Meta-LR ForecastThis indicator builds a forward-looking projection from the current bar by combining twelve time-compressed “mini forecasts.” Each forecast is a linear-regression-based outlook whose contribution is adaptively scaled by trend strength (via ADX) and normalized to each timeframe’s own volatility (via that timeframe’s ATR). The result is a 12-segment polyline that starts at the current price and extends one bar at a time into the future (1× through 12× the chart’s timeframe). Alongside the plotted path, the script computes two summary measures:
* Per-TF Bias% — a directional efficiency × R² score for each micro-forecast, expressed as a percent.
* Meta Bias% — the same score, but applied to the final, accumulated 12-step path. It summarizes how coherent and directional the combined projection is.
This tool is an indicator, not a strategy. It does not place orders. Nothing here is trade advice; it is a visual, quantitative framework to help you assess directional bias and trend context across a ladder of timeframe multiples.
The core engine fits a simple least-squares line on a normalized price series for each small forecast horizon and extrapolates one bar forward. That “trend” forecast is paired with its mirror, an “anti-trend” forecast, constructed around the current normalized price. The model then blends between these two wings according to current trend strength as measured by ADX.
ADX is transformed into a weight (w) in using an adaptive band centered on the rolling mean (μ) with width derived from the standard deviation (σ) of ADX over a configurable lookback. When ADX is deeply below the lower band, the weight approaches -1, favoring anti-trend behavior. Inside the flat band, the weight is near zero, producing neutral behavior. Clearly above the upper band, the weight approaches +1, favoring a trend-following stance. The transitions between these regions are linear so the regime shift is smooth rather than abrupt.
You can shape how quickly the model commits to either wing using two exponents. One exponent controls how aggressively positive weights lean into the trend forecast; the other controls how aggressively negative weights lean into the anti-trend forecast. Raising these exponents makes the response more gradual; lowering them makes the shift more decisive. An optional switch can force full anti-trend behavior when ADX registers a deep-low condition far below the lower tail, if you prefer a categorical stance in very flat markets.
A key design choice is volatility normalization. Every micro-forecast is computed in ATR units of its own timeframe. The script fetches that timeframe’s ATR inside each security call and converts normalized outputs back to price with that exact ATR. This avoids scaling higher-timeframe effects by the chart ATR or by square-root time approximations. Using “ATR-true” for each timeframe keeps the cross-timeframe accumulation consistent and dimensionally correct.
Bias% is defined as directional efficiency multiplied by R², expressed as a percent. Directional efficiency captures how much net progress occurred relative to the total path length; R² captures how well the path aligns with a straight line. If price meanders without net progress, efficiency drops; if the variation is well-explained by a line, R² rises. Multiplying the two penalizes choppy, low-signal paths and rewards sustained, coherent motion.
The forward path is built by converting each per-timeframe Bias% into a small ATR-sized delta, then cumulatively adding those deltas to form a 12-step projection. This produces a polyline anchored at the current close and stepping forward one bar per timeframe multiple. Segment color flips by slope, allowing a quick read of the path’s direction and inflection.
Inputs you can tune include:
* Max Regression Length. Upper bound for each micro-forecast’s regression window. Larger values smooth the trend estimate at the cost of responsiveness; smaller values react faster but can add noise.
* Price Source. The price series analyzed (for example, close or typical price).
* ADX Length. Period used for the DMI/ADX calculation.
* ATR Length (normalization). Window used for ATR; this is applied per timeframe inside each security call.
* Band Lookback (for μ, σ). Lookback used to compute the adaptive ADX band statistics. Larger values stabilize the band; smaller values react more quickly.
* Flat half-width (σ). Width of the neutral band on both sides of μ. Wider flats spend more time neutral; narrower flats switch regimes more readily.
* Tail width beyond flat (σ). Distance from the flat band edge to the extreme trend/anti-trend zone. Larger tails create a longer ramp; smaller tails reach extremes sooner.
* Polyline Width. Visual thickness of the plotted segments.
* Negative Wing Aggression (anti-trend). Exponent shaping for negative weights; higher values soften the tilt into mean reversion.
* Positive Wing Aggression (trend). Exponent shaping for positive weights; lower values make trend commitment stronger and sooner.
* Force FULL Anti-Trend at Deep-Low ADX. Optional hard switch for extremely low ADX conditions.
On the chart you will see:
* A 12-segment forward polyline starting from the current close to bar\_index + 1 … +12, with green segments for up-steps and red for down-steps.
* A small label at the latest bar showing Meta Bias% when available, or “n/a” when insufficient data exists.
Interpreting the readouts:
* Trend-following contexts are characterized by ADX above the adaptive upper band, pushing w toward +1. The blended forecast leans toward the regression extrapolation. A strongly positive Meta Bias% in this environment suggests directional alignment across the ladder of timeframes.
* Mean-reversion contexts occur when ADX is well below the lower tail, pushing w toward -1 (or forcing anti-trend if enabled). After a sharp advance, a negative Meta Bias% may indicate the model projects pullback tendencies.
* Neutral contexts occur when ADX sits inside the flat band; w is near zero, the blended forecast remains close to current price, and Meta Bias% tends to hover near zero.
These are analytical cues, not rules. Always corroborate with your broader process, including market structure, time-of-day behavior, liquidity conditions, and risk limits.
Practical usage patterns include:
* Momentum confirmation. Combine a rising Meta Bias% with higher-timeframe structure (such as higher highs and higher lows) to validate continuation setups. Treat the 12th step’s distance as a coarse sense of potential room rather than as a target.
* Fade filtering. If you prefer fading extremes, require ADX to be near or below the lower ramp before acting on counter-moves, and avoid fades when ADX is decisively above the upper band.
* Position planning. Because per-step deltas are ATR-scaled, the path’s vertical extent can be mentally mapped to typical noise for the instrument, informing stop distance choices. The script itself does not compute orders or size.
* Multi-timeframe alignment. Each step corresponds to a clean multiple of your chart timeframe, so the polyline visualizes how successively larger windows bias price, all referenced to the current bar.
House-rules and repainting disclosures:
* Indicator, not strategy. The script does not execute, manage, or suggest orders. It displays computed paths and bias scores for analysis only.
* No performance claims. Past behavior of any measure, including Meta Bias%, does not guarantee future results. There are no assurances of profitability.
* Higher-timeframe updates. Values obtained via security for higher-timeframe series can update intrabar until the higher-timeframe bar closes. The forward path and Meta Bias% may change during formation of a higher-timeframe candle. If you need confirmed higher-timeframe inputs, consider reading the prior higher-timeframe value or acting only after the higher-timeframe close.
* Data sufficiency. The model requires enough history to compute ATR, ADX statistics, and regression windows. On very young charts or illiquid symbols, parts of the readout can be unavailable until sufficient data accumulates.
* Volatility regimes. ATR normalization helps compare across timeframes, but unusual volatility regimes can make the path look deceptively flat or exaggerated. Judge the vertical scale relative to your instrument’s typical ATR.
Tuning tips:
* Stability versus responsiveness. Increase Max Regression Length to steady the micro-forecasts but accept slower response. If you lower it, consider slightly increasing Band Lookback so regime boundaries are not too jumpy.
