Inizia

Cerca negli script per "high low"

JK_Traders_Reality_LibLibrary "JK_Traders_Reality_Lib" This library contains common elements used in Traders Reality scripts calcPvsra(pvsraVolume, pvsraHigh, pvsraLow, pvsraClose, pvsraOpen, redVectorColor, greenVectorColor, violetVectorColor, blueVectorColor, darkGreyCandleColor, lightGrayCandleColor)   calculate the pvsra candle color and return the color as well as an alert if a vector candle has apperared. Situation "Climax" Bars with volume >= 200% of the average volume of the 10 previous chart TFs, or bars where the product of candle spread x candle volume is >= the highest for the 10 previous chart time TFs. Default Colors: Bull bars are green and bear bars are red. Situation "Volume Rising Above Average" Bars with volume >= 150% of the average volume of the 10 previous chart TFs. Default Colors: Bull bars are blue and bear are violet.   Parameters:      pvsraVolume (float) : the instrument volume series (obtained from request.sequrity)      pvsraHigh (float) : the instrument high series (obtained from request.sequrity)      pvsraLow (float) : the instrument low series (obtained from request.sequrity)      pvsraClose (float) : the instrument close series (obtained from request.sequrity)      pvsraOpen (float) : the instrument open series (obtained from request.sequrity)      redVectorColor (simple color) : red vector candle color      greenVectorColor (simple color) : green vector candle color      violetVectorColor (simple color) : violet/pink vector candle color      blueVectorColor (simple color) : blue vector candle color      darkGreyCandleColor (simple color) : regular volume candle down candle color - not a vector      lightGrayCandleColor (simple color) : regular volume candle up candle color - not a vector @return adr(length, barsBack)   Parameters:      length (simple int) : how many elements of the series to calculate on      barsBack (simple int) : starting possition for the length calculation - current bar or some other value eg last bar @return adr the adr for the specified lenght adrHigh(adr, fromDo)   Calculate the ADR high given an ADR   Parameters:      adr (float) : the adr      fromDo (simple bool) : boolean flag, if false calculate traditional adr from high low of today, if true calcualte from exchange midnight @return adrHigh the position of the adr high in price adrLow(adr, fromDo)   Parameters:      adr (float) : the adr      fromDo (simple bool) : boolean flag, if false calculate traditional adr from high low of today, if true calcualte from exchange midnight @return adrLow the position of the adr low in price splitSessionString(sessXTime)   given a session in the format 0000-0100:23456 split out the hours and minutes   Parameters:      sessXTime (simple string) : the session time string usually in the format 0000-0100:23456 @return calcSessionStartEnd(sessXTime, gmt)   calculate the start and end timestamps of the session   Parameters:      sessXTime (simple string) : the session time string usually in the format 0000-0100:23456      gmt (simple string) : the gmt offset string usually in the format GMT+1 or GMT+2 etc @return drawOpenRange(sessXTime, sessXcol, showOrX, gmt)   draw open range for a session   Parameters:      sessXTime (simple string) : session string in the format 0000-0100:23456      sessXcol (simple color) : the color to be used for the opening range box shading      showOrX (simple bool) : boolean flag to toggle displaying the opening range      gmt (simple string) : the gmt offset string usually in the format GMT+1 or GMT+2 etc @return void drawSessionHiLo(sessXTime, showRectangleX, showLabelX, sessXcolLabel, sessXLabel, gmt, sessionLineStyle)   Parameters:      sessXTime (simple string) : session string in the format 0000-0100:23456      showRectangleX (simple bool)      showLabelX (simple bool)      sessXcolLabel (simple color) : the color to be used for the hi/low lines and label      sessXLabel (simple string) : the session label text      gmt (simple string) : the gmt offset string usually in the format GMT+1 or GMT+2 etc      sessionLineStyle (simple string) : the line stile for the session high low lines @return void calcDst()   calculate market session dst on/off flags @return indicating if DST is on or off for a particular region timestampPreviousDayOfWeek(previousDayOfWeek, hourOfDay, gmtOffset, oneWeekMillis)   Timestamp any of the 6 previous days in the week (such as last Wednesday at 21 hours GMT)   Parameters:      previousDayOfWeek (simple string) : Monday or Satruday      hourOfDay (simple int) : the hour of the day when psy calc is to start      gmtOffset (simple string) : the gmt offset string usually in the format GMT+1 or GMT+2 etc      oneWeekMillis (simple int) : the amount if time for a week in milliseconds @return the timestamp of the psy level calculation start time getdayOpen()   get the daily open - basically exchange midnight @return the daily open value which is float price newBar(res)   new_bar: check if we're on a new bar within the session in a given resolution   Parameters:      res (simple string) : the desired resolution @return true/false is a new bar for the session has started toPips(val)   to_pips Convert value to pips   Parameters:      val (float) : the value to convert to pips @return the value in pips rLabel(ry, rtext, rstyle, rcolor, valid, labelXOffset)   a function that draws a right aligned lable for a series during the current bar   Parameters:      ry (float) : series float the y coordinate of the lable      rtext (simple string) : the text of the label      rstyle (simple string) : the style for the lable      rcolor (simple color) : the color for the label      valid (simple bool) : a boolean flag that allows for turning on or off a lable      labelXOffset (int) : how much to offset the label from the current position rLabelOffset(ry, rtext, rstyle, rcolor, valid, labelOffset)   a function that draws a right aligned lable for a series during the current bar   Parameters:      ry (float) : series float the y coordinate of the lable      rtext (string) : the text of the label      rstyle (simple string) : the style for the lable      rcolor (simple color) : the color for the label      valid (simple bool) : a boolean flag that allows for turning on or off a lable      labelOffset (int) rLabelLastBar(ry, rtext, rstyle, rcolor, valid, labelXOffset)   a function that draws a right aligned lable for a series only on the last bar   Parameters:      ry (float) : series float the y coordinate of the lable      rtext (string) : the text of the label      rstyle (simple string) : the style for the lable      rcolor (simple color) : the color for the label      valid (simple bool) : a boolean flag that allows for turning on or off a lable      labelXOffset (int) : how much to offset the label from the current position drawLine(xSeries, res, tag, xColor, xStyle, xWidth, xExtend, isLabelValid, xLabelOffset, validTimeFrame)   a function that draws a line and a label for a series   Parameters:      xSeries (float) : series float the y coordinate of the line/label      res (simple string) : the desired resolution controlling when a new line will start      tag (simple string) : the text for the lable      xColor (simple color) : the color for the label      xStyle (simple string) : the style for the line      xWidth (simple int) : the width of the line      xExtend (simple string) : extend the line      isLabelValid (simple bool) : a boolean flag that allows for turning on or off a label      xLabelOffset (int)      validTimeFrame (simple bool) : a boolean flag that allows for turning on or off a line drawn drawLineDO(xSeries, res, tag, xColor, xStyle, xWidth, xExtend, isLabelValid, xLabelOffset, validTimeFrame)   a function that draws a line and a label for the daily open series   Parameters:      xSeries (float) : series float the y coordinate of the line/label      res (simple string) : the desired resolution controlling when a new line will start      tag (simple string) : the text for the lable      xColor (simple color) : the color for the label      xStyle (simple string) : the style for the line      xWidth (simple int) : the width of the line      xExtend (simple string) : extend the line      isLabelValid (simple bool) : a boolean flag that allows for turning on or off a label      xLabelOffset (int)      validTimeFrame (simple bool) : a boolean flag that allows for turning on or off a line drawn drawPivot(pivotLevel, res, tag, pivotColor, pivotLabelColor, pivotStyle, pivotWidth, pivotExtend, isLabelValid, validTimeFrame, levelStart, pivotLabelXOffset)   draw a pivot line - the line starts one day into the past   Parameters:      pivotLevel (float) : series of the pivot point      res (simple string) : the desired resolution      tag (simple string) : the text to appear      pivotColor (simple color) : the color of the line      pivotLabelColor (simple color) : the color of the label      pivotStyle (simple string) : the line style      pivotWidth (simple int) : the line width      pivotExtend (simple string) : extend the line      isLabelValid (simple bool) : boolean param allows to turn label on and off      validTimeFrame (simple bool) : only draw the line and label at a valid timeframe      levelStart (int) : basically when to start drawing the levels      pivotLabelXOffset (int) : how much to offset the label from its current postion @return the pivot line series getPvsraFlagByColor(pvsraColor, redVectorColor, greenVectorColor, violetVectorColor, blueVectorColor, lightGrayCandleColor)   convert the pvsra color to an internal code   Parameters:      pvsraColor (color) : the calculated pvsra color      redVectorColor (simple color) : the user defined red vector color      greenVectorColor (simple color) : the user defined green vector color      violetVectorColor (simple color) : the user defined violet vector color      blueVectorColor (simple color) : the user defined blue vector color      lightGrayCandleColor (simple color) : the user defined regular up candle color @return pvsra internal code updateZones(pvsra, direction, boxArr, maxlevels, pvsraHigh, pvsraLow, pvsraOpen, pvsraClose, transperancy, zoneupdatetype, zonecolor, zonetype, borderwidth, coloroverride, redVectorColor, greenVectorColor, violetVectorColor, blueVectorColor)   a function that draws the unrecovered vector candle zones   Parameters:      pvsra (int) : internal code      direction (simple int) : above or below the current pa      boxArr (array) : the array containing the boxes that need to be updated      maxlevels (simple int) : the maximum number of boxes to draw      pvsraHigh (float) : the pvsra high value series      pvsraLow (float) : the pvsra low value series      pvsraOpen (float) : the pvsra open value series      pvsraClose (float) : the pvsra close value series      transperancy (simple int) : the transparencfy of the vecor candle zones      zoneupdatetype (simple string) : the zone update type      zonecolor (simple color) : the zone color if overriden      zonetype (simple string) : the zone type      borderwidth (simple int) : the width of the border      coloroverride (simple bool) : if the color overriden      redVectorColor (simple color) : the user defined red vector color      greenVectorColor (simple color) : the user defined green vector color      violetVectorColor (simple color) : the user defined violet vector color      blueVectorColor (simple color) : the user defined blue vector color cleanarr(arr)   clean an array from na values   Parameters:      arr (array) : the array to clean @return if the array was cleaned calcPsyLevels(oneWeekMillis, showPsylevels, psyType, sydDST)   calculate the psy levels 4 hour res based on how mt4 does it mt4 code int Li_4 = iBarShift(NULL, PERIOD_H4, iTime(NULL, PERIOD_W1, Li_0)) - 2 - Offset; ObjectCreate("PsychHi", OBJ_TREND, 0, Time , iHigh(NULL, PERIOD_H4, iHighest(NULL, PERIOD_H4, MODE_HIGH, 2, Li_4)), iTime(NULL, PERIOD_W1, 0), iHigh(NULL, PERIOD_H4, iHighest(NULL, PERIOD_H4, MODE_HIGH, 2, Li_4))); so basically because the session is 8 hours and we are looking at a 4 hour resolution we only need to take the highest high an lowest low of 2 bars we use the gmt offset to adjust the 0000-0800 session to Sydney open which is at 2100 during dst and at 2200 otherwize. (dst - spring foward, fall back) keep in mind sydney is in the souther hemisphere so dst is oposite of when london and new york go into dst   Parameters:      oneWeekMillis (simple int) : a constant value      showPsylevels (simple bool) : should psy levels be calculated      psyType (simple string) : the type of Psylevels - crypto or forex      sydDST (bool) : is Sydney in DST @return adrHiLo(length, barsBack, fromDO)   Parameters:      length (simple int) : how many elements of the series to calculate on      barsBack (simple int) : starting possition for the length calculation - current bar or some other value eg last bar      fromDO (simple bool) : boolean flag, if false calculate traditional adr from high low of today, if true calcualte from exchange midnight @return adr, adrLow and adrHigh - the adr, the position of the adr High and adr Low with respect to price drawSessionHiloLite(sessXTime, showRectangleX, showLabelX, sessXcolLabel, sessXLabel, gmt, sessionLineStyle, sessXcol)   Parameters:      sessXTime (simple string) : session string in the format 0000-0100:23456      showRectangleX (simple bool)      showLabelX (simple bool)      sessXcolLabel (simple color) : the color to be used for the hi/low lines and label      sessXLabel (simple string) : the session label text      gmt (simple string) : the gmt offset string usually in the format GMT+1 or GMT+2 etc      sessionLineStyle (simple string) : the line stile for the session high low lines      sessXcol (simple color) : - the color for the box color that will color the session @return void msToHmsString(ms)   converts milliseconds into an hh:mm string. For example, 61000 ms to '0:01:01'   Parameters:      ms (int) : - the milliseconds to convert to hh:mm @return string - the converted hh:mm string countdownString(openToday, closeToday, showMarketsWeekends, oneDay)   that calculates how much time is left until the next session taking the session start and end times into account. Note this function does not work on intraday sessions.   Parameters:      openToday (int) : - timestamps of when the session opens in general - note its a series because the timestamp was created using the dst flag which is a series itself thus producing a timestamp series      closeToday (int) : - timestamp of when the session closes in general - note its a series because the timestamp was created using the dst flag which is a series itself thus producing a timestamp series @return a countdown of when next the session opens or 'Open' if the session is open now      showMarketsWeekends (simple bool)      oneDay (simple int) countdownStringSyd(sydOpenToday, sydCloseToday, showMarketsWeekends, oneDay)   that calculates how much time is left until the next session taking the session start and end times into account. special case of intraday sessions like sydney   Parameters:      sydOpenToday (int)      sydCloseToday (int)      showMarketsWeekends (simple bool)      oneDay (simple int)
Libreria Pine Script®
di Justas123
2
Live Market - Performance MonitorLive Market — Performance Monitor Study material (no code) — step-by-step training guide for learners ________________________________________ 1) What this tool is — short overview This indicator is a live market performance monitor designed for learning. It scans price, volume and volatility, detects order blocks and trendline events, applies filters (volume & ATR), generates trade signals (BUY/SELL), creates simple TP/SL trade management, and renders a compact dashboard summarizing market state, risk and performance metrics. Use it to learn how multi-factor signals are constructed, how Greeks-style sensitivity is replaced by volatility/ATR reasoning, and how a live dashboard helps monitor trade quality. ________________________________________ 2) Quick start — how a learner uses it (step-by-step) 1. Add the indicator to a chart (any ticker / timeframe). 2. Open inputs and review the main groups: Order Block, Trendline, Signal Filters, Display. 3. Start with defaults (OB periods ≈ 7, ATR multiplier 0.5, volume threshold 1.2) and observe the dashboard on the last bar. 4. Walk the chart back in time (use the last-bar update behavior) and watch how signals, order blocks, trendlines, and the performance counters change. 5. Run the hands-on labs below to build intuition. ________________________________________ 3) Main configurable inputs (what you can tweak) • Order Block Relevant Periods (default ~7): number of consecutive candles used to define an order block. • Min. Percent Move for Valid OB (threshold): minimum percent move required for a valid order block. • Number of OB Channels: how many past order block lines to keep visible. • Trendline Period (tl_period): pivot lookback for detecting highs/lows used to draw trendlines. • Use Wicks for Trendlines: whether pivot uses wicks or body. • Extension Bars: how far trendlines are projected forward. • Use Volume Filter + Volume Threshold Multiplier (e.g., 1.2): requires volume to be greater than multiplier × average volume. • Use ATR Filter + ATR Multiplier: require bar range > ATR × multiplier to filter noise. • Show Targets / Table settings / Colors for visualization. ________________________________________ 4) Core building blocks — what the script computes (plain language) Price & trend: • Spot / LTP: current close price. • EMA 9 / 21 / 50: fast, medium, slow moving averages to define short/medium trend. o trend_bullish: EMA9 > EMA21 > EMA50 o trend_bearish: EMA9 < EMA21 < EMA50 o trend_neutral: otherwise Volatility & noise: • ATR (14): average true range used for dynamic target and filter sizing. • dynamic_zone = ATR × atr_multiplier: minimum bar range required for meaningful move. • Annualized volatility: stdev of price changes × sqrt(252) × 100 — used to classify volatility (HIGH/MEDIUM/LOW). Momentum & oscillators: • RSI 14: overbought/oversold indicator (thresholds 70/30). • MACD: EMA(12)-EMA(26) and a 9-period signal line; histogram used for momentum direction and strength. • Momentum (ta.mom 10): raw momentum over 10 bars. Mean reversion / band context: • Bollinger Bands (20, 2σ): upper, mid, lower. o price_position measures where price sits inside the band range as 0–100. Volume metrics: • avg_volume = SMA(volume, 20) and volume_spike = volume > avg_volume × volume_threshold o volume_ratio = volume / avg_volume Support & Resistance: • support_level = lowest low over 20 bars • resistance_level = highest high over 20 bars • current_position = percent of price between support & resistance (0–100) ________________________________________ 5) Order Block detection — concept & logic What it tries to find: a bar (the base) followed by N candles in the opposite direction (a classical order block setup), with a minimum % move to qualify. The script records the high/low of the base candle, averages them, and plots those levels as OB channels. How learners should think about it (conceptual): 1. An order block is a signature area where institutions (theory) left liquidity — often seen as a large bar followed by a sequence of directional candles. 2. This indicator uses a configurable number of subsequent candles to confirm that the pattern exists. 3. When found, it stores and displays the base candle’s high/low area so students can see how price later reacts to those zones. Implementation note for learners: the tool keeps a limited history of OB lines (ob_channels). When new OBs exceed the count, the oldest lines are removed — good practice to avoid clutter. ________________________________________ 6) Trendline detection — idea & interpretation • The script finds pivot highs and lows using a symmetric lookback (tl_period and half that as right/left). • It then computes a trendline slope from successive pivots and projects the line forward (extension_bars). • Break detection: Resistance break = close crosses above the projected resistance line; Support break = close crosses below projected support. Learning tip: trendlines here are computed from pivot points and time. Watch how changing tl_period (bigger = smoother, fewer pivots) alters the trendlines and break signals. ________________________________________ 7) Signal generation & filters — step-by-step 1. Primary triggers: o Bullish trigger: order block bullish OR resistance trendline break. o Bearish trigger: bearish order block OR support trendline break. 2. Filters applied (both must pass unless disabled): o Volume filter: volume must be > avg_volume × volume_threshold. o ATR filter: bar range (high-low) must exceed ATR × atr_multiplier. o Not in an existing trade: new trades only start if trade_active is false. 