Statistics

TE Feature Screen Stop Trading on Lagging Indicators. Start Measuring True Predictive Power. Are your indicators actually predicting the next move, or are they just taking credit for a trend that’s already happening? Introducing the Transfer Entropy Feature Screen. Built for quantitative researchers and serious algorithmic traders, this script leverages Information Theory to mathematically separate predictive signals from random market noise. Instead of relying on standard correlation, this engine uses Conditioned Transfer Entropy (TE). It deliberately strips out the stock's past momentum, forcing every indicator to prove it is bringing new, independent information to the table about where the price will be h bars from now. Tailored Specifically for the Stock Market This Equities Edition focuses strictly on institutional footprints and structural market mechanics: Order Flow & Volume Kinetics: Track Limit Order Absorption (churn), Close Location Value (CLV), and Unusual Volume (RVOL) Z-scores to spot institutional accumulation before the breakout. Structural Edges: Measure Overnight Gap extent and Standard Deviation Distance from the daily VWAP. Index Relative Strength: Dynamically compare the stock's acceleration against a benchmark index (like the SPY or QQQ) to find true market leaders. Built for Rigorous Quant Research To prevent curve-fitting, the script features a strict Walk-Forward backtesting engine. Input your exact calendar dates for In-Sample (Training) and Out-of-Sample (Testing) windows. The engine benchmarks every feature against randomized "null shuffle" data to generate a definitive Z-score, proving whether an indicator's edge is mathematically significant or just a lucky streak. Seamless Data Export: Bypassing TradingView's execution limits, the engine processes massive historical windows in the background and delivers a cleanly formatted CSV spreadsheet of the Z-scores directly to your email via alerts—perfect for building your own regime classification models. Stop guessing which features matter. Let the math tell you what actually moves the market. Setup Note for Users: To extract the data, set your IS/OOS calendar dates, toggle your desired features, and create a TradingView alert with "Send Email" checked. The script will automatically crunch the historical data and email you the CSV results upon the next bar close

Indicatore

Pump-and-Dump / Volatility Spike Flag Pump-and-Dump / Volatility Spike Flag flags abnormal single-candle volatility — not the manipulation scheme, but the classic sharp-spike-then-reverse price shape that shows up around news events (frequently seen on MCX crude oil and silver). HOW IT WORKS A candle is flagged only when two conditions occur together: its true range (which includes gap-opens) expands well beyond its rolling ATR, AND its volume expands well beyond its rolling average. Flagged spikes are tracked for a short window afterward — if price closes back through that candle's open before the window expires, it is separately flagged as a "Fade," indicating the initial move has started reversing. HOW TO USE Use the Spike flag as an early heads-up that a candle is statistically abnormal for current conditions. Use the Fade flag as the more actionable signal — it confirms the spike has already started giving back its move. This is an informational/analytical tool, not a buy or sell signal, and should be combined with your own risk management and market context. LIMITATIONS ATR and volume averages are backward-looking, so the first spike after a long quiet period needs a relatively larger move to trigger. This is a single-candle geometry and volume-shape detector — it cannot identify why a move happened (news, order-flow, or otherwise), and it does not predict direction after the fade. DISCLAIMER For educational/informational purposes only. Not financial advice. Past performance does not guarantee future results. Trade at your own risk and always use proper risk management.

Indicatore

Regime Classifier [RC Tools]RC Tools — Regime Classifier ───────────────────────────────────────────────────────────── █ OVERVIEW Most indicators assume a single market condition and quietly fail in another. This tool doesn't generate signals — it tells you which of four market regimes you are currently in, so you can judge whether your existing tools are operating in conditions that suit them. It is a context tool, not a decision tool. █ WHAT IT DOES Classifies each confirmed bar into one of four states and colours the chart background accordingly: • Trending — Expansion: directional, volatility rising • Trending — Exhaustion: directional, volatility compressing • Ranging — Quiet: no direction, low volatility • Ranging — Volatile: no direction, high volatility (chop) A table (top-right by default, repositionable) shows the current regime, how long price has been in it, and historical base rates — the average forward return and win rate seen after each regime, going back over the chart's full history. █ THE THEORY BEHIND IT Market behaviour is not stationary. A trend-following tool that performs well in directional expansion will bleed in volatile chop; a mean-reversion tool does the reverse. Rather than attempting to fix any single indicator, this tool identifies which environment you are in, using two independent dimensions — directionality and volatility state — that measure genuinely different properties of price behaviour rather than two correlated views of the same one. █ HOW IT IS CALCULATED DIRECTIONALITY — Efficiency Ratio over N bars: ER = |close − close | ÷ Σ|close − close | Bounded 0–1. A value near 1 means price travelled almost directly from A to B (trending); near 0 means it wandered (ranging). No fitted parameters beyond the lookback. The Efficiency Ratio was introduced by Perry Kaufman as the core input to his Adaptive Moving Average (KAMA); it is used here purely as a directionality measure, independent of any moving average. VOLATILITY STATE — realised volatility, percentile-ranked: RV = stdev(log(close/close ), N) RV is then ranked as a percentile against its own trailing distribution (default: 750 bars, ≈3 years on daily). An absolute volatility threshold is meaningless across assets — percentile ranking makes the classification behave identically on BTC, gold and equities with no parameter tuning. The two dimensions are crossed to yield the four states. Classification occurs ONLY on confirmed bar close — the background never updates mid-bar and then flips back. The base-rate table works by recording, for every historical bar, the forward N-bar return and whether it was positive, attributed back to whichever regime was active N bars earlier. Only fully-elapsed, already-known returns are used — nothing is looked up ahead of the current bar. █ SETTINGS & CONFIGURATION • Efficiency Ratio Lookback (default 20) — shorter = more responsive, noisier • Realised Volatility Lookback (default 20) • Percentile Ranking Window (default 750 bars ≈ 3 years daily) — longer = more stable, needs more history • Directionality Threshold (default 0.35) — the ER above which price is considered trending • Volatility Percentile Threshold (default 50) — the split between low and high volatility states • Forward Return Window (default 20 bars) — the horizon used for the base-rate table • Table position and background colours are fully configurable; the main-chart background painting can be toggled off if you only want the diagnostic pane █ HOW TO USE IT Use it as a filter on your existing process, not as an entry trigger. Example: if you run a breakout system, check whether it has historically performed in Ranging — Volatile; if not, consider standing aside when the background flags that state. Example: a mean-reversion system will typically show its worst results in Trending — Expansion. Works on any asset and timeframe with sufficient history for the percentile window. Best used on daily and above, where regime persistence is greatest. █ LIMITATIONS This tool classifies the PRESENT. It does not predict the future, and any use of it as a forecast is a misuse. • Regime identification is backward-looking by construction. The tool will confirm a regime change several bars AFTER it occurred. This lag cannot be removed without curve-fitting or repainting, and has not been. • Classification is unstable near threshold boundaries; expect flickering between states when ER or volatility percentile sit close to the cut-offs. • The percentile ranking requires substantial history. On assets with short histories, the ranking is unreliable and the tool should not be trusted. • The base-rate table's early entries are built on fewer samples than its later ones — treat statistics as provisional until a state has accumulated a meaningful sample count. • Four states is a deliberate simplification of a continuous reality. Markets do not actually occupy discrete regimes. • This script does NOT repaint. All classification is computed on confirmed bar close only. █ DISCLAIMER For educational and informational purposes only. Nothing here is financial advice. Past behaviour of any market regime does not indicate future results. Trade at your own risk.

Indicatore

ICT Pulse - Bias & Stats Dashboard ICT Pulse — Bias & Session Dashboard ICT Pulse is a dashboard-style indicator designed to summarize higher-timeframe context, session status, and liquidity conditions for discretionary ICT-style futures trading. The script does not generate buy or sell signals. Its purpose is to organize market context into a compact dashboard so traders can quickly understand where price is trading relative to previous ranges and whether session liquidity has been taken. How it works ICT Pulse compares the current price to the previous daily, weekly, and monthly ranges. For each range, it calculates whether price is trading in premium or discount by measuring the current close relative to the prior high, low, and midpoint. The dashboard then combines this higher-timeframe information with session conditions. It tracks the active Asia, London, and New York sessions, records each session’s high and low, and monitors whether those levels have later been traded through. The confluence score is a simple context score, not a signal system. Bullish and bearish scores are built from five conditions: * Daily range position * Weekly range position * Monthly range position * Whether opposing-side liquidity has been taken * Whether price is above or below the active session midpoint For example, the bullish score increases when price is in premium on higher timeframes, when downside liquidity has been taken, and when price is holding above the current session midpoint. The bearish score uses the opposite conditions. Main features * Daily, weekly, and monthly bias summary * Premium/discount status for previous daily, weekly, and monthly ranges * Active session detection * Current session range tracking * Asia, London, and New York high/low sweep status * Bullish and bearish confluence score * Dashboard-only layout to reduce chart clutter How to use it ICT Pulse is best used as a market-context tool before looking for entries. A trader can use it to check whether higher-timeframe conditions are aligned, whether important session liquidity has already been taken, and whether the current session is supporting bullish, bearish, or neutral conditions. Suggested workflow: 1. Check daily, weekly, and monthly bias. 2. Check whether price is in premium or discount. 3. Check whether Asia, London, or New York liquidity has been taken. 4. Compare the bullish and bearish confluence scores. 5. Use a separate execution model for entries, stops, and trade management. This script is intended for educational and analytical use only. It does not provide financial advice, trade recommendations, or guaranteed outcomes. Futures and financial market trading involves risk.

