum oscillator that calculates the rate of price change over 20 and 50 periods (days/weeks). Apart from quantifying momentum, it can be used for assessing relative strength, sectoral rotation & entry/exit signals.
Quantifying Momentum Strength
The Mswing's relationship with its EMA (e.g., 5-period or 9-period) is used for momentum analysis:
• M Swing >0 and Above EMA: Momentum is positive and accelerating (ideal for entries).
• M Swing >0 and Below EMA: Momentum is positive but decelerating (caution).
• M Swing <0 and Above EMA: Momentum is negative but improving (watch for reversals).
• M Swing <0 and Below EMA: Momentum is negative and worsening (exit or avoid).
Relative Strength Scanning (M Score)
Sort stocks by their M Swing using TradingView’s Pine scanner.
Compare the Mswing scores of indices/sectors to allocate capital to stronger groups (e.g., renewables vs. traditional energy).
Stocks with strong Mswing scores tend to outperform during bullish phases, while weak ones collapse faster in downtrends.
Entry and Exit Signals
Entry: Buy when Mswing crosses above 0 + price breaks key moving averages (50-day SMA). Use Mswing >0 to confirm valid breakouts. Buy dips when Mswing holds above EMA during retracements.
Exit: Mswing can be used for exiting a stock in 2 ways:
• Sell in Strength: Mswing >4 (overbought).
• Sell in Weakness: Mswing <0 + price below 50-day SMA.
Multi-Timeframe Analysis
• Daily: For swing trades.
• Weekly: For trend confirmation.
• Monthly: For long-term portfolio adjustments.
Precious Metals & GSR (Zeiierman)█ Overview
The Precious Metals & GSR (Zeiierman) is designed to provide traders and investors with a comprehensive view of the Gold-Silver Ratio (GSR) and other precious metal relationships. This tool helps evaluate the relative strength between different metals by analyzing their price ratios over historical periods, using quantile-based analysis and trend interpretation tables to highlight key insights.
The Gold-Silver Ratio (GSR) is a widely utilized metric in precious metals trading, representing the number of silver ounces required to purchase one ounce of gold. Historically, this ratio has fluctuated, providing traders with insights into the relative value of these two metals. By analyzing the GSR, traders can identify potential trading opportunities based on historical patterns and market dynamics.
By integrating customizable percentile bands, gradient coloring for performance visualization, and dynamic ratio analysis, this indicator assists in understanding how one metal is performing relative to another, making it useful for trend tracking, risk management, and portfolio allocation.
█ How It Works
The Precious Metals & GSR Indicator operates by fetching the latest prices of the selected precious metals in the user's chosen currency. It then calculates the ratio between two selected metals (Metal 1 and Metal 2) and analyzes this ratio over a specified period. By computing quantile bands and high/low bands, the indicator provides insights into the historical performance and current standing of the ratio.
⚪ Ratio Calculation
The core of this indicator is the metal ratio, calculated by dividing the price of Metal 1 by Metal 2.
A rising ratio means Metal 1 is outperforming Metal 2.
A falling ratio means Metal 2 is outperforming Metal 1.
The indicator automatically retrieves live market prices of Gold, Silver, Platinum, and Palladium to compute the ratio.
⚪ Quantile Ratio Bands
The indicator calculates the highest (max) and lowest (min) ratio levels over a user-defined period.
It also plots quantile bands at the 10th, 25th, 50th (median), 75th, and 90th percentiles, providing deeper statistical insights into how extreme or average the current ratio is.
The median (Q50) acts as a reference level, showing whether the ratio is above or below its historical midpoint.
⚪ Interpretation Table
The Ratio Interpretation Table provides a text-based summary of the ratio’s strength.
It detects whether Metal 1 is at a historical high, low, or within common ranges.
This helps traders and investors make informed decisions on whether the ratio is overextended, mean-reverting, or trending.
⚪ Precious Metals Table
Displays live market prices for Gold, Silver, Platinum, and Palladium.
Prices are shown in different units (oz, kg, grams, and troy ounces) based on user preferences.
A color-coded system highlights price changes, making it easier to track market movements.
⚪ Physical Holding Calculator
Users can enter their precious metal holdings to estimate their current value.
The system adjusts calculations based on weight, purity (24K, 22K, etc.), and unit of measurement.
The holding value is displayed in the selected currency (USD, EUR, GBP, etc.).