3. Trend confirmation: o The primary trigger is only confirmed if trend is bullish/neutral for buys or bearish/neutral for sells (EMA alignment). 4. Result: o When confirmed, a long or short trade is activated with TP/SL calculated from ATR multiples. ________________________________________ 8) Trade management — what the tool does after a signal • Entry management: the script marks a trade as trade_active and sets long_trade or short_trade flags. • TP & SL rules: o Long: TP = high + 2×ATR ; SL = low − 1×ATR o Short: TP = low − 2×ATR ; SL = high + 1×ATR • Monitoring & exit: o A trade closes when price reaches TP or SL. o When TP/SL hit, the indicator updates win_count and total_pnl using a very simple calculation (difference between TP/SL and previous close). o Visual lines/labels are drawn for TP and updated as the trade runs. Important learner notes: • The script does not store a true entry price (it uses close in its P&L math), so PnL is an approximation — treat this as a learning proxy, not a position accounting system. • There’s no sizing, slippage, or fee accounted — students must manually factor these when translating to real trades. • This indicator is not a backtesting strategy; strategy.* functions would be needed for rigorous backtest results. ________________________________________ 9) Signal strength & helper utilities • Signal strength is a composite score (0–100) made up of four signals worth 25 points each: 1. RSI extreme (overbought/oversold) → 25 2. Volume spike → 25 3. MACD histogram magnitude increasing → 25 4. Trend existence (bull or bear) → 25 • Progress bars (text glyphs) are used to visually show RSI and signal strength on the table. Learning point: composite scoring is a way to combine orthogonal signals — study how changing weights changes outcomes. ________________________________________ 10) Dashboard — how to read each section (walkthrough) The dashboard is split into sections; here's how to interpret them: 1. Market Overview o LTP / Change%: immediate price & daily % change. 2. RSI & MACD o RSI value plus progress bar (overbought 70 / oversold 30). o MACD histogram sign indicates bullish/bearish momentum. 3. Volume Analysis o Volume ratio (current / average) and whether there’s a spike. 4. Order Block Status o Buy OB / Sell OB: the average base price of detected order blocks or “No Signal.” 5. Signal Status o 🔼 BUY or 🔽 SELL if confirmed, or ⚪ WAIT. o No-trade vs Active indicator summarizing market readiness. 6. Trend Analysis o Trend direction (from EMAs), market sentiment score (composite), volatility level and band/position metrics. 7. Performance o Win Rate = wins / signals (percentage) o Total PnL = cumulative PnL (approximate) o Bull / Bear Volume = accumulated volumes attributable to signals 8. Support & Resistance o 20-bar highest/lowest — use as nearby reference points. 9. Risk & R:R o Risk Level from ATR/price as a percent. o R:R Ratio computed from TP/SL if a trade is active. 10. Signal Strength & Active Trade Status • Numeric strength + progress bar and whether a trade is currently active with TP/SL display. ________________________________________ 11) Alerts — what will notify you The indicator includes pre-built alert triggers for: • Bullish confirmed signal • Bearish confirmed signal • TP hit (long/short) • SL hit (long/short) • No-trade zone • High signal strength (score > 75%) Training use: enable alerts during a replay session to be notified when the indicator would have signalled. ________________________________________ 12) Labs — hands-on exercises for learners (step-by-step) Lab A — Order Block recognition 1. Pick a 15–30 minute timeframe on a liquid ticker. 2. Use default OB periods (7). Mark each time the dashboard shows a Buy/Sell OB. 3. Manually inspect the chart at the base candle and the following sequence — draw the OB zone by hand and watch later price reactions to it. 4. Repeat with OB periods 5 and 10; note stability vs noise. Lab B — Trendline break confirmation 1. Increase trendline period (e.g., 20), watch trendlines form from pivots. 2. When a resistance break is flagged, compare with MACD & volume: was momentum aligned? 3. Note false breaks vs confirmed moves — change extension_bars to see projection effects. Lab C — Filter sensitivity 1. Toggle Use Volume Filter off, and record the number and quality of signals in a 2-day window. 2. Re-enable volume filter and change threshold from 1.2 → 1.6; note how many low-quality signals are filtered out. Lab D — Trade management simulation 1. For each signalled trade, record the time, close entry approximation, TP, SL, and eventual hit/miss. 2. Compute actual PnL if you had entered at the open of the next bar to compare with the script’s PnL math. 3. Tabulate win rate and average R:R. Lab E — Performance review & improvement 1. Build a spreadsheet of signals over 30–90 periods with columns: Date, Signal type, Entry price (real), TP, SL, Exit, PnL, Notes. 2. Analyze which filters or indicators contributed most to winners vs losers and adjust weights. ________________________________________ 13) Common pitfalls, assumptions & implementation notes (things to watch) • P&L simplification: total_pnl uses close as a proxy entry price. Real entry/exit prices and slippage are not recorded — so PnL is approximate. • No position sizing or money management: the script doesn’t compute position size from equity or risk percent. • Signal confirmation logic: composite "signal_strength" is a simple 4×25 point scheme — explore different weights or additional signals. • Order block detection nuance: the script defines the base candle and checks the subsequent sequence. Be sure to verify whether the intended candle direction (base being bullish vs bearish) aligns with academic/your trading definition — read the code carefully and test. • Trendline slope over time: slope is computed using timestamps; small differences may make lines sensitive on very short timeframes — using bar_index differences is usually more stable. • Not a true backtester: to evaluate performance statistically you must transform the logic into a strategy script that places hypothetical orders and records exact entry/exit prices. ________________________________________ 14) Suggested improvements for advanced learners • Record true entry price & timestamp for accurate PnL. • Add position sizing: risk % per trade using SL distance and account size. • Convert to strategy. (Pine Strategy)* to run formal backtests with equity curves, drawdowns, and metrics (Sharpe, Sortino). • Log trades to an external spreadsheet (via alerts + webhook) for offline analysis. • Add statistics: average win/loss, expectancy, max drawdown. • Add additional filters: news time blackout, market session filters, multi-timeframe confirmation. • Improve OB detection: combine wick/body, volume spike at base bar, and liquidity sweep detection. ________________________________________ 15) Glossary — quick definitions • ATR (Average True Range): measure of typical range; used to size targets and stops. • EMA (Exponential Moving Average): trend smoothing giving more weight to recent prices. • RSI (Relative Strength Index): momentum oscillator; >70 overbought, <30 oversold. • MACD: momentum oscillator using difference of two EMAs. • Bollinger Bands: volatility bands around SMA. • Order Block: a base candle area with subsequent confirmation candles; a zone of institutional interest (learning model). • Pivot High/Low: local turning point defined by candles on both sides. • Signal Strength: combined score from multiple indicators. • Win Rate: proportion of signals that hit TP vs total signals. • R:R (Risk:Reward): ratio of potential reward (TP distance) to risk (entry to SL). ________________________________________ 16) Limitations & assumptions (be explicit) • This is an indicator for learning — not a trading robot or broker connection. • No slippage, fees, commissions or tie-in to real orders are considered. • The logic is heuristic (rule-of-thumb), not a guarantee of performance. • Results are sensitive to timeframe, market liquidity, and parameter choices. ________________________________________ 17) Practical classroom / study plan (4 sessions) • Session 1 — Foundations: Understand EMAs, ATR, RSI, MACD, Bollinger Bands. Run the indicator and watch how these numbers change on a single day. • Session 2 — Zones & Filters: Study order blocks and trendlines. Test volume & ATR filters and note changes in false signals. • Session 3 — Simulated trading: Manually track 20 signals, compute real PnL and compare to the dashboard. • Session 4 — Improvement plan: Propose changes (e.g., better PnL accounting, alternative OB rule) and test their impact. ________________________________________ 18) Quick reference checklist for each signal 1. Was an order block or trendline break detected? (primary trigger) 2. Did volume meet threshold? (filter) 3. Did ATR filter (bar size) show a real move? (filter) 4. Was trend aligned (EMA 9/21/50)? (confirmation) 5. Signal confirmed → mark entry approximation, TP, SL. 6. Monitor dashboard (Signal Strength, Volatility, No-trade zone, R:R). 7. After exit, log real entry/exit, compute actual PnL, update spreadsheet. ________________________________________ 19) Educational caveat & final note This tool is built for training and analysis: it helps you see how common technical building blocks combine into trade ideas, but it is not a trading recommendation. Use it to develop judgment, to test hypotheses, and to design robust systems with proper backtesting and risk control before risking capital. ________________________________________ 20) Disclaimer (must include) Training & Educational Only — This material and the indicator are provided for educational purposes only. Nothing here is investment advice or a solicitation to buy or sell financial instruments. Past simulated or historical performance does not predict future results. Always perform full backtesting and risk management, and consider seeking advice from a qualified financial professional before trading with real capital. ________________________________________
Indicatore Pine Script®
di aiTrendview-Charting-System
Reversal Point Dynamics⇋ Reversal Point Dynamics (RPD) This is not an indicator; it is a complete system for deconstructing the mechanics of a market reversal. Reversal Point Dynamics (RPD) moves far beyond simplistic pattern recognition, venturing into a deep analysis of the underlying forces that cause trends to exhaust, pause, and turn. It is engineered from the ground up to identify high-probability reversal points by quantifying the confluence of market dynamics in real-time. Where other tools provide a static signal, RPD delivers a dynamic probability. It understands that a true market turning point is not a single event, but a cascade of failing momentum, structural breakdown, and a shift in market order. RPD's core engine meticulously analyzes each of these dynamic components—the market's underlying state, its velocity and acceleration, its degree of chaos (entropy), and its structural framework. These forces are synthesized into a single, unified Probability Score, offering you an unprecedented, transparent view into the conviction behind every potential reversal. This is not a "black box" system. It is an open-architecture engine designed to empower the discerning trader. Featuring real-time signal projection, an integrated Fibonacci R2R Target Engine, and a comprehensive dashboard that acts as your Dynamics Control Center , RPD gives you a complete, holistic view of the market's state. The Theoretical Core: Deconstructing Market Dynamics RPD's analytical power is born from the intelligent synthesis of multiple, distinct theoretical models. Each pillar of the engine analyzes a different facet of market behavior. The convergence of these analyses—the "Singularity" event referenced in the dashboard—is what generates the final, high-conviction probability score. 1. Pillar One: Quantum State Analysis (QSA) This is the foundational analysis of the market's current state within its recent context. Instead of treating price as a random walk, QSA quantizes it into a finite number of discrete "states." Formulaic Concept: The engine establishes a price range using the highest high and lowest low over the Adaptive Analysis Period. This range is then divided into a user-defined number of Analysis Levels. The current price is mapped to one of these states (e.g., in a 9-level system, State 0 is the absolute low, and State 8 is the absolute high). Analytical Edge: This acts as a powerful foundational filter. The engine will only begin searching for reversal signals when the market has reached a statistically stretched, extreme state (e.g., State 0 or 8). The Edge Sensitivity input allows you to control exactly how close to this extreme edge the price must be, ensuring you are trading from points of maximum potential exhaustion. 2. Pillar Two: Price State Roc (PSR) - The Dynamics of Momentum This pillar analyzes the kinetic forces of the market: its velocity and acceleration. It understands that it’s not just where the price is, but how it got there that matters. Formulaic Concept: The psr function calculates two derivatives of price. Velocity: (price - price ). This measures the speed and direction of the current move. Acceleration: (velocity - velocity ). This measures the rate of change in that speed. A negative acceleration (deceleration) during a strong rally is a critical pre-reversal warning, indicating momentum is fading even as price may be pushing higher. Analytical Edge: The engine specifically hunts for exhaustion patterns where momentum is clearly decelerating as price reaches an extreme state. This is the mechanical signature of a weakening trend. 3. Pillar Three: Market Entropy Analysis - The Dynamics of Order & Chaos This is RPD's chaos filter, a concept borrowed from information theory. Entropy measures the degree of randomness or disorder in the market's price action. Formulaic Concept: The calculateEntropy function analyzes recent price changes. A market moving directionally and smoothly has low entropy (high order). A market chopping back and forth without direction has high entropy (high chaos). The value is normalized between 0 and 1. Analytical Edge: The most reliable trades occur in low-entropy, ordered environments. RPD uses the Entropy Threshold to disqualify signals that attempt to form in chaotic, unpredictable conditions, providing a powerful shield against whipsaw markets. 4. Pillar Four: The Synthesis Engine & Probability Calculation This is where all the dynamic forces converge. The final probability score is a weighted calculation that heavily rewards confluence. Formulaic Concept: The calculateProbability function intelligently assembles the final score: A Base Score is established from trend strength and entropy. An Entropy Score adds points for low entropy (order) and subtracts for high entropy (chaos). A significant Divergence Bonus is awarded for a classic momentum divergence. RSI & Volume Bonuses are added if momentum oscillators are in extreme territory or a volume spike confirms institutional interest. MTF & Adaptive Bonuses add further weight for alignment with higher timeframe structure. Analytical Edge: A signal backed by multiple dynamic forces (e.g., extreme state + decelerating momentum + low entropy + volume spike) will receive an exponentially higher probability score. This is the very essence of analyzing reversal point dynamics. The Command Center: Mastering the Inputs Every input is a precise lever of control, allowing you to fine-tune the RPD engine to your exact trading style, market, and timeframe. 🧠 Core Algorithm Predictive Mode (Early Detection): What It Is: Enables the engine to search for potential reversals on the current, unclosed bar. How It Works: Analyzes intra-bar acceleration and state to identify developing exhaustion. These signals are marked with a ' ? ' and are tentative. How To Use It: Enable for scalping or very aggressive day trading to get the earliest possible indication. Disable for swing trading or a more conservative approach that waits for full bar confirmation. Live Signal Mode (Current Bar): What It Is: A highly aggressive mode that plots tentative signals with a ' ! ' on the live bar based on projected price and momentum. These signals repaint intra-bar. How It Works: Uses a linear regression projection of the close to anticipate a reversal. How To Use It: For advanced users who use intra-bar dynamics for execution and understand the nature of repainting signals. Adaptive Analysis Period: What It Is: The main lookback period for the QSA, PSR, and Entropy calculations. This is the engine's "memory." How It Works: A shorter period makes the engine highly sensitive to local price swings. A longer period makes it focus only on major, significant market structure. How To Use It: Scalping (1-5m): 15-25. Day Trading (15m-1H): 25-40. Swing Trading (4H+): 40-60. Fractal Strength (Bars): What It Is: Defines the strength of the pivot detection used for confirming reversal events. How It Works: A value of '2' requires a candle's high/low to be more extreme than the two bars to its left and right. How To Use It: '2' is a robust standard. Increase to '3' for an even stricter definition of a structural pivot, which will result in fewer signals. MTF Multiplier: What It Is: Integrates pivot data from a higher timeframe for confluence. How It Works: A multiplier of '4' on a 15-minute chart will pull pivot data from the 1-hour chart (15 * 4 = 60m). How To Use It: Set to a multiple that corresponds to your preferred higher timeframe for contextual analysis. 🎯 Signal Settings Min Probability %: What It Is: Your master quality filter. A signal is only plotted if its score exceeds this threshold. How It Works: Directly filters the output of the final probability calculation. How To Use It: High-Quality (80-95): For A+ setups only. Balanced (65-75): For day trading. Aggressive (50-60): For scalping. Min Signal Distance (Bars): What It Is: A noise filter that prevents signals from clustering in choppy conditions. How It Works: Enforces a "cooldown" period of N bars after a signal. How To Use It: Increase in ranging markets to focus on major swings. Decrease on lower timeframes. Entropy Threshold: What It Is: Your "chaos shield." Sets the maximum allowable market randomness for a signal. How It Works: If calculated entropy is above this value, the signal is invalidated. How To Use It: Lower values (0.1-0.5): Extremely strict. Higher values (0.7-1.0): More lenient. 0.85 is a good balance. Adaptive Entropy & Aggressive Mode: What It Is: Toggles for dynamically adjusting the engine's core parameters. How It Works: Adaptive Entropy can slightly lower the required probability in strong trends. Aggressive Mode uses more lenient settings across the board. How To Use It: Keep Adaptive on. Use Aggressive Mode sparingly, primarily for scalping highly volatile assets. 📊 State Analysis Analysis Levels: What It Is: The number of discrete "states" for the QSA. How It Works: More levels create a finer-grained analysis of price location. How To Use It: 6-7 levels are ideal. Increasing to 9 can provide more precision on very volatile assets. Edge Sensitivity: What It Is: Defines how close to the absolute top/bottom of the range price must be. How It Works: '0' means price must be in the absolute highest/lowest state. '3' allows a signal within the top/bottom 3 states. How To Use It: '3' provides a good balance. Lower it to '1' or '0' if you only want to trade extreme exhaustion. The Dashboard: Your Dynamics Control Center The dashboard provides a transparent, real-time view into the engine's brain. Use it to understand the context behind every signal and to gauge the current market environment at a glance. 🎯 UNIFIED PROB SCORE TOTAL SCORE: The highest probability score (either Peak or Valley) the engine is currently calculating. This is your main at-a-glance conviction metric. The "Singularity" header refers to the event where market dynamics align—the event RPD is built to detect. Quality: A human-readable interpretation of the Total Score. "EXCEPTIONAL" (🌟) is a rare, A+ confluence event. "STRONG" (💪) is a high-quality, tradable setup. 📊 ORDER FLOW & COMPONENT ANALYSIS Volume Spike: Shows if the current volume is significantly higher than average (YES/NO). A 'YES' adds major confirmation. Peak/Valley Conf: This breaks down the probability score into its directional components, showing you the separate confidence levels for a potential top (Peak) versus a bottom (Valley). 🌌 MARKET STRUCTURE HTF Trend: Shows the direction of the underlying trend based on a Supertrend calculation. Entropy: The current market chaos reading. "🔥 LOW" is an ideal, ordered state for trading. "😴 HIGH" is a warning of choppy, unpredictable conditions. 🔮 FIB & R2R ZONE (Large Dashboard) This section gives you the status of the Fibonacci Target Engine. It shows if an Active Channel (entry zone) or Stop Zone (invalidation zone) is active and displays the precise price levels for the static entry, target, and stop calculated at the time of the signal. 🛡️ FILTERS & PREDICTIVES (Large Dashboard) This panel provides a status check on all the bonus filters. It shows the current RSI Status, whether a Divergence is present, and if a Live Pending signal is forming. The Visual Interface: A Symphony of Data Every visual element is designed for instant, intuitive interpretation of market dynamics. Signal Markers: These are the primary outputs of the engine. ▼/▲ b: A fully confirmed signal that has passed all filters. ? b: A tentative signal generated in Predictive Mode, indicating developing dynamics. ◈ b: This diamond icon replaces the standard triangle when the signal is confirmed by a strong momentum divergence, highlighting it as a superior setup where dynamics are misaligned with price. Harmonic Wave: The flowing, colored wave around the price. What It Represents: The market's "flow dynamic" and volatility. How to Interpret It: Expanding waves show increasing volatility. The color is tied to the "Quantum Color" in your theme, representing the underlying energy field of the market. Entropy Particles: The small dots appearing above/below price. What They Represent: A direct visualization of the "order dynamic." How to Interpret Them: Their presence signifies a low-entropy, ordered state ideal for trading. Their color indicates the direction of momentum (PSR velocity). Their absence means the market is too chaotic (high entropy). The Fibonacci Target Engine: The dynamic R2R system appearing post-signal. Static Fib Levels: Colored horizontal lines representing the market's "structural dynamic." The Green "Active Channel" Box: Your zone of consideration. An area to manage a potential entry. Development Philosophy Reversal Point Dynamics was engineered to answer a fundamental question: can we objectively measure the forces behind a market turn? It is a synthesis of concepts from market microstructure, statistics, and information theory. The objective was never to create a "perfect" system, but to build a robust decision-support tool that provides a measurable, statistical edge by focusing on the principle of confluence. By demanding that multiple, independent market dynamics align simultaneously, RPD filters out the vast majority of market noise. It is designed for the trader who thinks in terms of probability and risk management, not in terms of certainties. It is a tool to help you discount the obvious and bet on the unexpected alignment of market forces. "Markets are constantly in a state of uncertainty and flux and money is made by discounting the obvious and betting on the unexpected." — George Soros Trade with insight. Trade with anticipation. — Dskyz, for DAFE Trading Systems