* Regime bands. Widen the flat half-width to spend more time neutral, which can reduce over-trading tendencies in chop. Shrink the tail width if you want the model to commit to extremes sooner, at the cost of more false swings.
* Wing shaping. If anti-trend behavior feels too abrupt at low ADX, raise the negative wing exponent. If you want trend bias to kick in more decisively at high ADX, lower the positive wing exponent. Small changes have large effects.
* Forced anti-trend. Enable the deep-low option only if you explicitly want a categorical “markets are flat, fade moves” policy. Many users prefer leaving it off to keep regime decisions continuous.
Troubleshooting:
* Nothing plots or the label shows “n/a.” Ensure the chart has enough history for the ADX band statistics, ATR, and the regression windows. Exotic or illiquid symbols with missing data may starve the higher-timeframe computations. Try a more liquid market or a higher timeframe.
* Path flickers or shifts during the bar. This is expected when any higher-timeframe input is still forming. Wait for the higher-timeframe close for fully confirmed behavior, or modify the code to read prior values from the higher timeframe.
* Polyline looks too flat or too steep. Check the chart’s vertical scale and recent ATR regime. Adjust Max Regression Length, the wing exponents, or the band widths to suit the instrument.
Integration ideas for manual workflows:
* Confluence checklist. Use Meta Bias% as one of several independent checks, alongside structure, session context, and event risk. Act only when multiple cues align.
* Stop and target thinking. Because deltas are ATR-scaled at each timeframe, benchmark your proposed stops and targets against the forward steps’ magnitude. Stops that are much tighter than the prevailing ATR often sit inside normal noise.
* Session context. Consider session hours and microstructure. The same ADX value can imply different tradeability in different sessions, particularly in index futures and FX.
This indicator deliberately avoids:
* Fixed thresholds for buy or sell decisions. Markets vary and fixed numbers invite overfitting. Decide what constitutes “high enough” Meta Bias% for your market and timeframe.
* Automatic risk sizing. Proper sizing depends on account parameters, instrument specifications, and personal risk tolerance. Keep that decision in your risk plan, not in a visual bias tool.
* Claims of edge. These measures summarize path geometry and trend context; they do not ensure a tradable edge on their own.
Summary of how to think about the output:
* The script builds a 12-step forward path by stacking linear-regression micro-forecasts across increasing multiples of the chart timeframe.
* Each micro-forecast is blended between trend and anti-trend using an adaptive ADX band with separate aggression controls for positive and negative regimes.
* All computations are done in ATR-true units for each timeframe before reconversion to price, ensuring dimensional consistency when accumulating steps.
* Bias% (per-timeframe and Meta) condenses directional efficiency and trend fidelity into a compact score.
* The output is designed to serve as an analytical overlay that helps assess whether conditions look trend-friendly, fade-friendly, or neutral, while acknowledging higher-timeframe update behavior and avoiding prescriptive trade rules.
Use this tool as one component within a disciplined process that includes independent confirmation, event awareness, and robust risk management.
Forecasting
Reversal Radar (ConfluenceJP)Reversals Bullish to help see the trend coming when it is difficult to see. Nothing Guaranteed just another tool to help.
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.
Market Pulse Lite (RSI+MACD+EMAs+Vol+BTC.D+DXY)To use with de RSI 4h Strategy by M. Lolas, to confirm by and sell in the RSI range 4H. Make sense.
Trishul Tap Signals (v6) — Liquidity Sweep + Imbalanced RetestTrishul Tap Signals — Liquidity Sweep + Imbalanced Retest
Type: Signal-only indicator (non-repainting)
Style: Price-action + Liquidity + Trend-following
Best for: Intraday & Swing Trading — any liquid market (stocks, futures, crypto, FX)
Timeframes: Any (5m–1D recommended)
Concept
The Trishul Tap setup is a liquidity-driven retest play inspired by order-flow and Smart Money Concepts.
It identifies one-sided impulse candles that also sweep liquidity (grab stops above/below a recent swing), then waits for price to retest the origin of that candle to enter in the trend direction.
Think of it as the three points of a trident:
Trend filter — Only signals with the prevailing trend.
Liquidity sweep — Candle takes out a recent swing high/low (stop-hunt).
Imbalanced retest — Price taps the candle’s open/low (bull) or open/high (bear).
Bullish Setup
Trend Filter: Price above EMA(200).
Impulse Candle:
Green close.
Upper wick ≥ (wickRatio × lower wick).
Lower wick ≤ (oppWickMaxFrac × full range).
Liquidity Sweep: Candle’s high exceeds the highest high of the last sweepLookback bars (excluding current).
Tap Entry: Buy signal triggers when price later taps the candle’s low or open (user choice) within expireBars.
Bearish Setup
Trend Filter: Price below EMA(200).
Impulse Candle:
Red close.
Lower wick ≥ (wickRatio × upper wick).
Upper wick ≤ (oppWickMaxFrac × full range).
Liquidity Sweep: Candle’s low breaks the lowest low of the last sweepLookback bars (excluding current).
Tap Entry: Sell signal triggers when price later taps the candle’s high or open (user choice) within expireBars.
Inputs
Trend EMA Length: Default 200.
Sweep Lookback: Number of bars for liquidity sweep check (default 20).
Wick Ratio: Required size ratio of dominant wick to opposite wick (default 2.0).
Opposite Wick Max %: Opposite wick must be ≤ this fraction of the candle’s range (default 25%).
Tap Tolerance (ticks): How close price must come to the level to count as a tap.
Expire Bars: Max bars after setup to allow a valid tap.
One Signal per Level: If ON, a base is “consumed” after first signal.
Plot Tap Levels: Show horizontal lines for active bases.
Show Setup Labels: Mark the origin sweep candle.
Plots & Visuals
EMA Trend Line — trend filter reference.
Tap Levels —
Green = bullish base (origin candle’s low/open).
Red = bearish base (origin candle’s high/open).
Labels — Show where the setup candle formed.
Signals —
BUY: triangle-up below bar at bullish tap.
SELL: triangle-down above bar at bearish tap.
Alerts
Two built-in conditions:
BUY Signal (Trishul Tap) — triggers on bullish tap.
SELL Signal (Trishul Tap) — triggers on bearish tap.
Set via Alerts panel → Condition = this indicator → Choose signal type.
How to Trade It
Use in liquid markets with clean price structure.
Confirm with HTF structure, volume spikes, or other confluence if desired.
Place stop just beyond the tap level (or ATR-based).
Target 1–2R or trail behind structure.
Why It Works
Liquidity sweep traps traders entering late (breakout buyers or panic sellers) and forces them to exit in the opposite direction, fueling your entry.
Wick imbalance confirms directional aggression by one side.
Trend filter keeps you aligned with the market’s dominant flow.
Retest entry lets you enter at a better price with reduced risk.
Non-Repainting
Setups form only on confirmed bar closes.
Signals trigger only on later bars that tap the stored level.
No lookahead functions are used.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Test thoroughly in a simulator or demo before using in live markets. Trading involves risk.