Indicatore

Moving Averages Trend Four independently configurable moving averages (type, length, source, color each) let you build the classic multi-MA trend stack in one indicator — a long-term filter to define the overall regime, an intermediate MA for the broader trend, and a fast pair for tactical entries on pullbacks within it. Used purely as an overlay, this is a continuation tool: you only take trades in the direction the slower MAs already agree on, using the faster pair to time entries once price pulls back into alignment. The MA3/MA4 cross-signal layer is what sets this apart from a plain crossover system. Instead of waiting for the two faster MAs to physically cross — which is already stale information by the time it happens — it takes each MA's recent slope and projects it forward by a configurable number of bars, firing the buy/sell label as soon as that projected path crosses rather than the actual one, giving you a signal a few bars earlier than a textbook crossover. A minimum-separation filter (scaled to ATR) throws out weak "touch and go" near-misses, and the signal only fires when price is already sitting on the correct side of both MAs and each MA is still actively moving in that direction on the current bar — all of which is meant to filter out low-conviction crosses in choppy conditions. An optional daily+-only restriction keeps the signal from firing on intraday noise for traders who only want to act on it at swing timeframes. Best applied in trending or newly-trending markets, as a combined trend filter (from the 4 plotted MAs) and tactical entry trigger (from the cross signal) rather than as a mean-reversion tool — it has little to offer in a flat, range-bound market since the slope and separation conditions are designed specifically to avoid firing in that environment.

Indicatore

di MTG_MindTheGap

Event Probability Engine [Quantum Algo]Event Probability Engine ==================================================== 🔶 OVERVIEW Event Probability Engine is a statistical probability indicator that answers one question at the close of every bar: based on the measurable conditions active right now, what is the historical probability that price closes higher one, three, and five days from today? Instead of subjective pattern reading, the script builds and maintains a live rolling database of forward returns conditioned on eighteen observable market events — day-of-week seasonality, oversold and overbought readings, volume spikes, streaks, range position, volatility regime, pivot touches, and an optional lunar control — then pools the currently active events into a single composite probability, displayed as a TODAY headline, a full per-event statistics table, and a shaded forecast cone projected on the chart. It is designed for the daily timeframe. On other timeframes, the one, three, and five day horizons become one, three, and five bars. 🔶 WHAT IS AN EVENT STUDY? An event study measures what a market historically did after a defined, observable condition occurred — for example, what happened over the next five days every time the Relative Strength Index closed oversold, or every Monday, or every time volume spiked two standard deviations above normal. This indicator runs eighteen such studies continuously, in real time, on the chart's own data, and keeps every study honest with the statistical safeguards described below. 🔶 WHY THIS SCRIPT IS ORIGINAL 1. A live event database in Pine. Each of the eighteen events maintains its own rolling, capped sample of forward returns at three horizons, tagged with the market regime at the moment the event fired — a self-updating event-study framework, not a fixed backtest. 2. Shrinkage estimation. Every win rate is pulled toward fifty percent by a configurable number of pseudo-samples. An event with fifteen samples cannot display an extreme probability, because fifteen samples cannot justify one. 3. Overlap correction. State-based events (for example, an oversold reading persisting for a week) generate autocorrelated, overlapping samples that inflate apparent sample size. The effective sample size is deflated by the horizon length before any confidence calculation. 4. Wilson score bounds. Next to each five-day win rate, the table shows the Wilson confidence lower bound computed on the corrected sample size — the number an event must clear before its edge deserves trust, not its raw point estimate. 5. Regime conditioning with fallback. When enough samples exist in the current regime (bull or bear, defined by the two-hundred period exponential moving average), statistics are computed on regime-matched samples only, marked ® in the table. A bear-market Thursday is not assumed to behave like a bull-market Thursday. 6. Quality-weighted log-odds pooling. Active events are combined by weighted log-odds — a method related to Bayesian evidence combination — rather than naive win-rate averaging, so one strong, well-sampled edge is not diluted by three weak ones. 7. A built-in falsification control. Lunar phase events are included deliberately so the engine can audit a popular claim empirically: if full and new moons carry no edge, their quality scores sit near zero and they contribute nothing to the composite. A probability framework should be able to demonstrate which inputs fail, not only which appear to work. 🔶 HOW IT WORKS Event detection: On every bar close the script evaluates all eighteen conditions — Monday through Friday, adaptive or fixed oversold and overbought thresholds, volume z-score spikes, up and down streaks, range-low and range-high position, volatility expansion and compression by percentile rank, confirmed pivot support and resistance touches within an Average True Range distance, and the optional lunar events. Database recording: Whenever an event was active one, three, or five bars ago, the realized forward return is stored in that event's arrays, first-in-first-out at a configurable cap, together with the regime tag from the moment the event fired. Per-event statistics: The table reports, for every event, the shrinkage-adjusted win rate at each horizon, the Wilson lower bound, sample count, average forward return, profit factor, a zero-to-one-hundred quality score blending edge magnitude, sample sufficiency, and recent consistency, and the resulting directional bias. Composite probability: Active events passing the minimum-sample filter are pooled by quality-weighted log-odds into the TODAY headline (next-day probability of an up close with a visual meter), the one, three, and five day composite row with expected returns and a strength grade, and a projected forecast path with a shaded plus-and-minus one standard deviation cone drawn from the current close. Chart layer: Optional regime background tint, the regime line, live pivot support and resistance rails with prices, and historical event markers on the candles so past occurrences of every event can be reviewed directly on the chart. 🔶 HOW TO USE IT 1. Apply it to a daily chart of any liquid symbol — cryptocurrency, stocks, indices, forex, gold, futures. Let it load its history; sample counts grow with available bars. 2. Read the TODAY headline first: the next-day probability, the meter, and the expected one-day return. 3. Scan the table for the highlighted rows — those events are active right now. Judge each by its Wilson lower bound and quality score, not the raw win rate. 4. Use the composite row and forecast cone as context: STRONG requires both a meaningful probability distance from fifty percent and high average quality. 5. Treat readings near fifty percent as exactly what they are: weak evidence. This engine is intentionally built to display small honest numbers rather than large misleading ones. 6. Combine with your own analysis — the engine measures conditional history; it does not know tomorrow's news. 🔶 SETTINGS - Database: sample cap per event, minimum samples for composite inclusion, minimum regime-matched samples, shrinkage strength. - Events: oscillator length and thresholds (fixed or adaptive percentile), volume z-score, streak length, range lookback, pivot lookback and touch distance, lunar events on or off. - Statistics: Wilson z-score (default 1.645, a ninety percent one-sided bound). - Display: dashboard position and five text sizes, forecast cone, regime tint, regime line, pivot rails, candle markers. 🔶 ALERTS - Composite Bias Change — fires once per bar close whenever the five-day composite bias flips state, with the current one-day and five-day probabilities in the message. 🔶 FREQUENTLY ASKED QUESTIONS Does the indicator repaint? Statistics are recorded and evaluated on closed bars, and pivot events use confirmed pivots with their standard confirmation lag. The dashboard and forecast update on the live bar by design, as a dashboard should. Why do most probabilities sit near fifty percent? Because genuine conditional edges in daily data are small, and the shrinkage and overlap corrections are built to say so. Extreme displayed probabilities on thin samples are the signature of a dishonest tool. What does the ® mark mean? That event currently has enough regime-matched samples, so its statistics are computed only from the current bull or bear regime rather than the full history. Why are moon phases in a statistics tool? As a falsification control. The engine should be able to show which inputs carry no edge — and the user can watch it do exactly that. Can I use it intraday? Yes, but the horizons become bars instead of days, and day-of-week events lose their meaning. The design intent is the daily timeframe. 🔶 CREDITS This script stands on standard, publicly documented statistical methods, gratefully credited: the Wilson score interval by Edwin B. Wilson (1927), Laplace-style shrinkage estimation, and the event-study methodology long established in quantitative finance. Their combination into a live, regime-conditional, overlap-corrected event database with quality-weighted log-odds composite pooling, implemented entirely in Pine Script with capped arrays and user-defined types, is original work — no third-party or open-source script code was reused. 🔶 LIMITATIONS Probabilities derived from historical conditioning are estimates, not guarantees, and conditional edges in daily data are typically small. Sample databases need history to mature; young charts produce thin, heavily shrunk statistics by design. Day-of-week events assume a five-day session calendar. Regime conditioning depends on the two-hundred period regime definition. This is a research and confluence tool, not a standalone trading system. 🔶 DISCLAIMER This script is provided strictly for educational and informational purposes. It is not financial advice, an investment recommendation, or a solicitation to buy or sell any financial instrument. Past statistical behavior does not assure future results. Trading involves substantial risk. Always do your own research and manage risk independently.