Indicatore Pine Script®
di DskyzInvestments
45
Tensor Market Analysis Engine (TMAE)# Tensor Market Analysis Engine (TMAE) ## Advanced Multi-Dimensional Mathematical Analysis System *Where Quantum Mathematics Meets Market Structure* --- ## 🎓 THEORETICAL FOUNDATION The Tensor Market Analysis Engine represents a revolutionary synthesis of three cutting-edge mathematical frameworks that have never before been combined for comprehensive market analysis. This indicator transcends traditional technical analysis by implementing advanced mathematical concepts from quantum mechanics, information theory, and fractal geometry. ### 🌊 Multi-Dimensional Volatility with Jump Detection **Hawkes Process Implementation:** The TMAE employs a sophisticated Hawkes process approximation for detecting self-exciting market jumps. Unlike traditional volatility measures that treat price movements as independent events, the Hawkes process recognizes that market shocks cluster and exhibit memory effects. **Mathematical Foundation:** ``` Intensity λ(t) = μ + Σ α(t - Tᵢ) ``` Where market jumps at times Tᵢ increase the probability of future jumps through the decay function α, controlled by the Hawkes Decay parameter (0.5-0.99). **Mahalanobis Distance Calculation:** The engine calculates volatility jumps using multi-dimensional Mahalanobis distance across up to 5 volatility dimensions: - **Dimension 1:** Price volatility (standard deviation of returns) - **Dimension 2:** Volume volatility (normalized volume fluctuations) - **Dimension 3:** Range volatility (high-low spread variations) - **Dimension 4:** Correlation volatility (price-volume relationship changes) - **Dimension 5:** Microstructure volatility (intrabar positioning analysis) This creates a volatility state vector that captures market behavior impossible to detect with traditional single-dimensional approaches. ### 📐 Hurst Exponent Regime Detection **Fractal Market Hypothesis Integration:** The TMAE implements advanced Rescaled Range (R/S) analysis to calculate the Hurst exponent in real-time, providing dynamic regime classification: - **H > 0.6:** Trending (persistent) markets - momentum strategies optimal - **H < 0.4:** Mean-reverting (anti-persistent) markets - contrarian strategies optimal - **H ≈ 0.5:** Random walk markets - breakout strategies preferred **Adaptive R/S Analysis:** Unlike static implementations, the TMAE uses adaptive windowing that adjusts to market conditions: ``` H = log(R/S) / log(n) ``` Where R is the range of cumulative deviations and S is the standard deviation over period n. **Dynamic Regime Classification:** The system employs hysteresis to prevent regime flipping, requiring sustained Hurst values before regime changes are confirmed. This prevents false signals during transitional periods. ### 🔄 Transfer Entropy Analysis **Information Flow Quantification:** Transfer entropy measures the directional flow of information between price and volume, revealing lead-lag relationships that indicate future price movements: ``` TE(X→Y) = Σ p(yₜ₊₁, yₜ, xₜ) log ``` **Causality Detection:** - **Volume → Price:** Indicates accumulation/distribution phases - **Price → Volume:** Suggests retail participation or momentum chasing - **Balanced Flow:** Market equilibrium or transition periods The system analyzes multiple lag periods (2-20 bars) to capture both immediate and structural information flows. --- ## 🔧 COMPREHENSIVE INPUT SYSTEM ### Core Parameters Group **Primary Analysis Window (10-100, Default: 50)** The fundamental lookback period affecting all calculations. Optimization by timeframe: - **1-5 minute charts:** 20-30 (rapid adaptation to micro-movements) - **15 minute-1 hour:** 30-50 (balanced responsiveness and stability) - **4 hour-daily:** 50-100 (smooth signals, reduced noise) - **Asset-specific:** Cryptocurrency 20-35, Stocks 35-50, Forex 40-60 **Signal Sensitivity (0.1-2.0, Default: 0.7)** Master control affecting all threshold calculations: - **Conservative (0.3-0.6):** High-quality signals only, fewer false positives - **Balanced (0.7-1.0):** Optimal risk-reward ratio for most trading styles - **Aggressive (1.1-2.0):** Maximum signal frequency, requires careful filtering **Signal Generation Mode:** - **Aggressive:** Any component signals (highest frequency) - **Confluence:** 2+ components agree (balanced approach) - **Conservative:** All 3 components align (highest quality) ### Volatility Jump Detection Group **Volatility Dimensions (2-5, Default: 3)** Determines the mathematical space complexity: - **2D:** Price + Volume volatility (suitable for clean markets) - **3D:** + Range volatility (optimal for most conditions) - **4D:** + Correlation volatility (advanced multi-asset analysis) - **5D:** + Microstructure volatility (maximum sensitivity) **Jump Detection Threshold (1.5-4.0σ, Default: 3.0σ)** Standard deviations required for volatility jump classification: - **Cryptocurrency:** 2.0-2.5σ (naturally volatile) - **Stock Indices:** 2.5-3.0σ (moderate volatility) - **Forex Major Pairs:** 3.0-3.5σ (typically stable) - **Commodities:** 2.0-3.0σ (varies by commodity) **Jump Clustering Decay (0.5-0.99, Default: 0.85)** Hawkes process memory parameter: - **0.5-0.7:** Fast decay (jumps treated as independent) - **0.8-0.9:** Moderate clustering (realistic market behavior) - **0.95-0.99:** Strong clustering (crisis/event-driven markets) ### Hurst Exponent Analysis Group **Calculation Method Options:** - **Classic R/S:** Original Rescaled Range (fast, simple) - **Adaptive R/S:** Dynamic windowing (recommended for trading) - **DFA:** Detrended Fluctuation Analysis (best for noisy data) **Trending Threshold (0.55-0.8, Default: 0.60)** Hurst value defining persistent market behavior: - **0.55-0.60:** Weak trend persistence - **0.65-0.70:** Clear trending behavior - **0.75-0.80:** Strong momentum regimes **Mean Reversion Threshold (0.2-0.45, Default: 0.40)** Hurst value defining anti-persistent behavior: - **0.35-0.45:** Weak mean reversion - **0.25-0.35:** Clear ranging behavior - **0.15-0.25:** Strong reversion tendency ### Transfer Entropy Parameters Group **Information Flow Analysis:** - **Price-Volume:** Classic flow analysis for accumulation/distribution - **Price-Volatility:** Risk flow analysis for sentiment shifts - **Multi-Timeframe:** Cross-timeframe causality detection **Maximum Lag (2-20, Default: 5)** Causality detection window: - **2-5 bars:** Immediate causality (scalping) - **5-10 bars:** Short-term flow (day trading) - **10-20 bars:** Structural flow (swing trading) **Significance Threshold (0.05-0.3, Default: 0.15)** Minimum entropy for signal generation: - **0.05-0.10:** Detect subtle information flows - **0.10-0.20:** Clear causality only - **0.20-0.30:** Very strong flows only --- ## 🎨 ADVANCED VISUAL SYSTEM ### Tensor Volatility Field Visualization **Five-Layer Resonance Bands:** The tensor field creates dynamic support/resistance zones that expand and contract based on mathematical field strength: - **Core Layer (Purple):** Primary tensor field with highest intensity - **Layer 2 (Neutral):** Secondary mathematical resonance - **Layer 3 (Info Blue):** Tertiary harmonic frequencies - **Layer 4 (Warning Gold):** Outer field boundaries - **Layer 5 (Success Green):** Maximum field extension **Field Strength Calculation:** ``` Field Strength = min(3.0, Mahalanobis Distance × Tensor Intensity) ``` The field amplitude adjusts to ATR and mathematical distance, creating dynamic zones that respond to market volatility. **Radiation Line Network:** During active tensor states, the system projects directional radiation lines showing field energy distribution: - **8 Directional Rays:** Complete angular coverage - **Tapering Segments:** Progressive transparency for natural visual flow - **Pulse Effects:** Enhanced visualization during volatility jumps ### Dimensional Portal System **Portal Mathematics:** Dimensional portals visualize regime transitions using category theory principles: - **Green Portals (◉):** Trending regime detection (appear below price for support) - **Red Portals (◎):** Mean-reverting regime (appear above price for resistance) - **Yellow Portals (○):** Random walk regime (neutral positioning) **Tensor Trail Effects:** Each portal generates 8 trailing particles showing mathematical momentum: - **Large Particles (●):** Strong mathematical signal - **Medium Particles (◦):** Moderate signal strength - **Small Particles (·):** Weak signal continuation - **Micro Particles (˙):** Signal dissipation ### Information Flow Streams **Particle Stream Visualization:** Transfer entropy creates flowing particle streams indicating information direction: - **Upward Streams:** Volume leading price (accumulation phases) - **Downward Streams:** Price leading volume (distribution phases) - **Stream Density:** Proportional to information flow strength **15-Particle Evolution:** Each stream contains 15 particles with progressive sizing and transparency, creating natural flow visualization that makes information transfer immediately apparent. ### Fractal Matrix Grid System **Multi-Timeframe Fractal Levels:** The system calculates and displays fractal highs/lows across five Fibonacci periods: - **8-Period:** Short-term fractal structure - **13-Period:** Intermediate-term patterns - **21-Period:** Primary swing levels - **34-Period:** Major structural levels - **55-Period:** Long-term fractal boundaries **Triple-Layer Visualization:** Each fractal level uses three-layer rendering: - **Shadow Layer:** Widest, darkest foundation (width 5) - **Glow Layer:** Medium white core line (width 3) - **Tensor Layer:** Dotted mathematical overlay (width 1) **Intelligent Labeling System:** Smart spacing prevents label overlap using ATR-based minimum distances. Labels include: - **Fractal Period:** Time-based identification - **Topological Class:** Mathematical complexity rating (0, I, II, III) - **Price Level:** Exact fractal price - **Mahalanobis Distance:** Current mathematical field strength - **Hurst Exponent:** Current regime classification - **Anomaly Indicators:** Visual strength representations (○ ◐ ● ⚡) ### Wick Pressure Analysis **Rejection Level Mathematics:** The system analyzes candle wick patterns to project future pressure zones: - **Upper Wick Analysis:** Identifies selling pressure and resistance zones - **Lower Wick Analysis:** Identifies buying pressure and support zones - **Pressure Projection:** Extends lines forward based on mathematical probability **Multi-Layer Glow Effects:** Wick pressure lines use progressive transparency (1-8 layers) creating natural glow effects that make pressure zones immediately visible without cluttering the chart. ### Enhanced Regime Background **Dynamic Intensity Mapping:** Background colors reflect mathematical regime strength: - **Deep Transparency (98% alpha):** Subtle regime indication - **Pulse Intensity:** Based on regime strength calculation - **Color Coding:** Green (trending), Red (mean-reverting), Neutral (random) **Smoothing Integration:** Regime changes incorporate 10-bar smoothing to prevent background flicker while maintaining responsiveness to genuine regime shifts. ### Color Scheme System **Six Professional Themes:** - **Dark (Default):** Professional trading environment optimization - **Light:** High ambient light conditions - **Classic:** Traditional technical analysis appearance - **Neon:** High-contrast visibility for active trading - **Neutral:** Minimal distraction focus - **Bright:** Maximum visibility for complex setups Each theme maintains mathematical accuracy while optimizing visual clarity for different trading environments and personal preferences. --- ## 📊 INSTITUTIONAL-GRADE DASHBOARD ### Tensor Field Status Section **Field Strength Display:** Real-time Mahalanobis distance calculation with dynamic emoji indicators: - **⚡ (Lightning):** Extreme field strength (>1.5× threshold) - **● (Solid Circle):** Strong field activity (>1.0× threshold) - **○ (Open Circle):** Normal field state **Signal Quality Rating:** Democratic algorithm assessment: - **ELITE:** All 3 components aligned (highest probability) - **STRONG:** 2 components aligned (good probability) - **GOOD:** 1 component active (moderate probability) - **WEAK:** No clear component signals **Threshold and Anomaly Monitoring:** - **Threshold Display:** Current mathematical threshold setting - **Anomaly Level (0-100%):** Combined volatility and volume spike measurement - **>70%:** High anomaly (red warning) - **30-70%:** Moderate anomaly (orange caution) - **<30%:** Normal conditions (green confirmation) ### Tensor State Analysis Section **Mathematical State Classification:** - **↑ BULL (Tensor State +1):** Trending regime with bullish bias - **↓ BEAR (Tensor State -1):** Mean-reverting regime with bearish bias - **◈ SUPER (Tensor State 0):** Random walk regime (neutral) **Visual State Gauge:** Five-circle progression showing tensor field polarity: - **🟢🟢🟢⚪⚪:** Strong bullish mathematical alignment - **⚪⚪🟡⚪⚪:** Neutral/transitional state - **⚪⚪🔴🔴🔴:** Strong bearish mathematical alignment **Trend Direction and Phase Analysis:** - **📈 BULL / 📉 BEAR / ➡️ NEUTRAL:** Primary trend classification - **🌪️ CHAOS:** Extreme information flow (>2.0 flow strength) - **⚡ ACTIVE:** Strong information flow (1.0-2.0 flow strength) - **😴 CALM:** Low information flow (<1.0 flow strength) ### Trading Signals Section **Real-Time Signal Status:** - **🟢 ACTIVE / ⚪ INACTIVE:** Long signal availability - **🔴 ACTIVE / ⚪ INACTIVE:** Short signal availability - **Components (X/3):** Active algorithmic components - **Mode Display:** Current signal generation mode **Signal Strength Visualization:** Color-coded component count: - **Green:** 3/3 components (maximum confidence) - **Aqua:** 2/3 components (good confidence) - **Orange:** 1/3 components (moderate confidence) - **Gray:** 0/3 components (no signals) ### Performance Metrics Section **Win Rate Monitoring:** Estimated win rates based on signal quality with emoji indicators: - **🔥 (Fire):** ≥60% estimated win rate - **👍 (Thumbs Up):** 45-59% estimated win rate - **⚠️ (Warning):** <45% estimated win rate **Mathematical Metrics:** - **Hurst Exponent:** Real-time fractal dimension (0.000-1.000) - **Information Flow:** Volume/price leading indicators - **📊 VOL:** Volume leading price (accumulation/distribution) - **💰 PRICE:** Price leading volume (momentum/speculation) - **➖ NONE:** Balanced information flow - **Volatility Classification:** - **🔥 HIGH:** Above 1.5× jump threshold - **📊 NORM:** Normal volatility range - **😴 LOW:** Below 0.5× jump threshold ### Market Structure Section (Large Dashboard) **Regime Classification:** - **📈 TREND:** Hurst >0.6, momentum strategies optimal - **🔄 REVERT:** Hurst <0.4, contrarian strategies optimal - **🎲 RANDOM:** Hurst ≈0.5, breakout strategies preferred **Mathematical Field Analysis:** - **Dimensions:** Current volatility space complexity (2D-5D) - **Hawkes λ (Lambda):** Self-exciting jump intensity (0.00-1.00) - **Jump Status:** 🚨 JUMP (active) / ✅ NORM (normal) ### Settings Summary Section (Large Dashboard) **Active Configuration Display:** - **Sensitivity:** Current master sensitivity setting - **Lookback:** Primary analysis window - **Theme:** Active color scheme - **Method:** Hurst calculation method (Classic R/S, Adaptive R/S, DFA) **Dashboard Sizing Options:** - **Small:** Essential metrics only (mobile/small screens) - **Normal:** Balanced information density (standard desktop) - **Large:** Maximum detail (multi-monitor setups) **Position Options:** - **Top Right:** Standard placement (avoids price action) - **Top Left:** Wide chart optimization - **Bottom Right:** Recent price focus (scalping) - **Bottom Left:** Maximum price visibility (swing trading) --- ## 🎯 SIGNAL GENERATION LOGIC ### Multi-Component Convergence System **Component Signal Architecture:** The TMAE generates signals through sophisticated component analysis rather than simple threshold crossing: **Volatility Component:** - **Jump Detection:** Mahalanobis distance threshold breach - **Hawkes Intensity:** Self-exciting process activation (>0.2) - **Multi-dimensional:** Considers all volatility dimensions simultaneously **Hurst Regime Component:** - **Trending Markets:** Price above SMA-20 with positive momentum - **Mean-Reverting Markets:** Price at Bollinger Band extremes - **Random Markets:** Bollinger squeeze breakouts with directional confirmation **Transfer Entropy Component:** - **Volume Leadership:** Information flow from volume to price - **Volume Spike:** Volume 110%+ above 20-period average - **Flow Significance:** Above entropy threshold with directional bias ### Democratic Signal Weighting **Signal Mode Implementation:** - **Aggressive Mode:** Any single component triggers signal - **Confluence Mode:** Minimum 2 components must agree - **Conservative Mode:** All 3 components must align **Momentum Confirmation:** All signals require momentum confirmation: - **Long Signals:** RSI >50 AND price >EMA-9 - **Short Signals:** RSI <50 AND price 0.6):** - **Increase Sensitivity:** Catch momentum continuation - **Lower Mean Reversion Threshold:** Avoid counter-trend signals - **Emphasize Volume Leadership:** Institutional accumulation/distribution - **Tensor Field Focus:** Use expansion for trend continuation - **Signal Mode:** Aggressive or Confluence for trend following **Range-Bound Markets (Hurst <0.4):** - **Decrease Sensitivity:** Avoid false breakouts - **Lower Trending Threshold:** Quick regime recognition - **Focus on Price Leadership:** Retail sentiment extremes - **Fractal Grid Emphasis:** Support/resistance trading - **Signal Mode:** Conservative for high-probability reversals **Volatile Markets (High Jump Frequency):** - **Increase Hawkes Decay:** Recognize event clustering - **Higher Jump Threshold:** Avoid noise signals - **Maximum Dimensions:** Capture full volatility complexity - **Reduce Position Sizing:** Risk management adaptation - **Enhanced Visuals:** Maximum information for rapid decisions **Low Volatility Markets (Low Jump Frequency):** - **Decrease Jump