█ How to Use
⚪ Trend Identification
If the ratio is increasing, Metal 1 is gaining strength relative to Metal 2 → Possible Long Position on Metal 1 / Short on Metal 2
If the ratio is decreasing, Metal 2 is gaining strength relative to Metal 1 → Possible Short Position on Metal 1 / Long on Metal 2
⚪ Mean Reversion Strategy
When the ratio reaches the 90th percentile, Metal 1 is historically overextended (expensive) compared to Metal 2.
Traders may look to sell Metal 1 and buy Metal 2, expecting the ratio to decline back toward its historical average.
Example (Gold/Silver Ratio): If the GSR is above the 90th percentile, gold is very expensive relative to silver, suggesting a potential buying opportunity in silver and/or a selling opportunity in gold.
When the ratio reaches the 10th percentile, Metal 1 is historically undervalued (cheap) compared to Metal 2.
Traders may look to buy Metal 1 and sell Metal 2, expecting the ratio to rise back toward its historical average.
Example (Gold/Silver Ratio): If the GSR is below the 10th percentile, gold is very cheap relative to silver, suggesting a potential buying opportunity in gold and/or a selling opportunity in silver.
⚪ Common Strategy Based on GSR Insights
A common approach involves monitoring the ratio for extreme values based on historical data. When the ratio reaches historically high levels, it suggests that gold is expensive relative to silver, potentially indicating a buying opportunity for silver and/or a selling opportunity for gold. Conversely, when the ratio is at historically low levels, silver is expensive relative to gold, suggesting a potential buying opportunity for gold and/or selling opportunity for silver. This mean-reversion strategy relies on the tendency of the GSR to return to its historical average over time.
⚪ Hedging & Portfolio Diversification
If Gold is strongly outperforming Silver, investors may shift allocations to balance risk.
If Silver is rapidly gaining on Gold, it may indicate increased industrial demand or speculative interest.
⚪ Inflation & Economic Cycles
A rising Gold-Silver ratio often correlates with economic downturns and increased risk aversion.
A falling Gold-Silver ratio may signal stronger economic growth and higher inflation expectations.
█ Settings
Precious Metals Table
Select which metals to display (Gold, Silver, Platinum, Palladium)
Choose measurement units (oz, kg, grams, troy ounces)
Ratio Analysis
Select Metal 1 & Metal 2 for ratio calculation
Set historical length for quantile calculations
Interpretation Table
Enable automated insights based on ratio levels
Physical Holdings Calculator
Enter metal weight, purity, and unit
Select calculation currency
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Bollinger Bands + RSI [Uncle Sam Trading]The Bollinger Bands + RSI indicator combines two popular technical analysis tools, Bollinger Bands (BB) and the Relative Strength Index (RSI), into a unified framework designed to assess both market volatility and momentum. This indicator provides both visual signals on the chart, and allows you to set alerts. It is intended to help traders identify potential overbought/oversold conditions, trend reversals, and to refine trade entry and exit points.
Key Features:
Bollinger Bands: The indicator plots Bollinger Bands, which consist of a basis line (typically a 20-period Simple Moving Average), an upper band (basis + 2 standard deviations), and a lower band (basis - 2 standard deviations). The bands dynamically adjust to market volatility, widening during periods of increased volatility and contracting during periods of decreased volatility.
Relative Strength Index (RSI): The RSI, a momentum oscillator, is plotted in a separate pane below the price chart. It measures the magnitude of recent price changes to evaluate overbought or oversold conditions in the price of a stock or other asset. Traditional interpretation uses 70 and 30 as overbought and oversold levels, respectively.
Overbought/Oversold Zones Highlighting: This indicator uniquely highlights overbought and oversold zones directly on the price chart based on the RSI values. When the RSI is above the overbought level (default 70), a red-shaded area is displayed. When the RSI is below the oversold level (default 30), a green-shaded area is displayed. These visual cues enhance the identification of potential trend reversals.
Buy and Sell Signals: The indicator generates buy signals when the price crosses above the lower Bollinger Band and the RSI is below the oversold level (if the RSI filter is enabled). Sell signals are generated when the price crosses below the upper Bollinger Band and the RSI is above the overbought level (if the RSI filter is enabled). These signals are plotted as green upward-pointing triangles (buy) and red downward-pointing triangles (sell) on the chart.
Customizable Parameters: Users can adjust various settings, including:
Bollinger Bands Length: The number of periods used to calculate the moving average and standard deviation.
Bollinger Bands Standard Deviation: The multiplier used to determine the distance of the upper and lower bands from the basis.
RSI Length: The number of periods used to calculate the RSI.
RSI Overbought/Oversold Levels: The threshold values that define overbought and oversold conditions for the RSI.