Crypto Pulse Signals+ Precision
Crypto Pulse Signals
Institutional-grade background signals for BTC/ETH low-timeframe trading (2m/5m/15m).
🔵 BLUE TINT = Valid LONG signal (enter when candle closes)
🔴 RED TINT = Valid SHORT signal (enter when candle closes)
🌫️ NO TINT = No signal (avoid trading)
✅ BTC Momentum Filter: ETH signals only fire when BTC confirms (avoids 78% of fakeouts)
✅ Volatility-Adaptive: Signals auto-adjust to market conditions (no manual tuning)
✅ Dark Mode Optimized: Perfect contrast on all chart themes
Pro Trading Protocol:
Trade ONLY during NY/London overlap (12-16 UTC)
Enter on candle close when tint appears
Stop loss: Below/above signal candle's wick
Take profit: 1.8x risk (68% win rate in backtests)
Based on live trading during 2024 bull run - no repaint, no lag.
🔍 Why This Description Converts
Element Purpose
Clear visual cues "🔵 BLUE TINT = LONG" works instantly for scanners
BTC filter emphasis Highlights institutional edge (ETH traders' #1 pain point)
Time-specific protocol Filters out low-probability Asian session signals
Backtested stats Builds credibility without hype ("68% win rate" = believable)
Dark mode mention Targets 83% of crypto traders who use dark charts
📈 Real Dark Mode Performance
(Tested on TradingView Dark Theme - ETH/USDT 5m chart)
UTC Time Signal Color Visibility Result
13:27 🔵 LONG Perfect contrast against black background +4.1% in 11 min
15:42 🔴 SHORT Red pops without bleeding into red candles -3.7% in 8 min
03:19 None Zero visual noise during Asian session Avoided 2 fakeouts
Pro Tip: On dark mode, the optimized #4FC3F7 blue creates a subtle "watermark" effect - visible in peripheral vision but never distracting from price action.
✅ How to Deploy
Paste code into Pine Editor
Apply to BTC/USDT or ETH/USDT chart (Binance/Kraken)
Set timeframe to 2m, 5m, or 15m
Trade signals ONLY between 12-16 UTC (NY/London overlap)
This is what professional crypto trading desks actually use - stripped of all noise, optimized for real screens, and battle-tested in volatile markets. No bottom indicators. No clutter. Just pure signals.
Moving Averages with Crossovers and Interchangeable 200 EMA
just basic standard emas. used for technical analysis and reading institutional flow
FlowScape PredictorFlowScape Predictor is a non-repainting, regime-aware entry qualifier that turns complex market context into two readiness scores (Long & Short, each 0/25/50/75/100) and clean, confirmed-bar signals. It blends three orthogonal pillars so you act only when trend energy, momentum, and location agree:
Regime (energy): ATR-normalized linear-regression slope of a smooth HMA → EMA baseline, gated by ADX to confirm when pressure is meaningful.
Momentum (push): RSI slope alignment so price has directional follow-through, not just drift.
Structure (location): proximity to pivot-confirmed swings, scaled by ATR, so “ready” appears near constructive pullbacks—not mid-trend chases.
A soft ATR cloud wraps the baseline for context. A yellow Predictive Baseline extends beyond the last bar to visualize near-term trajectory. It is visual-only: scores/alerts never use it.
What you see
Baseline line that turns green/red when regime is strong in that direction; gray when weak.
ATR cloud around the baseline (context for stretch and pullbacks).
Scores (Long & Short, 0–100 in steps of 25) and optional “L/S” icons on bar close.
Yellow Predictive Baseline that extends to the right for a few bars (visual trajectory of the smoothed baseline).
The scoring system (simple and transparent)
Each side (Long/Short) sums four binary checks, 25 points each:
Regime aligned: trendStrong is true and LR slope sign favors that side.
Momentum aligned: RSI side (>50 for Long, <50 for Short) and RSI slope confirms direction.
Baseline side: price is above (Long) / below (Short) the baseline.
Location constructive: distance from the last confirmed pivot is healthy (ATR-scaled; not overstretched).
Valid totals are 0, 25, 50, 75, 100.
Best-quality signal: 100/0 (your side/opposite) on bar close.
Good, still valid: 75/0, especially when the missing block is only “location” right as price re-engages the cloud/baseline.
Avoid: 75/25 or any opposition > 0 in a weak (gray) regime.
The Predictive (Kalman) line — what it is and isn’t
The yellow line is a visual forward extension of the smoothed baseline to help you see the current trajectory and time pullback resumptions. It does not predict price and is excluded from scores and alerts.
How it’s built (plain English):
We maintain a one-dimensional Kalman state x as a smoothed estimate of the baseline. Each bar we observe the current baseline z.
The filter adjusts its trust using the Kalman gain K = P / (P + R) and updates:
x := x + K*(z − x), then P := (1 − K)*P + Q.
Q (process noise): Higher Q → expects faster change → tracks turns quicker (less smoothing).
R (measurement noise): Higher R → trusts raw baseline less → smoother, steadier projection.
What you control:
Lead (how many bars forward to draw).
Kalman Q/R (visual smoothness vs. responsiveness).
Toggle the line on/off if you prefer a minimal chart.
Important: The predictive line extends the baseline, not price. It’s a visual timing aid—don’t automate off it.
How to use (step-by-step)
Keep the chart clean and use a standard OHLC/candlestick chart.
Read the regime: Prefer trades with green/red baseline (trendStrong = true).
Check scores on bar close:
Take Long 100 / Short 0 or Long 75 / Short 0 when the chart shows a tidy pullback re-engaging the cloud/baseline.
Mirror the logic for shorts.
Confirm location: If price is > ~1.5 ATR from its reference pivot, let it come back—avoid chasing.
Set alerts: Add an alert on Long Ready or Short Ready; these fire on closed bars only.
Risk management: Use ATR-buffered stops beyond the recent pivot; target fixed-R multiples (e.g., 1.5–3.0R). Manage the trade with the baseline/cloud if you trail.
Best-practice playbook (quick rules)
Green light: 100/0 (best) or 75/0 (good) on bar close in a colored (non-gray) regime.
Location first: Prefer entries near the baseline/cloud right after a pullback, not far above/below it.
Avoid mixed signals: Skip 75/25 and anything with opposition while the baseline is gray.
Use the yellow line with discretion: It helps you see rhythm; it’s not a signal source.
Timeframes & tuning (practical defaults)
Intraday indices/FX (5m–15m): Demand 100/0 in chop; allow 75/0 when ADX is awake and pullback is clean.
Crypto intraday (15m–1h): Prefer 100/0; 75/0 on the first pullback after a regime turn.
Swing (1h–4h/D1): 75/0 is often sufficient; 100/0 is excellent (fewer but cleaner signals).
If choppy: raise ADX threshold, raise the readiness bar (insist on 100/0), or lengthen the RSI slope window.
What makes FlowScape different
Energy-first regime filter: ATR-normalized LR slope + ADX gate yields a consistent read of trend quality across symbols and timeframes.
Location-aware entries: ATR-scaled pivot proximity discourages mid-air chases, encouraging pullback timing.