Threshold:** Capture subtle movements - **Lower Hawkes Decay:** Treat moves as independent - **Reduce Dimensions:** Simplify analysis - **Increase Position Sizing:** Capitalize on compressed volatility - **Minimal Visuals:** Reduce distraction in quiet markets --- ## 🚀 ADVANCED TRADING STRATEGIES ### The Mathematical Convergence Method **Entry Protocol:** 1. **Fractal Grid Approach:** Monitor price approaching significant fractal levels 2. **Tensor Field Confirmation:** Verify field expansion supporting direction 3. **Portal Signal:** Wait for dimensional portal appearance 4. **ELITE/STRONG Quality:** Only trade highest quality mathematical signals 5. **Component Consensus:** Confirm 2+ components agree in Confluence mode **Example Implementation:** - Price approaching 21-period fractal high - Tensor field expanding upward (bullish mathematical alignment) - Green portal appears below price (trending regime confirmation) - ELITE quality signal with 3/3 components active - Enter long position with stop below fractal level **Risk Management:** - **Stop Placement:** Below/above fractal level that generated signal - **Position Sizing:** Based on Mahalanobis distance (higher distance = smaller size) - **Profit Targets:** Next fractal level or tensor field resistance ### The Regime Transition Strategy **Regime Change Detection:** 1. **Monitor Hurst Exponent:** Watch for persistent moves above/below thresholds 2. **Portal Color Change:** Regime transitions show different portal colors 3. **Background Intensity:** Increasing regime background intensity 4. **Mathematical Confirmation:** Wait for regime confirmation (hysteresis) **Trading Implementation:** - **Trending Transitions:** Trade momentum breakouts, follow trend - **Mean Reversion Transitions:** Trade range boundaries, fade extremes - **Random Transitions:** Trade breakouts with tight stops **Advanced Techniques:** - **Multi-Timeframe:** Confirm regime on higher timeframe - **Early Entry:** Enter on regime transition rather than confirmation - **Regime Strength:** Larger positions during strong regime signals ### The Information Flow Momentum Strategy **Flow Detection Protocol:** 1. **Monitor Transfer Entropy:** Watch for significant information flow shifts 2. **Volume Leadership:** Strong edge when volume leads price 3. **Flow Acceleration:** Increasing flow strength indicates momentum 4. **Directional Confirmation:** Ensure flow aligns with intended trade direction **Entry Signals:** - **Volume → Price Flow:** Enter during accumulation/distribution phases - **Price → Volume Flow:** Enter on momentum confirmation breaks - **Flow Reversal:** Counter-trend entries when flow reverses **Optimization:** - **Scalping:** Use immediate flow detection (2-5 bar lag) - **Swing Trading:** Use structural flow (10-20 bar lag) - **Multi-Asset:** Compare flow between correlated assets ### The Tensor Field Expansion Strategy **Field Mathematics:** The tensor field expansion indicates mathematical pressure building in market structure: **Expansion Phases:** 1. **Compression:** Field contracts, volatility decreases 2. **Tension Building:** Mathematical pressure accumulates 3. **Expansion:** Field expands rapidly with directional movement 4. **Resolution:** Field stabilizes at new equilibrium **Trading Applications:** - **Compression Trading:** Prepare for breakout during field contraction - **Expansion Following:** Trade direction of field expansion - **Reversion Trading:** Fade extreme field expansion - **Multi-Dimensional:** Consider all field layers for confirmation ### The Hawkes Process Event Strategy **Self-Exciting Jump Trading:** Understanding that market shocks cluster and create follow-on opportunities: **Jump Sequence Analysis:** 1. **Initial Jump:** First volatility jump detected 2. **Clustering Phase:** Hawkes intensity remains elevated 3. **Follow-On Opportunities:** Additional jumps more likely 4. **Decay Period:** Intensity gradually decreases **Implementation:** - **Jump Confirmation:** Wait for mathematical jump confirmation - **Direction Assessment:** Use other components for direction - **Clustering Trades:** Trade subsequent moves during high intensity - **Decay Exit:** Exit positions as Hawkes intensity decays ### The Fractal Confluence System **Multi-Timeframe Fractal Analysis:** Combining fractal levels across different periods for high-probability zones: **Confluence Zones:** - **Double Confluence:** 2 fractal levels align - **Triple Confluence:** 3+ fractal levels cluster - **Mathematical Confirmation:** Tensor field supports the level - **Information Flow:** Transfer entropy confirms direction **Trading Protocol:** 1. **Identify Confluence:** Find 2+ fractal levels within 1 ATR 2. **Mathematical Support:** Verify tensor field alignment 3. **Signal Quality:** Wait for STRONG or ELITE signal 4. **Risk Definition:** Use fractal level for stop placement 5. **Profit Targeting:** Next major fractal confluence zone --- ## ⚠️ COMPREHENSIVE RISK MANAGEMENT ### Mathematical Position Sizing **Mahalanobis Distance Integration:** Position size should inversely correlate with mathematical field strength: ``` Position Size = Base Size × (Threshold / Mahalanobis Distance) ``` **Risk Scaling Matrix:** - **Low Field Strength (<2.0):** Standard position sizing - **Moderate Field Strength (2.0-3.0):** 75% position sizing - **High Field Strength (3.0-4.0):** 50% position sizing - **Extreme Field Strength (>4.0):** 25% position sizing or no trade ### Signal Quality Risk Adjustment **Quality-Based Position Sizing:** - **ELITE Signals:** 100% of planned position size - **STRONG Signals:** 75% of planned position size - **GOOD Signals:** 50% of planned position size - **WEAK Signals:** No position or paper trading only **Component Agreement Scaling:** - **3/3 Components:** Full position size - **2/3 Components:** 75% position size - **1/3 Components:** 50% position size or skip trade ### Regime-Adaptive Risk Management **Trending Market Risk:** - **Wider Stops:** Allow for trend continuation - **Trend Following:** Trade with regime direction - **Higher Position Size:** Trend probability advantage - **Momentum Stops:** Trail stops based on momentum indicators **Mean-Reverting Market Risk:** - **Tighter Stops:** Quick exits on trend continuation - **Contrarian Positioning:** Trade against extremes - **Smaller Position Size:** Higher reversal failure rate - **Level-Based Stops:** Use fractal levels for stops **Random Market Risk:** - **Breakout Focus:** Trade only clear breakouts - **Tight Initial Stops:** Quick exit if breakout fails - **Reduced Frequency:** Skip marginal setups - **Range-Based Targets:** Profit targets at range boundaries ### Volatility-Adaptive Risk Controls **High Volatility Periods:** - **Reduced Position Size:** Account for wider price swings - **Wider Stops:** Avoid noise-based exits - **Lower Frequency:** Skip marginal setups - **Faster Exits:** Take profits more quickly **Low Volatility Periods:** - **Standard Position Size:** Normal risk parameters - **Tighter Stops:** Take advantage of compressed ranges - **Higher Frequency:** Trade more setups - **Extended Targets:** Allow for compressed volatility expansion ### Multi-Timeframe Risk Alignment **Higher Timeframe Trend:** - **With Trend:** Standard or increased position size - **Against Trend:** Reduced position size or skip - **Neutral Trend:** Standard position size with tight management **Risk Hierarchy:** 1. **Primary:** Current timeframe signal quality 2. **Secondary:** Higher timeframe trend alignment 3. **Tertiary:** Mathematical field strength 4. **Quaternary:** Market regime classification --- ## 📚 EDUCATIONAL VALUE AND MATHEMATICAL CONCEPTS ### Advanced Mathematical Concepts **Tensor Analysis in Markets:** The TMAE introduces traders to tensor analysis, a branch of mathematics typically reserved for physics and advanced engineering. Tensors provide a framework for understanding multi-dimensional market relationships that scalar and vector analysis cannot capture. **Information Theory Applications:** Transfer entropy implementation teaches traders about information flow in markets, a concept from information theory that quantifies directional causality between variables. This provides intuition about market microstructure and participant behavior. **Fractal Geometry in Trading:** The Hurst exponent calculation exposes traders to fractal geometry concepts, helping understand that markets exhibit self-similar patterns across multiple timeframes. This mathematical insight transforms how traders view market structure. **Stochastic Process Theory:** The Hawkes process implementation introduces concepts from stochastic process theory, specifically self-exciting point processes. This provides mathematical framework for understanding why market events cluster and exhibit memory effects. ### Learning Progressive Complexity **Beginner Mathematical Concepts:** - **Volatility Dimensions:** Understanding multi-dimensional analysis - **Regime Classification:** Learning market personality types - **Signal Democracy:** Algorithmic consensus building - **Visual Mathematics:** Interpreting mathematical concepts visually **Intermediate Mathematical Applications:** - **Mahalanobis Distance:** Statistical distance in multi-dimensional space - **Rescaled Range Analysis:** Fractal dimension measurement - **Information Entropy:** Quantifying uncertainty and causality - **Field Theory:** Understanding mathematical fields in market context **Advanced Mathematical Integration:** - **Tensor Field Dynamics:** Multi-dimensional market force analysis - **Stochastic Self-Excitation:** Event clustering and memory effects - **Categorical Composition:** Mathematical signal combination theory - **Topological Market Analysis:** Understanding market shape and connectivity ### Practical Mathematical Intuition **Developing Market Mathematics Intuition:** The TMAE serves as a bridge between abstract mathematical concepts and practical trading applications. Traders develop intuitive understanding of: - **How markets exhibit mathematical structure beneath apparent randomness** - **Why multi-dimensional analysis reveals patterns invisible to single-variable approaches** - **How information flows through markets in measurable, predictable ways** - **Why mathematical models provide probabilistic edges rather than certainties** --- ## 🔬 IMPLEMENTATION AND OPTIMIZATION ### Getting Started Protocol **Phase 1: Observation (Week 1)** 1. **Apply with defaults:** Use standard settings on your primary trading timeframe 2. **Study visual elements:** Learn to interpret tensor fields, portals, and streams 3. **Monitor dashboard:** Observe how metrics change with market conditions 4. **No trading:** Focus entirely on pattern recognition and understanding **Phase 2: Pattern Recognition (Week 2-3)** 1. **Identify signal patterns:** Note what market conditions produce different signal qualities 2. **Regime correlation:** Observe how Hurst regimes affect signal performance 3. **Visual confirmation:** Learn to read tensor field expansion and portal signals 4. **Component analysis:** Understand which components drive signals in different markets **Phase 3: Parameter Optimization (Week 4-5)** 1. **Asset-specific tuning:** Adjust parameters for your specific trading instrument 2. **Timeframe optimization:** Fine-tune for your preferred trading timeframe 3. **Sensitivity adjustment:** Balance signal frequency with quality 4. **Visual customization:** Optimize colors and intensity for your trading environment **Phase 4: Live Implementation (Week 6+)** 1. **Paper trading:** Test signals with hypothetical trades 2. **Small position sizing:** Begin with minimal risk during learning phase 3. **Performance tracking:** Monitor actual vs. expected signal performance 4. **Continuous optimization:** Refine settings based on real performance data ### Performance Monitoring System **Signal Quality Tracking:** - **ELITE Signal Win Rate:** Track highest quality signals separately - **Component Performance:** Monitor which components provide best signals - **Regime Performance:** Analyze performance across different market regimes - **Timeframe Analysis:** Compare performance across different session times **Mathematical Metric Correlation:** - **Field Strength vs. Performance:** Higher field strength should correlate with better performance - **Component Agreement vs. Win Rate:** More component agreement should improve win rates - **Regime Alignment vs. Success:** Trading with mathematical regime should outperform ### Continuous Optimization Process **Monthly Review Protocol:** 1. **Performance Analysis:** Review win rates, profit factors, and maximum drawdown 2. **Parameter Assessment:** Evaluate if current settings remain optimal 3. **Market Adaptation:** Adjust for changes in market character or volatility 4. **Component Weighting:** Consider if certain components should receive more/less emphasis **Quarterly Deep Analysis:** 1. **Mathematical Model Validation:** Verify that mathematical relationships remain valid 2. **Regime Distribution:** Analyze time spent in different market regimes 3. **Signal Evolution:** Track how signal characteristics change over time 4. **Correlation Analysis:** Monitor correlations between different mathematical components --- ## 🌟 UNIQUE INNOVATIONS AND CONTRIBUTIONS ### Revolutionary Mathematical Integration **First-Ever Implementations:** 1. **Multi-Dimensional Volatility Tensor:** First indicator to implement true tensor analysis for market volatility 2. **Real-Time Hawkes Process:** First trading implementation of self-exciting point processes 3. **Transfer Entropy Trading Signals:** First practical application of information theory for trade generation 4. **Democratic Component Voting:** First algorithmic consensus system for signal generation 5. **Fractal-Projected Signal Quality:** First system to predict signal quality at future price levels ### Advanced Visualization Innovations **Mathematical Visualization Breakthroughs:** - **Tensor Field Radiation:** Visual representation of mathematical field energy - **Dimensional Portal System:** Category theory visualization for regime transitions - **Information Flow Streams:** Real-time visual display of market information transfer - **Multi-Layer Fractal Grid:** Intelligent spacing and projection system - **Regime Intensity Mapping:** Dynamic background showing mathematical regime strength ### Practical Trading Innovations **Trading System Advances:** - **Quality-Weighted Signal Generation:** Signals rated by mathematical confidence - **Regime-Adaptive Strategy Selection:** Automatic strategy optimization based on market personality - **Anti-Spam Signal Protection:** Mathematical prevention of signal clustering - **Component Performance Tracking:** Real-time monitoring of algorithmic component success - **Field-Strength Position Sizing:** Mathematical volatility integration for risk management --- ## ⚖️ RESPONSIBLE USAGE AND LIMITATIONS ### Mathematical Model Limitations **Understanding Model Boundaries:** While the TMAE implements sophisticated mathematical concepts, traders must understand fundamental limitations: - **Markets Are Not Purely Mathematical:** Human psychology, news events, and fundamental factors create unpredictable elements - **Past Performance Limitations:** Mathematical relationships that worked historically may not persist indefinitely - **Model Risk:** Complex models can fail during unprecedented market conditions - **Overfitting Potential:** Highly optimized parameters may not generalize to future market conditions ### Proper Implementation Guidelines **Risk Management Requirements:** - **Never Risk More Than 2% Per Trade:** Regardless of signal quality - **Diversification Mandatory:** Don't rely solely on mathematical signals - **Position Sizing Discipline:** Use mathematical field strength for sizing, not confidence - **Stop Loss Non-Negotiable:** Every trade must have predefined risk parameters **Realistic Expectations:** - **Mathematical Edge, Not Certainty:** The indicator provides probabilistic advantages, not guaranteed outcomes - **Learning Curve Required:** Complex mathematical concepts require time to master - **Market Adaptation Necessary:** Parameters must evolve with changing market conditions - **Continuous Education Important:** Understanding underlying mathematics improves application ### Ethical Trading Considerations **Market Impact Awareness:** - **Information Asymmetry:** Advanced mathematical analysis may provide advantages over other market participants - **Position Size Responsibility:** Large positions based on mathematical signals can impact market structure - **Sharing Knowledge:** Consider educational contributions to trading community - **Fair Market Participation:** Use mathematical advantages responsibly within market framework ### Professional Development Path **Skill Development Sequence:** 1. **Basic Mathematical Literacy:** Understand fundamental concepts before advanced application 2. **Risk Management Mastery:** Develop disciplined risk control before relying on complex signals 3. **Market Psychology Understanding:** Combine mathematical analysis with behavioral market insights 4. **Continuous Learning:** Stay updated on mathematical finance developments and market evolution --- ## 🔮 CONCLUSION The Tensor Market Analysis Engine represents a quantum leap forward in technical analysis, successfully bridging the gap between advanced pure mathematics and practical trading applications. By integrating multi-dimensional volatility analysis, fractal market theory, and information flow dynamics, the TMAE reveals market structure invisible to conventional analysis while maintaining visual clarity and practical usability. ### Mathematical Innovation Legacy This indicator establishes new paradigms in technical analysis: - **Tensor analysis for market volatility understanding** - **Stochastic self-excitation for event clustering prediction** - **Information theory for causality-based trade generation** - **Democratic algorithmic consensus for signal quality enhancement** - **Mathematical field visualization for intuitive market understanding** ### Practical Trading Revolution Beyond mathematical innovation, the TMAE transforms practical trading: - **Quality-rated signals replace binary buy/sell decisions** - **Regime-adaptive strategies automatically optimize for market personality** - **Multi-dimensional risk management integrates mathematical volatility measures** - **Visual mathematical concepts make complex analysis immediately interpretable** - **Educational value creates lasting improvement in trading understanding** ### Future-Proof Design The mathematical foundations ensure lasting relevance: - **Universal mathematical principles transcend market evolution** - **Multi-dimensional analysis adapts to new market structures** - **Regime detection automatically adjusts to changing market personalities** - **Component democracy allows for future algorithmic additions** - **Mathematical visualization scales with increasing market complexity** ### Commitment to Excellence The TMAE represents more than an indicator—it embodies a philosophy of bringing rigorous mathematical analysis to trading while maintaining practical utility and visual elegance. Every component, from the multi-dimensional tensor fields to the democratic signal generation, reflects a commitment to mathematical accuracy, trading practicality, and educational value. ### Trading with Mathematical Precision In an era where markets grow increasingly complex and computational, the TMAE provides traders with mathematical tools previously available only to institutional quantitative research teams. Yet unlike academic mathematical models, the TMAE translates complex concepts into intuitive visual representations and practical trading signals. By combining the mathematical rigor of tensor analysis, the statistical power of multi-dimensional volatility modeling, and the information-theoretic insights of transfer entropy, traders gain unprecedented insight into market structure and dynamics. ### Final Perspective Markets, like nature, exhibit profound mathematical beauty beneath apparent chaos. The Tensor Market Analysis Engine serves as a mathematical lens that reveals this hidden order, transforming how traders perceive and interact with market structure. Through mathematical precision, visual elegance, and practical utility, the TMAE empowers traders to see beyond the noise and trade with the confidence that comes from understanding the mathematical principles governing market behavior. Trade with mathematical insight. Trade with the power of tensors. Trade with the TMAE. *"In mathematics, you don't understand things. You just get used to them." - John von Neumann* *With the TMAE, mathematical market understanding becomes not just possible, but intuitive.* — Dskyz, Trade with insight. Trade with anticipation.