Use RSI Filter for Signals: Enable/disable the RSI filter for buy and sell signals.
Colors: The colors of the Bollinger Bands, RSI, overbought/oversold levels, and zone highlights can be customized to suit user preferences.
Alerts: The indicator supports customizable alerts for various conditions, including:
Buy Signal: Triggered when a buy signal is generated.
Sell Signal: Triggered when a sell signal is generated.
Price Crossed Upper BB: Triggered when the price crosses above the upper Bollinger Band.
Price Crossed Lower BB: Triggered when the price crosses below the lower Bollinger Band.
RSI Overbought: Triggered when the RSI crosses above the overbought level.
RSI Oversold: Triggered when the RSI crosses below the oversold level.
How to Use:
The Bollinger Bands + RSI indicator can be used in various ways, including:
Identifying Potential Trend Reversals: Price crosses above the lower band coupled with an oversold RSI (and highlighted zone) may signal a bullish reversal. Conversely, a price cross below the upper band with an overbought RSI (and highlighted zone) may indicate a bearish reversal.
Confirming Trend Strength: In an uptrend, the price may "ride" the upper band, while in a downtrend, it may "ride" the lower band.
Exit Signals: Crossing the opposite band while in a trade, particularly with confirming RSI signals, is often used to identify potential exit points.
Combined with Other Analysis: This indicator works well in conjunction with other technical analysis tools, such as trend lines, support/resistance levels, chart patterns, and moving average-based strategies.
Disclaimer:
This indicator is for educational and informational purposes only and should not be considered as financial advice. Trading involves risk, and past performance is not indicative of future results. Always conduct thorough research and consider your risk tolerance before making any trading decisions.
Futuristic Indicator v3 - Enhanced Glow & Strength MetersTo ensure candles are display by script go to trading view settings and uncheck default Candle, Body and Wick to prevent them from plotting over your modified candles.
Futuristic Indicator v3 - Enhanced Glow & Strength Meters: Detailed Breakdown
This Modern styled Pine Script indicator is designed to enhance technical analysis by providing a visually striking OLED-style dashboard with multiple market insights. It integrates trend detection, momentum analysis, volatility tracking, and strength meters into a single, streamlined interface for traders.
1️⃣ Customizable Features for Flexibility
The indicator offers multiple user-configurable settings, allowing traders to adjust the display based on their trading strategy and preferences. Users can toggle elements such as strength meters, volatility indicators, trend arrows, moving averages, and buy/sell alerts. Additionally, background and candle colors can be customized for better readability.
🔹 Why is this useful?
Traders can customize their charts to focus on the data they care about.
Reduces chart clutter by allowing users to toggle features on or off.
2️⃣ Trend Detection Using EMAs
This indicator detects market trends using two Exponential Moving Averages (EMA):
A "Fast" EMA (shorter period) for quick trend shifts.
A "Slow" EMA (longer period) to confirm trends.
Comparison of the two EMAs determines if the trend is bullish (uptrend) or bearish (downtrend).
The indicator colors the trend lines accordingly and adds a trend arrow 📈📉 for quick visual cues.
🔹 Why is this useful?
EMA crossovers are widely used to identify trend reversals.
Provides clear visual cues for traders to confirm entry & exit points.
3️⃣ RSI-Based Momentum Analysis
The indicator integrates the Relative Strength Index (RSI) to gauge market momentum. The momentum value changes color dynamically based on whether it's in bullish (>50) or bearish (<50) territory.
🔹 Why is this useful?
RSI helps identify overbought and oversold conditions.
Detects trend strength by measuring the speed of price movements.
4️⃣ Bullish & Bearish Strength Meters
The indicator quantifies bullish and bearish market strength based on RSI and converts it into a percentage-based meter:
Bullish Strength (Long Strength)
Bearish Strength (Short Strength)
Strength meters are displayed using OLED-styled bars, dynamically changing in real-time.
🔹 Why is this useful?
Allows traders to visually gauge market sentiment at a glance.
Helps confirm if a trend has strong momentum or is losing strength.
5️⃣ Market Volatility Indicator (ATR-Based)
The indicator includes a volatility tracker using the Average True Range (ATR):
ATR is scaled up to provide easier readability.
Higher ATR values indicate higher market volatility.
🔹 Why is this useful?
Helps traders identify potential breakout or consolidation phases.
Allows better risk management by understanding price fluctuations.
6️⃣ Trend Strength Calculation
The indicator calculates trend strength based on the difference between the EMAs:
A higher trend strength value suggests a stronger directional trend.
Displayed as a percentage for better clarity.
