Adaptive ATR Stop Loss FinderPlots dynamic ATR-based stop levels with an automatically adjusting multiplier based on volatility. High/low stops and a live table display ATR×multiplier, helping swing and crypto traders protect profits and trail stops efficiently. Adjustable ATR length, smoothing, and colors.
波動率
Fibo & Gann Advanced Auto[CongTrader]🔍 Description:
"Fibo & Gann Advanced Auto by CongTrader" is a smart automatic indicator that combines Fibonacci Retracement & Extension levels with Gann Boxes and Fan lines, helping traders identify key support/resistance zones and potential turning points in the market.
This tool automatically detects recent swing highs/lows using pivots and overlays:
📏 Fibonacci Retracement & Extension (0.236 to 1.618)
🟪 Gann Box between 2 latest pivots
📐 Gann Fan Lines (1x1, 2x1, etc.)
🟢 Optional filtered Buy/Sell signals based on wave size and RSI
Designed for discretionary and technical traders who want a visual confirmation of price geometry and market structure.
📘 How to Use:
Apply to any chart & timeframe.
Adjust pivot sensitivity via “Pivot Length” input.
Look for confluence between Fib retracement/extension and Gann box edges for trade entries.
Gann fan lines help visualize trend angles or speed.
Combine with your own strategy for better confirmation (e.g., volume, candlestick pattern).
💡 Tip: Use in higher timeframes (H1, H4, D1) for cleaner and more reliable pivots.
🙏 Thanks:
Created with love and passion for the trading community by CongTrader.
If you find it helpful, please give a like or comment. Feedback is always appreciated!
⚠️ Disclaimer:
This script is for educational and informational purposes only.
It does not constitute financial advice and should not be used as a sole basis for trading decisions.
Always use proper risk management and perform your own analysis before entering any trade.
Trading involves risk, and past performance is not indicative of future results..#fibonacci #gann #gannbox #gannfan #elliottwave #marketstructure
#priceaction #autopivot #congtrader #tradingviewindicator
#technicalanalysis #tradingtools #forextrading #cryptoindicator
#tradingstrategy #tradingsetup #smartmoney #supportresistance
Traders Reality Rate Spike Monitor 0.1 betaTraders Reality Rate Spike Monitor
## **Early Warning System for Interest Rate-Driven Market Crashes**
Based on critical market analysis revealing the dangerous correlation between interest rate spikes and major market selloffs, this indicator provides **three-tier alerts** for US 10-Year Treasury yield acceleration.
### **📊 Key Market Intelligence:**
**Historical Precedent:** The 2018 market crash occurred when unrealized bank losses hit $256 billion with interest rates at just 2.5%. **Current unrealized losses have reached $560 billion** - more than double the 2018 levels - while rates sit at 4.5%.
**Critical Vulnerabilities:**
- **$559 billion in tech sector debt** maturing through 2025
- **65% of investment-grade debt** rated BBB (vulnerable to adverse conditions)
- **$9.5 trillion in total debt** requiring refinancing
- Every 1% rate increase costs the economy **$360 billion annually**
### **🚨 Alert System:**
**📊 WATCH (20+ basis points/3 days):** Early positioning signal
**⚠️ WARNING (30+ basis points/3 days):** Prepare for volatility
**🚨 CRITICAL (40+ basis points/3 days):** Historical crash threshold
### **💡 Why This Matters:**
Interest rate spikes historically trigger major market corrections:
- **2018:** 70 basis points spike → 20% S&P 500 crash
- **2025:** Similar pattern led to massive selloffs
- **Current risk:** 2x higher unrealized losses than 2018
### **⚡ Features:**
✅ **Zero chart clutter** - invisible until alerts trigger
✅ **Dynamic calculation** - automatically adjusts to current yield levels
✅ **Multi-timeframe compatibility** - works on any chart timeframe
✅ **Professional alerts** - with actual basis point calculations
### **🎯 Use Case:**
Perfect for traders and investors who understand that **debt refinancing pressure** and **unrealized bank losses** create systemic risks that manifest through interest rate volatility. When rates spike rapidly, leveraged positions unwind and markets crash.
**"Every point costs us $360 billion a year. Think of that."** - This indicator helps you see those critical rate movements before the market does.
---
**Disclaimer:** This indicator is for educational purposes. Past performance does not guarantee future results. Always manage risk appropriately.
---
This description positions your indicator as a **serious professional tool** based on real market analysis rather than just another technical indicator! 🚀
PLAIN VAMSThe PLAIN VAMS (Volatility-Adjusted Momentum Score) is a visual tool designed to help traders identify momentum shifts relative to prevailing volatility conditions. Unlike traditional momentum indicators, VAMS adapts dynamically to price fluctuations by comparing current price levels to volatility-based boundaries derived from customizable moving averages.
Key Features:
- Volatility-Adjusted Zones: Prices are evaluated against upper and lower dynamic boundaries, signaling potential overbought or oversold momentum conditions.
Two Modes:
- PLAIN VAMS (default): Uses a longer lookback period for smoother, trend-following behavior.
- RAW VAMS: A shorter lookback for high-sensitivity, intraday or scalping setups.
Customizable Moving Averages:
Choose from multiple MA types (EMA, SMA, WMA, etc.) to match your strategy preferences.
Visual Clarity:
- Color-coded candles for quick signal recognition.
- Optional background shading for immediate context.
- Boundary lines to define momentum thresholds.
How It Works:
The script calculates a moving average (based on user-selected type and period) and applies an upper and lower multiplier to create dynamic price boundaries. When price closes beyond these bands, it suggests a strong directional momentum move. The indicator is fully customizable to adapt to your trading style and timeframe.
Use Cases:
- Identify potential breakouts or trend continuations.
- Filter entries/exits based on momentum strength.
- Combine with other tools for confirmation in your strategy.
This indicator does not repaint or use future-looking data. It’s designed for discretionary and systematic traders looking for an adaptive way to visualize momentum relative to market volatility.
Seasonality Monte Carlo Forecaster [BackQuant]Seasonality Monte Carlo Forecaster
Plain-English overview
This tool projects a cone of plausible future prices by combining two ideas that traders already use intuitively: seasonality and uncertainty. It watches how your market typically behaves around this calendar date, turns that seasonal tendency into a small daily “drift,” then runs many randomized price paths forward to estimate where price could land tomorrow, next week, or a month from now. The result is a probability cone with a clear expected path, plus optional overlays that show how past years tended to move from this point on the calendar. It is a planning tool, not a crystal ball: the goal is to quantify ranges and odds so you can size, place stops, set targets, and time entries with more realism.
What Monte Carlo is and why quants rely on it
• Definition . Monte Carlo simulation is a way to answer “what might happen next?” when there is randomness in the system. Instead of producing a single forecast, it generates thousands of alternate futures by repeatedly sampling random shocks and adding them to a model of how prices evolve.
• Why it is used . Markets are noisy. A single point forecast hides risk. Monte Carlo gives a distribution of outcomes so you can reason in probabilities: the median path, the 68% band, the 95% band, tail risks, and the chance of hitting a specific level within a horizon.
• Core strengths in quant finance .
– Path-dependent questions : “What is the probability we touch a stop before a target?” “What is the expected drawdown on the way to my objective?”
– Pricing and risk : Useful for path-dependent options, Value-at-Risk (VaR), expected shortfall (CVaR), stress paths, and scenario analysis when closed-form formulas are unrealistic.
– Planning under uncertainty : Portfolio construction and rebalancing rules can be tested against a cloud of plausible futures rather than a single guess.
• Why it fits trading workflows . It turns gut feel like “seasonality is supportive here” into quantitative ranges: “median path suggests +X% with a 68% band of ±Y%; stop at Z has only ~16% odds of being tagged in N days.”
How this indicator builds its probability cone
1) Seasonal pattern discovery
The script builds two day-of-year maps as new data arrives:
• A return map where each calendar day stores an exponentially smoothed average of that day’s log return (yesterday→today). The smoothing (90% old, 10% new) behaves like an EWMA, letting older seasons matter while adapting to new information.
• A volatility map that tracks the typical absolute return for the same calendar day.
It calculates the day-of-year carefully (with leap-year adjustment) and indexes into a 365-slot seasonal array so “March 18” is compared with past March 18ths. This becomes the seasonal bias that gently nudges simulations up or down on each forecast day.
2) Choice of randomness engine
You can pick how the future shocks are generated:
• Daily mode uses a Gaussian draw with the seasonal bias as the mean and a volatility that comes from realized returns, scaled down to avoid over-fitting. It relies on the Box–Muller transform internally to turn two uniform random numbers into one normal shock.
• Weekly mode uses bootstrap sampling from the seasonal return history (resampling actual historical daily drifts and then blending in a fraction of the seasonal bias). Bootstrapping is robust when the empirical distribution has asymmetry or fatter tails than a normal distribution.
Both modes seed their random draws deterministically per path and day, which makes plots reproducible bar-to-bar and avoids flickering bands.
3) Volatility scaling to current conditions
Markets do not always live in average volatility. The engine computes a simple volatility factor from ATR(20)/price and scales the simulated shocks up or down within sensible bounds (clamped between 0.5× and 2.0×). When the current regime is quiet, the cone narrows; when ranges expand, the cone widens. This prevents the classic mistake of projecting calm markets into a storm or vice versa.
4) Many futures, summarized by percentiles
The model generates a matrix of price paths (capped at 100 runs for performance inside TradingView), each path stepping forward for your selected horizon. For each forecast day it sorts the simulated prices and pulls key percentiles:
• 5th and 95th → approximate 95% band (outer cone).
• 16th and 84th → approximate 68% band (inner cone).
• 50th → the median or “expected path.”
These are drawn as polylines so you can immediately see central tendency and dispersion.
5) A historical overlay (optional)
Turn on the overlay to sketch a dotted path of what a purely seasonal projection would look like for the next ~30 days using only the return map, no randomness. This is not a forecast; it is a visual reminder of the seasonal drift you are biasing toward.
