Strenth Comparison [joshu]Strenth Comparison visualizes relative performance across a basket of assets by measuring percent change from the chosen anchor timeframe’s open.
Each new anchor period resets the baseline to 0%, making it easy to spot leaders/laggards and momentum shifts over time.
Anchor timeframe (TF, default: 1W): The period used as the performance baseline.
Assets : Currencies or American Indices.
Symbols :
Currencies: CME:6S1!, CME:6E1!, CME:6B1!, CME:6J1!, CME:6A1!, CME:6N1!, TVC:DXY (inverted for comparability).
American Indices: CME_MINI:ES1!, CME_MINI:NQ1!, CBOT_MINI:YM1!, CME_MINI:RTY1!.
Visuals: All lines plotted in percent; DXY is inverted and highlighted; labels show the symbol at the latest bar; zero line for reference; vertical dividers mark new anchor periods.
Use cases: Compare strength/weakness within FX or US index baskets; monitor rotation, divergence, and leadership over weekly (or chosen) cycles.
Volatilidad
Inside Bar + Volume + MAs + RVol + Volume MilestonesDisplays :
Inside bar near 10 MA
Power volume
MA's
RVOL
HVQ/Y/E
Plots line on Tight Bar closing within 1.5%
RS movement compared to BM & Self
Wolf long or short this indicator is based on RSI, Stoch, BB , this indicator is giving a better understanding of short or long combined with 3 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.
Aladin 2.0 — Invite‑Only (Custom Smoother + Supertrend Filter)Aladin 2.0 invite‑only by @AryaTrades69
Overview
Aladin 2.0 blends a proprietary multi‑stage smoother baseline, volatility envelopes, and a Supertrend‑based ATR trailing filter to structure clean, bar‑close signals. Optional “golden‑zone style” retracement gating and mapped SL/TP zones are included. This is a tool for analysis, accuracy is best when you add manual confluence (trendlines, support/resistance) to filter out low‑quality signals.
What’s inside
Proprietary multi‑stage smoother (baseline)
Custom smoothed baseline with adjustable length and a smoothing coefficient. Drives core breakout logic without revealing internal formulas.
Volatility envelopes
Breakout candidates when price closes beyond adaptive volatility bands.
Supertrend‑based trend filter (optional, MTF)
ATR‑trailing regime filter to keep signals aligned with trend; can run on higher timeframes.
Golden‑zone style retracement gate (optional)
Only allow signals within a defined pullback zone of the recent range.
Spacing & structure controls
Minimum bars between signals plus a simple HH/LL gate to avoid clustered whipsaws.
SL/TP mapping (optional)
SL from most recent confirmed swing; ATR fallback if no swing is found.
TP1/TP2/TP3 by user‑defined R:R; move SL to breakeven at TP1.
Shaded zones for SL and target area (time‑limited for clarity).
How to use
Choose your timeframe (intraday to swing). Signals compute on bar close.
Enable the trend filter for strictly trend‑aligned entries (Supertrend‑based ATR trail). MTF is supported.
Use the golden‑zone gate to prioritize higher‑quality pullbacks.
Validate with manual confluence:
Trendlines, structure breaks
Support/resistance or supply/demand
Session/volatility context
Optionally enable SL/TP areas, set R:R, and configure alerts.
Inputs (key controls)
Smoother length & smoothing coefficient (baseline sensitivity/lag)
Range period & multiplier (volatility envelopes)
Min bars between signals (signal frequency)
Trend filter (ATR trail): factor, ATR period, line smoothing, optional higher timeframe
Golden‑zone retracement: lookback, min/max bounds
SL/TP: swing lookback, ATR fallback, TP1/2/3 R:R, zone display width
Alerts
Long/Short signal on bar close
TP1/TP2/TP3 hit
SL hit / Breakeven event
(Setup: Add Alert → Condition: Aladin 2.0 → choose event)
MTF & repaint policy
Signals are calculated on bar close; the trend filter uses security with lookahead off.
Swing‑based SL uses confirmed pivots.
With an HTF filter enabled on an LTF chart, the HTF line/state finalizes when the HTF bar closes (standard MTF behavior).
Best practices
Not a set‑and‑forget system. Accuracy improves when you manually filter weaker signals with trendlines and support/resistance, and prioritize clean market structure.
Consider conservative settings or the trend filter during choppy, low‑volatility periods.
Access
Invite‑Only. Request access via TradingView PM to @AryaTrades69.
Redistribution or code extraction is not permitted.
Disclaimer
For educational purposes only. Not financial advice.
No guarantees of profitability. Trading involves risk. Do your own research.