Indicatore Pine Script®
di DskyzInvestments
16
Sessions [Plug&Play]This indicator automatically highlights the three major FX trading sessions—Asia, London, and New York—on your chart and, at the close of each session, draws right-extended horizontal rays at that session’s high and low. It’s designed to help you visually identify when price is trading within each session’s range and to quickly see where the highest and lowest prices occurred before the next major session begins. Key Features: Session Boxes Draws a semi-transparent box around each session’s timeframe (Asia, London, New York) based on your local UTC offset. Each box dynamically expands in real time: as new candles form during the session, the box’s top and bottom edges update to match the highest high and lowest low seen so far in that session. When the session ends, the box remains on your chart, anchored to the exact candles that formed its boundaries. High/Low Rays As soon as a session closes (e.g., London session ends at 17:00 UTC+0 by default), two horizontal rays are drawn at that session’s final high and low. These rays are “pinned” to the exact candles where the high/low occurred, so they stay in place when you scroll or zoom. Each ray extends indefinitely to the right, providing a clear reference of the key supply/demand levels created during that session. Session Labels Optionally places a small “London,” “New York,” or “Asia” label at the top edge of each completed session’s box. Labels are horizontally centered within the session’s box and use a contrasting, easy-to-read font color. Customizable Appearance Show/Hide Each Session: Toggle display of London, New York, and Asia sessions separately. Time Ranges: By default, London is 08:00–17:00 (UTC), New York is 13:00–22:00 (UTC), and Asia is 00:00–07:00 (UTC). You can override each session’s start/end times using the “Time Range” picker. Color & Opacity: Assign custom colors to each session. Choose a global “Dark,” “Medium,” or “Light” opacity preset to adjust box fill transparency and border shading. Show/Hide Labels & Outlines: Turn the text labels and the box borders on or off independently. UTC Offset Support If your local broker feed or price data is not in UTC, simply adjust the “UTC Offset (+/–)” input. The indicator will recalculate session start/end times relative to your chosen offset. How to Use: Add the Indicator: Open TradingView’s Pine Editor, paste in this script, and click “Add to Chart.” By default, you’ll see three translucent boxes appear once each session begins (Asia, London, New York). Watch in Real Time: As soon as a session starts, its box will appear anchored to the first candle. The top and bottom of the box expand if new extremes occur. When the session closes, the final box remains visible and two horizontal rays mark that session’s high and low. Analyze Key Levels: Use the high- and low-level rays to gauge session liquidity zones—areas where stop orders, breakouts, or reversals often occur. For example, if London’s high is significantly above current price, it may act as resistance in the New York session. Customize to Your Needs: Toggle specific sessions on/off (e.g., if you only care about London and New York). Change each session’s color to match your chart theme. Adjust the “UTC Offset” so sessions align with your local time. Disable labels or box borders if you prefer a cleaner look. Inputs Overview: Show London/New York/Asia Session (bool): Show or hide each session’s box and its high/low rays. Time Range (session): Defines the start/end of each session in “HHMM–HHMM” (24h) format. Colour (color): Custom color for each session’s box fill, border, and high/low rays. Show Session Labels (bool): Toggle the “London,” “New York,” “Asia” text that appears at the top of each completed box. Show Range Outline (bool): Toggle the box border (if off, only a translucent fill is drawn). Opacity Preset (Dark/Medium/Light): Controls transparency of box fill and border. UTC Offset (+/–) (int): Adjusts session times for different time zones (e.g., +1 for UTC+1). Why It’s Useful: Quickly Identify Session Activity: Visually distinguish when each major trading session is active, then compare price action across sessions. Pinpoint High/Low Liquidity Levels: Drawn rays highlight where the market hit its extremes—critical zones for stop orders or breakout entries. Multi-Timeframe Context: By seeing historical session boxes and rays, you can locate recurring supply/demand areas, overlap zones, or session re-tests. Fully Automated Workflow: Once added to your chart, the script does all the work of tracking session boundaries and drawing high/low lines—no manual box or line drawing necessary. Example Use Cases: London Breakout Traders: See where London’s high/low formed, then wait for price to revisit those levels during the New York session. Range Breakout Strategies: If price consolidates inside the London box, use the boxed extremes as immediate targets for breakout entries. Intraday Liquidity Swings: During quieter hours, watch Asia’s high/low to identify potential support/resistance before London’s opening. Overlap Zones: Compare London’s range with Asia’s range to find areas of confluence—high-probability reversal or continuation zones.
Indicatore Pine Script®
di TBWS_Algo
Previous Highs & Lows (Customizable)Previous Highs & Lows (Customizable) This Pine Script indicator displays horizontal lines and labels for high, low, and midpoint levels across multiple timeframes. The indicator plots levels from the following periods: Today's session high, low, and midpoint Yesterday's high, low, and midpoint Current week's high, low, and midpoint Last week's high, low, and midpoint Last month's high, low, and midpoint Last quarter's high, low, and midpoint Last year's high, low, and midpoint Features Individual Controls: Each timeframe has separate toggles for showing/hiding high/low levels and midpoint levels. Custom Colors: Independent color selection for lines and labels for each timeframe group. Display Options: Adjustable line width (1-5 pixels) Variable label text size (tiny, small, normal, large, huge) Configurable label offset positioning Organization: Settings are grouped by timeframe in a logical sequence from most recent (today) to least recent (last year). Display Logic: Lines span the current trading day only. Labels are positioned to the right of the price action. The indicator automatically removes previous drawings to prevent chart clutter.
Indicatore Pine Script®
di J-V-Y-E
Swing Highs and Lows Detector🔍 Swing Highs and Lows Detector The Swing Highs and Lows Detector is a powerful tool for traders looking to identify meaningful structural shifts in price action, based on swing point logic and internal trend shifts. 📈 What It Does This indicator automatically identifies and labels: HH (Higher High) – Price broke above the previous swing high LH (Lower High) – Price failed to break the previous high, signaling potential weakness LL (Lower Low) – Price broke below the previous swing low HL (Higher Low) – Price maintained a higher support level, indicating strength The script distinguishes between bullish and bearish internal shifts and tracks the highest/lowest points between those shifts to determine the swing structure. ⚙️ How It Works You can choose between two shift detection modes: "Open": Compares closing price to the first open of the opposite streak "High/Low": Uses the high of bearish or low of bullish candles Once a shift is confirmed, the indicator scans the bars between shifts to find the most significant swing high or low When a valid swing is detected, it’s labeled directly on the chart with color-coded markers 🛎️ Built-in Alerts Set alerts for: Higher High Lower High Lower Low Higher Low These alerts help you catch key structural shifts in real time — great for breakout traders, structure-based analysts, and smart money concepts (SMC) strategies. ✅ How to Use Confirm Trend Strength or Reversals – Use HH/HL to confirm an uptrend, LL/LH to confirm a downtrend Combine with Liquidity Sweeps or Zones – Ideal for SMC or Wyckoff-style setups Entry/Exit Triggers – Use swing breaks to time entries or exits near key structural points
Indicatore Pine Script®
di The_Forex_Steward
5
IU Bigger than range strategyDESCRIPTION IU Bigger Than Range Strategy is designed to capture breakout opportunities by identifying candles that are significantly larger than the previous range. It dynamically calculates the high and low of the last N candles and enters trades when the current candle's range exceeds the previous range. The strategy includes multiple stop-loss methods (Previous High/Low, ATR, Swing High/Low) and automatically manages take-profit and stop-loss levels based on user-defined risk-to-reward ratios. This versatile strategy is optimized for higher timeframes and assets like BTC but can be fine-tuned for different instruments and intervals. USER INPUTS: Look back Length: Number of candles to calculate the high-low range. Default is 22. Risk to Reward: Sets the target reward relative to the stop-loss distance. Default is 3. Stop Loss Method: Choose between:(Default is "Previous High/Low") - Previous High/Low - ATR (Average True Range) - Swing High/Low ATR Length: Defines the length for ATR calculation (only applicable when ATR is selected as the stop-loss method) (Default is 14). ATR Factor: Multiplier applied to the ATR to determine stop-loss distance(Default is 2). Swing High/Low Length: Specifies the length for identifying swing points (only applicable when Swing High/Low is selected as the stop-loss method).(Default is 2) LONG CONDITION: The current candle’s range (absolute difference between open and close) is greater than the previous range. The closing price is higher than the opening price (bullish candle). SHORT CONDITIONS: The current candle’s range exceeds the previous range. The closing price is lower than the opening price (bearish candle). LONG EXIT: Stop-loss: - Previous Low - ATR-based trailing stop - Recent Swing Low Take-profit: - Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance). SHORT EXIT: Stop-loss: - Previous High - ATR-based trailing stop - Recent Swing High Take-profit: - Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance). ALERTS: Long Entry Triggered Short Entry Triggered WHY IT IS UNIQUE: This strategy dynamically adapts to different market conditions by identifying candles that exceed the previous range, ensuring that it only enters trades during strong breakout scenarios. Multiple stop-loss methods provide flexibility for different trading styles and risk profiles. The visual representation of stop-loss and take-profit levels with color-coded plots improves trade monitoring and decision-making. HOW USERS CAN BENEFIT FROM IT: Ideal for breakout traders looking to capitalize on momentum-driven price moves. Provides flexibility to customize stop-loss methods and fine-tune risk management parameters. Helps minimize drawdowns with a strong risk-to-reward framework while maximizing profit potential.
Strategia Pine Script®
di Shivam_Mandrai
HTF Hi-Lo Zones [CHE]HTF Hi-Lo Zones Indicator The HTF Hi-Lo Zones Indicator is a Pine Script tool designed to highlight important high and low values from a selected higher timeframe. It provides traders with clear visual zones where price activity has reached significant points, helping in decision-making by identifying potential support and resistance levels. This indicator is customizable, allowing users to select the resolution type, control the visualization of session ranges, and even display detailed information about the chosen timeframe. Key Functionalities 1. Timeframe Resolution Selection: - The indicator offers three modes to determine the resolution: - Automatic: Dynamically calculates the higher timeframe based on the current chart's resolution. - Multiplier: Allows users to apply a multiplier to the current chart's timeframe. - Manual: Enables manual input for custom resolution settings. - Each resolution type ensures flexibility to suit different trading styles and strategies. 2. Data Fetching for High and Low Values: - The indicator retrieves the current high and low values for the selected higher timeframe using `request.security`. - It also calculates the lowest and highest values over a configurable lookback period, providing insights into significant price movements within the chosen timeframe. 3. Session High and Low Detection: - The indicator detects whether the current value represents a new session high or low by comparing the highest and lowest values with the current data. - This is crucial for identifying breakouts or significant turning points during a session. 4. Visual Representation: - When a new session high or low is detected: - Range Zones: A colored box marks the session's high-to-low range. - Labels: Optional labels indicate "New High" or "New Low" for clarity. - Users can customize colors, transparency, and whether range outlines or labels should be displayed. 5. Information Box: - An optional dashboard displays details about the chosen timeframe resolution and current session activity. - The box's size, position, and colors are fully customizable. 6. Session Tracking: - Tracks session boundaries, updating the visualization dynamically as the session progresses. - Displays session-specific maximum and minimum values if enabled. 7. Additional Features: - Configurable dividers for session or daily boundaries. - Transparency and styling options for the displayed zones. - A dashboard for advanced visualization and information overlay. Key Code Sections Explained 1. Resolution Determination: - Depending on the user's input (Auto, Multiplier, or Manual), the script determines the appropriate timeframe resolution for higher timeframe analysis. - The resolution adapts dynamically based on intraday, daily, or higher-period charts. 2. Fetching Security Data: - Using the `getSecurityDataFunction`, the script fetches high and low values for the chosen timeframe, including historical and real-time data management to avoid repainting issues. 3. Session High/Low Logic: - By comparing the highest and lowest values over a lookback period, the script identifies whether the current value is a new session high or low, updating session boundaries and initiating visual indicators. 4. Visualization: - The script creates visual representations using `box.new` for range zones and `label.new` for session labels. - These elements update dynamically to reflect the most recent data. 5. Customization Options: - Users can configure the appearance, behavior, and displayed data through multiple input options, ensuring adaptability to individual trading preferences. This indicator is a robust tool for tracking higher timeframe activity, offering a blend of automation, customization, and visual clarity to enhance trading strategies. Disclaimer The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context. Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved. By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk. Best regards and happy trading Chervolino
Indicatore Pine Script®
di chervolino
CandleCandle: A Comprehensive Pine Script™ Library for Candlestick Analysis Overview The Candle library, developed in Pine Script™, provides traders and developers with a robust toolkit for analyzing candlestick data. By offering easy access to fundamental candlestick components like open, high, low, and close prices, along with advanced derived metrics such as body-to-wick ratios, percentage calculations, and volatility analysis, this library enables detailed insights into market behavior. This library is ideal for creating custom indicators, trading strategies, and backtesting frameworks, making it a powerful resource for any Pine Script™ developer. Key Features 1. Core Candlestick Data • Open : Access the opening price of the current candle. • High : Retrieve the highest price. • Low : Retrieve the lowest price. • Close : Access the closing price. 2. Candle Metrics • Full Size : Calculates the total range of the candle (high - low). • Body Size : Computes the size of the candle’s body (open - close). • Wick Size : Provides the combined size of the upper and lower wicks. 3. Wick and Body Ratios • Upper Wick Size and Lower Wick Size . • Body-to-Wick Ratio and Wick-to-Body Ratio . 4. Percentage Calculations • Upper Wick Percentage : The proportion of the upper wick size relative to the full candle size. • Lower Wick Percentage : The proportion of the lower wick size relative to the full candle size. • Body Percentage and Wick Percentage relative to the candle’s range. 5. Candle Direction Analysis • Determines if a candle is "Bullish" or "Bearish" based on its closing and opening prices. 6. Price Metrics • Average Price : The mean of the open, high, low, and close prices. • Midpoint Price : The midpoint between the high and low prices. 7. Volatility Measurement • Calculates the standard deviation of the OHLC prices, providing a volatility metric for the current candle. Code Architecture Example Functionality The library employs a modular structure, exporting various functions that can be used independently or in combination. For instance: // This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org // © DevArjun //@version=6 indicator("Candle Data", overlay = true) import DevArjun/Candle/1 as Candle // Body Size % bodySize = Candle.BodySize() // Determining the candle direction candleDirection = Candle.CandleDirection() // Calculating the volatility of the current candle volatility = Candle.Volatility() // Plotting the metrics (for demonstration) plot(bodySize, title="Body Size", color=color.blue) label.new(bar_index, high, candleDirection, style=label.style_circle) Scalability The modularity of the Candle library allows seamless integration into more extensive trading systems. Functions can be mixed and matched to suit specific analytical or strategic needs. Use Cases Trading Strategies Developers can use the library to create strategies based on candle properties such as: • Identifying long-bodied candles (momentum signals). • Detecting wicks as potential reversal zones. • Filtering trades based on candle ratios. Visualization Plotting components like body size, wick size, and directional labels helps visualize market behavior and identify patterns. Backtesting By incorporating volatility and ratio metrics, traders can design and test strategies on historical data, ensuring robust performance before live trading. Education This library is a great tool for teaching candlestick analysis and how each component contributes to market behavior. Portfolio Highlights Project Objective To create a Pine Script™ library that simplifies candlestick analysis by providing comprehensive metrics and insights, empowering traders and developers with advanced tools for market analysis. Development Challenges and Solutions • Challenge : Achieving high precision in calculating ratios and percentages. • Solution : Implemented robust mathematical operations and safeguarded against division-by-zero errors. • Challenge : Ensuring modularity and scalability. • Solution : Designed functions as independent modules, allowing flexible integration. Impact • Efficiency : The library reduces the time required to calculate complex candlestick metrics. • Versatility : Supports various trading styles, from scalping to swing trading. • Clarity : Clean code and detailed documentation ensure usability for developers of all levels. Conclusion The Candle library exemplifies the power of Pine Script™ in simplifying and enhancing candlestick analysis. By including this project in your portfolio, you showcase your expertise in: • Financial data analysis. • Pine Script™ development. • Creating tools that solve real-world trading challenges. This project demonstrates both technical proficiency and a keen understanding of market analysis, making it an excellent addition to your professional portfolio. Library "Candle" A comprehensive library to access and analyze the basic components of a candlestick, including open, high, low, close prices, and various derived metrics such as full size, body size, wick sizes, ratios, percentages, and additional analysis metrics. Open()   Open @description Returns the opening price of the current candle.   Returns: float - The opening price of the current candle. High()   High @description Returns the highest price of the current candle.   Returns: float - The highest price of the current candle. Low()   Low @description Returns the lowest price of the current candle.   Returns: float - The lowest price of the current candle. Close()   Close @description Returns the closing price of the current candle.   Returns: float - The closing price of the current candle. FullSize()   FullSize @description Returns the full size (range) of the current candle (high - low).   Returns: float - The full size of the current candle. BodySize()   BodySize @description Returns the body size of the current candle (open - close).   Returns: float - The body size of the current candle. WickSize()   WickSize @description Returns the size of the wicks of the current candle (full size - body size).   Returns: float - The size of the wicks of the current candle. UpperWickSize()   UpperWickSize @description Returns the size of the upper wick of the current candle.   Returns: float - The size of the upper wick of the current candle. LowerWickSize()   LowerWickSize @description Returns the size of the lower wick of the current candle.   Returns: float - The size of the lower wick of the current candle. BodyToWickRatio()   BodyToWickRatio @description Returns the ratio of the body size to the wick size of the current candle.   Returns: float - The body to wick ratio of the current candle. UpperWickPercentage()   UpperWickPercentage @description Returns the percentage of the upper wick size relative to the full size of the current candle.   Returns: float - The percentage of the upper wick size relative to the full size of the current candle. LowerWickPercentage()   LowerWickPercentage @description Returns the percentage of the lower wick size relative to the full size of the current candle.   Returns: float - The percentage of the lower wick size relative to the full size of the current candle. WickToBodyRatio()   WickToBodyRatio @description Returns the ratio of the wick size to the body size of the current candle.   Returns: float - The wick to body ratio of the current candle. BodyPercentage()   BodyPercentage @description Returns the percentage of the body size relative to the full size of the current candle.   Returns: float - The percentage of the body size relative to the full size of the current candle. WickPercentage()   WickPercentage @description Returns the percentage of the wick size relative to the full size of the current candle.   Returns: float - The percentage of the wick size relative to the full size of the current candle. CandleDirection()   CandleDirection @description Returns the direction of the current candle.   Returns: string - "Bullish" if the candle is bullish, "Bearish" if the candle is bearish. AveragePrice()   AveragePrice @description Returns the average price of the current candle (mean of open, high, low, and close).   Returns: float - The average price of the current candle. MidpointPrice()   MidpointPrice @description Returns the midpoint price of the current candle (mean of high and low).   Returns: float - The midpoint price of the current candle. Volatility()   Volatility @description Returns the standard deviation of the OHLC prices of the current candle.   Returns: float - The volatility of the current candle.