Inputs you control and how to think about them
Monte Carlo Simulation
• Price Series for Calculation . The source series, typically close.
• Enable Probability Forecasts . Master switch for simulation and drawing.
• Simulation Iterations . Requested number of paths to run. Internally capped at 100 to protect performance, which is generally enough to estimate the percentiles for a trading chart. If you need ultra-smooth bands, shorten the horizon.
• Forecast Days Ahead . The length of the cone. Longer horizons dilute seasonal signal and widen uncertainty.
• Probability Bands . Draw all bands, just 95%, just 68%, or a custom level (display logic remains 68/95 internally; the custom number is for labeling and color choice).
• Pattern Resolution . Daily leans on day-of-year effects like “turn-of-month” or holiday patterns. Weekly biases toward day-of-week tendencies and bootstraps from history.
• Volatility Scaling . On by default so the cone respects today’s range context.
Plotting & UI
• Probability Cone . Plots the outer and inner percentile envelopes.
• Expected Path . Plots the median line through the cone.
• Historical Overlay . Dotted seasonal-only projection for context.
• Band Transparency/Colors . Customize primary (outer) and secondary (inner) band colors and the mean path color. Use higher transparency for cleaner charts.
What appears on your chart
• A cone starting at the most recent bar, fanning outward. The outer lines are the ~95% band; the inner lines are the ~68% band.
• A median path (default blue) running through the center of the cone.
• An info panel on the final historical bar that summarizes simulation count, forecast days, number of seasonal patterns learned, the current day-of-year, expected percentage return to the median, and the approximate 95% half-range in percent.
• Optional historical seasonal path drawn as dotted segments for the next 30 bars.
How to use it in trading
1) Position sizing and stop logic
The cone translates “volatility plus seasonality” into distances.
• Put stops outside the inner band if you want only ~16% odds of a stop-out due to noise before your thesis can play.
• Size positions so that a test of the inner band is survivable and a test of the outer band is rare but acceptable.
• If your target sits inside the 68% band at your horizon, the payoff is likely modest; outside the 68% but inside the 95% can justify “one-good-push” trades; beyond the 95% band is a low-probability flyer—consider scaling plans or optionality.
2) Entry timing with seasonal bias
When the median path slopes up from this calendar date and the cone is relatively narrow, a pullback toward the lower inner band can be a high-quality entry with a tight invalidation. If the median slopes down, fade rallies toward the upper band or step aside if it clashes with your system.
3) Target selection
Project your time horizon to N bars ahead, then pick targets around the median or the opposite inner band depending on your style. You can also anchor dynamic take-profits to the moving median as new bars arrive.
4) Scenario planning & “what-ifs”
Before events, glance at the cone: if the 95% band already spans a huge range, trade smaller, expect whips, and avoid placing stops at obvious band edges. If the cone is unusually tight, consider breakout tactics and be ready to add if volatility expands beyond the inner band with follow-through.
5) Options and vol tactics
• When the cone is tight : Prefer long gamma structures (debit spreads) only if you expect a regime shift; otherwise premium selling may dominate.
• When the cone is wide : Debit structures benefit from range; credit spreads need wider wings or smaller size. Align with your separate IV metrics.
Reading the probability cone like a pro
• Cone slope = seasonal drift. Upward slope means the calendar has historically favored positive drift from this date, downward slope the opposite.
• Cone width = regime volatility. A widening fan tells you that uncertainty grows fast; a narrow cone says the market typically stays contained.
• Mean vs. price gap . If spot trades well above the median path and the upper band, mean-reversion risk is high. If spot presses the lower inner band in an up-sloping cone, you are in the “buy fear” zone.
• Touches and pierces . Touching the inner band is common noise; piercing it with momentum signals potential regime change; the outer band should be rare and often brings snap-backs unless there is a structural catalyst.
Methodological notes (what the code actually does)
• Log returns are used for additivity and better statistical behavior: sim_ret is applied via exp(sim_ret) to evolve price.
• Seasonal arrays are updated online with EWMA (90/10) so the model keeps learning as each bar arrives.
• Leap years are handled; indexing still normalizes into a 365-slot map so the seasonal pattern remains stable.
• Gaussian engine (Daily mode) centers shocks on the seasonal bias with a conservative standard deviation.
• Bootstrap engine (Weekly mode) resamples from observed seasonal returns and adds a fraction of the bias, which captures skew and fat tails better.
• Volatility adjustment multiplies each daily shock by a factor derived from ATR(20)/price, clamped between 0.5 and 2.0 to avoid extreme cones.
• Performance guardrails : simulations are capped at 100 paths; the probability cone uses polylines (no heavy fills) and only draws on the last confirmed bar to keep charts responsive.
• Prerequisite data : at least ~30 seasonal entries are required before the model will draw a cone; otherwise it waits for more history.
Strengths and limitations
• Strengths :
– Probabilistic thinking replaces single-point guessing.
– Seasonality adds a small but meaningful directional bias that many markets exhibit.
– Volatility scaling adapts to the current regime so the cone stays realistic.
• Limitations :
– Seasonality can break around structural changes, policy shifts, or one-off events.
– The number of paths is performance-limited; percentile estimates are good for trading, not for academic precision.
– The model assumes tomorrow’s randomness resembles recent randomness; if regime shifts violently, the cone will lag until the EWMA adapts.
– Holidays and missing sessions can thin the seasonal sample for some assets; be cautious with very short histories.
Tuning guide
• Horizon : 10–20 bars for tactical trades; 30+ for swing planning when you care more about broad ranges than precise targets.
• Iterations : The default 100 is enough for stable 5/16/50/84/95 percentiles. If you crave smoother lines, shorten the horizon or run on higher timeframes.
• Daily vs. Weekly : Daily for equities and crypto where month-end and turn-of-month effects matter; Weekly for futures and FX where day-of-week behavior is strong.
• Volatility scaling : Keep it on. Turn off only when you intentionally want a “pure seasonality” cone unaffected by current turbulence.
Workflow examples
• Swing continuation : Cone slopes up, price pulls into the lower inner band, your system fires. Enter near the band, stop just outside the outer line for the next 3–5 bars, target near the median or the opposite inner band.
• Fade extremes : Cone is flat or down, price gaps to the upper outer band on news, then stalls. Favor mean-reversion toward the median, size small if volatility scaling is elevated.
• Event play : Before CPI or earnings on a proxy index, check cone width. If the inner band is already wide, cut size or prefer options structures that benefit from range.
Good habits
• Pair the cone with your entry engine (breakout, pullback, order flow). Let Monte Carlo do range math; let your system do signal quality.
• Do not anchor blindly to the median; recalc after each bar. When the cone’s slope flips or width jumps, the plan should adapt.
• Validate seasonality for your symbol and timeframe; not every market has strong calendar effects.
Summary
The Seasonality Monte Carlo Forecaster wraps institutional risk planning into a single overlay: a data-driven seasonal drift, realistic volatility scaling, and a probabilistic cone that answers “where could we be, with what odds?” within your trading horizon. Use it to place stops where randomness is less likely to take you out, to set targets aligned with realistic travel, and to size positions with confidence born from distributions rather than hunches. It will not predict the future, but it will keep your decisions anchored to probabilities—the language markets actually speak.
Multi-Timeframe Bias Dashboard + VolatilityWhat it is: A corner table (overlay) that gives a quick higher-timeframe read for Daily / 4H / 1H using EMA alignment, MACD, RSI, plus a volatility gauge.
How it works (per timeframe):
EMA block (50/100/200): “Above/Below/Mixed” based on price vs all three EMAs.
MACD: “Bullish/Bearish/Neutral” from MACD line vs Signal and histogram sign.
RSI: Prints the value and an ↑/↓ based on 50 line.
Volatility: Compares ATR(14) to its SMA over 20 bars → High (>*1.2), Normal, Low (<*0.8).
Bias: Combines three votes (EMA, MACD, RSI):
Bullish if ≥2 bullish, Bearish if ≥2 bearish, else Mixed.
Display:
Rows: D / 4H / 1H.
Columns: Bias, EMA(50/100/200), RSI, MACD, Volatility.
Bias cell is color-coded (green/red/gray).
Position setting lets you park the table in Top Right / Bottom Right / Bottom Left (works on mobile too).
Use it for:
Quickly aligning intraday setups with higher-TF direction.
Skipping low-volatility periods.
Confirming momentum (MACD/RSI) when price returns to your OB/FVG zones.
Chicago 17:00-19:00 Overnight RangeThis indicator will map out range high and range low of previous 17:00 - 19:00 of the chart. It can also display mid range if needed
Opening Range — Chicago 17:00-19:00 (Customizable)Maps opening 2 hour range of Chicago timezone with the range high range low and medium zone. It can be customized to fit your needs
Enhanced Circle CandlestickEnhanced Circle Candlestick
This script transforms standard candlesticks into circles, visualizing momentum, volume, and volatility in a unique way. The size and color of the circles change based on the body size of the candlestick, while a change in color signifies a volume spike. Long wicks are also highlighted, providing a quick visual cue for potential reversals or indecision.
Features
Circle Visualization: Replaces the standard candlestick body with a circle. The size of the circle is determined by the size of the candlestick body, making it easy to spot periods of high momentum.Gradient Color: The circle's opacity changes based on the body size. Smaller bodies have a lighter color, while larger, more powerful bodies have a darker, more vivid color. This visual gradient provides a clear indication of a bar's strength.Volume Spike Highlight: The circle's color will change to a bright yellow when the current volume exceeds the average volume by a user-defined factor, indicating a significant influx of buying or selling pressure.Long Wick Markers: The script draws a small triangle above or below the candlestick when a wick's length surpasses a user-defined percentage of the body's size. This helps identify potential exhaustion, rejection, or indecision in the market.