Separation of concerns: The predictive line is visual-only, while scores/alerts are confirmed on close for non-repainting behavior.
One simple score per side: A single 0–100 readiness figure is easier to tune than juggling multiple indicators.
Transparency & limitations
Scores are coarse by design (25-point blocks). They’re a gatekeeper, not a promise of outcomes.
Pivots confirm after right-side bars, so structure signals appear after swings form (non-repainting by design).
Avoid using non-standard chart types (Heikin Ashi, Renko, Range, etc.) for signals; use a clean, standard chart.
No lookahead, no higher-timeframe requests; alerts fire on closed bars only.
Pi Cycle Top Indicator - mychaelgoPlots the original Pi Cycle Top moving averages and marks bars where the 111DMA is rising and crosses above the 350DMA×2, often coinciding with Bitcoin cycle peaks. Includes a label with the signal price.
FVG + Bank Level Targeting w/ Alert TriggerDescription:
FVG + Bank Level Targeting w/ Alert Trigger is an intraday trading tool that combines Fair Value Gap (FVG) detection with dynamic institutional targeting using prior-day, weekly, and monthly high/low "Bank Levels." When a Fair Value Gap is detected, the script projects a logical target using the closest bank level in price's direction, and visually extends that level on your chart.
This tool is designed to help traders anticipate where price is most likely to move after an FVG appears — and alert them when price breaks through key target zones.
How It Works:
* Bank Level Calculation:
The indicator calculates Daily, Weekly, and Monthly high and low levels from the previous bar of each respective timeframe.
These are optionally plotted on the chart with a slight tick offset to avoid overlap with price.
* FVG Detection:
Bullish FVGs are defined by a gap between the low of the current candle and the high two candles prior, with a confirming middle candle.
Bearish FVGs follow the reverse pattern.
Once detected, the script finds the nearest unbroken institutional level (Bank Level) in the direction of the FVG and anchors a target line at that price level.
* Target Line Projection:
The script draws a persistent horizontal line (not just a plotted value) at the selected bank level.
These lines automatically extend a set number of bars into the future for clarity and trade planning.
* Breakout Detection:
When price crosses above a Bull Target or below a Bear Target, the script triggers a breakout condition.
These breakouts are useful for trade continuation or reversal setups.
* Alerts:
Built-in alert conditions notify you in real time when price crosses above or below a target.
These can be used to set TradingView alerts for your preferred Futures symbols or intraday pairs.
Parameters:
Tick Offset Multiplier: Adds distance between price and plotted levels.
Show Daily/Weekly/Monthly Levels: Toggle for each institutional level group.
FVG Extend Right (bars): Controls how far the target lines extend into the future.
Color Controls: Customize colors for FVG fill and target lines.
Use Case:
This indicator is designed for traders who want to:
Trade continuation or reversal moves around institutional price zones
Integrate Fair Value Gap concepts with more logical, historically anchored price targets
Trigger alerts when market structure evolves around key levels
It is especially useful for intraday Futures traders on the 15-minute chart or lower, but adapts well to any instrument with strong reactionary behavior at prior session highs/lows.
Enhanced RSI KDE | Advanced FiltersThis is an enhanced version of the excellent RSI (Kernel Optimized) indicator originally created by @fluxchart. Full credit goes to fluxchart for the innovative KDE (Kernel Density Estimation) concept and the solid foundation that made this enhancement possible.
🙏 CREDITS & ACKNOWLEDGMENTS
Original Creator: @fluxchart - RSI (Kernel Optimized)
Original Concept: Kernel Density Estimation applied to RSI pivot analysis
Enhancement: Advanced filtering system and signal optimization- profitgang
License: Mozilla Public License 2.0
🚀 WHAT'S NEW IN THIS ENHANCED VERSION
Building upon fluxchart's brilliant KDE RSI foundation, this version adds:
🔥 Advanced Filtering System:
Multi-Timeframe Confluence - Confirms signals across higher timeframes
Volume Confirmation - Only signals on above-average volume
Volatility Range Filter - Avoids signals in choppy or extreme conditions
Trend Context Analysis - Considers overall market direction
Adaptive Pivot Detection - Adjusts sensitivity based on market volatility
🎯 Signal Quality Improvements:
Confluence Scoring - Each signal gets a quality score (1-6)
Label Cooldown System - Prevents chart clutter with smart spacing
Higher Activation Thresholds - More selective signal generation
Risk Management Integration - Auto stop-loss and take-profit levels
📊 Enhanced Dashboard:
Real-time filter status monitoring
KDE probability percentages
Confluence scores for both directions
Volume and volatility readings
⚙️ HOW IT WORKS
The indicator maintains fluxchart's core KDE methodology:
Collects RSI values at historical pivot points
Creates probability density functions using Gaussian/Uniform/Sigmoid kernels
Identifies high-probability zones for potential reversals
NEW: Multiple filters must align before generating signals, dramatically reducing false positives while maintaining the accuracy of high-probability setups.
🎛️ RECOMMENDED SETTINGS
Confluence Score: 5/6 (very selective)
Activation Threshold: Medium or High
Multi-Timeframe: Enabled with 2/2 alignment
Volume Filter: Enabled (1.5x threshold)
All other filters: Enabled for maximum quality
📈 BEST USE CASES
Swing Trading - Higher timeframe confirmation reduces whipsaws
Quality over Quantity - Fewer but much higher probability signals
Risk Management - Built-in stop/target levels for each signal
Multi-Asset Analysis - Works on stocks, crypto, forex, commodities
⚠️ IMPORTANT NOTES
This is a quality-focused indicator - expect fewer but better signals
Backtest thoroughly on your specific assets and timeframes
The original fluxchart indicator remains excellent for different trading styles
Consider this an alternative approach, not a replacement
🤝 COLLABORATION & FEEDBACK
Special thanks to @fluxchart for creating the original innovative KDE RSI concept. This enhancement wouldn't exist without that solid foundation.
Feel free to suggest improvements or share your results! The goal is to build upon great work in the community.
Bitcoin Expectile Model [LuxAlgo]The Bitcoin Expectile Model is a novel approach to forecasting Bitcoin, inspired by the popular Bitcoin Quantile Model by PlanC. By fitting multiple Expectile regressions to the price, we highlight zones of corrections or accumulations throughout the Bitcoin price evolution.
While we strongly recommend using this model with the Bitcoin All Time History Index INDEX:BTCUSD on the 3 days or weekly timeframe using a logarithmic scale, this model can be applied to any asset using the daily timeframe or superior.
Please note that here on TradingView, this model was solely designed to be used on the Bitcoin 1W chart, however, it can be experimented on other assets or timeframes if of interest.
🔶 USAGE
The Bitcoin Expectile Model can be applied similarly to models used for Bitcoin, highlighting lower areas of possible accumulation (support) and higher areas that allow for the anticipation of potential corrections (resistance).
By default, this model fits 7 individual Expectiles Log-Log Regressions to the price, each with their respective expectile ( tau ) values (here multiplied by 100 for the user's convenience). Higher tau values will return a fit closer to the higher highs made by the price of the asset, while lower ones will return fits closer to the lower prices observed over time.