Indicatore

di Quantum-Algo

Martingale Range Breakout # Martingale Range Breakout **Martingale Range Breakout** is a session-based breakout and flip-tracking indicator designed to study range expansion behavior after a defined range. This script builds a custom time-based range, tracks breakout direction, monitors flip attempts, and displays live trade-state data with rolling performance stats directly on the chart. --- ## Core Concept The indicator creates a range from a selected session window. By default, the range is built from: **8:00 AM – 8:50 AM New York Time** Once the range locks, the script watches for price to break above or below the range. * Break above the range = **Long Active** * Break below the range = **Short Active** * If price reverses and breaks the opposite side, the script counts that as a **flip** * If price reaches the full range extension before 4 flips, it marks the setup as a **WIN** * If the setup reaches 4 flips, it marks the setup as a **LOSS** --- ## Martingale Flip Logic This indicator is based on a Martingale-style flip model. The idea is that when a breakout fails and price flips to the opposite side of the range, the next position size is increased to help recover the previous failed attempt. Example position sequence: * Flip 1: **1 contract** * Flip 2: **2 contracts** * Flip 3: **4 contracts** * Flip 4: **Loss** Each flip represents the market failing in one direction and then triggering the opposite side of the range. The goal of the Martingale model is for the final successful breakout to recover the previous failed flips and still finish the sequence in profit. The table tracks the current trade state and flip count, allowing traders to see what stage of the Martingale sequence the setup is currently in. --- ## Visual Range Boxes The script draws two clean visual zones on the chart. **Yellow Box** Shows the original session range. **Green Box** Shows the full expansion zone based on the range size. The final target levels are calculated as: * Buy final target = **Range High + Full Range Distance** * Sell final target = **Range Low - Full Range Distance** This makes it easy to see both the breakout levels and the final expansion targets. --- ## Live Trade State Tracking The table displays the current setup condition in real time. Possible states include: * **WAITING** * **LONG ACTIVE** * **SHORT ACTIVE** * **WIN** * **LOSS** The table also shows the current flip count, helping traders quickly identify how many times the setup has reversed. --- ## Built-In Rolling Statistics The indicator tracks the last selected number of completed setups and displays performance data inside the chart table. Stats include: * Last N trade count * Wins and losses * Rolling win rate * Rolling R total * Average winning range size * Average losing range size * Current range size * Win sample count * Loss sample count * Average minutes to win * Average minutes to loss The rolling sample size can be adjusted in the settings. --- ## Breakeven Win Rate Requirement This model uses a negative-risk-reward structure, meaning each win is smaller than each full loss. The R Total calculation is based on: * Win = **+0.14285R** * Loss = **-1R** Because each full loss is much larger than each win, the system needs a very high win rate to be profitable. The approximate breakeven win rate is: **87.5%** That means the strategy must win more than **87.5%** of completed setups to show positive expectancy under this model. * Below **87.5% win rate** = negative expectancy * At **87.5% win rate** = around breakeven * Above **87.5% win rate** = positive expectancy This is why the rolling win-rate tracker is important. It helps traders quickly see whether the most recent sample is performing above or below the required profitability threshold. Even though the Martingale flip model can create a high win rate, the full loss is much larger than the average win. Because of that, risk management is extremely important. --- ## R-Multiple Model The R Total section helps estimate whether the recent rolling sample is profitable based on the script’s fixed reward-to-risk model. Instead of only showing win rate, the script also calculates the overall R performance across the selected sample. This helps traders avoid focusing only on a high win rate and instead evaluate whether the system is actually profitable after accounting for the larger full-loss event. --- ## Customizable Settings You can adjust: * Session start hour * Session start minute * Session end hour * Session end minute * Rolling trade sample size * Show or hide the stats section * Table position: * Top Right * Middle Right * Bottom Right --- ## Best Use Case This indicator is best used as a visual research tool for traders studying: * Morning range breakouts * Range expansion behavior * Flip-based entry models * Martingale-style recovery logic * High-win-rate breakout systems * Negative-risk-reward models * Breakeven win-rate requirements * Time-to-outcome behavior * Rolling sample performance --- ## Important Risk Notice This is an indicator only. It does not place trades automatically and should not be considered financial advice. Martingale-style systems can increase risk quickly because each failed flip requires a larger position size. While the model may recover losses when the breakout eventually succeeds, the downside can become large when multiple flips fail. A system like this does not only need to win often — it needs to win enough to overcome the size of its losses. Under this model, that means maintaining a win rate above approximately **87.5%**. Always test thoroughly, use proper risk management, and understand the full risk before applying any strategy live.

Indicatore

di Who7is7Like7God

Free Float Displays the chart symbol's free float value in the indicator's status line and Data Window, without drawing a visible plot on the chart. The script uses `syminfo.shares_outstanding_float`, which provides the number of floating shares outstanding for the current symbol when TradingView has such data available. Because this value is symbol-level data rather than bar-level price data, it should generally remain constant across the chart's bars and across timeframes (within the same reporting period).

Indicatore

Multi-Timeframe MACD Cascade & SNR v6 Janice Janice 1st try 64%, inside the MACD crossover zone on various timeframes, trade reversals (pullbacks or throwbacks). When volume is high, trade in the direction of the momentum. Use the 52 EMA across the 45m, 1h, 2h, 90m, 3h, and 4h+ timeframes—even if higher-timeframe resistance/support is pushing against the trend. This can be combined with Zone and SNR (Support & Resistance) for execution.

Strategia

ChatgptLibrary Library "ChatgptLibrary" TODO: add library description here effective_period(high_series, low_series, volume_series, period_length, lookback_length, max_search) Calculates adaptive effective period. Parameters: high_series (float) : High price series. low_series (float) : Low price series. volume_series (float) : Volume series. period_length (simple int) : Base period. lookback_length (simple int) : EMA lookback multiplier. max_search (int) : Maximum search distance. Returns: Adaptive effective period. adaptive_ema(source, high_series, low_series, volume_series, period_length, lookback_length, max_search) Adaptive EMA using effective period. Parameters: source (float) : Source series. high_series (float) : High price series. low_series (float) : Low price series. volume_series (float) : Volume series. period_length (simple int) : Base period. lookback_length (simple int) : EMA lookback multiplier. max_search (int) : Maximum search distance. Returns: Adaptive EMA, alpha and effective period. adaptive_channel(high_series, low_series, volume_series, period_length, lookback_length, smooth_length, max_search) Adaptive price channel. Parameters: high_series (float) : High price series. low_series (float) : Low price series. volume_series (float) : Volume series. period_length (simple int) : Base period. lookback_length (simple int) : EMA lookback multiplier. smooth_length (simple int) : EMA smoothing. max_search (int) : Maximum search distance. Returns: Effective period, upper, lower, middle and width. adaptive_rsi(source, high_series, low_series, volume_series, period_length, lookback_length, max_search) Adaptive RSI. Parameters: source (float) : Source series. high_series (float) : High price series. low_series (float) : Low price series. volume_series (float) : Volume series. period_length (simple int) : Base period. lookback_length (simple int) : EMA lookback multiplier. max_search (int) : Maximum search distance. Returns: Adaptive RSI and effective period. adaptive_atr(high_series, low_series, close_series, volume_series, period_length, lookback_length, max_search) Adaptive ATR. Parameters: high_series (float) : High price series. low_series (float) : Low price series. close_series (float) : Close price series. volume_series (float) : Volume series. period_length (simple int) : Base period. lookback_length (simple int) : EMA lookback multiplier. max_search (int) : Maximum search distance. Returns: Adaptive ATR and effective period. adaptive_macd(source, high_series, low_series, volume_series, fast_period, slow_period, signal_period, lookback_length, max_search) Adaptive MACD. Parameters: source (float) : Source series. high_series (float) : High price series. low_series (float) : Low price series. volume_series (float) : Volume series. fast_period (simple int) : Fast adaptive period. slow_period (simple int) : Slow adaptive period. signal_period (int) : Signal EMA period. lookback_length (simple int) : EMA lookback multiplier. max_search (int) : Maximum search distance. Returns: MACD, Signal, Histogram. adaptive_bollinger(source, high_series, low_series, volume_series, period_length, deviation, lookback_length, max_search) Adaptive Bollinger Bands. Parameters: source (float) : Source series. high_series (float) : High price series. low_series (float) : Low price series. volume_series (float) : Volume series. period_length (simple int) : Base period. deviation (float) : Standard deviation multiplier. lookback_length (simple int) : EMA lookback multiplier. max_search (int) : Maximum search distance. Returns: Upper band, Middle band, Lower band, Band width and Effective period. adaptive_supertrend(high_series, low_series, close_series, volume_series, period_length, multiplier, lookback_length, max_search) Adaptive SuperTrend. Parameters: high_series (float) : High price series. low_series (float) : Low price series. close_series (float) : Close price series. volume_series (float) : Volume series. period_length (simple int) : Base period. multiplier (float) : ATR multiplier. lookback_length (simple int) : EMA lookback multiplier. max_search (int) : Maximum search distance. Returns: SuperTrend, Trend Direction and Effective Period. adaptive_donchian(high_series, low_series, volume_series, period_length, lookback_length, max_search) Adaptive Donchian Channel. Parameters: high_series (float) : High price series. low_series (float) : Low price series. volume_series (float) : Volume series. period_length (simple int) : Base period. lookback_length (simple int) : EMA lookback multiplier. max_search (int) : Maximum search distance. Returns: Upper band, Lower band, Middle line, Width and Effective period. adaptive_keltner(source, high_series, low_series, close_series, volume_series, period_length, multiplier, lookback_length, max_search) Adaptive Keltner Channel. Parameters: source (float) : Source series. high_series (float) : High price series. low_series (float) : Low price series. close_series (float) : Close price series. volume_series (float) : Volume series. period_length (simple int) : Base period. multiplier (float) : ATR multiplier. lookback_length (simple int) : EMA lookback multiplier. max_search (int) : Maximum search distance. Returns: Upper band, Middle band, Lower band, Width and Effective period. adaptive_adx(high_series, low_series, close_series, volume_series, period_length, lookback_length, max_search) Adaptive ADX. Parameters: high_series (float) : High price series. low_series (float) : Low price series. close_series (float) : Close price series. volume_series (float) : Volume series. period_length (simple int) : Base period. lookback_length (simple int) : EMA lookback multiplier. max_search (int) : Maximum search distance. Returns: ADX, +DI, -DI and Effective Period. adaptive_stochastic(close_series, high_series, low_series, volume_series, period_length, smooth_k, smooth_d, lookback_length, max_search) Adaptive Stochastic. Parameters: close_series (float) : Close price series. high_series (float) : High price series. low_series (float) : Low price series. volume_series (float) : Volume series. period_length (simple int) : Base period. smooth_k (int) : K smoothing. smooth_d (int) : D smoothing. lookback_length (simple int) : EMA lookback multiplier. max_search (int) : Maximum search distance. Returns: K, D and Effective Period. adaptive_cci(high_series, low_series, close_series, volume_series, period_length, lookback_length, max_search) Adaptive Commodity Channel Index. Parameters: high_series (float) : High price series. low_series (float) : Low price series. close_series (float) : Close price series. volume_series (float) : Volume series. period_length (simple int) : Base period. lookback_length (simple int) : EMA lookback multiplier. max_search (int) : Maximum search distance. Returns: CCI and Effective Period. adaptive_williams_r(high_series, low_series, close_series, volume_series, period_length, lookback_length, max_search) Adaptive Williams %R. Parameters: high_series (float) : High price series. low_series (float) : Low price series. close_series (float) : Close price series. volume_series (float) : Volume series. period_length (simple int) : Base period. lookback_length (simple int) : EMA lookback multiplier. max_search (int) : Maximum search distance. Returns: Williams %R and Effective Period. adaptive_roc(source, high_series, low_series, volume_series, period_length, lookback_length, max_search) Adaptive Rate of Change. Parameters: source (float) : Source series. high_series (float) : High price series. low_series (float) : Low price series. volume_series (float) : Volume series. period_length (simple int) : Base period. lookback_length (simple int) : EMA lookback multiplier. max_search (int) : Maximum search distance. Returns: ROC and Effective Period. adaptive_pivot(source, left_bars, right_bars) Adaptive Pivot Detector. Parameters: source (float) : Source series. left_bars (int) : Left pivot bars. right_bars (int) : Right pivot bars. Returns: Pivot High, Pivot Low, Pivot High Price, Pivot Low Price. adaptive_divergence(price_source, indicator_source, pivot_length) Adaptive Divergence Detector. Parameters: price_source (float) : Price series. indicator_source (float) : Indicator series. pivot_length (int) : Pivot length. Returns: Bullish divergence, Bearish divergence and Divergence strength. adaptive_pivot_divergence(price_source, signal_source, pivot_length) Adaptive Pivot Divergence Detector. Parameters: price_source (float) : Price series. signal_source (float) : Indicator series. pivot_length (int) : Pivot length. Returns: Bullish divergence, Bearish divergence and Divergence strength. adaptive_flat_channel(upper_channel, lower_channel, flat_length, tolerance) Adaptive Flat Channel Detector. Parameters: upper_channel (float) : Upper channel. lower_channel (float) : Lower channel. flat_length (int) : Number of bars to evaluate. tolerance (float) : Maximum allowed movement. Returns: Flat upper, Flat lower and Flat channel. adaptive_breakout_strength(close_series, upper_channel, lower_channel, channel_width, volume_series, volume_length) Adaptive Breakout Strength. Parameters: close_series (float) : Close price. upper_channel (float) : Upper channel. lower_channel (float) : Lower channel. channel_width (float) : Channel width. volume_series (float) : Volume. volume_length (simple int) : Volume EMA length. Returns: Breakout direction and Breakout strength. adaptive_channel_rejection(open_series, high_series, low_series, close_series, upper_channel, lower_channel) Adaptive Channel Rejection. Parameters: open_series (float) : Open price. high_series (float) : High price. low_series (float) : Low price. close_series (float) : Close price. upper_channel (float) : Upper channel. lower_channel (float) : Lower channel. Returns: Rejection direction and Rejection strength. adaptive_channel_compression(channel_width, compression_length) Adaptive Channel Compression. Parameters: channel_width (float) : Width of the channel. compression_length (simple int) : Number of bars. Returns: Compression ratio, Is compressing, Is expanding. adaptive_market_energy(channel_width, volume_series, volume_length) Adaptive Market Energy. Parameters: channel_width (float) : Width of channel. volume_series (float) : Volume series. volume_length (simple int) : Volume EMA length. Returns: Energy score. adaptive_market_phase(adx, rsi, compression_ratio, breakout_strength) Adaptive Market Phase. Parameters: adx (float) : Adaptive ADX. rsi (float) : Adaptive RSI. compression_ratio (float) : Channel compression ratio. breakout_strength (float) : Breakout strength. Returns: Market phase. adaptive_rsi_zigzag(rsi_series, center_level, lookback_length) Adaptive RSI Zigzag Detector. Parameters: rsi_series (float) : RSI series. center_level (float) : Center level. lookback_length (int) : Number of bars. Returns: Zigzag count and Zigzag detected. adaptive_flat_level(level_series, flat_length, tolerance) Adaptive Flat Level Detector. Parameters: level_series (float) : Channel upper or lower series. flat_length (int) : Number of bars. tolerance (float) : Maximum allowed movement. Returns: Flat state and Flat strength. adaptive_level_strength(level_series, high_series, low_series, tolerance, lookback_length) Adaptive Level Strength. Parameters: level_series (float) : Support or resistance level. high_series (float) : High price series. low_series (float) : Low price series. tolerance (float) : Touch tolerance. lookback_length (int) : Number of bars. Returns: Touch count and Level strength. adaptive_breakout_probability(breakout_strength, level_strength, compression_ratio, volume_ratio) Adaptive Breakout Probability. Parameters: breakout_strength (float) : Breakout strength. level_strength (float) : Level strength. compression_ratio (float) : Channel compression ratio. volume_ratio (float) : Volume ratio. Returns: Breakout probability. adaptive_reversal_probability(rsi, divergence_strength, rejection_strength, flat_strength, channel_width_percent) Adaptive Reversal Probability. Parameters: rsi (float) : Relative Strength Index. divergence_strength (float) : Divergence strength. rejection_strength (float) : Rejection strength. flat_strength (float) : Flat level strength. channel_width_percent (float) : Channel width percentage. Returns: Reversal probability. adaptive_trend_exhaustion(rsi, adx, momentum, roc) Adaptive Trend Exhaustion. Parameters: rsi (float) : Relative Strength Index. adx (float) : Average Directional Index. momentum (float) : Momentum. roc (float) : Rate of Change. Returns: Trend exhaustion score. adaptive_channel_memory(upper_channel, lower_channel, tolerance, lookback_length) Adaptive Channel Memory. Parameters: upper_channel (float) : Upper channel. lower_channel (float) : Lower channel. tolerance (float) : Maximum channel difference. lookback_length (int) : Number of bars. Returns: Memory score. adaptive_false_breakout(breakout_strength, rejection_strength, volume_ratio) Adaptive False Breakout Detector. Parameters: breakout_strength (float) : Breakout strength. rejection_strength (float) : Rejection strength. volume_ratio (float) : Current volume divided by average volume. Returns: False breakout probability. adaptive_trap_detector(breakout_direction, breakout_strength, rejection_strength, rsi) Adaptive Trap Detector. Parameters: breakout_direction (int) : Breakout direction. breakout_strength (float) : Breakout strength. rejection_strength (float) : Rejection strength. rsi (float) : Relative Strength Index. Returns: Trap direction and Trap probability. adaptive_rsi_behavior(rsi, zigzag_count, divergence_strength, rejection_strength) Adaptive RSI Behavior. Parameters: rsi (float) : Relative Strength Index. zigzag_count (int) : RSI zigzag count. divergence_strength (float) : Divergence strength. rejection_strength (float) : Rejection strength. Returns: RSI behavior score. adaptive_market_behavior(trend_strength, reversal_probability, breakout_probability, exhaustion, energy, rsi_behavior) Adaptive Market Behavior. Parameters: trend_strength (float) : Trend strength. reversal_probability (float) : Reversal probability. breakout_probability (float) : Breakout probability. exhaustion (float) : Trend exhaustion. energy (float) : Market energy. rsi_behavior (float) : RSI behavior. Returns: Market behavior score.