Settings
Bullish/Bearish Color: Customize the base colors for bullish (green) and bearish (red) circles.Volume Spike Color: Choose the color for the circle when a volume spike occurs.Volume Spike Factor: Set the multiplier for the volume spike detection. For example, a value of 2.0 means a volume spike is detected when the current volume is twice the 20-period moving average.Circle Opacity (0-100): Adjust the base transparency of the circles. Lower numbers result in more opaque (solid) colors.Opacity Factor: Controls how quickly the color gradient changes based on the body size. A higher value makes the color change more dramatic.Wick Length Factor (vs Body): Set the threshold for marking long wicks. A value of 0.8 means a wick is marked if its length is 80% or more of the candlestick body's size.
How to Use
Add this indicator to your chart.Open the Chart Settings.In the "Symbol" tab, set the transparency of the candlestick "Body" to 0%. (This step is essential because the indicator's settings will not be applied when the indicator is not selected, and the default platform settings take precedence.)
I do not speak English at all. Please understand that if you send me a message, I may not be able to reply, or my reply may have a different meaning. Thank you for your understanding.
EEI Strategy — Greedy/Guarded v1.2Purpose
Day‑trading strategy (5‑min focus) that hunts “armed” setups (PRE) and confirms them (GO) with greedy-but‑guarded execution. It adapts to symbol type, trend strength, and how long it’s been since the last signal.
Core signals & regime
Trend/Regime: EMA‑200 (intraday bias), VWAP, and a non‑repainting HTF EMA (via request.security(...) ).
Momentum/Structure: Manual Wilder DMI/ADX, micro‑ribbon (EMA 8/21), Bollinger‑Keltner squeeze + “squeeze fire,” BOS (break of swing high/low), pullback to band.
Liquidity/Vol: RVOL vs SMA(volume) + a latch (keeps eligibility a few bars after the first spike).
Volatility: ATR + ATR EMA (expansion).
PRE / GO engine
Score (0–100) aggregates trend, momentum, RVOL, squeeze, OBV slope, ribbon, pullback, BOS, and an Opening‑Range (OR) proximity penalty.
PRE arms when the adjusted score ≥ threshold and basic hygiene passes (ATR%, cooldown, etc.).
GO confirms within a dynamic window (1–3 bars):
Wick‑break mode on hot momentum (trend‑day / high ADX+RVOL): stop orders above/below the PRE high/low with a tick buffer.
Close‑through mode otherwise: close must push through PRE high/low plus ATR buffer.
Chase guard: entry cannot be too far from PRE price (ATR‑based), with a tiny extra allowance when the 8/21 ribbon aligns.
Multiple PREs per squeeze (capped) + per‑entry cooldown.
Adaptive behavior
Presets (Conservative/Balanced/Aggressive/Turbo) shift score/ADX/RVOL/ATR gates, GO window, cooldown, and max chase.
Profiles / Auto by Symbol:
Mega Trend (e.g., AMD/NVDA/TSLA/AAPL): looser chase, ATR stop, chandelier trail.
Mid Guarded (e.g., TTD/COIN/SOFI): swing stop, EMA trail, moderate gates.
Small Safe (e.g., BTAI/BBAI class): tighter gates, more guardrails.
BBAI micro‑override: easier arming (lower score/ADX/RVOL), multi‑PRE=3, swing stop + EMA trail, lighter OR penalty.
Trend‑day detector: if ADX hot + RVOL strong + ATR expanding + distance from day‑open large → GO window = 1 and wick‑break mode.
Mid‑day relaxers: mild score bonus between 10:30–14:30 to keep signals flowing in quieter tape.
Auto‑Relaxer (no‑signal fallback): after N bars without PRE/GO, gradually lowers score/ADX/RVOL/ATR% gates and raises max chase so the engine doesn’t stall on sleepy symbols.
Auto‑Session fallback: if RTH session isn’t detected (some tickers/premarket), it falls back to daily boundaries so Opening Range and day‑open logic still work.
Risk & exits
Initial stop per side chosen by ATR, Swing, or OR (computed every bar; no conditional calls).
Scaled targets: TP1/TP2 (R‑based) + runner with optional Chandelier or EMA trailing.
BE logic: optional move to breakeven after TP1; trailing can start after TP1 if configured.
Opening Range (OR)
Computes day open, OR high/low over configurable minutes; applies a penalty when entries are too close to OR boundary (lighter for small caps/BBAI). Protects against boundary whips.
Alerts & visuals
Alertconditions: PRE Long/Short Armed, GO Long/Short + explicit alert() calls for once‑per‑bar automation.
Plots: EMA‑200, HTF EMA, BB/KC bands, OR lines, squeeze shading, and PRE markers.
Why it’s robust
Non‑repainting HTF technique, all series precomputed every bar, no function calls hidden in conditionals that could break history dependence, and consistent state handling (var + sentinels).
Tuning cheat‑sheet (fast wins)
More trades: lower scoreBase, adxHot, or rvolMinBase a notch; reduce cooldownBase; increase maxPREperSqueeze.
Fewer whips: increase closeBufferATR, wickBufferTicks, or atrMinPct; reduce maxChaseATRBase.
Trend capture: use trailType="Chandelier", smaller trailLen, slightly larger trailMult; set preset="Aggressive".
Choppy names: prefer stopMode="Swing", enable EMA trail, keep OR penalty on.
New RSI📌 New RSI
The New RSI is a modern, enhanced version of the classic RSI created in 1978 — redesigned for today’s fast-moving markets, where algorithmic trading and AI dominate price action.
This indicator combines:
Adaptive RSI: Adjusts its calculation length in real time based on market volatility, making it more responsive during high volatility and smoother during calm periods.
Dynamic Bands: Upper and lower bands calculated from historical RSI volatility, helping you spot overbought/oversold conditions with greater accuracy.
Trend & Regime Filters: EMA and ADX-based detection to confirm signals only in favorable market conditions.
Volume Confirmation: Signals appear only when high trading volume supports the move — green volume for bullish setups and red volume for bearish setups — filtering out weak and unreliable trades.
💡 How it works:
A LONG signal appears when RSI crosses above the lower band and the volume is high with a bullish candle.
A SHORT signal appears when RSI crosses below the upper band and the volume is high with a bearish candle.
Trend and higher timeframe filters (optional) can help improve precision and adapt to different trading styles.
✅ Best Use Cases:
Identify high-probability reversals or pullbacks with strong momentum confirmation.
Avoid false signals by trading only when volume validates the move.
Combine with your own support/resistance or price action strategy for even higher accuracy.
⚙️ Fully Customizable:
Adjustable RSI settings (length, volatility adaptation, smoothing)
Dynamic band sensitivity
Volume threshold multiplier
Higher timeframe RSI filter
Color-coded background for market regime visualization
This is not just another RSI — it’s a complete, next-gen momentum tool designed for traders who want accuracy, adaptability, and confirmation in every signal.
Heiken Ashi + Ichimoku Baseline ScalperHi
This a trend identification strategy. You can hold your trade as long as the signals are in your favor.
Information-Geometric Market DynamicsInformation-Geometric Market Dynamics
The Information Field: A Geometric Approach to Market Dynamics
By: DskyzInvestments
Foreword: Beyond the Shadows on the Wall
If you have traded for any length of time, you know " the feeling ." It is the frustration of a perfect setup that fails, the whipsaw that stops you out just before the real move, the nagging sense that the chart is telling you only half the story. For decades, technical analysis has relied on interpreting the shadows—the patterns left behind by price. We draw lines on these shadows, apply indicators to them, and hope they reveal the future.
But what if we could stop looking at the shadows and, instead, analyze the object casting them?
This script introduces a new paradigm for market analysis: Information-Geometric Market Dynamics (IGMD) . The core premise of IGMD is that the price chart is merely a one-dimensional projection of a much richer, higher-dimensional reality—an " information field " generated by the collective actions and beliefs of all market participants.
This is not just another collection of indicators. It is a unified framework for measuring the geometry of the market's information field—its memory, its complexity, its uncertainty, its causal flows—and making high-probability decisions based on that deeper reality. By fusing advanced mathematical and informational concepts, IGMD provides a multi-faceted lens through which to view market behavior, moving beyond simple price action into the very structure of market information itself.
Prepare to move beyond the flatland of the price chart. Welcome to the information field.
The IGMD Framework: A Multi-Kernel Approach
What is a Kernel? The Heart of Transformation
In mathematics and data science, a kernel is a powerful and elegant concept. At its core, a kernel is a function that takes complex, often inscrutable data and transforms it into a more useful format. Think of it as a specialized lens or a mathematical "probe." You cannot directly measure abstract concepts like "market memory" or "trend quality" by looking at a price number. First, you must process the raw price data through a specific mathematical machine—a kernel—that is designed to output a measurement of that specific property. Kernels operate by performing a sort of "similarity test," projecting data into a higher-dimensional space where hidden patterns and relationships become visible and measurable.
Why do creators use them? We use kernels to extract features —meaningful pieces of information—that are not explicitly present in the raw data. They are the essential tools for moving beyond surface-level analysis into the very DNA of market behavior. A simple moving average can tell you the average price; a suite of well-chosen kernels can tell you about the character of the price action itself.
The Alchemist's Challenge: The Art of Fusion
Using a single kernel is a challenge. Using five distinct, computationally demanding mathematical engines in unison is an immense undertaking. The true difficulty—and artistry—lies not just in using one kernel, but in fusing the outputs of many . Each kernel provides a different perspective, and they can often give conflicting signals. One kernel might detect a strong trend, while another signals rising chaos and uncertainty. The IGMD script's greatest strength is its ability to act as this alchemist, synthesizing these disparate viewpoints through a weighted fusion process to produce a single, coherent picture of the market's state. It required countless hours of testing and calibration to balance the influence of these five distinct analytical engines so they work in harmony rather than cacophony.
The Five Kernels of Market Dynamics
The IGMD script is built upon a foundation of five distinct kernels, each chosen to probe a unique and critical dimension of the market's information field.
1. The Wavelet Kernel (The "Microscope")
What it is: The Wavelet Kernel is a signal processing function designed to decompose a signal into different frequency scales. Unlike a Fourier Transform that analyzes the entire signal at once, the wavelet slides across the data, providing information about both what frequencies are present and when they occurred.