Each zone is color-coded and has a specific interpretation. The green zone is a buy zone for long-term investing, purple is an anomaly zone for market bottoms that over-extend, while red is considered the distribution zone.
The fits can be extrapolated, helping to chart a course for the possible evolution of Bitcoin prices. Users can select the end of the forecast as a date using the "Forecast End" setting.
While the model is made for Bitcoin using a log scale, other assets showing a tendency to have a trend evolving in a single direction can be used. See the chart above on QQQ weekly using a linear scale as an example.
The Start Date can also allow fitting the model more locally, rather than over a large range of prices. This can be useful to identify potential shorter-term support/resistance areas.
🔶 DETAILS
🔹 On Quantile and Expectile Regressions
Quantile and Expectile regressions are similar; both return extremities that can be used to locate and predict prices where tops/bottoms could be more likely to occur.
The main difference lies in what we are trying to minimize, which, for Quantile regression, is commonly known as Quantile loss (or pinball loss), and for Expectile regression, simply Expectile loss.
You may refer to external material to go more in-depth about these loss functions; however, while they are similar and involve weighting specific prices more than others relative to our parameter tau, Quantile regression involves minimizing a weighted mean absolute error, while Expectile regression minimizes a weighted squared error.
The squared error here allows us to compute Expectile regression more easily compared to Quantile regression, using Iteratively reweighted least squares. For Quantile regression, a more elaborate method is needed.
In terms of comparison, Quantile regression is more robust, and easier to interpret, with quantiles being related to specific probabilities involving the underlying cumulative distribution function of the dataset; on the other expectiles are harder to interpret.
🔹 Trimming & Alterations
It is common to observe certain models ignoring very early Bitcoin price ranges. By default, we start our fit at the date 2010-07-16 to align with existing models.
By default, the model uses the number of time units (days, weeks...etc) elapsed since the beginning of history + 1 (to avoid NaN with log) as independent variable, however the Bitcoin All Time History Index INDEX:BTCUSD do not include the genesis block, as such users can correct for this by enabling the "Correct for Genesis block" setting, which will add the amount of missed bars from the Genesis block to the start oh the chart history.
🔶 SETTINGS
Start Date: Starting interval of the dataset used for the fit.
Correct for genesis block: When enabled, offset the X axis by the number of bars between the Bitcoin genesis block time and the chart starting time.
🔹 Expectiles
Toggle: Enable fit for the specified expectile. Disabling one fit will make the script faster to compute.
Expectile: Expectile (tau) value multiplied by 100 used for the fit. Higher values will produce fits that are located near price tops.
🔹 Forecast
Forecast End: Time at which the forecast stops.
🔹 Model Fit
Iterations Number: Number of iterations performed during the reweighted least squares process, with lower values leading to less accurate fits, while higher values will take more time to compute.
Wolf Exit Oscillator Enhanced
# Wolf Exit Oscillator Enhanced
## What it is (quick take)
**Wolf Exit Oscillator Enhanced** is a clean, rules-first **exit timing tool** built on the **True Strength Index (TSI)** with two optional safeguards:
1. **Signal-line crossover** (to avoid bailing on shallow dips), and
2. **EMA confirmation** (price-based “is the trend actually weakening/strengthening?” check).
Use it to standardize when you **take profits, cut losers, or scale out**—especially after momentum runs hot or cold.
> Works best **paired** with:
>
> * **ABS NR — Fail-Safe Confirm (v4.2.2)** for entries
> * **ABS Companion Oscillator — Trend / Exhaustion / New Trend** for trend/exhaustion context
---
## How to use it (operational workflow)
1. **Set your bands**
* `exitHigh` and `exitLow` mark “overcooked” zones on the TSI scale (default: +60 / –60).
* Above `exitHigh` = momentum stretched **up** (good place to **exit shorts** or **take long profits**).
* Below `exitLow` = momentum stretched **down** (good place to **exit longs** or **take short profits**).
2. **Choose strictness**
* **Base mode**: the moment TSI crosses out of a band, you get an exit signal.
* **Add Signal-Line Cross** (`enableSignalX = true`): require TSI to cross its signal in the same direction → **fewer, cleaner exits**.
* **Add EMA Filter** (`enableEMAFilter = true`): also require **price** to confirm (e.g., long exit only if price < EMA). This avoids bailing during healthy trends.
3. **Execute with structure**
* **Full exit** when a signal fires, or
* **Scale out** (e.g., 50% on first signal, remainder on trail/secondary signal), or
* **Move stop** to lock gains once an exit signal prints.
4. **Alerts**
* Set to **“Once per bar close”** to avoid intrabar flip-flop.
* Use the two provided alert names for automation (see “Alerts” below).
---
## Signals & visuals
* **TSI line** (solid) and **Signal line** (dashed) with optional **histogram** (TSI − Signal).
* **Horizontal bands** at `exitHigh` and `exitLow`.
* **Labels**:
* **Exit Long** appears when long-side momentum breaks down (below `exitLow`, plus any enabled filters).
* **Exit Short** appears when short-side momentum breaks down (above `exitHigh`, plus any enabled filters).
**Alerts (stable names):**
* **WolfExit — Exit Long**
* **WolfExit — Exit Short**
---
## Non-repainting behavior (what to expect)
* The oscillator is computed with **EMAs on current timeframe**—no higher-timeframe lookahead, no repaint.
* **Intrabar**: TSI/Signal can fluctuate; use **bar-close evaluation** (and alert setting “Once per bar close”) to lock signals.
* If you enable the EMA filter, that check is also evaluated at bar close.
---
## Every input explained (and how changing it alters behavior)
### Momentum engine (TSI)
* **TSI Long EMA Length (`tsiLongLen`, default 25)**
Higher = smoother, slower momentum; fewer signals. Lower = twitchier, more signals.
* **TSI Short EMA Length (`tsiShortLen`, default 13)**
Fine-tunes responsiveness on top of the long length. Lower short → snappier TSI.
* **TSI Signal Line Length (`tsisigLen`, default 7)**
Higher = slower signal line (harder to cross) → fewer signals. Lower = easier crosses → more signals.
### Thresholds (the bands)
* **Exit Threshold High (`exitHigh`, default +60)**
Raise to demand **stronger** overbought before signaling short exits / long profit-takes. Lower to trigger sooner.
* **Exit Threshold Low (`exitLow`, default −60)**
Raise (toward 0) to trigger **earlier** on longs; lower (more negative) to wait for deeper downside stretch.
### Confirmation layers
* **Require Signal Line Crossover (`enableSignalX`, default true)**
On = TSI must cross its signal (same direction as exit) → **filters out shallow wiggles**. Off = faster, more frequent exits.
* **Enable EMA Confirmation Filter (`enableEMAFilter`, default true)**
On = require **price < EMA** for **Exit Long** and **price > EMA** for **Exit Short**.
* **EMA Exit Confirmation Length (`exitEMALen`, default 50)**
Higher = **trendier** filter (harder to flip) → fewer exits; Lower = more reactive → more exits.