Libreria Pine Script®
di DevArjun
5
supertrendLibrary "supertrend" supertrend : Library dedicated to different variations of supertrend supertrend_atr(length, multiplier, atrMaType, source, highSource, lowSource, waitForClose, delayed)   supertrend_atr: Simple supertrend based on atr but also takes into consideration of custom MA Type, sources   Parameters:      length (simple int) : : ATR Length      multiplier (simple float) : : ATR Multiplier      atrMaType (simple string) : : Moving Average type for ATR calculation. This can be sma, ema, hma, rma, wma, vwma, swma      source (float) : : Default is close. Can Chose custom source      highSource (float) : : Default is high. Can also use close price for both high and low source      lowSource (float) : : Default is low. Can also use close price for both high and low source      waitForClose (simple bool) : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.      delayed (simple bool) : : if set to true lags supertrend atr stop based on target levels.   Returns: dir : Supertrend direction supertrend : BuyStop if direction is 1 else SellStop supertrend_bands(bandType, maType, length, multiplier, source, highSource, lowSource, waitForClose, useTrueRange, useAlternateSource, alternateSource, sticky)   supertrend_bands: Simple supertrend based on atr but also takes into consideration of custom MA Type, sources   Parameters:      bandType (simple string) : : Type of band used - can be bb, kc or dc      maType (simple string) : : Moving Average type for Bands. This can be sma, ema, hma, rma, wma, vwma, swma      length (simple int) : : Band Length      multiplier (float) : : Std deviation or ATR multiplier for Bollinger Bands and Keltner Channel      source (float) : : Default is close. Can Chose custom source      highSource (float) : : Default is high. Can also use close price for both high and low source      lowSource (float) : : Default is low. Can also use close price for both high and low source      waitForClose (simple bool) : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.      useTrueRange (simple bool) : : Used for Keltner channel. If set to false, then high-low is used as range instead of true range      useAlternateSource (simple bool) : - Custom source is used for Donchian Chanbel only if useAlternateSource is set to true      alternateSource (float) : - Custom source for Donchian channel      sticky (simple bool) : : if set to true borders change only when price is beyond borders.   Returns: dir : Supertrend direction supertrend : BuyStop if direction is 1 else SellStop supertrend_zigzag(length, history, useAlternativeSource, alternativeSource, source, highSource, lowSource, waitForClose, atrlength, multiplier, atrMaType)   supertrend_zigzag: Zigzag pivot based supertrend   Parameters:      length (simple int) : : Zigzag Length      history (simple int) : : number of historical pivots to consider      useAlternativeSource (simple bool)      alternativeSource (float)      source (float) : : Default is close. Can Chose custom source      highSource (float) : : Default is high. Can also use close price for both high and low source      lowSource (float) : : Default is low. Can also use close price for both high and low source      waitForClose (simple bool) : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.      atrlength (simple int) : : ATR Length      multiplier (simple float) : : ATR Multiplier      atrMaType (simple string) : : Moving Average type for ATR calculation. This can be sma, ema, hma, rma, wma, vwma, swma   Returns: dir : Supertrend direction supertrend : BuyStop if direction is 1 else SellStop zupertrend(length, history, useAlternativeSource, alternativeSource, source, highSource, lowSource, waitForClose, atrlength, multiplier, atrMaType)   zupertrend: Zigzag pivot based supertrend   Parameters:      length (simple int) : : Zigzag Length      history (simple int) : : number of historical pivots to consider      useAlternativeSource (simple bool)      alternativeSource (float)      source (float) : : Default is close. Can Chose custom source      highSource (float) : : Default is high. Can also use close price for both high and low source      lowSource (float) : : Default is low. Can also use close price for both high and low source      waitForClose (simple bool) : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.      atrlength (simple int) : : ATR Length      multiplier (simple float) : : ATR Multiplier      atrMaType (simple string) : : Moving Average type for ATR calculation. This can be sma, ema, hma, rma, wma, vwma, swma   Returns: dir : Supertrend direction supertrend : BuyStop if direction is 1 else SellStop zsupertrend(zigzagpivots, history, source, highSource, lowSource, waitForClose, atrMaType, atrlength, multiplier)   zsupertrend: Same as zigzag supertrend. But, works on already calculated array rather than Calculating fresh zigzag   Parameters:      zigzagpivots (array) : : Precalculated zigzag pivots      history (simple int) : : number of historical pivots to consider      source (float) : : Default is close. Can Chose custom source      highSource (float) : : Default is high. Can also use close price for both high and low source      lowSource (float) : : Default is low. Can also use close price for both high and low source      waitForClose (simple bool) : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.      atrMaType (simple string) : : Moving Average type for ATR calculation. This can be sma, ema, hma, rma, wma, vwma, swma      atrlength (simple int) : : ATR Length      multiplier (simple float) : : ATR Multiplier   Returns: dir : Supertrend direction supertrend : BuyStop if direction is 1 else SellStop
Libreria Pine Script®
di Trendoscope
UVR Crypto TrendINDICATOR OVERVIEW: UVR CRYPTO TREND The UVR Crypto Trend indicator is a custom-built tool designed specifically for cryptocurrency markets, utilizing advanced volatility, momentum, and trend-following techniques. It aims to identify trend reversals and provide buy and sell signals by analyzing multiple factors, such as price volatility(UVR), RSI (Relative Strength Index), CMF (Chaikin Money Flow), and EMA (Exponential Moving Average). The indicator is optimized for CRYPTO MARKETS only. KEY FEATURES AND HOW IT WORKS Volatility Analysis with UVR The UVR (Ultimate Volatility Rate) is a proprietary calculation that measures market volatility by comparing significant price extremes and smoothing the data over time. Purpose: UVR aims to reduce noise in low-volatility environments and highlight significant movements during higher-volatility periods. While it strives to improve filtering in low-volatility conditions, it does not guarantee perfect performance, making it a balanced and adaptable tool for dynamic markets like cryptocurrency. HOW UVR (ULTIMATE VOLATILITY RATE) IS CALCULATED UVR is calculated using a method that ensures precise measurement of market volatility by comparing price extremes across consecutive candles: Volatility Components: Two values are calculated to represent potential price fluctuations: The absolute difference between the current candle's high and the previous candle's low: Volatility Component 1=∣High−Low ∣ The absolute difference between the previous candle's high and the current candle's low: Volatility Component 2=∣High −Low∣ Volatility Ratio: The larger of the two components is selected as the Volatility Ratio, ensuring UVR captures the most significant movement: Volatility Ratio=max(Volatility Component 1,Volatility Component 2) Smoothing with SMMA: To stabilize the volatility calculation, the Volatility Ratio is smoothed using a Smoothed Moving Average (SMMA) over a user-defined period (e.g., 14 candles): UVR=(UVR(Previous)×(Period−1)+Volatility Ratio)/Period ​ This calculation ensures UVR adapts dynamically to market conditions, focusing on significant price movements while filtering out noise. RSI FOR MOMENTUM DETECTION RSI (Relative Strength Index) identifies overbought and oversold conditions. Trend Confirmation at the 50 Level RSI values crossing above 50 signal the potential start of an upward trend. RSI values crossing below 50 indicate the potential start of a downward trend. Key Reversals at Extreme Levels RSI detects trend reversals at overbought (>70) and oversold (<30) levels. For example: Overbought Trend Reversal: RSI >70 followed by bearish price action signals a potential downtrend. Oversold Trend Reversal: RSI <30 with bullish confirmation signals a potential uptrend. Rare Extreme RSI Readings Extreme levels, such as RSI <12 (oversold) or RSI >88 (overbought), are used to identify rare yet powerful reversals. ---HOW IT DIFFERS FROM OTHER INDICATORS--- Using UVR High and Low Values The Ultimate Volatility Rate (UVR) focuses on analyzing the high and low price ranges of the market to measure volatility. Unlike traditional trend indicators that rely primarily on momentum or moving average crossovers, UVR leverages price extremes to better identify trend reversals. This approach ensures fewer false signals during low-volatility phases and more accurate trend detection during high-volatility conditions. UVR as the Core Component The indicator is fundamentally built around UVR as the primary filter, while supporting tools like RSI (momentum detection), CMF (volume confirmation), and EMA (trend validation) complement its functionality. By integrating these additional components, the indicator provides a multidimensional analysis rather than relying solely on a single approach. Dynamic Adaptation to Volatility UVR dynamically adjusts to market conditions, striving to improve filtering in low-volatility phases. While not flawless, this approach minimizes false signals and adapts more effectively to varying levels of market activity. Trend Clouds for Visual Guidance UVR-based dynamic clouds visually mark high and low price areas, highlighting potential consolidation or retracement zones. These clouds serve as guides for setting stop-loss or take-profit levels, offering clear risk management strategies. BUY AND SELL SIGNAL LOGIC BUY CONDITIONS Momentum-Based Buy-Entry RSI >50, CMF >0, and the close price is above EMA50. The price difference between open and close exceeds a threshold based on UVR. Oversold Reversal RSI <30 and CMF >0 with a strong bullish candle (close > open and UVR-based sensitivity filter). Breakout Confirmation The price breaks above a previously identified resistance, with conditions for RSI and CMF supporting the breakout. Reversal from Oversold RSI Extreme RSI <12 on the previous candle with a strong rebound on the current candle with UVR confirmation filter. SELL CONDITIONS Momentum-Based Sell-Entry RSI <50, CMF <0, and the close price is below EMA50. The price difference between open and close exceeds the UVR threshold. Overbought Reversal RSI >70 with bearish price action (open > close and UVR-based sensitivity filter). Breakdown Confirmation The price breaks below a previously identified support, with RSI and CMF supporting the breakdown. Reversal from Overbought RSI Extreme RSI >88 on the previous candle with a bearish confirmation on the current candle with UVR confirmation filter. BUY AND SELL SIGNALS VISUALIZATION The UVR Crypto Trend Indicator visually represents buy and sell conditions using dynamic plots, making it easier for traders to interpret and act on the signals. Below is an explanation of the visual representation: Buy Signals and Visualization Signal Trigger: A buy signal is generated when one of the defined Buy Conditions is met (e.g., RSI >50, CMF >0, price above EMA50). Visual Representation: A blue upward arrow appears at the candle where the buy condition is triggered. A blue cloud forms above the price candles, representing the strength of the bullish trend. The cloud dynamically adapts to market volatility, using the UVR calculation to mark support zones or consolidation levels. Purpose of the Blue Cloud: It acts as a visual guide for price movements and stay horizontal when the trend is not moving up Sell Signals and Visualization Signal Trigger: A sell signal is generated when one of the defined Sell Conditions is met (e.g., RSI <50, CMF <0, price below EMA50). Visual Representation: A red downward arrow appears at the candle where the sell condition is triggered. A red cloud forms below the price candles, representing the strength of the bearish trend. Like the blue cloud, it uses the UVR calculation to dynamically mark resistance zones or potential retracement levels. Purpose of the Red Cloud: It acts as a visual guide for price movements and stay horizontal when the trend is not moving down. CONCLUSION The UVR Crypto Trend indicator provides a powerful tool for trend reversal detection by combining volatility analysis, momentum confirmation, and trend-following techniques. Its unique use of the Ultimate Volatility Rate (UVR) as a core element, supported by proven indicators like RSI, CMF, and EMA, ensures reliable and actionable signals tailored for the crypto market's dynamic nature. By leveraging UVR’s high and low price range analysis, it achieves a level of precision that traditional indicators lack, making it a high-performing system for cryptocurrency traders.
Indicatore Pine Script®
di ebecihalil
Trading Sessions with Highs and LowsTrading Sessions with Highs and Lows is designed to visually highlight specific trading sessions on the chart, providing traders with key insights into market behavior during these time periods. Here’s a detailed explanation of how the indicator works: Key Features 1. Session Boxes: • The indicator plots colored boxes on the chart to represent the price range of defined trading sessions. • Each box spans the session’s start and end times and encapsulates the high and low prices during that period. • Two trading sessions are defined by default: • USA Trading Session: 9:30 AM - 4:00 PM (New York Time). • UK Trading Session: 8:00 AM - 4:30 PM (London Time). 2. Session Labels: • The name of the session (e.g., “USA” or “UK”) is displayed above the session box for clear identification. 3. High and Low Markers: • Markers are added to the chart at the session’s high and low points: • High Marker: A green label indicating the session high. • Low Marker: A red label indicating the session low. 4. Dynamic Reset: • After the session ends, the session high and low values are reset to na to prepare for the next trading day. 5. Customizable Background Colors: • Each session’s box has a distinct, semi-transparent background color for better visual separation. How It Works 1. Core Functionality: • A function, plot_box, takes the session name, start time, end time, and background color as input. • It calculates whether the current time is within the session. • During the session: • It tracks the session’s highest and lowest prices. • It identifies the bars where the high and low occurred. • At the session’s end: • It plots a box on the chart covering the session’s time and price range. • Labels are created for the session name and its high/low points. 2. Session Timing: • Timestamps for the USA and UK trading sessions are calculated using the timestamp function with respective time zones. 3. Visual Elements: • The box.new function draws the session boxes on the chart. • The label.new function creates session name and high/low labels. Usage • Overlay Mode: The indicator is applied directly on the price chart (overlay=true), making it easy to visualize session-specific price behavior. • Trading Strategy: • Identify session-specific support and resistance levels. • Observe price action trends during key trading periods. • Align trading decisions with session dynamics. Customization While the indicator is preset for the USA and UK trading sessions, it can be easily modified: 1. Add/Remove Sessions: Define additional sessions by providing their start and end times. 2. Change Colors: Update the background_color in the plot_box calls to use different colors for sessions. 3. Adjust Time Zones: Replace the current time zones with others relevant to your trading style. Visualization Example • USA Session: • Time: 9:30 AM - 4:00 PM (New York Time). • Box Color: Semi-transparent orange. • UK Session: • Time: 8:00 AM - 4:30 PM (London Time). • Box Color: Semi-transparent green. Why Use This Indicator? 1. Market Awareness: Easily spot price behavior during high-liquidity trading periods. 2. Trend Analysis: Analyze how sessions overlap or affect each other. 3. Session Boundaries: Use session high/low levels as dynamic support and resistance zones. This indicator is an essential tool for intraday and swing traders who want to align their strategies with key market timings.
Indicatore Pine Script®
di djanmamur
Equal Highs and LowsDescription: The ‘Equal Highs and Lows’ indicator is a technical analysis tool that marks identical price levels on a trading chart using the current time-frame, assisting traders in identifying potential support and resistance zones or liquidity draws. It creates a horizontal line connecting points where the price has created equal highs and lows within a specified lookback period. Unique to this tool, it maintains a clean chart by removing the line once the price surpasses the equal highs or falls below the equal lows, ensuring only the currently relevant equal highs and lows are highlighted. Features: Customization Options: Users can adjust the appearance of the lines (color, width, and style) to match their chart setup or preferences. Users can also choose to extend the lines marking the equal highs/lows to the right of the chart making the equal high/low levels more easier to visualize. User-Defined Lookback Length: The number of bars to look back for finding equal highs and lows can be set by the user, allowing for flexibility in different market conditions. How It Works: The indicator meticulously scans the chart over a user-specified lookback duration, identifying bars with matching high or low values that have not been mitigated on the current chat timeframe, thereby constructing an index of equal values. It subsequently connects these equal values on the chart with a line. While this intuitive indicator does not forecast future market trends, it emphasizes significant price levels derived from historical data. Usage: Identifying Support and Resistance: The lines drawn by the indicator can be used to identify potential support and resistance zones and/or draws of liquidity, which are crucial for making informed trading decisions. Strategy Development: Traders can incorporate the visual cues provided by the indicator into their trading strategies, using them as one of the factors for entry or exit decisions. Originality: This indicator presents a distinctive method for pinpointing and illustrating equal highs and lows, granting traders a crucial insight into key price levels. It stands apart from conventional indicators by offering extensive personalization and employing a novel approach to augment chart analysis. Uniquely, it retains only unmitigated equal high/low levels on the chart, automatically discarding mitigated price levels once the price has reached that level. Conclusion: The "Equal Highs and Lows" indicator is a practical tool for traders looking to enhance their chart analysis with visual cues of significant price levels. Its customization options and innovative approach make it a valuable addition to the trading toolkit, suitable for various trading styles and strategies.