The Kernels I Use:
Haar Kernel: The simplest wavelet, a square-wave shape defined by the coefficients . It excels at detecting sharp, sudden changes.
Daubechies 2 (db2) Kernel: A more complex and smoother wavelet shape that provides a better balance for analyzing the nuanced ebb and flow of typical market trends.
How it Works in the Script: This kernel is applied iteratively. It first separates the finest "noise" (detail d1) from the first level of trend (approximation a1). It then takes the trend a1 and repeats the process, extracting the next level of cycle (d2) and trend (a2), and so on. This hierarchical decomposition allows us to separate short-term noise from the long-term market "thesis."
2. The Hurst Exponent Kernel (The "Memory Gauge")
What it is: The Hurst Exponent is derived from a statistical analysis kernel that measures the "long-term memory" or persistence of a time series. It is the definitive measure of whether a series is trending (H > 0.5), mean-reverting (H < 0.5), or random (H = 0.5).
How it Works in the Script: The script employs a method based on Rescaled Range (R/S) analysis. It calculates the average range of price movements over increasingly larger time lags (m1, m2, m4, m8...). The slope of the line plotting log(range) vs. log(lag) is the Hurst Exponent. Applying this complex statistical analysis not to the raw price, but to the clean, wavelet-decomposed trend lines, is a key innovation of IGMD.
3. The Fractal Dimension Kernel (The "Complexity Compass")
What it is: This kernel measures the geometric complexity or "jaggedness" of a price path, based on the principles of fractal geometry. A straight line has a dimension of 1; a chaotic, space-filling line approaches a dimension of 2.
How it Works in the Script: We use a version based on Ehlers' Fractal Dimension Index (FDI). It calculates the rate of price change over a full lookback period (N3) and compares it to the sum of the rates of change over the two halves of that period (N1 + N2). The formula d = (log(N1 + N2) - log(N3)) / log(2) quantifies how much "longer" and more convoluted the price path was than a simple straight line. This kernel is our primary filter for tradeable (low complexity) vs. untradeable (high complexity) conditions.
4. The Shannon Entropy Kernel (The "Uncertainty Meter")
What it is: This kernel comes from Information Theory and provides the purest mathematical measure of information, surprise, or uncertainty within a system. It is not a measure of volatility; a market moving predictably up by 10 points every bar has high volatility but zero entropy .
How it Works in the Script: The script normalizes price returns by the ATR, categorizes them into a discrete number of "bins" over a lookback window, and forms a probability distribution. The Shannon Entropy H = -Σ(p_i * log(p_i)) is calculated from this distribution. A low H means returns are predictable. A high H means returns are chaotic. This kernel is our ultimate gauge of market conviction.
5. The Transfer Entropy Kernel (The "Causality Probe")
What it is: This is by far the most advanced and computationally intensive kernel in the script. Transfer Entropy is a non-parametric measure of directed information flow between two time series. It moves beyond correlation to ask: "Does knowing the past of Volume genuinely reduce our uncertainty about the future of Price?"
How it Works in the Script: To make this work, the script discretizes both price returns and the chosen "driver" (e.g., OBV) into three states: "up," "down," or "neutral." It then builds complex conditional probability tables to measure the flow of information in both directions. The Net Transfer Entropy (TE Driver→Price minus TE Price→Driver) gives us a direct measure of causality . A positive score means the driver is leading price, confirming the validity of the move. This is a profound leap beyond traditional indicator analysis.
Chapter 3: Fusion & Interpretation - The Field Score & Dashboard
Each kernel is a specialist providing a piece of the puzzle. The Field Score is where they are fused into a single, comprehensive reading. It's a weighted sum of the normalized scores from all five kernels, producing a single number from -1 (maximum bearish information field) to +1 (maximum bullish information field). This is the ultimate "at-a-glance" metric for the market's net state, and it is interpreted through the dashboard.
The Dashboard: Your Mission Control
Field Score & Regime: The master metric and its plain-English interpretation ("Uptrend Field", "Downtrend Field", "Transitional").
Kernel Readouts (Wave Align, H(w), FDI, etc.): The live scores of each individual kernel. This allows you to see why the Field Score is what it is. A high Field Score with all components in agreement (all green or red) is a state of High Coherence and represents a high-quality setup.
Market Context: Standard metrics like RSI and Volume for additional confluence.
Signals: The raw and adjusted confluence counts and the final, calculated probability scores for potential long and short entries.
Pattern: Shows the dominant candlestick pattern detected within the currently forming APEX range box and its calculated confidence percentage.
Chapter 4: Mastering the Controls - The Inputs Menu
Every parameter is a lever to fine-tune the IGMD engine.
📊 Wavelet Transform: Kernel ( Haar for sharp moves, db2 for smooth trends) and Scales (depth of analysis) let you tune the script's core microscope to your asset's personality.
📈 Hurst Exponent: The Window determines if you're assessing short-term or long-term market memory.
🔍 Fractal Dimension & ⚡ Entropy Volatility: Adjust the lookback windows to make these kernels more or less sensitive to recent price action. Always keep "Normalize by ATR" enabled for Entropy for consistent results.
🔄 Transfer Entropy: Driver lets you choose what causal force to measure (e.g., OBV, Volume, or even an external symbol like VIX). The throttle setting is a crucial performance tool, allowing you to balance precision with script speed.
⚡ Field Fusion • Weights: This is where you can customize the model's "brain." Increase the weights for the kernels that best align with your trading philosophy (e.g., w_hurst for trend followers, w_fdi for chop avoiders).
📊 Signal Engine: Mode offers presets from Conservative to Aggressive . Min Confluence sets your evidence threshold. Dynamic Confluence is a powerful feature that automatically adapts this threshold to the market regime.
🎨 Visuals & 📏 Support/Resistance: These inputs give you full control over the chart's appearance, allowing you to toggle every visual element for a setup that is as clean or as data-rich as you desire.
Chapter 5: Reading the Battlefield - On-Chart Visuals
Pattern Boxes (The Large Rectangles): These are not simple range boxes. They appear when the Field Score crosses a significance threshold, signaling a potential ignition point.
Color: The color reflects the dominant candlestick pattern that has occurred within that box's duration (e.g., green for Bull Engulf).
Label: Displays the dominant pattern, its duration in bars, and a calculated Confidence % based on field strength and pattern clarity.
Bar Pattern Boxes (The Small Boxes): If enabled, these highlight individual, significant candlestick patterns ( BE for Bull Engulf, H for Hammer) on a bar-by-bar basis.
Signal Markers (▲ and ▼): These appear only when the Signal Engine's criteria are all met. The number is the calculated Probability Score .
RR Rails (Dashed Lines): When a signal appears, these lines automatically plot the Entry, Stop Loss (based on ATR), and two Take Profit targets (based on Risk/Reward ratios). They dynamically break and disappear as price touches each level.
Support & Resistance Lines: Plots of the highest high ( Resistance ) and lowest low ( Support ) over a lookback, providing key structural levels.
Chapter 6: Development Philosophy & A Final Word
One single question: " What is the market really doing? " It represents a triumph of complexity, blending concepts from signal processing, chaos theory, and information theory into a cohesive framework. It is offered for educational and analytical purposes and does not constitute financial advice. Its goal is to elevate your analysis from interpreting flat shadows to measuring the rich, geometric reality of the market's information field.
As the great mathematician Benoit Mandelbrot , father of fractal geometry, noted:
"Clouds are not spheres, mountains are not cones, coastlines are not circles, and bark is not smooth, nor does lightning travel in a straight line."
Neither does the market. IGMD is a tool designed to navigate that beautiful, complex, and fractal reality.
— Dskyz, Trade with insight. Trade with anticipation.
VWATR + VIX + VVIX Trend Regime### 🤖 VWATR + VIX + VVIX Trend Regime — Your Ultimate Volatility Dashboard! 📊
This isn't just another indicator; it's a comprehensive dashboard that brings together everything you need to understand market volatility focused on Futures. It merges price-based movement with market-wide fear and sentiment, giving you a powerful edge in your trading and risk management. Think of it as your personal volatility sidekick, ready to help you navigate market uncertainty like a pro!
***
### ✨ What's Inside?
* **VWATR (Volume-Weighted ATR):** A super-smart measure of price movement that pays close attention to where the big money is flowing.
* **VIX (The "Fear Gauge"):** Tracks the expected volatility of the S&P 500, essentially telling you how nervous the market is feeling.
* **VVIX (The "VIX of VIX"):** This one's for the pros! It measures how volatile the VIX itself is, giving you an early heads-up on potential fear spikes.
* **VX Term Structure:** A clever way to see if traders are preparing for a crisis. It compares the two nearest VIX futures to spot a rare signal called "backwardation."
* **Z-Scores:** It helps you spot when VIX and VVIX are at historic highs or lows, making it easier to predict when things might return to normal.
* **Divergence Score:** A unique tool to flag potential market shifts when the VIX and VVIX start moving in completely different directions.
* **Regime Classification:** The script automatically labels the market as "Full Panic," "Known Crisis," "Surface Calm," "Stress," or "Normal," so you always know where you stand.
* **Gradient Bars:** A visual treat! The background of your chart changes color to reflect real-time volatility shifts, giving you an instant feel for the market's mood.
* **Alerts:** Get push notifications on your phone for key events like "Full Panic" or "Backwardation" so you never miss a beat.
***
### 📝 Panel/Table Outputs
This is your mission control! The on-screen table gives you a clean summary of the current market regime, VIX and VVIX values, their ratios, term structure, Z-scores, and signals. Everything you need, right where you can see it.
***
### 🚀 How to Get Started
1. **Check your data:** You'll need access to real-time data for VIX, VVIX, VX1!, and VX2!. A paid subscription might be necessary for this.
2. **Add it to your chart:** Use the indicator on any chart (we've set it to `overlay=false`) to get your full volatility dashboard.
3. **Tweak it to perfection:** Head over to the Settings panel to customize the thresholds, colors, and your all-important "Jolt Value."