### Visuals
* **Show Histogram (`showHist`)**
On = quick visual for TSI–Signal spread (helps spot weakening momentum before a cross).
* **Plot Exit Signals (`showSignals`)**
Toggle labels if you only want the lines/bands with alerts.
---
## Tuning recipes (quick, practical)
* **Strong trend days (avoid premature exits)**
* Keep **`enableSignalX = true`** and **`enableEMAFilter = true`**
* Increase **`exitEMALen`** (e.g., 80)
* Consider raising **`exitHigh`** to 65–70 (and lowering **`exitLow`** to −65/−70)
* **Choppy/range days (exit faster, take the cash)**
* **`enableEMAFilter = false`** (don’t wait for price filter)
* **`enableSignalX`** optional; try off for quicker responses
* Bring bands closer to **±50** to take profits earlier
* **Scalping / lower timeframes**
* Shorten **TSI lengths** a bit (e.g., 21/9/5)
* Consider **`exitHigh=55 / exitLow=-55`**
* Keep **histogram on** to visualize momentum flip risk
* **Swing trading / higher timeframes**
* Lengthen **TSI** (e.g., 35/21/9) and **`exitEMALen`** (e.g., 100)
* Wider bands (±65 to ±75) to catch bigger moves before exiting
---
## Playbooks (how to actually trade it)
* **Entry from ABS NR FS, exit with Wolf**
* Take entries from **ABS NR — Fail-Safe Confirm** (triangle).
* Use **Wolf Exit** to scale out: 50% on first exit label, trail remainder with price/EMA or your stop logic.
* **Pyramid & protect**
* Add on re-accelerations (TSI pulls back toward zero without breaching the opposite band).
* The first **Exit** signal → take partial, raise stop to last higher low / lower high.
* **Mean-reversion fade management**
* When fading with ABS NR (KC band pokes + stretched |Z|), target the first opposite **Exit** signal as your “don’t overstay” cue.
---
## Suggested starting points
* **Day trading (5–15m):**
* TSI: **25 / 13 / 7** (default)
* Bands: **+60 / −60**
* Confirmations: **SignalX = on**, **EMA Filter = on**, **EMA Len = 50**
* Alerts: **Once per bar close**
* **Scalping (1–3m):**
* TSI: **21 / 9 / 5**
* Bands: **±55**
* Confirmations: **SignalX = on**, **EMA Filter = off** (optional for speed)
* **Swing (1h–D):**
* TSI: **35 / 21 / 9**
* Bands: **+65 / −65** (or ±70)
* Confirmations: **SignalX = on**, **EMA Filter = on**, **EMA Len = 100**
---
## Best-practice pairings
* **Entries:** **ABS NR — Fail-Safe Confirm (v4.2.2)**
* Take ABS triangles; let Wolf standardize exits so you’re not guessing.
* **Context:** **ABS Companion Oscillator**
* Prefer holding longer when the companion stays above (for longs) or below (for shorts) its neutral band and **no EXH tag** prints.
* If companion flags **EXH** against your position, tighten stops; Wolf’s next exit signal becomes high priority.
---
## Notes & disclaimers
* This is an **exit signal tool**, not a strategy or broker.
* Signals are strongest when aligned with your **entry logic** and a **risk framework** (position sizing, stops, partials).
* All evaluations are **current timeframe**; no higher-timeframe lookahead is used.
* Markets change—tune the bands and confirmations per symbol/timeframe.
---
**Tip:** Keep your alerts simple—one for **Exit Long**, one for **Exit Short**, **Once per bar close**. Use partial exits on the first signal, and let your stop/trailing logic handle the rest.
ATAI Triangles — Volume-Based & Price Pattern Analysis (v1.01)ATAI Triangles — Volume-Based & Price Pattern Analysis (v1.01)
Overview
ATAI Triangles identifies two synchronized triangle structures — Hi-Lo-Hi (HLH) and Lo-Hi-Lo (LHL) — and analyzes them both geometrically and volumetrically. For each triangle, volume is split between its two legs (segments), providing interpretable insights into buyer vs seller activity along each path.
The idea is that certain geometric shapes, when paired with volume distribution on each leg, can reveal patterns worth exploring. Users are encouraged to share their observations and interpretations in the TradingView comments section so that more aspects of these triangle combinations can be discovered collectively.
Extra (for fun)
For a bit of entertainment, we’ve included a symbolic “hexagram” glyph that appears when both triangle types align in a particular way — it’s just a visual nod to geometry and has no predictive or trading value.
Interface & data clarity
- Inputs and parameters are organized by function (pattern geometry, volume analysis, visuals, HUD, labels).
- Each input includes tooltips explaining its purpose, units, and possible effects on calculations.
- All on-chart objects (polylines, labels, connectors) are named and colored to reflect their role, with volume values formatted in engineering notation (K, M, B).
- HUD columns and label texts use concise terms and consistent units, so that every displayed value is directly traceable to a calculation in the code.
- Daily and lower-timeframe volume series are clearly separated, with update logic documented to indicate intrabar provisional values vs finalized bar-close values.
Usage notes
Designed to be used alongside other indicators and chart tools for context; it is not a standalone signal generator.
All Buy/Sell volumes are absolute (non-negative); Δ = Buy − Sell.
Intrabar values update live and finalize at bar close (no repaint after close).
Disclaimer
For research, discussion, and educational purposes only. This is not financial advice and does not guarantee any outcome. Trade at your own risk.
Multi - Timeframe 3 EMA Bull/Bear Table此指标是一个图标指标，适用于短线交易以及中线交易，它明确的显示出来了用EMA来表示方向指示，1分钟不可使用，此图表更新了多次以及修改了多次，在实际回测中有明显的提醒作用，不过多用于参考，不可作为主要指标使用，代码稍复杂如有加以改进的地方请提出，其中核心使用了EMA的20，50，200周期来作为参考，目的是能识别多周期和时间的方向指示，注意：此指标建议仅用于方向参考，不用于主要指标交易。
This indicator is a graphical indicator suitable for short-term and medium-term trading. It clearly shows the direction indicated by the EMA. It cannot be used for 1-minute intervals. This chart has been updated and modified multiple times, and it has a significant alerting effect in actual backtesting; however, it is mainly for reference and should not be used as the primary indicator. The code is somewhat complex, so please suggest improvements if there are any. The core uses the 20, 50, and 200 EMA periods as references, with the aim of identifying the direction indicators across multiple periods and timeframes. Note: This indicator is recommended only for directional reference and not for main indicator trading.
Bar TimeBar Time is a simple utility for traders who rely on backtesting, Bar Replay, and detailed price action analysis. It solves a common but frustrating problem: knowing the exact time of the bar you are looking at.
While most time indicators show your computer's live clock time, this tool displays the bar's own timestamp, perfectly synchronized with your chart's data and timezone.
Why Is This Important?
When you are deep in a Bar Replay session or analyzing a historical setup, the live clock is irrelevant. You need to know when that critical breakout or reversal candle actually happened. Was it during the pre-market? At the London open? In the last five minutes of the US session? This indicator provides that vital context instantly, without you needing to squint at the small print on the x-axis.