Indicatore Pine Script®
di outofoptions
3
Mxwll Price Action Suite [Mxwll]Introducing the Mxwll Price Action Suite! The Mxwll Price Action Suite is an all-in-one analysis indicator incorporating elements of SMC and also ideas extending beyond the trading methodology! Features Internal structures External structures Customizable Sensitivities BoS/CHoCH Order Blocks HH/LH/LL/LH Areas Rolling TF highs/lows Rolling Volume Comparisons Auto Fibs And more! The image above shows the indicator's market structure identification capabilities. Internal BoS and CHoCH structures in addition to overarching market structures are available with customizable sensitivities. The image above shows the indicator identifying order blocks! Additionally, HH/LH/LL/LH areas are also identified. The image above shows a rolling area of interest. These areas can be compared to supply/demand zones, where traders might consider a bargain long/short/sell area. The indicator displays a rolling 4hr high/low and 1D high/low, alongside auto fibonacci levels with a customizable sensitivity. Finally, the Mxwll Price Action Suite shows relevant session information. Table information Current Session Countdown to session close Next Session Countdown to next session open Rolling 4-Hr volume intensity Rolling 24-Hr volume intensity Introducing the Mxwll SMC Suite! The Mxwll SMC Suite is an all-in-one analysis indicator incorporating elements of SMC and also ideas extending beyond the trading methodology! Features Internal structures External structures Customizable Sensitivities BoS/CHoCH Order Blocks HH/LH/LL/LH Areas Rolling TF highs/lows Rolling Volume Comparisons Auto Fibs And more! The image above shows the indicator's market structure identification capabilities. Internal BoS and CHoCH structures in addition to overarching market structures are available with customizable sensitivities. The image above shows the indicator identifying order blocks! Additionally, HH/LH/LL/LH areas are also identified. The image above shows a rolling area of interest. These areas can be compared to supply/demand zones, where traders might consider a bargain long/short/sell area. The indicator displays a rolling 4hr high/low and 1D high/low, alongside auto fibonacci levels with a customizable sensitivity. Finally, the Mxwll Price Action Suite shows relevant session information. Table information Current Session Countdown to session close Next Session Countdown to next session open Rolling 4-Hr volume intensity Rolling 24-Hr volume intensity Expanded Features of Mxwll Price Action Suite Internal and External Structures Internal Structures: These elements refer to the price formations and patterns that occur within a smaller scope or a specific trading session. The suite can detect intricate details like minor support/resistance levels or short-term trend reversals. External Structures: These involve larger, more significant market patterns and trends spanning multiple sessions or time frames. This capability helps traders understand overarching market directions. Customizable Sensitivities Adjusting sensitivity settings allows users to tailor the indicator's responsiveness to market changes. Higher sensitivity can catch smaller fluctuations, while lower sensitivity might focus on more significant, reliable market moves. Break of Structure (BoS) and Change of Character (CHoCH) BoS: This feature identifies points where the price breaks a significant structure, potentially indicating a new trend or a trend reversal. CHoCH: Detects subtle shifts in the market's behavior, which could suggest the early stages of a trend change before they become apparent to the broader market. Order Blocks and Market Phases Order Blocks: These are essentially price levels or zones where significant trading activities previously occurred, likely pointing to the positions of smart money. HH/LH/LL/LH Areas: Identifying Higher Highs (HH), Lower Highs (LH), Lower Lows (LL), and Lower Highs (LH) helps in understanding the trend and market structure, aiding in predictive analysis. Rolling Timeframe Highs/Lows and Volume Comparisons Tracks highs and lows over specified rolling periods, providing dynamic support and resistance levels. Compares volume data across different timeframes to assess the strength or weakness of the current price movements. Auto Fibonacci Levels Automatically calculates and plots Fibonacci retracement levels, a popular tool among traders to identify potential reversal points based on past movements. Session Data and Volume Intensity Session Information: Displays current and upcoming trading sessions along with countdown timers, which is crucial for day traders and those trading on session overlaps. Volume Intensity: Measures and compares the volume within the last 4 hours and 24 hours to gauge market activity and potential breakout/breakdown movements. Visualizations and Practical Use Dynamic Visuals: The suite provides dynamic visual aids, such as real-time updating of high/low markers and Fibonacci levels, which adjust as new data comes in. This feature is critical in fast-paced markets. Strategic Entry/Exit Points: By identifying order blocks and using Fibonacci levels, traders can pinpoint strategic entry and exit points, maximizing potential returns. Risk Management: Enhanced features like session countdowns and volume intensity help in better risk management by providing traders with more data on market sentiment and potential volatility.
Indicatore Pine Script®
di MXWLL-Capital-Trading
182
Fib Pivot Points HLThis TradingView indicator allows users to select a specific timeframe (TF) and then analyzes the high, low, and closing prices from the past period within that TF to calculate a central pivot point. The pivot point is determined using the formula (High + Close + Low) / 3, providing a key level around which the market is expected to pivot or change direction. In addition to the central pivot point, the indicator enhances its utility by incorporating Fibonacci levels. These levels are calculated based on the range from the low to the high of the selected timeframe. For instance, a Fibonacci level like R0.38 would be calculated by adding 38% of the high-low range to the pivot point, giving traders potential resistance levels above the pivot. Key features of this indicator include: Timeframe Selection: Users can choose their desired timeframe, such as weekly, daily, etc., for analysis. Pivot Point Calculation: The indicator calculates the pivot point based on the previous period's high, low, and closing prices within the selected timeframe. Fibonacci Levels: Adds Fibonacci retracement levels to the pivot point, offering traders additional layers of potential support and resistance based on the natural Fibonacci sequence. This indicator is particularly useful for traders looking to identify potential turning points in the market and key levels of support and resistance based on historical price action and the Fibonacci sequence, which is widely regarded for its ability to predict market movements. Example: Suppose you're analyzing the EUR/USD currency pair using this indicator with a weekly timeframe setting. The previous week's price action showed a high of 1.2100, a low of 1.1900, and the week closed at 1.2000. Using the formula ( High + Close + Low ) / 3 (High+Close+Low)/3, the pivot point would be calculated as ( 1.2100 + 1.2000 + 1.1900 ) / 3 = 1.2000. Thus, the central pivot point for the current week is at 1.2000. The range from the low to the high is 1.2100 − 1.1900 = 0.0200 1.2100−1.1900=0.0200. To calculate a specific Fibonacci level, such as R0.38, you would add 38% of the high-low range to the pivot point: 1.2000 + ( 0.0200 ∗ 0.38 ) = 1.2076 1.2000+(0.0200∗0.38)=1.2076. Thus, the R0.38 Fibonacci resistance level is at 1.2076. Similarly, you can calculate other Fibonacci levels such as S0.38 (Support level at 38% retracement) by subtracting 38% of the high-low range from the pivot point. Traders can use the pivot point as a reference for the market's directional bias: prices above the pivot point suggest bullish sentiment, while prices below indicate bearish sentiment. The Fibonacci levels act as potential stepping stones for price movements, offering strategic points for entry, exit, or placing stop-loss orders.
Indicatore Pine Script®
di microupnup
4
Fake BreakoutThis indicator detect fake breakout on previous day high/low and option previous swing high and low Rule Detect Fake Breakout On Previous Day High/Low Or Swing high low Fake Breakout - 1) Detect previous day high/low or swing high/low 2) A) If price revisit on previous day high/swing high look for upside breakout after input number of candle (1-5) price came back to previous high and breakout happen downside it show sell because its fake breakout of previous day high or swing high B) If price revisit on previous day low/swing low look for downside breakout after input number of candle (1-5) price came back to previous low and breakout upside of previous day low it show Buy because its fake breakout of previous day low or swing low Disclaimer -Traders can use this script as a starting point for further customization or as a reference for developing their own trading strategies. It's important to note that past performance is not indicative of future results, and thorough testing and validation are recommended before deploying any trading strategy.
Indicatore Pine Script®
di samscripter
3
Ticker Correlation Reference IndicatorHello, I am super excited to be releasing this Ticker Correlation assessment indicator. This is a big one so let us get right into it! Inspiration: The inspiration for this indicator came from a similar indicator by Balipour called the Correlation with P-Value and Confidence Interval. It’s a great indicator, you should check it out! I used it quite a lot when looking for correlations; however, there were some limitations to this indicator’s functionality that I wanted. So I decided to make my own indicator that had the functionality I wanted. I have been using this for some time but decided to actual spruce it up a bit and make it user friendly so that I could share it publically. So let me get into what this indicator does and, most importantly, the expanded functionality of this indicator. What it does: This indicator determines the correlation between 2 separate tickers. The user selects the two tickers they wish to compare and it performs a correlation assessment over a defaulted 14 period length and displays the results. However, the indicator takes this much further. The complete functionality of this indicator includes the following: 1. Assesses the correlation of all 4 ticker variables (Open, High, Low and Close) over a user defined period of time (defaulted to 14); 2. Converts both tickers to a Z-Score in order to standardize the data and provide a side by side comparison; 3. Displays areas of high and low correlation between all 4 variables; 4. Looks back over the consistency of the relationship (is correlation consistent among the two tickers or infrequent?); 5. Displays the variance in the correlation (there may be a statistically significant relationship, but if there is a high variance, it means the relationship is unstable); 6. Permits manual conversion between prices; and 7. Determines the degree of statistical significance (be it stable, unstable or non-existent). I will discuss each of these functions below. Function 1: Assesses the correlation of all 4 variables. The only other indicator that does this only determines the correlation of the close price. However, correlation between all 4 variables varies. The correlation between open prices, high prices, low prices and close prices varies in statistically significant ways. As such, this indicator plots the correlation of all 4 ticker variables and displays each correlation. Assessing this matters because sometimes a stock may not have the same magnitude in highs and lows as another stock (one stock may be more bullish, i.e. attain higher highs in comparison to another stock). Close price is helpful but does not pain the full picture. As such, the indicator displays the correlation relationship between all 4 variables (image below): Function 2: Converts both tickers to Z-Score Z-Score is a way of standardizing data. It simply measures how far a stock is trading in relation to its mean. As such, it is a way to express both tickers on a level playing field. Z-Score was also chosen because the Z-Score Values (0 – 4) also provide an appropriate scale to plot correlation lines (which range from 0 to 1). The primary ticker (Ticker 1) is plotted in blue, the secondary comparison ticker (Ticker 2) is plotted in a colour changing format (which will be discussed below). See the image below: Function 3: Displays areas of high and low correlation While Ticker 1 is plotted in a static blue, Ticker 2 (the comparison ticker) is plotted in a dynamic, colour changing format. It will display areas of high correlation (i.e. areas with a P value greater than or equal to 0.9 or less than and equal to -0.9) in green, areas of moderate correlation in white. Areas of low correlation (between 0.4 and 0 or -0.4 and 0) are in red. (see image below): Function 4: Checks consistency of relationship While at the time of assessing a stock there very well maybe a high correlation, whether that correlation is consistent or not is the question. The indicator employs the use of the SMA function to plot the average correlation over a defined period of time. If the correlation is consistently high, the SMA should be within an area of statistical significance (over 0.5 or under -0.5). If the relationship is inconsistent, the SMA will read a lower value than the actual correlation. You can see an example of this when you compare ETH to Tezos in the image below: You can see that the correlation between ETH and Tezo’s on the high level seems to be inconsistent. While the current correlation is significant, the SMA is showing that the average correlation between the highs is actually less than 0.5. The indicator also tells the user narratively the degree of consistency in the statistical relationship. This will be discussed later. Function 5: Displays the variance When it comes to correlation, variance is important. Variance simply means the distance between the highest and lowest value. The indicator assess the variance. A high degree of variance (i.e. a number surpassing 0.5 or greater) generally means the consistency and stability of the relationship is in issue. If there is a high variance, it means that the two tickers, while seemingly significantly correlated, tend to deviate from each other quite extensively. The indicator will tell the user the variance in the narrative bar at the bottom of the chart (see image below): Function 6: Permits manual conversion of price One thing that I frequently want and like to do is convert prices between tickers. If I am looking at SPX and I want to calculate a price on SPY, I want to be able to do that quickly. This indicator permits you to do that by employing a regression based formula to convert Ticker 1 to Ticker 2. The user can actually input which variable they would like to convert, whether they want to convert Ticker 1 Close to Ticker 2 Close, or Ticker 1 High to Ticker 2 High, or low or open. To do this, open the settings and click “Permit Manual Conversion”. This will then take the current Ticker 1 Close price and convert it to Ticker 2 based on the regression calculations. If you want to know what a specific price on Ticker 1 is on Ticker 2, simply click the “Allow Manual Price Input” variable and type in the price of Ticker 1 you want to know on Ticker 2. It will perform the calculation for you and will also list the standard error of the calculation. Below is an example of calculating a SPY price using SPX data: Above, the indicator was asked to convert an SPX price of 4,100 to a SPY price. The result was 408.83 with a standard error of 4.31, meaning we can expect 4,100 to fall within 408.83 +/- 4.31 on SPY. Function 7: Determines the degree of statistical significance The indicator will provide the user with a narrative output of the degree of statistical significance. The indicator looks beyond simply what the correlation is at the time of the assessment. It uses the SMA and the highest and lowest function to make an assessment of the stability of the statistical relationship and then indicates this to the user. Below is an example of IWM compared to SPY: You will see, the indicator indicates that, while there is a statistically significant positive relationship, the relationship is somewhat unstable and inconsistent. Not only does it tell you this, but it indicates the degree of inconsistencies by listing the variance and the range of the inconsistencies. And below is SPY to DIA: SPY to BTCUSD: And finally SPY to USDCAD Currency: Other functions: The indicator will also plot the raw or smoothed correlation result for the Open, High, Low or Close price. The default is to close price and smoothed. Smoothed just means it is displaying the SMA over the raw correlation score. Unsmoothing it will show you the raw correlation score. The user also has the ability to toggle on and off the correlation table and the narrative table so that they can just review the chart (the side by side comparison of the 2 tickers). Customizability All of the functions are customizable for the most part. The user can determine the length of lookback, etc. The default parameters for all are 14. The only thing not customizable is the assessment used for determining the stability of a statistical relationship (set at 100 candle lookback) and the regression analysis used to convert price (10 candle lookback). User Notes and important application tips: #1: If using the manual calculation function to convert price, it is recommended to use this on the hourly or daily chart. #2: Leaving pre-market data on can cause some errors. It is recommended to use the indicator with regular market hours enabled and extended market hours disabled. #3: No ticker is off limits. You can compare anything against anything! Have fun with it and experiment! Non-Indicator Specific Discussions: Why does correlation between stocks mater? This can matter for a number of reasons. For investors, it is good to diversify your portfolio and have a good array of stocks that operate somewhat independently of each other. This will allow you to see how your investments compare to each other and the degree of the relationship. Another function may be getting exposure to more expensive tickers. I am guilty of trading IWM to gain exposure to SPY at a reduced cost basis :-). What is a statistically significant correlation? The rule of thumb is anything 0.5 or greater is considered statistically significant. The ideal setup is 0.9 or more as the effect is almost identical. That said, a lot of factors play into statistical significance. For example, the consistency and variance are 2 important factors most do not consider when ascertaining significance. Perhaps IWM and SPY are significantly correlated today, but is that a reliable relationship and can that be counted on as a rule? These are things that should be considered when trading one ticker against another and these are things that I have attempted to address with this indicator! Final notes: I know I usually do tutorial videos. I have not done one here, but I will. Check back later for this. I hope you enjoy the indicator and please feel free to share your thoughts and suggestions! Safe trades all!
Indicatore Pine Script®
di Steversteves
4
NSDT Lattice WebThis script creates a "web" by connecting different points of candles. All configurable by the trader. There are 4 basic parts to a candle: Open, High, Low, and Close With this script, you can connect any point of one candle in the past to any point of another current candle. For example: High to High, High to Low, High to Open, High to close Low to High, Low to Low, Low to Open, Low to Close Open to High, Open to Low, Open to Open, Open to Close Close to High, Close to Low, Close to Open, Close to Close The script will change the line colors based on whether the current plot is higher or lower than the previous plot. Try out different connection points to see what works for you. Connecting High to High and Low to Low, might easily show you when the market is making higher highs or lower lows, indicating a potential movement. Run it on replay at a higher speed and see how it may potentially help identify area of congestion or trends.