Changelog (v2.0)
Optional MTF ATR‑trail trend filter (Supertrend concept)
Golden‑zone style retracement gating
Min‑bars spacing and basic HH/LL gating
SL/TP mapping with BE at TP1 and shaded zones
Stability and performance improvements
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.
Tony O's Euler BandsTony O’s Euler Bands is a volatility-based overlay that uses the mathematical constant e (~2.71828) to scale price bands in a non-linear way. Unlike traditional Bollinger Bands or Keltner Channels, these bands are spaced by exponential functions of volatility (σ), creating zones that expand and contract more dynamically across different market regimes.
How it works:
A configurable moving average (EMA/SMA/RMA/WMA) is used as the basis.
Volatility (σ) is calculated as the standard deviation of returns over a user-defined lookback.
Four band levels are plotted above and below the basis at distances equal to:
basis × 𝑒^(𝑚⋅𝜎⋅𝑘)
where m is a user multiplier and k = {2, 4, 6, 8} for each successive band.
This produces inner bands that highlight mild deviations and outer bands that signal extreme moves.
What makes it unique:
Uses e as the base for band expansion instead of linear multiples or Fibonacci ratios.
Bands scale multiplicatively, making them more consistent across assets and price scales.
Multiple symmetric bands per side, color-coded from green (mild) to purple (extreme) for intuitive visual cues.
Optional transparent fill to show volatility envelopes without obscuring price action.
How to use:
Trend monitoring: Sustained closes beyond an inner band can indicate momentum; closes beyond outer bands can signal overextension.
Reversion spotting: Touches on extreme bands (level 4) can highlight potential exhaustion points.
Works on any asset/timeframe; adjust basis length, volatility lookback, and multiplier to suit your market.
0DTE Credit Spreads IndicatorDescription:
This indicator is designed for SPX traders operating on the 15-minute timeframe, specifically targeting 0 Days-to-Expiration (0DTE) options with the intention to let them expire worthless.
It automatically identifies high-probability entry points for Put Credit Spreads (PCS) and Call Credit Spreads (CCS) by combining intraday price action with a custom volatility filter.
Key Features:
Optimized exclusively for SPX on the 15-minute chart.
Intraday volatility conditions adapt based on real-time VIX readings, allowing credit expectations to adjust to market environment.
Automatic visual labeling of PCS and CCS opportunities.
Built-in stop loss level display for risk management.
Optional same-day PCS/CCS signal allowance.
Fully adjustable colors and display preferences.
How It Works (Concept Overview):
The script monitors intraday momentum, relative volatility levels, and proprietary pattern recognition to determine favorable spread-selling conditions.
When conditions align, a PCS or CCS label appears on the chart along with a stop loss level.
VIX is used at the moment of signal to estimate the ideal option credit range.
Recommended Use:
SPX only, 15-minute timeframe.
Intended for 0DTE options held to expiration, though you may take profits earlier based on your own strategy.
Works best during regular US market hours.
Disclaimer:
This script is for informational and educational purposes only and is not financial advice. Trading options carries risk. Always perform your own analysis before entering a trade.
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.
GreenRushR - Confluence HUD (v1.7)Hello traders,
Does it feel like the market perfectly snipes your stop-loss before reversing in the direction you originally predicted? This is one of the most common frustrations in trading, and it often happens when we're on the wrong side of the overall market structure.
The GreenRushR HUD was built from the ground up to solve this exact problem.
It's a comprehensive, all-in-one dashboard that lives on your chart, giving you an instant, crystal-clear view of the trend across nine key timeframes—from the monthly all the way down to the 1-minute. By consolidating this data, the HUD helps you quickly identify when the Higher Timeframes (HTF), Market Structure, and Lower Timeframes (LTF) are in alignment, allowing you to trade with the institutional flow, not against it.
Key Features
📈 All-in-One Dashboard: Instantly see the trend status of the Monthly, Weekly, Daily, 4-Hour, 1-Hour, 30-Minute, 15-Minute, 5-Minute, and 1-Minute timeframes.
🚥 Confluence Signals: The main display shows you the status of three key groups (HTF, Structure, LTF) and gives a clear "CONFLUENCE" signal when key timeframes are aligned, highlighting high-probability conditions.
🔔 "A-Grade" Setup Alerts: The script includes a powerful, pre-configured alert condition for "A-Grade" setups. This allows you to receive a notification the moment a high-probability, multi-timeframe alignment occurs.
🎯 Built-in Exit Logic: To aid in trade management and backtesting, the script includes logic to track multiple potential exit strategies based on ATR (for Stop Loss & Take Profit), Heikin Ashi reversals, and bias flips.