4. **Start trading smarter:** Use the dashboard to inform your trades, hedge your portfolio, and manage risk with confidence.
***
### ⚙️ Customization & Key Settings
* `showVWATR`: Toggle your price-volatility metric on or off.
* `showExpectedVol`: See the expected volatility as a percentage of the current price.
* `joltLevel`: This is a very important line on your chart! It's your personal trigger for when volatility is getting a little too wild. More on this below.
* `enableGradientBars`: Turn the awesome colored background on or off.
* `enableTable`: Hide or show your information table.
* `VIX/VVIX/VX1!/VX2! symbols`: If your broker uses different symbols for these, you can change them here.
* `VIX/VVIX thresholds`: Adjust these levels to fine-tune the indicator to your personal risk tolerance.
***
### 💡 Jolt Value: A Quick Guide for Smart Traders 🧠
The **jolt value** is your personal tripwire for volatility. Think of it as a warning light on your car's dashboard. You set the level, and when volatility (VWATR) crosses that line, you get an instant signal that something interesting is happening.
**How to Set Your Jolt Value:**
The ideal jolt value is dynamic. You want to keep it just a little above the current VIX level to stay alert without getting too many false alarms.
| Current VIX Level | Market Regime | Recommended Jolt Value |
| :--- | :--- | :--- |
| Under 15 | Calm/Complacent | 15–16 |
| 15–20 | Typical/Normal | 16–18 |
| 20–30 | Cautious/Active | 18–22 |
| Over 30 | Stress/Panic | 30+ |
**A Pro Tip for August 2025:** Since the VIX is hovering around 14.7, setting your jolt value to **16.5** is a great starting point for keeping an eye on things. If the VIX starts to climb above 20, you should adjust your jolt level to match the new reality.
***
### ⚠️ Important Things to Note
* You might experience some data delays if you're not on a paid TradingView plan or your broker does not provide real-time data for the VIX also VIX is only active during NY session, so it's not advised to use it outside of normal trading hours!
ATR: Body % + Ranges and AnomaliesATR: Body % + Ranges and Anomalies
This indicator provides a dual analysis of price bars to help you better understand market dynamics and volatility. It combines two powerful concepts into one tool: a candle body percentage and a range analysis with an anomaly-excluding average.
Key Features:
1. Candle Body Percentage
This feature plots the size of the candle's body as a percentage of its total high-low range.
A high percentage (e.g., above the 50% gray line) indicates strong, directional movement. The more solid the body is relative to its wicks, the more conviction is behind that move.
The 100% red line marks "Marubozu" candles—bars with no wicks, showing absolute control by buyers or sellers.
2. Range Analysis with Anomalies
This is a unique part of the indicator that helps you identify and understand normal vs. abnormal volatility.
Custom SMA: It calculates an average range of the last N bars, but it smartly excludes "anomalous" bars (spikes or unusually small ranges) from the calculation. This gives you a more reliable baseline for normal volatility.
Anomaly Detection: Bars are colored differently based on their range:
Blue: Small anomalies (range less than 0.5 * ATR). These often occur during periods of low liquidity or indecision.
Red: Large anomalies (range greater than 1.8 * ATR). These can signal a sudden burst of volatility, breakout events, or capitulation.
ATR Range % Label: The label on the chart shows the current bar's range as a percentage of the custom SMA. This tells you how much larger or smaller the current bar's range is compared to a clean average.
How to Use:
Spotting Trends: Use the Body % to confirm the strength of a trend. A series of bars with high body percentages can indicate a strong, healthy trend.
Identifying Volatility: Use the Range Analysis to find areas of interest. A large red anomaly bar could signal a significant event, while a series of blue anomalies might suggest the market is in a tight consolidation before a breakout.
Contextual Analysis: The combination of these tools can provide powerful context. For example, a bar with a high Body % and a red anomaly color suggests a strong, volatile move that could be a turning point or the start of a major trend.
Experiment with the input settings to fine-tune the ATR and SMA periods for different timeframes and assets.
Fabian Z-ScoreFabian Z-Score — % Distance & Z-Scores for SPX / DJI / XLU
What it does
This indicator measures how far three market proxies are from a moving average and standardizes those distances into z-scores so you can spot stretch/mean-reversion and relative out/under-performance.
Universe: S&P 500 (SPX), Dow Jones (DJI) and Utilities (XLU). You can change any of these in Inputs.
Anchor MA: user-selectable MA type (SMA/EMA/RMA/WMA/VWMA/HMA/LSMA/ALMA) and length (default 39; a popular weekly anchor).
Outputs
% from MA: 100 × (𝐶𝑙𝑜𝑠𝑒 − 𝑀𝐴) / 𝑀𝐴
Time-series Z: z-score of the last N % distances (default 39) → “how stretched vs its own history?”
Cross-sectional Z: z-score of each % distance within the trio on this bar → “who’s strongest vs the others right now?”
A compact mini table (top-right) shows the latest values for each symbol: % from MA, Z(ts) and Z(xsec).
Panels & Visualization
Toggle what you want to see in View:
Plot % distance — raw % above/below the MA (0% line shown).
Plot time-series Z — standardized stretch with ±Threshold guides (default ±2σ).
Plot cross-sectional Z — relative z across SPX, DJI, XLU (0 = at the trio’s mean).
Smoothing — optional light MA on the plotted series (set to 1 for none).
A price-panel Moving Average is drawn with your chosen type/length for visual context.
Colors: SPX = teal, DJI = orange, XLU = purple.
Alerts
Two built-in alert conditions (time-series Z only):
“Z(ts) crosses up +Thr” — any of the three crosses above +Threshold.
“Z(ts) crosses down -Thr” — any crosses below −Threshold.
When enabled, the chart background tints faint green (up cross) or red (down cross) on those bars.
How to use (ideas, not advice)
On weekly charts, a 39-length MA/Z lookback often captures major risk-on/off swings. (Fabian Timing)
Deep negative Z(ts) (e.g., ≤ −2σ or −3σ) frequently accompanies panic and mean-reversion setups.
High positive Z(ts) suggests over-extension; watch for momentum fades.
Cross-sectional Z helps rank leadership today:
Z(xsec) > 0 → stronger than the trio’s mean this bar; Z(xsec) < 0 → weaker.
Utilities (XLU) turning positive x-sec while the others are negative can hint at defensive rotation.
If all 3 are above 0, go long, if below 0 go cash.
Combine: look for extreme Z(ts) aligning with lead/lag Z(xsec) to time entries/exits or hedges.
Inputs (quick reference)
Symbols: SPX / DJI / XLU (editable).
MA type & length: SMA, EMA, RMA, WMA, VWMA, HMA, LSMA, ALMA; default EMA(39).
Z-score lookback (ts): default 39.
Smoothing on plots: default 1 (off).
Z threshold (±): default 2.0 (guide lines & alerts).
ATR x2 AUTODescription:
This indicator automatically plots ATR-based horizontal levels for each of the most recent candles, helping traders visualize potential stop-loss hunting zones, breakout areas, or price reaction points.
It works by taking the Average True Range (ATR) over a customizable period and multiplying it by a user-defined factor (default: ×2). For each of the last N candles (default: 5), it calculates and draws:
Below green candles (bullish) → A horizontal line placed ATR × multiplier below the candle’s low.
Above red candles (bearish) → A horizontal line placed ATR × multiplier above the candle’s high.
Doji candles → No line is drawn.
Each line extends to the right indefinitely, allowing traders to monitor how price reacts when returning to these ATR-based levels. This makes the tool useful for:
Identifying likely stop-loss clusters below bullish candles or above bearish candles.
Anticipating liquidity sweeps and fakeouts.
Supporting breakout or reversal strategies.
Key Features:
Customizable ATR length, multiplier, number of recent candles, and line thickness.
Separate colors for bullish and bearish candle levels.
Automatic real-time updates for each new bar.
Clean overlay on the main price chart.
Inputs:
ATR Length → Period used for ATR calculation.
Multiplier → Factor applied to the ATR distance.
Number of Candles → How many recent candles to track.
Line Thickness and Colors → Full visual customization.
Usage Tip:
These levels can be combined with key market structure points such as support/resistance, trendlines, or the 200 EMA to anticipate high-probability price reactions.
ABS Companion Oscillator — Trend / Exhaustion / New Trend (v1.1)
# ABS Companion Oscillator — Trend / Exhaustion / New Trend (v1.1)
## What it is (quick take)
**ABS CO** is a unified **–100…+100 trend oscillator** that fuses:
* **Regime**: EMA stack (fast/slow/long) + **HTF slope** (e.g., 60-minute)
* **Momentum**: **TSI** vs its signal
* **Stretch**: session-anchored **VWAP Z-score** for exhaustion and “fresh-trend” sanity checks
It paints the oscillator with **lime** in upstate, **red** in downstate, **gray** in neutral, and tags:
* **NEW↑ / NEW↓** when a **new trend** likely starts (zero-line cross with acceptable stretch)
* **EXH↑ / EXH↓** when an **existing trend looks exhausted** (large |Z| + momentum rollback)
> Use it as a **direction filter and context layer**. Works great in front of an entry engine and behind an exit tool.
---
## How to use it (operational workflow)
1. **Read the state**
* **Uptrend** when the oscillator is **≥ upThresh** (default +55) → prefer **long-side** plays.
* **Downtrend** when the oscillator is **≤ dnThresh** (default −55) → prefer **short-side** plays.
* **Neutral** between thresholds → be selective or flat; expect chop.
2. **Act on events**
* **NEW↑ / NEW↓**: zero-line cross with acceptable |Z| (not already overstretched). Treat as **trend start** cues.
* **EXH↑ / EXH↓**: trend state with **high |Z|** and TSI rollback versus its signal. Treat as **trend fatigue**; avoid fresh go-with entries and tighten risk.
3. **Practical pairing**
* Use **up/down state** (or above/below **neutralBand**) as your go/no-go filter for entries.
* Prioritize entries **with** NEW↑/NEW↓ and **without** nearby EXH tags.