Libreria

Simple BOS/CHoCH Entry Signals Buy signal 1. Bullish CHoCH or BOS occurs. 2. Trend is bullish. 3. Price closes above the previous swing high. 4. Plot a Buy arrow. Sell signal 1. Bearish CHoCH or BOS occurs. 2. Trend is bearish. 3. Price closes below the previous swing low. 4. Plot a Sell arrow.

Indicatore

For-Loop Consensus MA | MiesOnCharts For-Loop Consensus MA Overview For-Loop Consensus MA is a trend indicator that replaces a single moving average with an ensemble of exponential moving averages (EMAs) and asks them to "vote" on the direction of the market. Instead of committing to one length -- where a value of 20 and a value of 50 can disagree and either can be wrong at any given time -- it evaluates many lengths at once and only signals a trend when a large majority of them agree. The result is a single line whose colour reflects the level of agreement across the whole set of lookbacks. The idea behind it A recurring problem with moving-average trend tools is parameter sensitivity: the "best" length is only known in hindsight and changes with market conditions. A short EMA reacts quickly but whipsaws in noise; a long EMA is stable but late. Picking one is a compromise. This indicator borrows a concept from statistics and machine learning known as model averaging (also called ensembling or bagging): rather than trusting one model, you build many variations of it and combine their outputs. The aggregate is generally more robust than any single member, because the idiosyncratic errors of individual lengths tend to cancel out while the shared trend signal reinforces. Two things are aggregated here: The line itself -- the average of all EMAs in the ensemble, producing a smoothed consensus curve. The direction vote -- the fraction of EMAs that price is currently trading above. How it works The script uses a for loop to construct and maintain a series of EMAs spanning a range of lengths: It steps from Min EMA Length to Max EMA Length in increments of Length Step (for example 20, 40, 60… 140). Each EMA is computed manually from its smoothing factor alpha = 2 / (length + 1), and its running value is stored in a persistent array -- one slot per length -- so every member carries its state forward bar to bar. On each bar the loop does two things: it sums the EMA values (to build the consensus line), and it counts how many EMAs price closes above (to build the vote). From these: Consensus line = the mean of all EMAs in the ensemble. Vote share = number of EMAs price is above ÷ total number of EMAs, a value between 0 and 1. Signal logic The vote share drives the trend state through a symmetric threshold: Bullish when the vote share is greater than or equal to the Supermajority Vote Share input (default 0.7) -- i.e. at least 70% of the lookbacks agree price is in an uptrend. The line turns green. Bearish when the vote share is at or below its mirror (1 - threshold, so 0.3 at the default) -- at least 70% agree on a downtrend. The line turns red. Neutral in between, when the ensemble is split and no supermajority exists. The line is grey, indicating indecision or a ranging market. Requiring a supermajority rather than a simple majority is deliberate: it filters out the marginal, split-vote conditions where moving averages are least reliable, and only commits to a trend colour when the evidence across timescales is broad. Inputs Source -- the price series the EMAs are built from (default: close). Min EMA Length / Max EMA Length -- the shortest and longest lookbacks in the ensemble. A wider span blends more timescales. Length Step -- the spacing between ensemble members. A smaller step packs in more EMAs (finer, heavier); a larger step uses fewer. Supermajority Vote Share -- how strong the agreement must be before a trend is declared. Higher values (e.g. 0.8) demand stronger consensus and produce fewer, more selective signals; lower values (e.g. 0.6) are more responsive but less discriminating. How to use it Trend context -- read the colour of the line as a regime filter. Green suggests a broad-based uptrend across lookbacks; red a broad downtrend; grey a lack of consensus where trend-following is riskier. Trend confirmation -- the line can be used alongside price structure or other tools to confirm that a move is supported across multiple horizons rather than by one arbitrary length. Neutral zones -- grey stretches highlight indecision and can be treated as periods to stand aside or tighten expectations. Two alert conditions are included -- Consensus MA Long (bullish) and Consensus MA Short (bearish) -- so the trend states can be wired to TradingView alerts. Notes and limitations Like all moving-average-based tools, this indicator is reactive: it describes the trend that price is already in and will lag turning points. It does not predict future prices. Signals reflect agreement among lagging averages, so expect the trend colour to change after a reversal has begun, not before it. Wider length ranges and larger supermajority thresholds increase robustness at the cost of responsiveness. There is no universally correct setting; adjust to the instrument and timeframe you trade. This script is a decision-support tool, not a standalone trading system and not financial advice. It does not include risk management and makes no representation about future performance. Test any settings on your market before relying on them.