How to Use This Indicator
Wait for Alignment: Look for the dashboard's main groups (HTF and Structure) to show a clear bullish (teal) or bearish (coral) alignment.
Confirm with an Alert: Wait for an "A-Grade Setup" alert to fire, confirming a high-probability entry condition based on the script's logic.
Trade with Confidence: Use the confluence signal as a powerful confirmation for your existing trading plan, helping you avoid low-quality setups and trades against the trend.
Settings
Bullish/Bearish Color: Customize the colors of the dashboard to fit your chart theme.
ATR Multipliers: Adjust the ATR multipliers to set custom Stop Loss and Take Profit levels that suit your risk tolerance.
Enable A-Grade Setup Alerts: A simple toggle to turn the main alert condition on or off.
How to Get Access
This is an invite-only script.
To request access, please leave a comment below or send me a direct message here on TradingView. I will grant you access as soon as possible.
You can also find more information by visiting the website listed on my TradingView profile.
Disclaimer: This indicator is for educational purposes only and should not be considered financial advice. All trading involves substantial risk. Past performance is not indicative of future results. Please trade responsibly.
Advanced VWAP Position SizerBelow is a TradingView description for the "Advanced VWAP Position Sizer" script, written in a clear and concise manner suitable for the platform's indicator description field. The description highlights the script's purpose, features, and usage instructions, tailored to its functionality based on the provided code.
---
### Advanced VWAP Position Sizer
**Category:** Custom Indicators
**Type:** Overlay
The **Advanced VWAP Position Sizer** is a powerful trading tool that combines the Volume Weighted Average Price (VWAP) with dynamic position sizing based on your portfolio risk tolerance. This indicator calculates the VWAP with customizable anchor periods and band levels, then determines the optimal trade size to ensure the full distance between the VWAP centerline and a selected band does not exceed 0.3% of your daily portfolio balance. Ideal for day traders seeking to manage risk effectively while leveraging VWAP-based strategies.
#### Key Features:
- **Customizable VWAP**: Adjust the anchor period (Session, Week, Month, Quarter, Year, Decade, Century, Earnings, Dividends, Splits) to reset the VWAP calculation based on your preferred timeframe.
- **Band Calculations**: Displays upper and lower bands using Standard Deviation or Percentage-based multipliers (1.0, 2.0, 3.0), with options to show/hide each band level.
- **Percentage Difference**: Calculates the percentage difference between the VWAP centerline and the selected band (Upper or Lower), automatically chosen based on trade direction (Long/Short).
- **Position Sizing**: Determines the number of shares to trade based on a user-defined portfolio balance and a 0.3% risk limit, accounting for stop loss distance, commissions, and slippage.
- **Interactive Table**: Displays real-time data including Risk per Trade, VWAP-to-Band Distance, Band % Difference, Risk per Share, Shares, and Position Value, with black text for readability.
- **Flexible Entry**: Supports manual entry price or uses the current price, with customizable stop levels relative to the band distance.
#### How to Use:
1. **Input Your Settings**:
- Set your daily **Portfolio Balance** (e.g., $50,000) to reflect your current capital.
- Adjust the **Risk % of Portfolio** (default 0.3%) to define your risk tolerance.
- Choose your **Direction** (Long or Short) and **Band** (Upper, Lower, or Auto by Direction).
- Select **Entry Price** mode (Current Price or Manual) and set a manual entry if needed.
- Configure **VWAP Settings** (Anchor Period, Source, Offset) and **Bands Settings** (Calculation Mode, Multipliers).
- Add **Commission** and **Slippage** per share, and enable **Fractional Shares** if desired.
- Position the table (Top Right, Bottom Right, Top Left, Bottom Left).
2. **Interpret the Table**:
- **Risk / Trade**: Total risk amount based on your portfolio and risk percentage.
- **VWAP→Band Dist**: Dollar distance from VWAP to the selected band.
- **Band % Diff**: Percentage difference between VWAP and the band, ensuring it stays within 0.3% of your portfolio.
- **Risk / Share**: Risk per share including stop distance and costs.
- **Shares**: Recommended number of shares to trade.
- **Position $**: Total position value based on shares and entry price.
3. **Trading Strategy**:
- Use the VWAP as a trend indicator and the bands for potential entry/exit points.
- Adjust your position size to align with the calculated shares, ensuring your risk does not exceed 0.3% of your portfolio balance.
- Monitor the **Entry** and **Stop** plots for trade execution and risk management.
#### Notes:
- This indicator overlays on the price chart and requires volume data to function correctly.