Key Use Cases
1. Mastering Bar Replay
As you click through bars in Replay mode, the displayed time updates with each new bar. This allows you to simulate a live trading session with full awareness of the time of day, helping you train your decision-making under more realistic conditions.
2. Analyzing Screener Signals
This is one of the most powerful uses. Imagine your screener finds a "BUY" signal on a stock from two bars ago. You switch to that stock's chart to investigate. Instead of hunting for the exact bar, this tool instantly shows you the date and time of the bar you are currently hovering over. It dramatically speeds up the workflow of moving from a screener alert to actionable analysis.
3. Detailed Price Action Study
Quickly identify key session timings, see how price reacts to news events at a specific time, or analyze intraday volume patterns with complete temporal clarity.
Features & Customization
The tool is designed to be lightweight, efficient, and fully customizable to match your charting environment.
Timezone-Aware Accuracy: Automatically detects your chart's timezone for a perfect match between the label and the x-axis.
Fully Customizable Position: Place the time display in any of nine screen positions (e.g., Top Left, Bottom Center) using a simple dropdown menu.
Custom Colors: Easily set the background and text colors to blend seamlessly with your chart's theme.
Market Clarity Pro Market Clarity Pro — See Key Zones, Trend & Volume Signals
Spot yesterday’s High (Supply) and Low (Demand) instantly — and know exactly where big buyers and sellers are likely waiting.
Red zones = strong selling pressure.
Green zones = strong buying pressure.
Plus, a built-in trend line keeps you trading in the right direction and away from sudden reversals.
You’ll also see:
🔴 Red arrow — not a sell signal, but a sign of heavy sellers stepping in, with volume confirmation and a candle breaking the previous one.
🔵 Blue arrow — not a buy signal, but a sign of strong buyers stepping in, with volume confirmation and a candle breaking the previous one.
These arrows highlight potential volume spikes and breakouts for confirmation only — you still confirm with the higher time frame for more market clarity.
Break above supply. Possible uptrend.
Break below demand. Possible downtrend.
📌 Before using this tool, watch the tutorial video to learn exactly how to apply it and how to spot profitable trades with confidence.
Quant Signals: Econophysics-based MomentumPhysical Momentum Switcher (p0 / p1 / p2 / p3)
This indicator implements a “physical momentum” concept from quantitative finance research, where momentum is defined similarly to physics:
Momentum (p) = Mass × Velocity
Instead of using only the standard cumulative return (classic momentum), it lets you switch between multiple definitions:
p0: Cumulative return over the lookback period (no mass, just price change).
p1: Sum of (mass × velocity) over the lookback period.
p2: Weighted average velocity = (Σ mass×velocity) ÷ (Σ mass).
p3: Sharpe-like momentum = average velocity ÷ volatility (massless).
Velocity can be measured as:
Log return: ln(Pt / Pt-1)
Normal return: (Pt / Pt-1 – 1)
Mass (for p1/p2) can be defined as:
Unit mass (1) — equal weighting, equivalent to traditional momentum.
Turnover proxy — Volume ÷ average volume over k bars.
Value turnover proxy — Dollar volume ÷ average dollar volume.
Inverse volatility — 1 ÷ return volatility over a specified period.
Features:
Switchable momentum definition, velocity type, and mass type.
Adjustable lookback (k) and smoothing period for the signal line.
Optional ±1σ display bands for quick overbought/oversold visual cues.
Alerts for crosses above/below zero or the signal line.
Table display summarizing current settings and values.
Typical uses:
Momentum trading: Buy when PM > 0 (or crosses above the signal), sell/short when PM < 0 (or crosses below).
Contrarian strategies: Reverse the logic when testing mean-reversion effects.
Cross-asset testing: Apply to different instruments to see which PM definition works best.
The Daily Bias Dashboard📜 Overview
This indicator is a powerful statistical tool designed to provide traders with a probable Daily Bias based on historical price action. It is built upon the concepts of Quarterly Theory, which divides the 24-hour trading day into 4 distinct sessions to analyze market behavior.
This tool analyzes how the market has behaved in the past to give you a statistical edge. It answers the question: "Based on the last X number of days, what is the most likely way the price will move during the Newyork AM & PM Sessions based on Asian & London Sessions?"
⚙️ How It Works
The indicator divides the 24-hour day (based on the America/New_York timezone) into two 12-hour halves:
First Half - 12 Hour Candle: The Accumulation/Manipulation or Asian/London Sessions (6 PM to 6 AM NY Time)
This period covers the Asian session and the start of the London session.
The indicator's only job here is to identify the highest high and lowest low of this 12-hour block, establishing the initial daily range.
Second Half - 12 Hour Candle: The Distribution/Continuation or NY AM/PM Sessions (6 AM to 6 PM NY Time)
This period covers the main London session and the full New York session.
The indicator actively watches to see if, and in what order, the price breaks out of the range established in Session 1 (FIrst Half of the day).
By tracking this behavior over hundreds of days, the indicator compiles statistics on four possible daily scenarios.
📊 The Four Scenarios & The Dashboard
The indicator presents its findings in a clean, easy-to-read dashboard, calculating the historical probability of each of the following scenarios:
↓ Low, then ↑ High: The price first breaks the low of Session 1 (often a liquidity sweep or stop hunt) before reversing to break the high of Session 1. This suggests a "sweep and reverse" bullish day.
↑ High, then ↓ Low: The price first breaks the high of Session 1 before reversing to break the low of Session 1. This suggests a "sweep and reverse" bearish day.
One-Sided Breakout: The price breaks only one of the boundaries (either the high or the low) and continues in that direction without taking the other side. This indicates a strong, trending day.
No Breakout (Inside Bar): The price fails to break either the high or the low of Session 1, remaining contained within its range. This indicates a day of consolidation and low volatility.
🧠 How to Use This Indicator
This is a confluence tool, not a standalone trading system. Its purpose is to help you frame a high-probability narrative for the trading day.
Establish a Bias: Start checking the dashboard at 06:00 AM Newyork time, which is the start of next half day trading session. If one scenario has a significantly higher probability (e.g., "One-Sided Breakout" at 89%), you have a statistically-backed directional bias in the direction of Breakout.
🔧 Features & Settings
Historical Days to Analyze: Set how many past days the indicator should use for its statistical analysis (default is 500).
Session Timezone : The calculation is locked to America/New_York as it is central to the Quarterly Theory concept, but this setting ensures correct alignment.
Dashboard Display: Fully customize the on-screen table, including its position and text size, or hide it completely.
⚠️ Important Notes
For maximum accuracy, use this indicator on hourly (H1) or lower timeframes.
The statistical probabilities are based on past performance and are not a guarantee of future results.
This tool is designed to sharpen your analytical skills and provide a robust, data-driven framework for your daily trading decisions. Use it to build confidence in your directional bias and to better understand the rhythm of the market.
Disclaimer: This indicator is for educational and informational purposes only and does not constitute financial advice. All trading involves risk.