🔹 Why is this useful?
Helps traders differentiate between strong and weak trends.
Reduces the likelihood of entering weak or choppy markets.
7️⃣ OLED-Style Dashboard for Market Data
A futuristic OLED-styled table is used to display critical market data in a visually appealing way:
Trend direction (Bullish/Bearish with an arrow 📈📉).
Current price.
Momentum value.
Strength meters (Bullish/Bearish).
Trend strength percentage.
Volatility Meter
The dashboard uses high-contrast colors and neon glow effects, making it easier to read against dark backgrounds.
🔹 Why is this useful?
Provides a centralized view of key trading metrics.
Eliminates the need to manually calculate trend strength.
8️⃣ Modern Style Neon Glow Effects
To enhance visibility, the indicator applies glowing effects to:
Moving Averages (EMAs): Highlighted with layered glow effects.
Candlesticks: Borders and wicks dynamically change color based on trend direction.
🔹 Why is this useful?
Improves readability in low-contrast or dark-mode charts.
Helps traders spot trends faster without reading numerical data.
9️⃣ Automated Buy & Sell Alerts
The script triggers alerts when momentum crosses key levels:
Above 55 → Potential Long Setup
Below 45 → Potential Short Setup.
🔹 Why is this useful?
Alerts help traders react quickly without constantly monitoring the chart.
Reduces the risk of missing critical trade opportunities.
🔹 Final Summary: Why is This Indicator Useful?
This futuristic cyberpunk-styled trading tool enhances traditional market analysis by combining technical indicators with high-visibility visuals.
🔹 Key Benefits:
✅ Customizable Display – Toggle elements based on trading needs.
✅ Trend Detection – EMAs highlight uptrends & downtrends.
✅ Momentum Tracking – RSI-based momentum gauge identifies strong moves.
✅ Strength Meters – Bullish/Bearish power is clearly visualized.
✅ Volatility Insights – ATR-based metric highlights market turbulence.
✅ Trend Strength Analysis – Quantifies trend intensity.
✅ Dashboard – Provides a centralized, easy-to-read data panel.
✅ Cyberpunk Neon Glow – Enhances clarity with stylish aesthetics.
✅ Real-Time Alerts – Helps traders react to key opportunities.
This indicator is designed to be both functional and visually appealing, making market analysis more intuitive and efficient. 🚀
XAUUSD Multi-Timeframe Trend AnalyzerOverview
The "XAUUSD Multi-Timeframe Trend Analyzer" is an advanced script designed to provide a comprehensive analysis of the XAUUSD (Gold/US Dollar) trend across multiple timeframes simultaneously. By combining several key technical indicators, this tool helps traders quickly assess the market direction and trend strength for M15, M30, H1, H4, and D1 timeframes.
Multi-Timeframe Analysis: Displays the trend direction and strength across M15, M30, H1, H4, and D1 timeframes, allowing for a complete overview in a single glance.
Comprehensive Indicator Blend: Utilizes six popular technical indicators to determine the trend—Moving Averages, RSI, MACD, Bollinger Bands, DMI, and Parabolic SAR.
Trend Strength Scoring: Provides a numerical trend strength score (from -6 to 6) based on the alignment of the indicators, with positive values indicating uptrends and negative values for downtrends.
Visual Table Display: Displays results in a color-coded table (green for uptrend, red for downtrend, yellow for neutral) with a strength score for each timeframe, helping traders quickly assess market conditions.
How It Works
This script calculates the overall trend and its strength for each selected timeframe by analyzing six widely-used technical indicators:
Moving Averages (MA): The script uses a Fast and a Slow Moving Average. When the Fast MA crosses above the Slow MA, it indicates an uptrend. When the Fast MA crosses below, it signals a downtrend.
Relative Strength Index (RSI): The RSI is used to assess momentum. An RSI value above 50 suggests bullish momentum, while a value below 50 suggests bearish momentum.
Moving Average Convergence Divergence (MACD): MACD measures momentum and trend direction. When the MACD line crosses above the signal line, it signals bullish momentum; when it crosses below, it signals bearish momentum.
Bollinger Bands: These measure price volatility. When the price is above the middle Bollinger Band, the script considers the trend to be bullish, and when it's below, bearish.
Directional Movement Index (DMI): The DMI compares positive directional movement (DI+) and negative directional movement (DI-). A stronger DI+ over DI- signals an uptrend and vice versa.
Parabolic SAR: This indicator is used for determining potential trend reversals and setting stop-loss levels. If the price is above the Parabolic SAR, it indicates an uptrend, and if below, a downtrend.