Indicatore

di MiesOnCharts

ATR Divided by 4 he Average True Range (ATR) is the gold standard for measuring market volatility. However, for active intraday traders, scalpers, or those looking to fine-tune their risk management, the standard ATR can often feel too wide. Enter the Fractional ATR (ATR / 4). This indicator calculates the traditional Average True Range and divides it by four, isolating exactly 25% of the asset’s recent average volatility. Why Divide ATR by 4? Using a fraction of the ATR allows traders to adapt to market noise on a more granular level. Here is how you can apply the ATR/4 to your trading strategy: High-Probability Intraday Targets: If an asset typically moves $4 a day (Standard ATR), aiming for a $1 move (ATR/4) represents a highly realistic, high-probability profit target for day traders and scalpers. Tighter, Volatility-Adjusted Stop Losses: Using a full 1x or 2x ATR for a stop loss can sometimes mean risking too much capital or giving back too much floating profit. Using ATR/4 allows you to trail your stops tightly while still factoring in the asset's current micro-volatility, keeping you out of the standard "market noise." Grid Trading and Scaling In: If you build positions over time, using an arbitrary static number (like buying every $0.50 down) ignores market conditions. Spacing your limit orders by an ATR/4 distance ensures your grid adapts to expanding or contracting volatility. How it Works The math is straightforward and transparent: It calculates the standard Average True Range based on your chosen period. It divides that exact value by 4. It plots the resulting value as an easy-to-read oscillator in a separate pane below your chart. Features & Settings Customizable ATR Length: By default, the indicator uses the industry-standard 14-period lookback. You can easily adjust this in the settings menu to fit your specific timeframe or strategy (e.g., a 5-period for hyper-responsive data, or a 21-period for smoother data). Clean Visuals: Plots cleanly in a lower pane so it does not clutter your main price chart. Best Timeframes This indicator is universally applicable but shines particularly well on lower timeframes (1m, 5m, 15m) when trying to capture a fraction of the Higher Timeframe (1H, 4H, Daily) volatility. Disclaimer: This script is for educational and analytical purposes only. Always backtest your risk management strategies before applying them to live capital.

Indicatore

Isotropic Coordinate System (ICS)Library "ICS" Isotropic Coordinate System (ICS): a dimensionless price-time space for scale-invariant chart geometry. Vertical axis: y = ln(price) / sigma, where sigma is the Yang-Zhang (2000) minimum-variance, drift-independent, gap-consistent OHLC volatility estimator. Horizontal axis: two scalings via the XScale enum. legacy : x = bars / lookback. Linear window fraction. Backward compatible. isotropic : x = sqrt(bars / lookback), with y additionally divided by sqrt(lookback). Diffusion-consistent (sqrt-time scaling), so that tan(theta) equals the z-score of the move and 45 degrees corresponds to a move of exactly one standard deviation of the n-bar log-return distribution. Assumes approximately iid returns within the sigma window (the standard assumption behind sqrt-time scaling; see Danielsson & Zigrand, 2006, for its known limits under vol clustering and jumps). Every output (angle, length, area, centroid) is a pure dimensionless number, comparable across symbols, currencies, and timeframes. Reference: Yang, D. & Zhang, Q. (2000), "Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices", The Journal of Business, 73(3), 477-492. yangZhangSigma(length) Yang-Zhang volatility estimator. Minimum-variance, unbiased, drift-independent, and consistent with opening gaps (Yang & Zhang, 2000). Uses the unbiased sample variance (biased = false) for both the overnight and open-to-close components, matching the estimator's unbiasedness claim. Parameters: length (simple int) : (simple int) Rolling window length. Must be >= 2. Returns: (series float) Per-bar sigma, floored at 1e-10. toX(bars, lookback, mode) Dimensionless horizontal coordinate. Parameters: bars (int) : (series int) Signed bar distance from the anchor. lookback (int) : (series int) Window length acting as the horizontal unit. mode (series XScale) : (series XScale) Scaling mode. Returns: (series float) Signed dimensionless x. toY(price, sigma, lookback, mode) Dimensionless vertical coordinate. Parameters: price (float) : (series float) Price. Must be > 0. sigma (float) : (series float) Yang-Zhang sigma. Must be > 1e-10. lookback (int) : (series int) Window length (used by isotropic mode only). mode (series XScale) : (series XScale) Scaling mode. Returns: (series float) Dimensionless y, or na when inputs are invalid. moveZScore(dLogPrice, sigma, bars) Z-score of a log-price move over n bars: dLog / (sigma * sqrt(n)). In isotropic mode this equals tan(theta) of the same move. Parameters: dLogPrice (float) : (series float) ln(target) - ln(anchor). sigma (float) : (series float) Per-bar Yang-Zhang sigma. Must be > 1e-10. bars (int) : (series int) Number of bars in the move. Must be > 0. Returns: (series float) The z-score, or na when inputs are invalid. triangle(td, anchorPrice, anchorBar, targetPrice, targetBar, sig, lookback, mode) Right triangle between an anchor and a target, computed entirely in ICS space. Writes results in place into `td` and returns it. On invalid inputs every field is set to na, so world X never receives contaminated numbers. Parameters: td (TriangleData) : (TriangleData) Output object, updated in place. anchorPrice (float) : (series float) Anchor price (world A). Must be > 0. anchorBar (int) : (series int) Anchor bar_index. targetPrice (float) : (series float) Target price (world A). Must be > 0. targetBar (int) : (series int) Target bar_index. Must differ from anchorBar. sig (float) : (series float) Yang-Zhang sigma. Must be > 1e-10. lookback (int) : (series int) Horizontal unit window. mode (series XScale) : (series XScale) Scaling mode. Returns: (TriangleData) The same `td`, for chaining. pinTriangle(td, anchorPrice, anchorBar, extremePrice, bodyPrice, curBar, sig, lookback, mode) Pin (wick) triangle with three vertices in ICS space: A = anchor, B = candle extreme, C = candle body edge. Side BC is the wick. theta = signed angle at A between AB and AC. Since xB = xC, the shoelace area reduces exactly to 0.5 * |yB - yC| * |dx|. Parameters: td (TriangleData) : (TriangleData) Output object, updated in place. anchorPrice (float) : (series float) Anchor price (hh or ll). Must be > 0. anchorBar (int) : (series int) Anchor bar_index. extremePrice (float) : (series float) Candle extreme (high or low). Must be > 0. bodyPrice (float) : (series float) Candle body edge. Must be > 0. curBar (int) : (series int) Current bar_index. Must differ from anchorBar. sig (float) : (series float) Yang-Zhang sigma. Must be > 1e-10. lookback (int) : (series int) Horizontal unit window. mode (series XScale) : (series XScale) Scaling mode. Returns: (TriangleData) The same `td`, for chaining. zeroTri(td) Resets a TriangleData to na. Use when the structure is inactive, so inactive periods never enter moving averages or normalization as fake zero values. Parameters: td (TriangleData) : (TriangleData) Object to reset, updated in place. Returns: (TriangleData) The same `td`, for chaining. TriangleData One triangle's measurements in ICS space. All fields dimensionless. Fields: theta (series float) : Signed hypotenuse angle in degrees; in isotropic mode tan(theta) is the z-score of the move. dy (series float) : Signed Euclidean magnitude of the hypotenuse. area (series float) : Triangle area (>= 0). centroidY (series float) : Vertical centroid of the triangle. FrozenAnchors Anchors frozen at a reference bar, plus activity state. Fields: hh (series float) : Highest high at the freeze bar (world-A price units). ll (series float) : Lowest low at the freeze bar (world-A price units). mid (series float) : Geometric mean sqrt(hh * ll) at the freeze bar. bar_x (series int) : bar_index of the freeze bar. time_x (series int) : time of the freeze bar. is_active (series bool) : Whether the frozen structure is currently active.

Libreria

RS/Correlation Panel **RS/Correlation Panel** A single-table dashboard that benchmarks the current chart's symbol against any reference ticker you choose (SPY, QQQ, BTC, or any other symbol) across multiple timeframes — correlation, today's relative performance, short-term relative strength, and a longer IBD-style relative strength rating — plus historical daily move statistics for the symbol itself. **Inputs** - **Benchmark Ticker** — the symbol to compare against. Defaults to SPY, but accepts any ticker (QQQ, individual stocks, or crypto via its exchange prefix, e.g. COINBASE:BTCUSD). - **Correlation Lookback (bars)** — number of bars used for the rolling correlation calculation. Default 20. - **Daily Stats Lookback (days)** — number of trading days used to calculate average rise/fall and green/red day percentages. Default 60. - **Short-Term RS/RW Lookback (bars)** — the window used for the medium-term relative strength/weakness reading, sitting between the 1-day and quarterly reads. Default 10. - **Table Position** — corner of the chart where the table is displayed. **Table Rows** - **Correlation** — rolling correlation coefficient between the symbol and the benchmark over the chosen lookback, tagged Strong / Moderate / Weak based on absolute value. - **Symbol's Today's Move / Benchmark's Today's Move** — each instrument's current-session percent change, calculated from that day's open to the live/last close. - **RS/RW Today** — the difference between the symbol's and benchmark's daily percent change. Positive means the symbol is outperforming the benchmark today; negative means it's underperforming. - **N-Bar RS/RW** — the same outperformance/underperformance concept, but measured as the difference in rate-of-change over the user-defined short-term lookback (default 10 bars). This fills the gap between a single day's move and a full quarterly trend. - **IBD-Style RS** — a quarterly-weighted relative strength calculation modeled on the classic IBD Relative Strength methodology: the symbol's and benchmark's trailing performance are each computed across four rolling quarters (weighted 40/20/20/20, most recent quarter weighted heaviest), then compared as a percentage difference. This is a slower-moving, trend-level strength read — it won't react much to a single day's move, by design. - **Avg % Rise / Fall** — average percentage gain on up days and average percentage loss on down days, calculated over the Daily Stats Lookback period. - **Green Days % / Red Days %** — percentage of days in the lookback period that closed up versus down. **Notes** - All relative-strength and correlation metrics reference the same user-selected benchmark, so switching the input updates every row consistently. - The IBD-Style RS calculation is a reproduction of the standard quarterly-weighted RS methodology and is intended to complement — not replace — short-term price action analysis. - This is a decision-support tool, not a standalone trading signal. Always confirm readings against price structure, volume, and catalysts before acting.