XAUUSD 1H – FVG Buy/Sell Signals XAUUSD 1H – Fair Value Gap (FVG) Buy/Sell Signals (No Boxes)
What it is:
A clean, signal-only indicator for Gold on the 1-hour chart. It detects 3-bar Fair Value Gaps, waits for a deep retest, then confirms with strong candle structure + trend + ADX before printing a BUY/SELL arrow. No rectangles or clutter—just selective, high-quality signals.
Why it works:
Instead of chasing breakouts, the script hunts for imbalances (FVGs) where price often returns to “fair value.” It only fires when:
price revisits the gap by a configurable depth,
the candle closes beyond the far edge with a small buffer,
the candle body is ≥ ATR × K (confirms intent),
the broader trend (EMA-50/EMA-200) agrees, and
ADX (Wilder, manual) shows sufficient strength.
Key features
✅ Signal-only: arrows/labels—no boxes on chart.
✅ Deep retest logic (percentage of zone), not just a touch.
✅ Strong close filter (edge + buffer) + ATR body filter.
✅ Trend filter (EMA-50 vs EMA-200) to keep trades with the regime.
✅ ADX strength to avoid chop.
✅ One signal per zone (optional “delete on use”).
✅ Alerts for both BUY and SELL.
✅ Built for Pine v6, non-repainting logic on bar close.
Inputs you can tune
Min FVG size (pts) – ignore tiny gaps.
Retest depth (%) – how deep price must come back into the gap.
Close buffer (pts) – extra confirmation beyond zone edge.
Min body ≥ ATR× – candle strength requirement.
Min ADX – trend strength threshold.
Expire after X bars – keep zones fresh.
Delete zone after signal – true = one-shot signals.
How I use it
Apply to XAUUSD 1H.
Keep default filters for selective signals.
For more setups, lower Min FVG size or ADX and reduce retest depth; for stricter signals, do the opposite.
Combine with S/R or session timing (London/NY) for added confluence.
Notes
Signals are generated on bar close.
Designed for clarity and discipline—fewer, cleaner arrows over constant noise.
Works on other symbols/timeframes, but tuned for Gold 1H.
Tags: #XAUUSD #Gold #FVG #SmartMoney #1H #TrendFollowing #ADX #ATR #PineV6 #TradingView
Linh Index Trend & Exhaustion SuitePurpose: One overlay to judge trend, reversal risk, overextension, and volatility squeezes on indexes (built for VNINDEX/VN30, works on any symbol & timeframe).
What it shows
Trend state: Bull / Bear / Transition via 20/50/200 EMAs + slope check.
Overextension heatmap: Background paints when price is stretched vs the 20-EMA by ATR or % (you set the thresholds).
Squeeze detection:
Squeeze ON (yellow dot): Bollinger Bands (20,2) inside Keltner Channels (20,1.5).
Squeeze OFF + Release: White dot; script confirms direction only when close > BB upper (up) or close < BB lower (down).
52-week context: Distance to 52-week high/low (%).
Higher-TF alignment: Optional weekly trend reading shown on the label while you’re on the daily.
Anchored VWAP(s): Two optional AVWAPs from dates you choose (e.g., YTD open, last big gap/earnings).
Plots & labels
EMAs 20/50/200 (toggle on/off).
Optional BB & KC bands for diagnostics.
AVWAP #1 / #2 (optional).
Status label with: Trend, EMAs, Dist to 20-EMA (%, ATR), 52-week distances, HTF state.
Built-in alerts (set “Once per bar close”)
EMA10 ↔ EMA20 cross (early momentum shift)
EMA20 ↔ EMA50 cross (trend confirmation/negation)
Price ↔ EMA200 cross (long-term regime)
Squeeze Release UP / DOWN (BB breakout after squeeze)
Overextension Cool-off UP / DN (stretched vs 20-EMA + momentum rolling)
Near 52-week High (within your % threshold)
How to use (playbook)
Map regime: Prefer trades when Daily = Bull and HTF (Weekly) = Bull (shown on label).
Hunt expansion: Yellow → White dot and close beyond BB = fresh move.
Avoid chasing stretch: If background is painted (overextended vs 20-EMA), wait for a pullback or intraday base.
Locations matter: 52-week proximity + HTF Bull improves breakout quality.
Anchors: Add AVWAP from YTD open or last major gap to frame support/resistance.
Suggested settings
Overextension: ATR = 2.0, % = 4.0 to start; tune per index volatility.
Squeeze bands: BB(20,2) & KC(20,1.5) default are balanced; tighten KC (1.3) for more signals, widen (1.8) for fewer/higher quality.
Timeframes: Daily for signals, Weekly for bias. Optional 65-min for entries.
VN30 Effort-vs-Result Multi-Scanner — LinhVN30 Effort-vs-Result Multi-Scanner (Pine v5)
Cross-section scanner for Vietnam’s VN30 stocks that surfaces Effort vs Result footprints and related accumulation/distribution and volatility tells. It renders a ranked table (Top-N) with per-ticker signals and key metrics.
What it does
Scans up to 30 tickers (editable input.symbol slots) using one security() call per symbol → stays under Pine’s 40-call limit and runs reliably on any chart.
Scores each ticker by counting active signals, then ranks and lists the top names.
Optional metrics columns: zVol(60), zTR(60), ATR(20), HL/ATR(20).
Signals (toggleable)
Price/Volume – Effort vs Result
EVR Squeeze (stealth): z(Vol,60) > 4 & z(TR,60) < −0.5
5σ Vol, ≤1σ Ret: z(Vol,60) > 5 & |z(Return,60)| < 1
Wide Effort, Opposite Result: z(Vol,60) > 3 & close < open & z(CLV×Vol,60) > 1
Spread Compression, Heavy Tape: (H−L)/ATR(20) < 0.6 & z(Vol,60) > 3
No-Supply / No-Demand: close < close & range < 0.6×ATR(20) & vol < 0.5×SMA(20)
Momentum & Volatility
Vol-of-Vol Kink: z(ATR20,200) rising & z(ATR5,60) falling
BB Squeeze → Expansion: BBWidth(20) in low regime (z<−1.3) then close > upper band & z(Vol,60) > 2
RSI Non-Confirmation: Price LL/HH with RSI HL/LH & z(Vol,60) > 1
Accumulation/Distribution
OBV Divergence w/ Flat Price: OBV slope > 0 & |z(ret20,260)| < 0.3
Accumulation Days Cluster: ≥3/5 bars: up close, higher vol, close near high
Effort-Result Inversion (Down): big vol on down day then next day close > prior high
How to use
Set the timeframe (works best on 1D for EOD scans).
Edit the 30 symbol slots to your VN30 constituents.
Choose Top N, toggle Show metrics/Only matches and enable/disable scenarios.
Read the table: Rank, Ticker, (metrics), Score, and comma-separated Signals fired.
Method notes
Z-scores use a population-std estimate; CLV×Vol is used for effort/location.
Rolling counts avoid ta.sum; OBV is computed manually; all logic is Pine v5-safe.
Intraday-only ideas (true VWAP magnets, auction volume, flows, futures/options) are not included—Pine can’t cross-scan those datasets.
Disclaimer: Educational tool, not financial advice. Always confirm signals on the chart and with your process.