* Keep holding while the oscillator stays in state and no EXH appears; consider scaling out on EXH or on your exit tool.
---
## Visual semantics & alerts
* **ABS CO line** (–100…+100): lime in upstate, red in downstate, gray in neutral.
* **Horizontal guides**: `Up` threshold, `Down` threshold, `Zero`, and optional **neutral band** lines.
* **Background heat** (optional): shaded when EXH conditions trigger (lime/red tint with intensity scaled by |Z|).
* **Tags**: `NEW↑`, `NEW↓`, `EXH↑`, `EXH↓`.
**Alerts (stable):**
* **ABS CO — New Uptrend** (NEW↑)
* **ABS CO — New Downtrend** (NEW↓)
* **ABS CO — Exhausted Up** (EXH↑)
* **ABS CO — Exhausted Down** (EXH↓)
Set alerts to **“Once per bar close”** for clean signals.
---
## Non-repainting behavior
* HTF queries use **lookahead\_off**.
* With **Strict NR = true**, the HTF slope is taken from the **prior completed** HTF bar; events evaluate on confirmed bars → **safer, fewer, cleaner**.
* NEW/EXH tags finalize at bar close. Disabling strictness yields earlier but noisier responses.
---
## Every input explained (and how it changes behavior)
### A) Trend & HTF structure
* **EMA Fast / Slow / Long (`emaFastLen`, `emaSlowLen`, `emaLongLen`)**
Control the baseline regime. Larger = smoother, fewer flips; smaller = snappier, more flips.
* **HTF EMA Len (`htfLen`)** & **HTF timeframe (`htfTF`)**
HTF slope filter. Longer len or higher TF = steadier bias (fewer state changes); shorter/ lower = more sensitive.
* **Strict NR (`strictNR`)**
`true` uses the **previous** HTF bar for slope and evaluates on confirmed bars → cleaner, slower.
### B) Momentum (TSI)
* **TSI Long / Short / Signal (`tsiLong`, `tsiShort`, `tsiSig`)**
Standard TSI. Larger values = smoother momentum, fewer EXH triggers; smaller = snappier, more EXH sensitivity.
### C) Stretch (VWAP Z-score)
* **VWAP Z-score length (`zLen`)**
Window for Z over session-anchored VWAP distance. Larger = smoother |Z|; smaller = more reactive stretch detection.
* **Exhaustion |Z| (`zHot`)**
Minimum |Z| to flag **EXH**. Raise to demand **bigger** stretch (fewer EXH); lower to catch milder excess.
* **Max |Z| for NEW (`zNewMax`)**
NEW requires |Z| **≤ zNewMax** (avoid “new trend” when already stretched). Lower = stricter; higher = more NEW tags.
### D) States & thresholds
* **Uptrend threshold (`upThresh`)** / **Downtrend threshold (`dnThresh`)**
Where the oscillator flips into trend states. Widen (e.g., +60/−60) to reduce false states; narrow to get earlier signals.
* **Neutral band (`neutralBand`)**
Visual buffer around zero for “meh” momentum. Larger band = fewer go/no-go flips near zero.
### E) Visuals & tags
* **Show New / Show Exhausted (`showNew`, `showExh`)**
Toggle the tag labels.
* **Shade exhaustion heat (`plotHeat`)**
On = color background when EXH fires. Helpful for scanning.
### F) Smoothing
* **Osc smoothing (`smoothLen`)**
EMA over the raw composite. Higher = steadier line (fewer whip flips); lower = faster turns.
---
## Tuning recipes
* **Trend-day bias (follow moves longer)**
* Raise **`upThresh`** to \~60 and **`dnThresh`** to \~−60
* Keep **`zNewMax`** low (1.0–1.2) to avoid “fresh trend” when stretched
* **`smoothLen`** 3–5 to reduce noise
* **Range-day bias (fade edges)**
* Keep thresholds closer (e.g., +50/−50) for quicker state changes
* Lower **`zHot`** slightly (1.6–1.7) to catch earlier exhaustion
* Consider slightly shorter TSI (e.g., 21/9/5) for faster EXH response
* **Scalping LTF (1–3m)**
* TSI 21/9/5, **`smoothLen`** 1–2
* Thresholds +/-50; **`zNewMax`** 1.0–1.2; **`zHot`** 1.6–1.8
* StrictNR **off** if you want earlier calls (accept more noise)
* **Swing / HTF (1h–D)**
* TSI 35/21/9, **`smoothLen`** 4–7
* Thresholds +/-60\~65; **`zNewMax`** 1.2; **`zHot`** 1.8–2.0
* StrictNR **on** for cleaner bias
---
## Playbooks (how to actually trade it)
* **Go/No-Go Filter**
* Only take **long entries** when the oscillator is **above the neutral band** (preferably ≥ `upThresh`).
* Only take **short entries** when **below** the neutral band (preferably ≤ `dnThresh`).
* Avoid fresh go-with entries if an **EXH** tag appears; let the next setup re-arm.
* **Trend Genesis**
* Treat **NEW↑ / NEW↓** as “green light” for **first pullback** entries in the new direction (ideally within acceptable |Z|).
* **Trend Maturity**
* When in a position and **EXH** prints **against** you, tighten stops, take partials, or lean on your exit tool to protect gains.
---
## Suggested starting points
* **Day trading (5–15m):**
* TSI 25/13/7, `smoothLen=3`, thresholds **+55 / −55**, `zNewMax = 1.2`, `zHot = 1.8`, **StrictNR = true**
* **Scalping (1–3m):**
* TSI 21/9/5, `smoothLen=1–2`, thresholds **+50 / −50**, `zNewMax = 1.1–1.2`, `zHot = 1.6–1.8`, **StrictNR = false** (optional)
* **Swing (1h–D):**
* TSI 35/21/9, `smoothLen=4–6`, thresholds **+60 / −60**, `zNewMax = 1.2`, `zHot = 1.9–2.0`, **StrictNR = true**
---
## Notes & best practices
* **Session anchoring**: Z-score is session-anchored (resets by trading date). If you trade outside standard sessions, verify your data session.
* **Instrument specificity**: Tune **`zHot`**, **`zNewMax`**, and thresholds per symbol and timeframe.
* **Bar-close discipline**: Evaluate tags at **bar close** to avoid intrabar flip-flop.
* This is a **context/confirmation tool**, not a broker or strategy. Combine with your entry/exit rules and position sizing.
---
**Tip:** Start with the suggested day-trading profile. Use this oscillator as your **gate** (only trade with it), let your entry engine time executions, and rely on your exit tool for standardized profit-taking.
ABS NR — Fail-Safe Confirm (v4.2.2)
# ABS NR — Fail-Safe Confirm (v4.2.2)
## What it is (quick take)
**ABS NR FS** is a **non-repainting “arm → confirm” entry framework** for intraday and swing execution. It blends:
* **Regime** (EMA stack + 60-min slope),
* **Location** (Keltner basis/edges),
* **Stretch** (session-anchored **VWAP Z-score**),
* **Momentum gating** (TSI cross/slope),
* **Guards** (session window, minimum ATR%, gap filter, optional market alignment).
You’ll see a **small dot** when a setup is **armed** (candidate) and a **triangle** when that setup **confirms** within a user-defined number of bars. A **gray “X”** marks a timeout (candidate canceled).
> Tip: This entry tool works best when paired with a trend context filter and a dedicated exit tool.
---
## How to use it (operational workflow)
1. **Read the regime**
* **Bull trend**: fast > slow > long EMA **and** 60-min slope up.
* **Bear trend**: fast < slow < long EMA **and** 60-min slope down.
* **Range**: neither bull nor bear.
2. **Wait for a candidate (dot)**
Two families:
* **Reclaim (trend-following):** price crosses the **KC basis** with acceptable |Z| (not overstretched) and passes the TSI gate.
* **Fade (range-revert):** price **pokes a KC band**, prints a **reversal wick**, |Z| is stretched, and TSI gate agrees.
3. **Trade the confirmation (triangle)**
The confirm must occur **within N bars** and follow your chosen **Confirm mode** logic (see Inputs). If confirmation doesn’t arrive in time, an **X** cancels the candidate.
4. **Use guards to avoid junk**
Session windows (US focus), minimum ATR%, gap guard, and optional **market alignment** (e.g., SPY above EMA20 for longs).
5. **Manage the position**
* Entries: take **triangles** in the direction of your playbook (reclaims with trend; fades in clean ranges).
* Filters and exits: use your own process or pair with a trend/exit companion.
---
## Visual semantics & alerts
* **Candidate L / S (dot)** → a setup armed on this bar.
* **CONFIRM L / S (triangle)** → actionable signal that met confirm rules within your time window.
* **Cancel L / S (X)** → candidate expired without confirmation; ignore the dot.
**Alerts (stable names for automation):**
* **ABS FS — Confirmed** → fires on confirmed long or short.
* **ABS FS — Candidate Armed** → fires as a candidate arms.
---
## Non-repainting behavior (why signals don’t repaint)
* All HTF requests use **lookahead\_off**.
* With **Strict NR = true**, the 60-min slope uses the **prior completed** 60-min bar and arming/confirming only occurs on confirmed bars.
* Confirmation triangles finalize on bar close.
* If you disable strictness, signals may appear slightly earlier but with more intrabar sensitivity.
---
## Inputs reference (what each control does and the trade-offs)
### A) Behavior / Modes
**Mode** (`Turbo / Aggressive / Balanced / Conservative`)
Changes multiple internal thresholds:
* **Turbo** → most signals; relaxes prior-bar break & VWAP-side checks and time/vol/gap guards. Highest frequency, highest noise.
* **Aggressive** → more signals than Balanced, fewer than Turbo.
* **Balanced** → default; steady trade-off of frequency vs. quality.
* **Conservative** → tightens |Z| and other checks; fewest but cleanest signals.
**Strict NR (bar close + prior HTF 60m)**
* **true** = safer: uses prior 60-min slope; arms/confirms on confirmed bars → **fewer/cleaner** signals.
* **false** = earlier and more reactive; slightly noisier.