- The table updates on the last bar and may not display on timeframes (1D or above) if "Hide VWAP on 1D or Above" is enabled.
- Ensure your portfolio balance is updated daily to reflect accurate risk calculations.
- Compatible with Pine Script v6; adjust to v5 if compatibility issues arise.
**Disclaimer**: This is not financial advice. Consult a financial advisor and avoid sharing personal identifiable information.
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.
[Top] LHAMA SupertrendLHAMA Supertrend - Advanced Adaptive Trend Following System
Overview
The LHAMA Supertrend is an innovative trend-following indicator that combines adaptive moving average technology with intelligent signal confirmation. Unlike traditional supertrend indicators that rely on simple moving averages, this system uses my Low-High Adaptive Moving Average (🦙 LHAMA) algorithm that dynamically adjusts to market volatility and price action patterns. It is much more responsive to sudden price changes than traditional supertrend indicators, allowing you to jump in earlier and catch more of the move, and it manages this responsiveness without significantly increasing the number of false signals.
What Makes This Original
This indicator introduces several unique concepts not found in standard trend-following tools:
LHAMA Algorithm : The core innovation is the Low-High Adaptive Moving Average, which adapts its responsiveness based on the frequency of new highs and lows within a lookback period. This creates a more intelligent baseline that responds appropriately to different market conditions.
Delayed Confirmation System : Rather than generating immediate signals on price crossovers, the indicator implements a sophisticated confirmation mechanism using slope analysis. Signals are only triggered when both trend direction and momentum align, significantly reducing false signals.
Volume Integration : Optional volume weighting enhances the adaptive calculation, giving more weight to price movements during high-volume periods.
Daily Reset Functionality : Unique daily reset feature helps realign the indicator after overnight gaps, particularly useful for equity markets.
How It Works
LHAMA Calculation
The LHAMA baseline adapts using a coefficient derived from:
Frequency of new highs and lows in the lookback period
Optional volume weighting factor
Smoothed adaptation rate based on market activity
The calculation:
lhama = previous_lhama + momentum_adaptation * (price - previous_lhama)
Where the momentum adaptation increases when markets are making new highs or lows, allowing faster response during trending conditions while providing stability during consolidation.
Signal Generation
The indicator uses a two-stage signal process:
Trend Identification : Price position relative to LHAMA determines basic trend bias
Slope Confirmation : ATR-normalized slope analysis confirms momentum direction
Signal Timing : Buy/sell signals only trigger when trend direction and slope momentum align
Visual Components
LHAMA Line : The adaptive baseline with optional angle-based gradient coloring that visualizes momentum strength
Trend Clouds : Dynamic fill areas that adapt to the last confirmed signal direction
ATR Halo : Opposite-side ATR band providing optional additional context for stop-loss placement
Confirmation Signals : Clear BUY/SELL labels only appear after full confirmation
How to Use
Basic Setup
Apply to any timeframe and symbol
Default LHAMA length of 15 periods works well for most applications
Accuracy depends greatly on chart timeframe and symbol, so make sure to backtest before relying on any signals. For example, ES and NQ work best on the 15m timeframe while GC and CL work best on the 5m.
Enable daily reset for equity markets to handle overnight gaps
Signal Interpretation
Immediate Heads-up : Small triangles show instant trend changes for awareness. These are your warnings to get ready to buy or sell if price takes off. (If many triangles are being printed in both directions, that is a warning that the market is ranging and you should not blindly follow a BUY/SELL signal without additional confirmation.)
Confirmed Signals : BUY/SELL labels appear only after slope confirms the direction
Cloud Color : Locked to the last confirmed signal direction for clear regime identification
Advanced Features
Flat Threshold : Adjust the angle threshold to filter out sideways market noise
Gradient Mode : Toggle between classic supertrend coloring and momentum-based gradients
ATR Halo : Use the opposite-side cloud as a more generous trailing stop level
Risk Management
The indicator provides multiple levels for stop-loss placement:
Tight : Edge of the main trend cloud
Standard : The LHAMA Line itself
Generous : ATR halo boundary
Best Practices
Timeframe Selection : Not all timeframes on all symbols are created equal. Make sure to scroll to the left and verify that your current chart timeframe isn't throwing out tons of bad signals. This will be easy to spot as it show up as constant rapid flipping from buy to sell.
Market Conditions : Performs best in trending markets. The flat threshold setting helps filter out poor performance during strong sideways action, but no indicator is perfect.
Confirmation : Wait for confirmed BUY/SELL signals rather than acting on immediate trend flips for better risk-adjusted returns.