Indicatore

Bingbull Quantum T-Score MTF Adaptive Bingbull Quantum T-Score MTF Adaptative This indicator measures how statistically stretched price is from its mean, using an adaptive Student-t normalization instead of the classic Gaussian Z-Score, and then interprets that stretch according to the prevailing market regime: as a potential mean-reversion condition when the market is statistically mean-reverting, or as trend-continuation strength when it is trending. It combines a multi-timeframe dashboard, a regime filter, an asymmetric breakout module, optional volume/volatility/macro confirmers, and graphical "sigma thermometers".

Indicatore

Clean Levels Allows you to manually enter GEX Levels, HVL, Globex VAH, VAL, POC, PW VAH, VAL, and POC, as well as Previous Previous Week (PWPW) VAH, VAL, POC and Current Week (CW) VAH, VAL, POC

Indicatore

di calvennstarre

StocksDeveloperAlerts Library "StocksDeveloperAlerts" AutoTrader Web alert builder by Stocks Developer — turn TradingView alerts into real broker orders across many accounts and brokers. Ready-made functions for single orders, options the easy way, 8 option structures (straddle/strangle/spreads/iron condor/iron fly), custom multi-leg, account or group targeting, and your own risk limits. No alert-text typing. stocksdeveloper.in order(symbol, exchange, producttype, tradetype, account, group, lots, quantity, ordertype, price, triggerprice, validity, amo, optiontype, strike, expiry, spothint, usespot, onslicefailure, risk, extra) Build an alert message for a single order (stock, futures or one option leg). This is the full builder; equity() and option() are shorter wrappers over it. Set exactly one of account/group and exactly one of lots/quantity. Add optiontype to make it an option order. Parameters: symbol (string) : (series string) Broker-independent symbol, e.g. "NIFTY", "BANKNIFTY", "SBIN". For options, pass the underlier (e.g. "NIFTY"), not a full contract. exchange (string) : (series string) Exchange code, e.g. "NSE"/"BSE" for stocks, "NFO" for options and futures. producttype (string) : (series string) INTRADAY, DELIVERY, NORMAL or MTF. tradetype (string) : (series string) BUY or SELL. account (string) : (series string) Place in this single account. Set this OR group. group (string) : (series string) Place in every live account in this group. Set this OR account. lots (int) : (series int) Number of lots. Set this OR quantity. quantity (int) : (series int) Exact quantity. Set this OR lots. ordertype (string) : (series string) MARKET (default), LIMIT, STOP_LOSS or SL_MARKET. price (float) : (series float) Limit price (required for LIMIT). triggerprice (float) : (series float) Trigger price (for stop-loss orders). validity (string) : (series string) DAY (default) or IOC. amo (bool) : (series bool) true for an after-market order. optiontype (string) : (series string) CE for a call, PE for a put. Adding this makes it an option order. strike (string) : (series string) ATM (default), ATM+1 / ATM-2, OTM / OTM2, ITM / ITM2, or an exact strike like "24500". Requires optiontype. expiry (string) : (series string) weekly (default), next, monthly, or an exact date like "10-JUL-2026". Requires optiontype. spothint (string) : (series string) Advanced: a spot price to help option-strike selection. usespot (bool) : (series bool) Advanced: use the spot hint for strike selection. onslicefailure (string) : (series string) Advanced: continue (default), alert or retry, if a large order that was auto-split has a slice fail. risk (string) : (series string) A risk block from risk() — for example risk=atw.risk(maxloss=5000). extra (string) : (series string) Advanced: any extra "key=value" lines to pass through unchanged (one per line). Returns: (series string) The ready-to-send alert message. equity(symbol, exchange, producttype, tradetype, account, group, lots, quantity, ordertype, price, triggerprice, validity, amo, risk, extra) Build an alert for a single stock or futures order (no option fields). Set exactly one of account/group and exactly one of lots/quantity. Parameters: symbol (string) : (series string) Broker-independent symbol, e.g. "SBIN". exchange (string) : (series string) Exchange code, e.g. "NSE" or "NFO". producttype (string) : (series string) INTRADAY, DELIVERY, NORMAL or MTF. tradetype (string) : (series string) BUY or SELL. account (string) : (series string) Single account. Set this OR group. group (string) : (series string) Group of accounts. Set this OR account. lots (int) : (series int) Number of lots. Set this OR quantity. quantity (int) : (series int) Exact quantity. Set this OR lots. ordertype (string) : (series string) MARKET (default), LIMIT, STOP_LOSS or SL_MARKET. price (float) : (series float) Limit price (required for LIMIT). triggerprice (float) : (series float) Trigger price (for stop-loss orders). validity (string) : (series string) DAY (default) or IOC. amo (bool) : (series bool) true for an after-market order. risk (string) : (series string) A risk block from risk(). extra (string) : (series string) Extra "key=value" lines to pass through unchanged. Returns: (series string) The ready-to-send alert message. option(symbol, exchange, producttype, tradetype, optiontype, strike, expiry, account, group, lots, quantity, ordertype, price, triggerprice, validity, amo, spothint, usespot, risk, extra) Build an option order the easy way — give the underlier and pick the strike + expiry; no need to type the full option symbol. Set exactly one of account/group and exactly one of lots/quantity. Parameters: symbol (string) : (series string) The underlier, e.g. "NIFTY", "BANKNIFTY". exchange (string) : (series string) Options exchange code, e.g. "NFO". producttype (string) : (series string) INTRADAY, DELIVERY, NORMAL or MTF. tradetype (string) : (series string) BUY or SELL. optiontype (string) : (series string) CE for a call, PE for a put. strike (string) : (series string) ATM (default), ATM+1 / ATM-2, OTM / OTM2, ITM / ITM2, or an exact strike like "24500". expiry (string) : (series string) weekly (default), next, monthly, or an exact date like "10-JUL-2026". account (string) : (series string) Single account. Set this OR group. group (string) : (series string) Group of accounts. Set this OR account. lots (int) : (series int) Number of lots. Set this OR quantity. quantity (int) : (series int) Exact quantity. Set this OR lots. ordertype (string) : (series string) MARKET (default), LIMIT, STOP_LOSS or SL_MARKET. price (float) : (series float) Limit price (required for LIMIT). triggerprice (float) : (series float) Trigger price (for stop-loss orders). validity (string) : (series string) DAY (default) or IOC. amo (bool) : (series bool) true for an after-market order. spothint (string) : (series string) Advanced: a spot price to help strike selection. usespot (bool) : (series bool) Advanced: use the spot hint for strike selection. risk (string) : (series string) A risk block from risk(). extra (string) : (series string) Extra "key=value" lines to pass through unchanged. Returns: (series string) The ready-to-send alert message. straddle(symbol, exchange, producttype, account, group, lots, quantity, expiry, direction, ordertype, price, onlegfailure, risk, extra) Straddle — buy (or sell) a call and a put at the money. direction "BUY" = long straddle, "SELL" = short straddle. Parameters: symbol (string) : (series string) The underlier, e.g. "NIFTY". exchange (string) : (series string) Options exchange code, e.g. "NFO". producttype (string) : (series string) INTRADAY, DELIVERY, NORMAL or MTF. account (string) : (series string) Single account. Set this OR group. group (string) : (series string) Group of accounts. Set this OR account. lots (int) : (series int) Number of lots. Set this OR quantity. quantity (int) : (series int) Exact quantity. Set this OR lots. expiry (string) : (series string) weekly (default), next, monthly, or an exact date. direction (string) : (series string) BUY (default) builds the structure as named; SELL flips every leg. ordertype (string) : (series string) MARKET (default) or LIMIT. price (float) : (series float) Limit price (required for LIMIT). onlegfailure (string) : (series string) alert (default), cancel or continue, if one leg cannot be placed. risk (string) : (series string) A risk block from risk(). extra (string) : (series string) Extra "key=value" lines to pass through unchanged. Returns: (series string) The ready-to-send alert message. strangle(symbol, exchange, producttype, account, group, lots, quantity, width, expiry, direction, ordertype, price, onlegfailure, risk, extra) Strangle — buy (or sell) an out-of-the-money call and put, each 'width' strikes out. direction "BUY" = long strangle, "SELL" = short strangle. Parameters: symbol (string) : (series string) The underlier, e.g. "NIFTY". exchange (string) : (series string) Options exchange code, e.g. "NFO". producttype (string) : (series string) INTRADAY, DELIVERY, NORMAL or MTF. account (string) : (series string) Single account. Set this OR group. group (string) : (series string) Group of accounts. Set this OR account. lots (int) : (series int) Number of lots. Set this OR quantity. quantity (int) : (series int) Exact quantity. Set this OR lots. width (int) : (series int) How far out of the money the legs sit, in strike steps (default 2). expiry (string) : (series string) weekly (default), next, monthly, or an exact date. direction (string) : (series string) BUY (default) or SELL (flips every leg). ordertype (string) : (series string) MARKET (default) or LIMIT. price (float) : (series float) Limit price (required for LIMIT). onlegfailure (string) : (series string) alert (default), cancel or continue. risk (string) : (series string) A risk block from risk(). extra (string) : (series string) Extra "key=value" lines to pass through unchanged. Returns: (series string) The ready-to-send alert message. bullCall(symbol, exchange, producttype, account, group, lots, quantity, width, expiry, direction, ordertype, price, onlegfailure, risk, extra) Bull call spread — buy a call at the money and sell a call 'width' strikes out. Use direction "SELL" to reverse. Parameters: symbol (string) : (series string) The underlier, e.g. "NIFTY". exchange (string) : (series string) Options exchange code, e.g. "NFO". producttype (string) : (series string) INTRADAY, DELIVERY, NORMAL or MTF. account (string) : (series string) Single account. Set this OR group. group (string) : (series string) Group of accounts. Set this OR account. lots (int) : (series int) Number of lots. Set this OR