---
### B) Keltner Channel (location engine)
* **KC EMA Length (`kcLen`)**
Higher → smoother basis (fewer basis crosses). Lower → snappier basis (more crosses).
* **ATR Length (`atrLen`)**
Higher → steadier band width; Lower → more reactive band width.
* **KC ATR Mult (`kcMult`)**
Higher → wider bands (fewer edge pokes → fewer fades). Lower → narrower (more fades).
---
### C) Trend & HTF slope
* **Trend EMA Fast/Slow/Long (`emaFastLen / emaSlowLen / emaLongLen`)**
Larger = slower regime flips (fewer reclaims); smaller = faster flips (more reclaims).
* **HTF EMA Len (60m) (`htfLen`)**
Larger = steadier HTF slope (fewer signals); smaller = more sensitive (more signals).
---
### D) VWAP Z-Score (stretch / mean-revert logic)
* **VWAP Z-Length (`zLen`)**
Window for Z over session-anchored VWAP distance. Larger = smoother |Z| (fewer fades/re-entries). Smaller = more reactive (more).
* **Range Fade |Z| (base) (`zFadeBase`)**
Minimum |Z| to allow **fades** in ranges. Raise to demand more stretch (fewer fades). Lower to take more fades.
* **Max |Z| Trend Re-entry (base) (`maxZTrendBase`)**
Caps how stretched price can be and still permit **reclaims** with trend. Lower = stricter (avoid chases). Higher = will chase further.
---
### E) TSI Momentum Gate
* **TSI Long/Short/Signal (`tsiLong / tsiShort / tsiSig`)**
Larger = smoother/laggier momentum; smaller = snappier.
* **TSI gate (`CrossOnly / CrossOrSlope / Off`)**
* **CrossOnly**: require TSI cross of its signal (strict).
* **CrossOrSlope**: cross *or* favorable slope (balanced default).
* **Off**: no momentum gate (most signals, most noise).
---
### F) Guards (filters to avoid low-quality tape)
* **US focus 09:35–10:30 & 14:00–15:45 (base) (`useTimeBase`)**
`true` limits to high-quality windows. `false` trades all session.
* **Skip N bars after 09:30 ET (`skipFirst`)**
Skips the open scramble. Larger = skip longer.
* **Min volatility ATR% (base)** = `useVolMinBase` + `atrPctMinBase`
Requires `ATR(10)/Close*100 ≥ atrPctMinBase`. Raise threshold to avoid dead tape; lower to accept quieter sessions.
* **Gap guard (base)** = `gapGuardBase` + `gapMul`
Blocks signals when the opening gap exceeds `gapMul * ATR`. Increase `gapMul` to allow more gapped opens; decrease to be stricter.
---
### G) Visuals & Sides
* **Plot Keltner (`plotKC`)** → show/hide basis & bands.
* **Show Longs / Show Shorts** → enable/disable each side.
---
### H) Fail-Safe Confirmation
* **Confirm mode (`BreakHighOnly / BreakHigh+Hold / TwoBarImpulse`)**
* **BreakHighOnly**: confirm by taking out the armed bar’s extreme. Fastest, most frequent.
* **BreakHigh+Hold**: must **break**, have **body ≥ X·ATR**, **and** hold above/below the basis → higher quality, fewer signals.
* **TwoBarImpulse**: decisive follow-through vs. prior bar with **body ≥ X·ATR** → momentum-biased confirmations.
* **Confirm within N bars (`confirmBars`)**
Confirmation window size. Smaller = faster validation; larger = more patience (can be later).
* **Impulse body ≥ X·ATR (`impulseBodyATR`)**
Raise for stronger confirmations (fewer weak triangles). Lower to accept lighter pushes.
* **Require market alignment (`needMarket`) + `marketTicker`**
When enabled: Longs require **market > EMA20 (5m)**; Shorts require **market < EMA20 (5m)**.
* **Diagnostics: Show debug letters (`debug`)**
Tiny “B/C” audit marks for base/confirm while tuning.
---
## Tuning recipes (quick, practical)
* **If you’re getting chopped:**
* Set **Mode = Conservative**
* **Confirm mode = BreakHigh+Hold**
* Raise **impulseBodyATR** (e.g., 0.45)
* Keep **needMarket = true**
* Keep **Strict NR = true**
* **If you need more signals:**
* **Mode = Aggressive** (or Turbo if you accept more noise)
* **Confirm mode = BreakHighOnly**
* Lower **impulseBodyATR** (0.25–0.30)
* Increase **confirmBars** to 3
* **Range-day focus (fades):**
* Keep session guard on
* Raise **zFadeBase** to demand real stretch
* Keep **maxZTrendBase** moderate (don’t chase)
* **Trend-day focus (reclaims):**
* Slightly **lower `maxZTrendBase`** (avoid chasing excessive stretch)
* Use **CrossOrSlope** TSI gating
* Consider turning **needMarket** on
---
## Best practices & notes
* **Instrument specificity:** Tune Z, TSI, and guards per symbol and timeframe.
* **Session awareness:** Session filter uses **exchange-local** time; adjust for non-US markets.
* **Automation:** Use the two provided alert names; they’re stable.
* **Risk management:** Confirmation improves quality but doesn’t remove risk. Always pre-define stop/size logic.
---
## Suggested starting point (balanced profile)
* **Mode = balanced**
* **Strict NR = true**
* **Confirm mode = BreakHigh+Hold**
* **confirmBars = 2**
* **impulseBodyATR ≈ 0.35**
* **needMarket = off** (turn on for extra confluence)
* Leave Keltner/TSI defaults; then nudge `zFadeBase` and `maxZTrendBase` to match your symbol.
---
*This tool is a signal generator, not a broker or strategy. Validate on your markets/timeframes and integrate with your risk plan.*
Key Indicators Dashboard (KID)Key Indicators Dashboard (KID) — Comprehensive Market & Trend Metrics
📌 Overview
The Key Indicators Dashboard (KID) is an advanced multi-metric market analysis tool designed to consolidate essential technical, volatility, and relative performance data into a single on-chart table. Instead of switching between multiple indicators, KID centralizes these key measures, making it easier to assess a stock’s technical health, volatility state, trend status, and relative strength at a glance.
🛠 Key Features
⦿ Average Daily Range (ADR %): Measures average daily price movement over a specified period. It is calculated by averaging the daily price range (high - low) over a set number of days (default 20 days).
⦿ Average True Range (ATR): Measures volatility by calculating the average of a true range over a specific period (default 14). It helps traders gauge the typical extent of price movement, regardless of the direction.
⦿ ATR%: Expresses the Average True Range as a percentage of the price, which allows traders to compare the volatility of stocks with different prices.
⦿ Relative Strength (RS): Compares a stock’s performance to a chosen benchmark index (default NIFTYMIDSML400) over a specific period (default 50 days).
⦿ RS Score (IBD-style): A normalized 1–100 rating inspired by Investor’s Business Daily methodology.
How it works: The RS Score is based on a weighted average of price changes over 3 months (40%), 6 months (20%), 9 months (20%), and 12 months (20%).
The raw value is converted into a percentage return, then normalized over the past 252 trading days so the lowest value maps to 1 and the highest to 100.
This produces a percentile-style score that highlights the strongest stocks in relative terms.
⦿ Relative Volume (RVol): Compares a stock's current volume to its average volume over a specific period (default 50). It is calculated by dividing the current volume by the average historical volume.
⦿ Average ₹ Volume (Turnover): Represents the total monetary value of shares traded for a stock. It's calculated by multiplying a day's closing price by its volume, with the final value converted to crores for clarity. This metric is a key indicator of a stock's liquidity and overall market interest.
⦿ Moving Average Extension: Measures how far a stock's current price has moved from from a selected moving average (EMA or SMA). This deviation is normalized by the stock's volatility (ATR%), with a default threshold of 6 ATR used to indicate that the stock is significantly extended and is marked with a selected shape (default Red Flag).
⦿ 52-Weeks High & Low: Measures a stock's current price in relation to its highest and lowest prices over the past year. It calculates the percentage a stock is below its 52-week high and above its 52-week low.
⦿ Market Capitalization: Market Cap represents the total value of all outstanding.
⦿ Free Float: It is the value of shares readily available for public trading, with the Free Float Percentage showing the proportion of shares available to the public.
⦿ Trend: Uses Supertrend indicator to identify the current trend of a stock's price. A factor (default 3) and an ATR period (default 10) is used to signal whether the trend is up or down.
⦿ Minervini Trend Template (MTT): It is a set of technical criteria designed to identify stocks in strong uptrends.
Price > 50-DMA > 150-DMA > 200-DMA
200-DMA is trending up for at least 1 month
Price is at least 30% above its 52-week low.
Price is within at least 25 percent of its 52-week high
Table highlights when a stock meets all above criteria.
⦿ Sector & Industry: Display stock's sector and industry, provides categorical classification to assist sector-based analysis. The sector is a broad economic classification, while the industry is a more specific group within that sector.
⦿ Moving Averages (MAs): Plot up to four customizable Moving Averages on a chart. You can independently set the type (Simple or Exponential), the source price, and the length for each MA to help visualize a stock's underlying trend.
MA1: Default 10-EMA
MA2: Default 20-EMA
MA3: Default 50-EMA
MA4: Default 200-EMA
⦿ Moving Average (MA) Crossover: It is a trend signal that occurs when a shorter-term moving average crosses a longer-term one. This script identifies these crossover events and plots a marker on the chart to visually signal a potential change in trend direction.
User-configurable MAs (short and long).
A bullish crossover occurs when the short MA crosses above the long MA.
A bearish crossover occurs when the short MA crosses below the long MA.
⦿ Inside Bar (IB): An Inside Bar is a candlestick whose entire price range is contained within the range of the previous bar. This script identifies this pattern, which often signals consolidation, and visually marks bullish and bearish inside bars on the chart with distinct colors and labels.
⦿ Tightness: Identifies periods of low volatility and price consolidation. It compares the price range over a short lookback period (default 3) to the average daily range (ADR). When the lookback range is smaller than the ADR, the indicator plots a marker on the chart to signal consolidation.