Key Parameters
LHAMA Length (15) : Controls the lookback period for adaptive calculation
Daily Reset : Helps maintain accuracy across overnight gaps
Flat Threshold (5°) : Filters out low-momentum signals
Volume Weighting : Enhances adaptation during high-volume periods
Alerts
The indicator provides two alert types:
"BUY (confirmed)": Triggers when bullish trend and upward slope align
"SELL (confirmed)": Triggers when bearish trend and downward slope align
These alerts fire only on confirmed signals, not on immediate price crossovers, providing higher-quality notifications.
Innovation Summary
This indicator advances trend-following methodology by introducing adaptive baseline calculation, intelligent signal confirmation, and comprehensive visual feedback systems. The combination of LHAMA adaptation, slope-based confirmation, and multi-layered risk management tools creates a more sophisticated approach to trend analysis than traditional supertrend indicators.
The result is a tool that maintains responsiveness during trending conditions while providing stability during consolidation, with clear visual cues for entry, exit, and risk management decisions.
VIX Term Structure Tracker [VX1!/VX2!]1. Data Preparation
The script starts by fetching four key data series on a daily ("D") timeframe:
VIX (CBOE:VIX): The spot VIX index, a real-time measure of market expectations of future volatility.
VX1! (CBOE:VX1!): The price of the front-month (nearest to expiration) VIX futures contract.
VX2! (CBOE:VX2!): The price of the next-month VIX futures contract.
SPX (SP:SPX): The S&P 500 Index, which serves as a benchmark for the overall market.
2. Term Structure and Market Psychology
The core of the indicator lies in analyzing the relationship between the futures prices.
term_slope = vx2 - vx1: This calculates the difference between the next-month and front-month VIX futures prices.
Contango: If vx2 > vx1, the slope is positive, and the market is in contango. This is the "normal" state, where traders expect volatility to be lower in the future. The script colors this background a light green.
Backwardation: If vx2 < vx1, the slope is negative, and the market is in backwardation. This is a rare state indicating elevated fear. It means traders are willing to pay a premium for short-term protection against volatility, implying that an increase in fear is imminent. The script colors this background a light red.
3. Roll Yield Calculation
roll_yield = ((vx1 - vix) / days_to_expiry) * 100: This calculates the estimated return (or loss) from rolling a futures position from the spot VIX to the front-month future. This is a key metric for understanding the cost of holding VIX futures. A negative roll yield means it is expensive to hold a long VIX position.
4. Equilibrium and Z-Score
This section of the code provides a statistical measure to determine how extreme the current term structure is compared to its historical average.
avg_slope = ta.sma(term_slope, 252): This calculates the one-year simple moving average of the term structure slope.
z_score: This is the most powerful part of the indicator. It measures how many standard deviations the current term_slope is from its one-year average.
A Z-score of +2 or higher indicates the market is in an extreme state of contango (complacency), where volatility is abnormally low.
A Z-score of -2 or lower indicates an extreme state of backwardation (fear), where there's an abnormal surge in short-term volatility expectations.
5. Visualizations & Signals
The script presents a comprehensive view of these metrics on the chart.
plot(term_slope): Shows a blue line representing the VIX term structure slope.
bgcolor(...): Visually highlights periods of contango (light green) and backwardation (light red).
plot(roll_yield): Displays a column chart showing the roll yield, indicating the cost or benefit of holding VIX futures.
plot(z_score): Shows an orange line representing the Z-score, with horizontal lines at +2 and -2 to highlight extreme conditions.
plotshape(...): These are your trading signals. A red arrow pointing up (shape.labelup) appears at the bottom of the chart when the Z-score drops below -2 (extreme backwardation), and a green arrow pointing down (shape.labeldown) appears at the top when the Z-score goes above +2 (extreme contango).
6. Interpretation and Trading Signals
The script provides a clear framework for interpreting market sentiment:
Extreme Backwardation Signal (Red Arrow Up): When the Z-score falls to -2 or below, it signals a period of extreme market fear. This is often an excellent contrarian signal for buying the VIX (or related products) and/or for caution in long equity positions.
Extreme Contango Signal (Green Arrow Down): When the Z-score rises to +2 or above, it signals a period of extreme market complacency. This can be a contrarian signal for selling the VIX (or related products) and/or for potential short-term weakness in the S&P 500.
The VIX/SPX Risk Ratio also provides a good visual of volatility relative to the S&P 500, with an increasing ratio signaling a rising risk environment.
Ultimately, this indicator provides a powerful way to visualize the VIX futures term structure and use statistical analysis (Z-score) to find high-probability signals of extreme market sentiment.
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).