quantity. quantity (int) : (series int) Exact quantity. Set this OR lots. width (int) : (series int) Distance between the two strikes, in strike steps (default 2). expiry (string) : (series string) weekly (default), next, monthly, or an exact date. direction (string) : (series string) BUY (default) or SELL (flips every leg). ordertype (string) : (series string) MARKET (default) or LIMIT. price (float) : (series float) Limit price (required for LIMIT). onlegfailure (string) : (series string) alert (default), cancel or continue. risk (string) : (series string) A risk block from risk(). extra (string) : (series string) Extra "key=value" lines to pass through unchanged. Returns: (series string) The ready-to-send alert message. bearPut(symbol, exchange, producttype, account, group, lots, quantity, width, expiry, direction, ordertype, price, onlegfailure, risk, extra) Bear put spread — buy a put at the money and sell a put 'width' strikes out. Use direction "SELL" to reverse. Parameters: symbol (string) : (series string) The underlier, e.g. "NIFTY". exchange (string) : (series string) Options exchange code, e.g. "NFO". producttype (string) : (series string) INTRADAY, DELIVERY, NORMAL or MTF. account (string) : (series string) Single account. Set this OR group. group (string) : (series string) Group of accounts. Set this OR account. lots (int) : (series int) Number of lots. Set this OR quantity. quantity (int) : (series int) Exact quantity. Set this OR lots. width (int) : (series int) Distance between the two strikes, in strike steps (default 2). expiry (string) : (series string) weekly (default), next, monthly, or an exact date. direction (string) : (series string) BUY (default) or SELL (flips every leg). ordertype (string) : (series string) MARKET (default) or LIMIT. price (float) : (series float) Limit price (required for LIMIT). onlegfailure (string) : (series string) alert (default), cancel or continue. risk (string) : (series string) A risk block from risk(). extra (string) : (series string) Extra "key=value" lines to pass through unchanged. Returns: (series string) The ready-to-send alert message. bullPut(symbol, exchange, producttype, account, group, lots, quantity, width, expiry, direction, ordertype, price, onlegfailure, risk, extra) Bull put spread (credit) — sell a put at the money and buy a put 'width' strikes out. Use direction "SELL" to reverse. Parameters: symbol (string) : (series string) The underlier, e.g. "NIFTY". exchange (string) : (series string) Options exchange code, e.g. "NFO". producttype (string) : (series string) INTRADAY, DELIVERY, NORMAL or MTF. account (string) : (series string) Single account. Set this OR group. group (string) : (series string) Group of accounts. Set this OR account. lots (int) : (series int) Number of lots. Set this OR quantity. quantity (int) : (series int) Exact quantity. Set this OR lots. width (int) : (series int) Distance between the two strikes, in strike steps (default 2). expiry (string) : (series string) weekly (default), next, monthly, or an exact date. direction (string) : (series string) BUY (default) or SELL (flips every leg). ordertype (string) : (series string) MARKET (default) or LIMIT. price (float) : (series float) Limit price (required for LIMIT). onlegfailure (string) : (series string) alert (default), cancel or continue. risk (string) : (series string) A risk block from risk(). extra (string) : (series string) Extra "key=value" lines to pass through unchanged. Returns: (series string) The ready-to-send alert message. bearCall(symbol, exchange, producttype, account, group, lots, quantity, width, expiry, direction, ordertype, price, onlegfailure, risk, extra) Bear call spread (credit) — sell a call at the money and buy a call 'width' strikes out. Use direction "SELL" to reverse. Parameters: symbol (string) : (series string) The underlier, e.g. "NIFTY". exchange (string) : (series string) Options exchange code, e.g. "NFO". producttype (string) : (series string) INTRADAY, DELIVERY, NORMAL or MTF. account (string) : (series string) Single account. Set this OR group. group (string) : (series string) Group of accounts. Set this OR account. lots (int) : (series int) Number of lots. Set this OR quantity. quantity (int) : (series int) Exact quantity. Set this OR lots. width (int) : (series int) Distance between the two strikes, in strike steps (default 2). expiry (string) : (series string) weekly (default), next, monthly, or an exact date. direction (string) : (series string) BUY (default) or SELL (flips every leg). ordertype (string) : (series string) MARKET (default) or LIMIT. price (float) : (series float) Limit price (required for LIMIT). onlegfailure (string) : (series string) alert (default), cancel or continue. risk (string) : (series string) A risk block from risk(). extra (string) : (series string) Extra "key=value" lines to pass through unchanged. Returns: (series string) The ready-to-send alert message. ironCondor(symbol, exchange, producttype, account, group, lots, quantity, width, wing, expiry, direction, ordertype, price, onlegfailure, risk, extra) Iron condor — sell a call and a put 'width' strikes out, and buy a call and a put 'width'+'wing' strikes out as protection. direction "BUY" builds this credit condor; "SELL" reverses it. Parameters: symbol (string) : (series string) The underlier, e.g. "NIFTY". exchange (string) : (series string) Options exchange code, e.g. "NFO". producttype (string) : (series string) INTRADAY, DELIVERY, NORMAL or MTF. account (string) : (series string) Single account. Set this OR group. group (string) : (series string) Group of accounts. Set this OR account. lots (int) : (series int) Number of lots. Set this OR quantity. quantity (int) : (series int) Exact quantity. Set this OR lots. width (int) : (series int) How far out the sold legs sit, in strike steps (default 2). wing (int) : (series int) Extra distance out to the protective legs, in strike steps (defaults to width). expiry (string) : (series string) weekly (default), next, monthly, or an exact date. direction (string) : (series string) BUY (default) or SELL (flips every leg). ordertype (string) : (series string) MARKET (default) or LIMIT. price (float) : (series float) Limit price (required for LIMIT). onlegfailure (string) : (series string) alert (default), cancel or continue. risk (string) : (series string) A risk block from risk(). extra (string) : (series string) Extra "key=value" lines to pass through unchanged. Returns: (series string) The ready-to-send alert message. ironFly(symbol, exchange, producttype, account, group, lots, quantity, wing, expiry, direction, ordertype, price, onlegfailure, risk, extra) Iron fly — sell a call and a put at the money, and buy a call and a put 'wing' strikes out as protection. direction "BUY" builds this credit fly; "SELL" reverses it. Parameters: symbol (string) : (series string) The underlier, e.g. "NIFTY". exchange (string) : (series string) Options exchange code, e.g. "NFO". producttype (string) : (series string) INTRADAY, DELIVERY, NORMAL or MTF. account (string) : (series string) Single account. Set this OR group. group (string) : (series string) Group of accounts. Set this OR account. lots (int) : (series int) Number of lots. Set this OR quantity. quantity (int) : (series int) Exact quantity. Set this OR lots. wing (int) : (series int) How far out the protective legs sit, in strike steps (default 2). expiry (string) : (series string) weekly (default), next, monthly, or an exact date. direction (string) : (series string) BUY (default) or SELL (flips every leg). ordertype (string) : (series string) MARKET (default) or LIMIT. price (float) : (series float) Limit price (required for LIMIT). onlegfailure (string) : (series string) alert (default), cancel or continue. risk (string) : (series string) A risk block from risk(). extra (string) : (series string) Extra "key=value" lines to pass through unchanged. Returns: (series string) The ready-to-send alert message. leg(optiontype, strike, tradetype, multiplier) Build one option leg string for use with multiLeg(), e.g. atw.leg("CE", "ATM+2", "SELL", 2) -> "CE ATM+2 SELL x2". Parameters: optiontype (string) : (series string) CE for a call, PE for a put. strike (string) : (series string) ATM, ATM+2, OTM2, ITM1, or an exact strike like "24500". tradetype (string) : (series string) BUY or SELL for this leg. multiplier (int) : (series int) Size multiplier for this leg (default 1). Returns: (series string) The leg descriptor. multiLeg(symbol, exchange, producttype, legs, account, group, lots, quantity, expiry, ordertype, price, onlegfailure, risk, extra) Build an alert for a fully custom multi-leg order from a list of legs (1 to 10) made with leg(). Set exactly one of account/group and exactly one of lots/quantity. Parameters: symbol (string) : (series string) The underlier, e.g. "NIFTY". exchange (string) : (series string) Options exchange code, e.g. "NFO". producttype (string) : (series string) INTRADAY, DELIVERY, NORMAL or MTF. legs (array) : (array) The legs, e.g. array.from(atw.leg("PE","ATM-2","SELL"), atw.leg("PE","ATM-6","BUY")). account (string) : (series string) Single account. Set this OR group. group (string) : (series string) Group of accounts. Set this OR account. lots (int) : (series int) Number of lots. Set this OR quantity. quantity (int) : (series int) Exact quantity. Set this OR lots. expiry (string) : (series string) weekly (default), next, monthly, or an exact date. ordertype (string) : (series string) MARKET (default) or LIMIT. price (float) : (series float) Limit price (required for LIMIT). onlegfailure (string) : (series string) alert (default), cancel or continue. risk (string) : (series string) A risk block from risk(). extra (string) : (series string) Extra "key=value" lines to pass through unchanged. Returns: (series string) The ready-to-send alert message. riskLimits(maxloss, forceexit, entrywindow, blockExpiry) Build a risk-limits block to attach to any order via risk=. Example: risk=atw.riskLimits(maxloss=5000). These are your own limits; see the Alert Automation guide for exactly how each one behaves. Parameters: maxloss (float) : (series float) Maximum day loss for the account, in your account currency. forceexit (string) : (series string) A square-off time as "HH:mm", e.g. "15:15". entrywindow (string) : (series string) An allowed entry-time window "HH:mm-HH:mm", e.g. "09:30-14:30". blockExpiry (bool) : (series bool) Block new entries on the instrument's expiry day. Returns: (series string) The risk lines, ready to pass as risk=.