⦿ PowerBar (Purple Dot): Identifies candles with a strong price move on high volume. By default, it plots a purple dot when a stock moves up or down by at least 5% and has a minimum volume of 500,000. More dots indicate higher volatility and liquidity.
⦿ Squeezing Range (SQ): Identifies periods of low volatility, which can often precede a significant price move. It checks if the Bollinger Bands have narrowed to a range that is smaller than the Average True Range (ATR) for a set number of consecutive bars (default 3).
(UpperBB - LowerBB) < (ATR × 2)
⦿ Mark 52-Weeks High and Low: Marks and labels a stock's 52-Week High and Low prices directly on the chart. It draws two horizontal lines extending from the candles where the highest and lowest prices occurred over the past year, providing a clear visual reference for long-term price extremes.
⏳PineScreener Filters
The indicator’s alert conditions act as filters for PineScreener.
Price Filter: Minimum and maximum price cutoffs (default ₹25 - ₹10000).
Daily Price Change Filter: Minimum and maximum daily percent change (default -5% and 5%).
🔔 Built-in Alerts
Supports alert creation for:
ADR%, ATR/ATR %, RS, RS Rating, Turnover
Moving Average Crossover (Bullish/Bearish)
Minervini Trend Template
52-Week High/Low
Inside Bars (Bullish/Bearish)
Tightness
Squeezing Range (SQ)
⚙️ Customizable Visualization
Switchable between vertical or horizontal layout.
Works in dark/light mode
User-configurable to toggle any indicator ON or OFF.
User-configurable Moving (EMA/SMA), Period/Lengths and thresholds.
⦿ (Optional) : For horizontal table orientation increase Top Margin to 16% in Chart (Canvas) settings to avoid chart overlapping with table.
⚡ Add this script to your chart and start making smarter trade decisions today! 🚀
Queso Heat IndexQueso Heat Index (QHI) — ATR-Adaptive Edge-Pressure Gauge
QHI measures how strongly price is pressing the edges of a rolling consolidation window. It heats up when price repeatedly pushes the window up , cools down when it pushes down , and drifts back toward neutral when price wanders in the middle. Everything is ATR-normalized so it adapts across symbols and timeframes.
Output: a signed score from −100 … +100
> 0 = bullish pressure (hot)
< 0 = bearish pressure (cold)
≈ 0 = neutral (no side dominating)
What you’ll see on the chart
Rolling “box” (Donchian window): top, bottom, and midline.
Optional compact-box shading when the window height is small relative to ATR.
Background “thermals”: tinted red when Heat > Hot threshold, blue when Heat < Cold threshold (intensity scales with the score).
Optional Heat line (−100..+100), optional 0/±80 thresholds, and optional push markers (PU/PD).
Optional table showing the current Heat score, placeable in any corner.
How it works (under the hood)
Consolidation window — Over lookback bars we track highest high (top), lowest low (bottom), and midpoint. The window is called “compact” when box height ≤ ATR × maxRangeATR .
ATR-based push detection — A bar is a push-up if high > prior window high + (epsATR × ATR + tick buffer) . A push-down if low < prior window low − (epsATR × ATR + tick buffer) . We also measure how many ATRs beyond the edge the bar traveled.
Heat gains (symmetric) — Each push adds/subtracts Heat:
base gain + streak bonus × consecutive pushes + magnitude bonus × ATRs beyond edge .
Decay toward neutral — Each bar, Heat decays by a percentage. Decay is:
– higher in the middle band of the box, and
– adaptive : the farther (in ATRs) from the relevant band (top when hot, bottom when cold), the faster it decays; hugging the band slows decay.
Midpoint bias (optional) — Gentle drift toward hot when trading above mid, toward cold when below mid, with a dead-zone near mid so tiny wobbles don’t matter.
Reset on regime flip (optional) — First valid push from the opposite side can snap Heat back to 0 before applying new gains.
How to read it
Rising hot with slow decay → strong upside pressure; pullbacks that hold near the top band often continue.
Flip to cold after being hot → regime change risk; tighten risk or consider the other side.
Compact window + rising hot (or cold) → squeeze-and-go conditions.
Neutral (≈ 0) → edges aren’t being pressured; expect mean-reversion inside the box.
Key inputs (what they do)
Window & ATR
lookback : size of the Donchian window (longer = smoother, slower).
atrLen : ATR period for all volatility-scaled thresholds.
maxRangeATR : defines “compact” windows for optional shading.
topBottomFrac : how thick the top/bottom bands are (used for decay/pressure logic).
Push detection (ATR-based)
epsATR : how many ATRs beyond the prior edge to count as a real push.
tickBuff : fixed extra ticks beyond the ATR epsilon (filters micro-breaches).
Heat gains
gainBase : main fuel per push.
gainPerStreak : rewards consecutive pushes.
gainPer1ATRBrk : adds more for stronger breakouts past the edge.
resetOppSide : snap back to 0 on the first opposite-side push.
Decay
decayPct : baseline % removed each bar.
decayAccelMid : multiplies decay when price is in the middle band.
adaptiveDecay , decayMinMult , decayPerATR , decayMaxMult : scale decay with ATR distance from the nearest “target” band (top if hot, bottom if cold).
Midpoint bias
useMidBias : enable/disable drift above/below midpoint.
midDeadFrac : width of neutral (no-drift) zone around mid.
midBiasPerBar : max drift per bar at the box edge.
Visuals (all default to OFF for a clean chart)
Plot Heat line + Show 0/±80 lines (only shows thresholds if Heat line is on).
Hot/Cold thresholds & transparency floors for background shading.
Push markers (PU/PD).
Heat score table : toggle on; choose any corner.
Tuning quick-starts
Daily trending equities : lookback 40–60; epsATR 0.10–0.25; gainBase 12–18; gainPerStreak 0.5–1.5; gainPer1ATRBrk 1–2; decayPct 3–6; adaptiveDecay ON (decayPerATR 0.5–0.8).
Intraday / noisy : raise epsATR and tickBuff to filter noise; keep decayPct modest so Heat can build.
Weekly swing : longer lookback/atrLen; slightly lower decayPct so regimes persist.
Alerts (included)
New window HIGH (push-up)
New window LOW (push-down)
Heat turned HOT (crosses above your Hot threshold)
Heat turned COLD (crosses below your Cold threshold)
Best practices & notes
Use QHI as a pressure gauge , not a standalone system—combine with your entry/exit plan and risk rules.
On thin symbols, increase epsATR and/or tickBuff to avoid spurious pushes.
Gap days can register large pushes; ATR scaling helps but consider context.
Want the Heat in a separate pane? Use the companion panel version; keep this overlay for background/box visuals.
Pine v6. Warm-up: values appear as soon as one bar of window history exists.
TL;DR
QHI quantifies how hard price is leaning on a consolidation edge.
It’s ATR-adaptive, streak- and magnitude-aware, and cools off intelligently when momentum fades.
Watch for thermals (background), the score (−100..+100), and fresh push alerts to time entries in the direction of pressure.
Relative Volatility Mass [SciQua]The ⚖️ Relative Volatility Mass (RVM) is a volatility-based tool inspired by the Relative Volatility Index (RVI) .
While the RVI measures the ratio of upward to downward volatility over a period, RVM takes a different approach:
It sums the standard deviation of price changes over a rolling window, separating upward volatility from downward volatility .
The result is a measure of the total “volatility mass” over a user-defined period, rather than an average or normalized ratio.
This makes RVM particularly useful for identifying sustained high-volatility conditions without being diluted by averaging.
────────────────────────────────────────────────────────────
╭────────────╮
How It Works
╰────────────╯
1. Standard Deviation Calculation
• Computes the standard deviation of the chosen `Source` over a `Standard Deviation Length` (`stdDevLen`).
2. Directional Separation
• Volatility on up bars (`chg > 0`) is treated as upward volatility .
• Volatility on down bars (`chg < 0`) is treated as downward volatility .
3. Rolling Sum
• Over a `Sum Length` (`sumLen`), the upward and downward volatilities are summed separately using `math.sum()`.
4. Relative Volatility Mass
• The two sums are added together to get the total volatility mass for the rolling window.
Formula:
RVM = Σ(σ up) + Σ(σ down)
where σ is the standard deviation over `stdDevLen`.
╭────────────╮
Key Features
╰────────────╯
Directional Volatility Tracking – Differentiates between volatility during price advances vs. declines.
Rolling Volatility Mass – Shows the total standard deviation accumulation over a given period.
Optional Smoothing – Multiple MA types, including SMA, EMA, SMMA (RMA), WMA, VWMA.
Bollinger Band Overlay – Available when SMA is selected, with adjustable standard deviation multiplier.
Configurable Source – Apply RVM to `close`, `open`, `hl2`, or any custom source.
╭─────╮
Usage
╰─────╯
Trend Confirmation: High RVM values can confirm strong trending conditions.
Breakout Detection: Spikes in RVM often precede or accompany price breakouts.
Volatility Cycle Analysis: Compare periods of contraction and expansion.
RVM is not bounded like the RVI, so absolute values depend on market volatility and chosen parameters.
Consider normalizing or using smoothing for easier visual comparison.
╭────────────────╮
Example Settings
╰────────────────╯
Short-term volatility detection: `stdDevLen = 5`, `sumLen = 10`
Medium-term trend volatility: `stdDevLen = 14`, `sumLen = 20`
Enable `SMA + Bollinger Bands` to visualize when volatility is unusually high or low relative to recent history.
╭───────────────────╮
Notes & Limitations
╰───────────────────╯
Not a directional signal by itself — use alongside price structure, volume, or other indicators.
Higher `sumLen` will smooth short-term fluctuations but reduce responsiveness.
Because it sums, not averages, values will scale with both volatility and chosen window size.
╭───────╮
Credits
╰───────╯
Based on the Relative Volatility Index concept by Donald Dorsey (1993).
TradingView
SciQua - Joshua Danford