Trend Strength Calculation
The script calculates a trend strength score for each timeframe:
Each indicator adds or subtracts 1 to the score based on whether it aligns with an uptrend or a downtrend.
A score of 6 indicates a Strong Uptrend, with all indicators aligned bullishly.
A score of -6 indicates a Strong Downtrend, with all indicators aligned bearishly.
Intermediate scores (e.g., 2 or -2) indicate Weak Uptrend or Weak Downtrend, suggesting that not all indicators are in agreement.
A score between 1 and -1 indicates a Neutral trend, suggesting uncertainty in the market.
How to Use
Assess Trend Direction and Strength: The table provides an easy-to-read summary of the trend and its strength on different timeframes. Look for timeframes where the strength is high (either 6 for a strong uptrend or -6 for a strong downtrend) to confirm the market’s overall direction.
Use in Conjunction with Other Strategies: This indicator is designed to provide a comprehensive view of the market. Traders should combine it with other strategies, such as price action analysis or candlestick patterns, to further confirm their trades.
Trend Reversal or Continuation: A weak trend (e.g., a strength of 2 or -2) could signal a possible reversal or a trend that has lost momentum. Strong trends (with a strength of 6 or -6) indicate higher confidence in trend continuation.
Multiple Timeframe Confirmation: Look for alignment across multiple timeframes to confirm the strength and direction of the trend before entering trades. For example, if M15, M30, and H1 are all showing a strong uptrend, it suggests a higher probability of the trend continuing.
Customization Options
- Adjustable Indicators: Users can modify the length and parameters of the Moving Averages, RSI, MACD, Bollinger Bands, DMI, and Parabolic SAR to suit their trading style.
- Flexible Timeframes: You can toggle between different timeframes (M15, M30, H1, H4, D1) to focus on the intervals most relevant to your strategy.
Ideal For
- Traders looking for a detailed, multi-timeframe trend analysis tool for XAUUSD.
- Traders who rely on trend-following strategies and need confirmation across multiple timeframes.
- Those who prefer a multi-indicator approach to avoid false signals and improve the accuracy of their trades.
Disclaimer
This indicator is for informational and educational purposes only. It is recommended to combine this with proper risk management strategies and your own analysis. Past performance does not guarantee future results. Always perform your own due diligence before making trading decisions.
TASC 2024.11 Ultimate Strength Index█ OVERVIEW
This script implements the Ultimate Strength Index (USI) indicator, introduced by John Ehlers in his article titled "Ultimate Strength Index (USI)" from the November 2024 edition of TASC's Traders' Tips . The USI is a modified version of Wilder's original Relative Strength Index (RSI) that incorporates Ehlers' UltimateSmoother lowpass filter to produce an output with significantly reduced lag.
█ CONCEPTS
Many technical indicators, including the RSI, lag due to their heavy reliance on historical data. John Ehlers reformulated the RSI to substantially reduce lag by applying his UltimateSmoother filter to upward movements ( strength up - SU ) and downward movements ( strength down - SD ) in the time series, replacing the standard process of smoothing changes with rolling moving averages (RMAs). Ehlers' recent works, covered in our recent script publications, have shown that the UltimateSmoother is an effective alternative to other classic averages, offering notably less lag in its response.
Ehlers also modified the RSI formula to produce an index that ranges from -1 to +1 instead of 0 to 100. As a result, the USI indicates bullish conditions when its value moves above 0 and bearish conditions when it falls below 0.
The USI retains many of the strengths of the traditional RSI while offering the advantage of reduced lag. It generally uses a larger lookback window than the conventional RSI to achieve similar behavior, making it suitable for trend trading with longer data lengths. When applied with shorter lengths, the USI's peaks and valleys tend to align closely with significant turning points in the time series, making it a potentially helpful tool for timing swing trades.
█ CALCULATIONS
The first step in the USI's calculation is determining each bar's strength up (SU) and strength down (SD) values. If the current bar's close exceeds the previous bar's, the calculation assigns the difference to SU. Otherwise, SU is zero. Likewise, if the current bar's close is below the previous bar's, it assigns the difference to SD. Otherwise, SD is zero.
Next, instead of the RSI's typical smoothing process, the USI's calculation applies the UltimateSmoother to the short-term average SU and SD values, reducing high-frequency chop in the series with low lag.
Finally, this formula determines the USI value:
USI = ( Ult (SU) − Ult (SD)) / ( Ult (SU) + Ult (SD)),
where Ult (SU) and Ult (SD) are the smoothed average strength up and strength down values.