Libreria

di StocksDeveloper

Income ETF vs Benchmark Comparator Compare the performance of income/covered call ETFs (JEPI, JEPQ, QYLD, QQQI, XYLD, SPYI) against their benchmark ETFs (SPY, QQQ) to determine if income strategies outperform buy-and-hold. Features: Total Returns: Year-by-year and period total returns (price appreciation + dividends, non-reinvested) Dividend Yields: Annual dividend percentages for both income and benchmark ETFs NAV Decay: Measures underperformance of income ETF vs benchmark Dividend Extraction Analysis: Shows hypothetical benchmark returns if you extracted the same dividends by selling shares Sharpe Ratios: Risk-adjusted returns for performance comparison Predefined Pairs: Quick selection of common comparisons or custom symbol input Customizable Display: Adjustable table position and font size How to Use: Select a comparison pair (e.g., "JEPI vs SPY") or choose "Custom" to compare any two symbols Also put the ticker in analysis in the chart and 1D time frame Review yearly performance, dividends, and risk metrics in the table Ideal for investors evaluating whether income ETF strategies justify their NAV decay compared to traditional index investing.

Indicatore

di HenriqueCentieiro

ZeroGEX Daily Gamma Levels Manually plot key options-positioning levels on your chart: Gamma Flip, Call Wall, Put Wall, and Max Gamma / Pin. These levels are used by SPY, SPX, and QQQ traders to identify potential support, resistance, pinning zones, and volatility-regime shifts. HOW TO USE 1. Add the indicator. 2. Open Settings and enter today's Gamma Flip, Call Wall, Put Wall, and Max Gamma / Pin. Each draws as a horizontal line with a price label, plus an on-chart info box. Set any level to 0 to hide it. Optional price-cross alerts are included. This script is manual-entry only — it does not pull data. Daily gamma levels are published for free at zerogex.io. For informational and educational purposes only. Not financial advice.

Indicatore

Seasonality: Forex Indices [invincible3]Seasonality: Forex Index Seasonality: Forex Index is a visual seasonality dashboard designed to help traders analyze historical yearly patterns across major currency indexes. The indicator displays compact 365-day seasonal mini charts directly on the price chart. Each currency index is shown in its own separate panel, allowing traders to quickly compare seasonal strength, weakness, turning points, and recurring calendar-based tendencies throughout the year. Included forex indexes: • Australian Dollar • Canadian Dollar • Swiss Franc • Dollar Index • Euro • British Pound • Japanese Yen Each currency includes two seasonal curves: Blue Line — All Years Average Shows the long-term historical seasonal tendency for the selected currency index. Yellow Line — Weighted Average Shows a weighted seasonal curve designed to give more importance to recent seasonal behavior while still preserving the broader historical pattern. The dashboard is fully customizable. Users can enable or disable individual currency indexes, choose whether to display the All Years curve, the Weighted Average curve, or both, and adjust the widget width, distance from candles, column spacing, panel height, row gap, and dashboard placement. Key Features: • Seasonality dashboard for major forex indexes • Includes AUD, CAD, CHF, DXY, EUR, GBP and JPY • 365-day calendar-based seasonal curves • All Years average and Weighted Average comparison • Separate mini chart for each currency index • Monthly grid lines and month labels • Adjustable dashboard size, spacing, and placement • Right-side dashboard placement option • Auto-theme color support • Manual customization for line colors, grid, background, and text • Clean visual panels for quick seasonal comparison This indicator is useful for identifying periods where major currencies have historically shown stronger or weaker seasonal tendencies. It can help traders add seasonal context to forex pairs, dollar strength analysis, macro bias, trend structure, and technical setups. The seasonality curves are intended as a relative historical guide, not exact price forecasts. This indicator does not generate direct buy or sell signals. Seasonality should be used as a supporting research tool together with price action, trend analysis, macro fundamentals, confirmation, and proper risk management.

Indicatore

Absorption Zones + Hold-Rate Stats Absorption Zones + Hold-Rate Stats WHAT THIS PUBLICATION ADDS Most volume tools show you WHERE unusual activity happened. This script does two things beyond that, and the second one is the reason it exists: 1. It detects ABSORPTION - bars where one side hits the market aggressively (measured with real intrabar up/down volume from a lower timeframe), yet price refuses to move, which is the classic footprint of large passive orders defending a level - and turns each event into a zone. 2. It then tracks every zone FORWARD and reports the outcome statistics on your exact symbol and timeframe: how many zones were retested, how often a retest actually held, how long the first test took, and the median reaction size in ATR. The indicator audits itself instead of asking you to trust its drawings. To my knowledge, self-measured hold-rate reporting for absorption zones is not available in existing public scripts. HOW ABSORPTION IS DETECTED - Intrabar delta: each chart bar is split into lower-timeframe bars (auto: 60min on D+, 15min on 4H+, 5min on 1H+, 1min below; manual override available). Volume of rising intrabars counts as buying, falling as selling; their difference is the bar's delta. Where intrabar history is not available, a close-location estimate is used and the table reports the real intrabar coverage so you always know the data quality. - Two detection models, selectable: a) Delta absorption: bar volume above the Nth percentile of the lookback window (default 80th of 200 bars), |delta|/volume above a minimum share (default 0.12), and the close positioned AGAINST the aggression - heavy selling that closes in the top of the bar means someone absorbed it (bullish), and vice versa. b) Effort vs result: volume above the percentile threshold while the bar range ranks BELOW its percentile cap (default 50th) - huge effort, no result - with the close direction defining the side. - Each zone gets a transparency-scored grade (A/B/C) built from volume percentile (35%), delta share (30%), close position (20%) and effort-vs-result compression (15%). The label tooltip shows every component. - The zone box spans the part of the bar where the passive orders acted: from the low up to a configurable fraction of the range for bullish zones, mirrored for bearish. HOW OUTCOMES ARE MEASURED - A zone is TESTED when price returns into it on a later bar. - It counts as HELD if, after the first test, price moves the configured number of ATR (default 1.5, ATR measured at test time) away from the zone edge before the zone breaks; it is BROKEN when price closes (or wicks, selectable) through the far edge. If neither happens within the resolve window (default 40 bars), the zone is resolved by whether the target was reached. Same-bar conflicts are resolved as BROKEN, so the reported hold-rate is conservative. - Untested zones older than the age limit expire and are excluded, so statistics only describe zones that price actually revisited. - The table reports, separately for bullish and bearish zones: zones formed, tested share, hold-rate with sample size, median bars to first test, and median reaction in ATR multiples. HOW TO USE - Treat active zones as locations where large passive interest was proven, not as automatic signals. The retest of a fresh A-grade zone is the event worth your attention; the marker and alerts fire exactly there. - Read the table first: if the hold-rate on your symbol/timeframe is near a coin flip or the sample is small, lower the sensitivity (raise the volume percentile, raise the min delta share) or move to a higher timeframe. - The zone edge and the sweep low/high give natural invalidation levels. - Six alerts are available: new bullish/bearish zone, bullish/bearish zone retest, bullish/bearish zone break. SETTINGS GUIDE - Percentile lookback 200 / volume threshold 80 work on most liquid markets. For quiet instruments lower the threshold to 70; for very active ones raise it to 90 to keep only exceptional bars. - Zone width 0.5 matches "the half of the bar where the fight happened"; 0.25-0.35 gives tighter, stricter zones. - Hold target 1.5 ATR suits intraday; swing traders may prefer 2-3 ATR with a longer resolve window. LIMITATIONS - READ BEFORE USING - Intrabar delta is an approximation built from lower-timeframe bars, not exchange tick data. The coverage row in the table shows exactly what share of bars used real intrabar data. - Detection runs on confirmed bars only, so zones and events do not repaint; the cost is that everything appears at bar close, never mid-bar. - The hold-rate is descriptive statistics of the loaded chart history, not a forecast. Past zone behaviour does not guarantee future results. This is a decision-support tool, not a signal service. Open-source under MPL 2.0 - study, fork and improve it freely.

Indicatore

di PersonalConcentrat

MA Z-Score Deviation A valuation oscillator that measures how far price has stretched from its statistical fair value defined here as its moving average, expressed as a standardized score rather than raw price units. How it works Base: A moving average (SMA, EMA, or WMA) serves as the reference "fair value" line. Deviation from this baseline is calculated as a log ratio (log(price / MA)) rather than a simple price difference, so the reading stays comparable across different price levels and time periods: a 5% premium or discount reads the same whether the instrument is at $10 or $500. Standardization: the deviation is divided by its own rolling dispersion to produce a score that expresses how rich or cheap price is relative to its typical range, not just in absolute terms. Two dispersion methods are available: Standard Deviation: the classical measure of typical variability. MAD: a median-based measure that's more resistant to distortion from one-off outlier bars. Blend: a weighted combination of both, adjustable via the MAD Weight input. Display scaling: the score is passed through a bounded transform for cleaner visual scaling on the chart, while the underlying valuation ranking is preserved. Inputs Source & MA type (SMA/EMA/WMA) and length Lookback length for the dispersion calculation, independent from the MA length, letting you compare long-term fair value against recent volatility conditions Dispersion method (Stdev / MAD / Blend) and blend weight Display scaling factor Reading the indicator Positive values indicate price is trading at a premium to its baseline; negative values indicate a discount. Values beyond ±2 suggest a notable premium/discount relative to recent conditions; beyond ±3 suggests a substantial one. Because the baseline is statistical rather than fixed, the "fair value" and its bands adjust automatically as market conditions evolve. Notes / limitations This measures statistical richness/cheapness relative to a moving average, not intrinsic or fundamental value; it's a technical valuation lens, not a fundamental one. Financial return distributions have fatter tails than a normal distribution assumes, so extreme readings can occur more frequently than the underlying statistical model implies; treat scores as relative positioning, not precise probabilities. Alerts trigger only on confirmed bar closes to avoid firing on intrabar noise.

Indicatore