Indicatore Pine Script®
di NorthStarDayTrading
2
VisibleChart█   OVERVIEW This library is a Pine programmer’s tool containing functions that return values calculated from the range of visible bars on the chart. This is now possible in Pine Script™ thanks to the recently-released chart.left_visible_bar_time and chart.right_visible_bar_time built-ins, which return the opening time of the leftmost and rightmost bars on the chart. These values update as traders scroll or zoom their charts, which gives way to a class of indicators that can dynamically recalculate and draw visuals on visible bars only, as users scroll or zoom their charts. We hope this library's functions help you make the most of the world of possibilities these new built-ins provide for Pine scripts. For an example of a script using this library, have a look at the Chart ​VWAP indicator. █   CONCEPTS Chart properties The new chart.left_visible_bar_time and chart.right_visible_bar_time variables return the opening time of the leftmost and rightmost bars on the chart. They are only two of many new built-ins in the `chart.*` namespace. See this blog post for more information, or look them up by typing "chart." in the Pine Script™ Reference Manual . Dynamic recalculation of scripts on visible bars Any script using chart.left_visible_bar_time or chart.right_visible_bar_time acquires a unique property, which triggers its recalculation when traders scroll or zoom their charts in such a way that the range of visible bars on the chart changes. This library's functions use the two recent built-ins to derive various values from the range of visible bars. Designing your scripts for dynamic recalculation For the library's functions to work correctly, they must be called on every bar. For reliable results, assign their results to global variables and then use the variables locally where needed — not the raw function calls. Some functions like `barIsVisible()` or `open()` will return a value starting on the leftmost visible bar. Others such as `high()` or `low()` will also return a value starting on the leftmost visible bar, but their correct value can only be known on the rightmost visible bar, after all visible bars have been analyzed by the script. You can plot values as the script executes on visible bars, but efficient code will, when possible, create resource-intensive labels, lines or tables only once in the global ​scope using var , and then use the setter functions to modify their properties on the last bar only. The example code included in this library uses this method. Keep in mind that when your script uses chart.left_visible_bar_time or chart.right_visible_bar_time , your script will recalculate on all bars each time the user scrolls or zooms their chart. To provide script users with the best experience you should strive to keep calculations to a minimum and use efficient code so that traders are not always waiting for your script to recalculate every time they scroll or zoom their chart. Another aspect to consider is the fact that the rightmost visible bar will not always be the last bar in the dataset. When script users scroll back in time, a large portion of the time series the script calculates on may be situated after the rightmost visible bar. We can never assume the rightmost visible bar is also the last bar of the time series. Use `barIsVisible()` to restrict calculations to visible bars, but also consider that your script can continue to execute past them. Look first. Then leap. █   FUNCTIONS The library contains the following functions: barIsVisible()   Condition to determine if a given bar is within the users visible time range.   Returns: (bool) True if the the calling bar is between the `chart.left_visible_bar_time` and the `chart.right_visible_bar_time`. high()   Determines the value of the highest `high` in visible bars.   Returns: (float) The maximum high value of visible chart bars. highBarIndex()   Determines the `bar_index` of the highest `high` in visible bars.   Returns: (int) The `bar_index` of the `high()`. highBarTime()   Determines the bar time of the highest `high` in visible bars.   Returns: (int) The `time` of the `high()`. low()   Determines the value of the lowest `low` in visible bars.   Returns: (float) The minimum low value of visible chart bars. lowBarIndex()   Determines the `bar_index` of the lowest `low` in visible bars.   Returns: (int) The `bar_index` of the `low()`. lowBarTime()   Determines the bar time of the lowest `low` in visible bars.   Returns: (int) The `time` of the `low()`. open()   Determines the value of the opening price in the visible chart time range.   Returns: (float) The `open` of the leftmost visible chart bar. close()   Determines the value of the closing price in the visible chart time range.   Returns: (float) The `close` of the rightmost visible chart bar. leftBarIndex()   Determines the `bar_index` of the leftmost visible chart bar.   Returns: (int) A `bar_index`. rightBarIndex()   Determines the `bar_index` of the rightmost visible chart bar.   Returns: (int) A `bar_index` bars()   Determines the number of visible chart bars.   Returns: (int) The number of bars. volume()   Determines the sum of volume of all visible chart bars.   Returns: (float) The cumulative sum of volume. ohlcv()   Determines the open, high, low, close, and volume sum of the visible bar time range.   Returns: ( ) A tuple of the OHLCV values for the visible chart bars. Example: open is chart left, high is the highest visible high, etc. chartYPct(​pct)   Determines a price level as a percentage of the visible bar price range, which depends on the chart's top/bottom margins in "Settings/Appearance".   Parameters:      pct : (series float) Percentage of the visible price range (50 is 50%). Negative values are allowed.   Returns: (float) A price level equal to the `pct` of the price range between the high and low of visible chart bars. Example: 50 is halfway between the visible high and low. chartXTimePct(​pct)   Determines a time as a percentage of the visible bar time range.   Parameters:      pct : (series float) Percentage of the visible time range (50 is 50%). Negative values are allowed.   Returns: (float) A time in UNIX format equal to the `pct` of the time range from the `chart.left_visible_bar_time` to the `chart.right_visible_bar_time`. Example: 50 is halfway from the leftmost visible bar to the rightmost. chartXIndexPct(​pct)   Determines a `bar_index` as a percentage of the visible bar time range.   Parameters:      pct : (series float) Percentage of the visible time range (50 is 50%). Negative values are allowed.   Returns: (float) A time in UNIX format equal to the `pct` of the time range from the `chart.left_visible_bar_time` to the `chart.right_visible_bar_time`. Example: 50 is halfway from the leftmost visible bar to the rightmost. whenVisible(​src, whenCond, length)   Creates an array containing the `length` last `src` values where `whenCond` is true for visible chart bars.   Parameters:      src : (series int/float) The source of the values to be included.      whenCond : (series bool) The condition determining which values are included. Optional. The default is `true`.      length : (simple int) The number of last values to return. Optional. The default is all values.   Returns: (float ) The array ID of the accumulated `src` values. avg(​src)   Gathers values of the source over visible chart bars and averages them.   Parameters:      src : (series int/float) The source of the values to be averaged. Optional. Default is `close`.   Returns: (float) A cumulative average of values for the visible time range. median(​src)   Calculates the median of a source over visible chart bars.   Parameters:      src : (series int/float) The source of the values. Optional. Default is `close`.   Returns: (float) The median of the `src` for the visible time range. vVwap(​src)   Calculates a volume-weighted average for visible chart bars.   Parameters:      src : (series int/float) Source used for the ​VWAP calculation. Optional. Default is `hlc3`.   Returns: (float) The ​VWAP for the visible time range.
Libreria Pine Script®
di PineCoders
63
Price Action Brooks ProPrice Action Brooks Pro (PABP) - Professional Trading Indicator ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 OVERVIEW Price Action Brooks Pro (PABP) is a professional-grade TradingView indicator developed based on Al Brooks' Price Action trading methodology. It integrates decades of Al Brooks' trading experience and price action analysis techniques into a comprehensive technical analysis tool, helping traders accurately interpret market structure and identify trading opportunities. • Applicable Markets: Stocks, Futures, Forex, Cryptocurrencies • Timeframes: 1-minute to Daily (5-minute chart recommended) • Theoretical Foundation: Al Brooks Price Action Trading Method ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 CORE FEATURES ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1️⃣ INTELLIGENT GAP DETECTION SYSTEM Automatically identifies and marks three critical types of gaps in the market. TRADITIONAL GAP • Detects complete price gaps between bars • Upward gap: Current bar's low > Previous bar's high • Downward gap: Current bar's high < Previous bar's low • Hollow border design - doesn't obscure price action • Color coding: Upward gaps (light green), Downward gaps (light pink) • Adjustable border: 1-5 pixel width options TAIL GAP • Detects price gaps between bar wicks/shadows • Analyzes across 3 bars for precision • Identifies hidden market structure BODY GAP • Focuses only on gaps between bar bodies (open/close) • Filters out wick noise • Disabled by default, enable as needed Trading Significance: • Gaps signal strong momentum • Gap fills provide trading opportunities • Consecutive gaps indicate trend continuation ✓ Independent alert system for all gap types ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2️⃣ RTH BAR COUNT (Trading Session Counter) Intelligent counting system designed for US stock intraday trading. FEATURES • RTH Only Display: Regular Trading Hours (09:30-15:00 EST) • 5-Minute Chart Optimized: Displays every 3 bars (15-minute intervals) • Daily Auto-Reset: Counting starts from 1 each trading day SMART COLOR CODING • 🔴 Red (Bars 18 & 48): Critical turning moments (1.5h & 4h) • 🔵 Sky Blue (Multiples of 12): Hourly markers (12, 24, 36...) • 🟢 Light Green (Bar 6): Half-hour marker (30 minutes) • ⚫ Gray (Others): Regular 15-minute interval markers Al Brooks Time Theory: • Bar 18 (90 min): First 90 minutes determine daily trend • Bar 48 (4 hours): Important afternoon turning point • Hourly markers: Track institutional trading rhythm ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3️⃣ FOUR-LINE EMA SYSTEM Professional-grade configurable moving average system. DEFAULT CONFIGURATION • EMA 20: Short-term trend (Al Brooks' most important MA) • EMA 50: Medium-short term reference • EMA 100: Medium-long term confirmation • EMA 200: Long-term trend and bull/bear dividing line FLEXIBLE CUSTOMIZATION Each EMA can be independently configured: • On/Off toggle • Data source selection (close/high/low/open, etc.) • Custom period length • Offset adjustment • Color and transparency COLOR SCHEME • EMA 20: Dark brown, opaque (most important) • EMA 50/100/200: Blue-purple gradient, 70% transparent TRADING APPLICATIONS • Bullish Alignment: Price > 20 > 50 > 100 > 200 • Bearish Alignment: 200 > 100 > 50 > 20 > Price • EMA Confluence: All within <1% = major move precursor Al Brooks Quote: "The EMA 20 is the most important moving average. Almost all trading decisions should reference it." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 4️⃣ PREVIOUS VALUES (Key Prior Price Levels) Automatically marks important price levels that often act as support/resistance. THREE INDEPENDENT CONFIGURATIONS Each group configurable for: • Timeframe (1D/60min/15min, etc.) • Price source (close/high/low/open/CurrentOpen, etc.) • Line style and color • Display duration (Today/TimeFrame/All) SMART OPEN PRICE LABELS ⭐ • Auto-displays "Open" label when CurrentOpen selected • Label color matches line color • Customizable label size TYPICAL SETUP • 1st Line: Previous close (Support/Resistance) • 2nd Line: Previous high (Breakout target) • 3rd Line: Previous low (Support level) Al Brooks Magnet Price Theory: • Previous open: Price frequently tests opening price • Previous high/low: Strongest support/resistance • Breakout confirmation: Breaking prior levels = trend continuation ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 5️⃣ INSIDE & OUTSIDE BAR PATTERN RECOGNITION Automatically detects core candlestick patterns from Al Brooks' theory. ii PATTERN (Consecutive Inside Bars) • Current bar contained within previous bar • Two or more consecutive • Labels: ii, iii, iiii (auto-accumulates) • High-probability breakout setup • Stop loss: Outside both bars Trading Significance: "Inside bars are one of the most reliable breakout setups, especially three or more consecutive inside bars." - Al Brooks OO PATTERN (Consecutive Outside Bars) • Current bar engulfs previous bar • Two or more consecutive • Labels: oo, ooo (auto-accumulates) • Indicates indecision or volatility increase ioi PATTERN (Inside-Outside-Inside) • Three-bar combination: Inside → Outside → Inside • Auto-detected and labeled • Tug-of-war pattern • Breakout direction often very strong SMART LABEL SYSTEM • Auto-accumulation counting • Dynamic label updates • Customizable size and color • Positioned above bars ✓ Independent alerts for all patterns ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 USE CASES INTRADAY TRADING ✓ Bar Count (timing rhythm) ✓ Traditional Gap (strong signals) ✓ EMA 20 + 50 (quick trend) ✓ ii/ioi Patterns (breakout points) SWING TRADING ✓ Previous Values (key levels) ✓ EMA 20 + 50 + 100 (trend analysis) ✓ Gaps (trend confirmation) ✓ iii Patterns (entry timing) TREND FOLLOWING ✓ All four EMAs (alignment analysis) ✓ Gaps (continuation signals) ✓ Previous Values (targets) BREAKOUT TRADING ✓ iii Pattern (high-reliability setup) ✓ Previous Values (targets) ✓ EMA 20 (trend direction) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎨 DESIGN FEATURES PROFESSIONAL COLOR SCHEME • Gaps: Hollow borders + light colors • Bar Count: Smart multi-color coding • EMAs: Gradient colors + transparency hierarchy • Previous Values: Customizable + smart labels CLEAR VISUAL HIERARCHY • Important elements: Opaque (EMA 20, bar count) • Reference elements: Semi-transparent (other EMAs, gaps) • Hollow design: Doesn't obscure price action USER-FRIENDLY INTERFACE • Clear functional grouping • Inline layout saves space • All colors and sizes customizable ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📚 AL BROOKS THEORY CORE READING PRICE ACTION "Don't try to predict the market, read what the market is telling you." PABP converts core concepts into visual tools: • Trend Assessment: EMA system • Time Rhythm: Bar Count • Market Structure: Gap analysis • Trade Setups: Inside/Outside Bars • Support/Resistance: Previous Values PROBABILITY THINKING • ii pattern: Medium probability • iii pattern: High probability • iii + EMA 20 support: Very high probability ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ TECHNICAL SPECIFICATIONS • Pine Script Version: v6 • Maximum Objects: 500 lines, 500 labels, 500 boxes • Alert Functions: 8 independent alerts • Supported Timeframes: All (5-min recommended for Bar Count) • Compatibility: All TradingView plans, Mobile & Desktop ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 RECOMMENDED INITIAL SETTINGS GAPS • Traditional Gap: ✓ • Tail Gap: ✓ • Border Width: 2 BAR COUNT • Use Bar Count: ✓ • Label Size: Normal EMA • EMA 20: ✓ • EMA 50: ✓ • EMA 100: ✓ • EMA 200: ✓ PREVIOUS VALUES • 1st: close (Previous close) • 2nd: high (Previous high) • 3rd: low (Previous low) INSIDE & OUTSIDE BAR • All patterns: ✓ • Label Size: Large ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🌟 WHY CHOOSE PABP? ✅ Solid Theoretical Foundation Based on Al Brooks' decades of trading experience ✅ Complete Professional Features Systematizes complex price action analysis ✅ Highly Customizable Every feature adjustable to personal style ✅ Excellent Performance Optimized code ensures smooth experience ✅ Continuous Updates Constantly improving based on feedback ✅ Suitable for All Levels Benefits beginners to professionals ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📖 RECOMMENDED LEARNING Al Brooks Books: • "Trading Price Action Trends" • "Trading Price Action Trading Ranges" • "Trading Price Action Reversals" Learning Path: 1. Understand basic candlestick patterns 2. Learn EMA applications 3. Master market structure analysis 4. Develop trading system 5. Continuous practice and optimization ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ RISK DISCLOSURE IMPORTANT NOTICE: • For educational and informational purposes only • Does not constitute investment advice • Past performance doesn't guarantee future results • Trading involves risk and may result in capital loss • Trade according to your risk tolerance • Test thoroughly in demo account first RESPONSIBLE TRADING: • Always use stop losses • Control position sizes reasonably • Don't overtrade • Continuous learning and improvement • Keep trading journal ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📜 COPYRIGHT Price Action Brooks Pro (PABP) Author: © JimmC98 License: Mozilla Public License 2.0 Pine Script Version: v6 Acknowledgments: Thanks to Dr. Al Brooks for his contributions to price action trading. This indicator is developed based on his theories. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Experience professional-grade price action analysis now! "The best traders read price action, not indicators. But when indicators help you read price action better, use them." - Al Brooks
Indicatore Pine Script®
di JimmC98
1
Liquidity Grab + RSI Divergence═══════════════════════════════════════════════════════════════ LIQUIDITY GRAB + RSI DIVERGENCE INDICATOR ═══════════════════════════════════════════════════════════════ 📌 OVERVIEW This indicator identifies high-probability reversals by combining: • Liquidity sweeps (stop hunts) • RSI divergence confirmation • Filters false breakouts automatically ═══════════════════════════════════════════════════════════════ 🟢 BUY SIGNAL (Green Triangle Up) REQUIRES BOTH CONDITIONS: 1. Liquidity Grab Below Previous Low • Price breaks BELOW recent low • Candle CLOSES ABOVE that low • Traps sellers who shorted the breakdown 2. Bullish RSI Divergence • Price: Lower Low (LL) • RSI: Higher Low (HL) • Shows weakening downward momentum ➜ Result: Potential bullish reversal ═══════════════════════════════════════════════════════════════ 🔴 SELL SIGNAL (Red Triangle Down) REQUIRES BOTH CONDITIONS: 1. Liquidity Grab Above Previous High • Price breaks ABOVE recent high • Candle CLOSES BELOW that high • Traps buyers who bought the breakout 2. Bearish RSI Divergence • Price: Higher High (HH) • RSI: Lower High (LH) • Shows weakening upward momentum ➜ Result: Potential bearish reversal ═══════════════════════════════════════════════════════════════ 📊 VISUAL INDICATORS Main Signals: 🔺 Large Green Triangle = BUY (Liq Grab + Bullish Div) 🔻 Large Red Triangle = SELL (Liq Grab + Bearish Div) Reference Levels: ━ Red Line = Previous High Level ━ Green Line = Previous Low Level Additional Markers (Optional): ○ Small Green Circle = Liquidity grab low only ○ Small Red Circle = Liquidity grab high only ✕ Small Blue Cross = Bullish divergence only ✕ Small Orange Cross = Bearish divergence only ═══════════════════════════════════════════════════════════════ ⚙️ SETTINGS 1. Lookback Period (Default: 20) • Range: 5-100 • Sets how far back to identify previous highs/lows • Higher = fewer but stronger levels • Lower = more frequent but weaker levels 2. RSI Length (Default: 14) • Range: 5-50 • Standard RSI calculation period • 14 is industry standard 3. RSI Divergence Lookback (Default: 5) • Range: 3-20 • Controls pivot point sensitivity • Higher = fewer divergence signals • Lower = more divergence signals 4. Show Labels (Default: ON) • Toggle BUY/SELL text labels • Disable for cleaner chart view ═══════════════════════════════════════════════════════════════ 💡 HOW TO USE Step 1: WAIT FOR CONFIRMATION • Only trade LARGE TRIANGLE signals • Ignore small circles/crosses alone Step 2: CHECK TIMEFRAME • Best on: 15min, 1H, 4H, Daily • Avoid: 1min, 5min (too noisy) Step 3: CONFIRM CONTEXT • Check overall market trend • Identify key support/resistance • Look for confluence with price action Step 4: ENTRY & RISK MANAGEMENT • Enter on signal candle close or pullback • Stop loss below/above the liquidity grab wick • Target: Previous swing high/low or key levels • Risk/Reward: Minimum 1:2 ratio Step 5: SET ALERTS • Create alert for "BUY Signal" • Create alert for "SELL Signal" • Never miss opportunities ═══════════════════════════════════════════════════════════════ ✅ BEST PRACTICES DO: ✓ Use on multiple timeframes for confluence ✓ Combine with support/resistance zones ✓ Wait for both conditions (liq grab + divergence) ✓ Practice on demo account first ✓ Use proper position sizing DON'T: ✗ Trade every small circle/cross ✗ Use on very low timeframes (<15min) ✗ Ignore overall market context ✗ Trade without stop loss ✗ Risk more than 1-2% per trade ═══════════════════════════════════════════════════════════════ ⚠️ IMPORTANT NOTES • This is a CONFIRMATION tool, not a holy grail • No indicator is 100% accurate • Combine with your trading strategy • Backtest on your preferred instruments • Adjust parameters for your trading style • Higher timeframes = more reliable signals • Always use risk management ═══════════════════════════════════════════════════════════════ 🔔 ALERTS INCLUDED Two alert conditions are built-in: 1. "BUY Signal" - Liquidity Grab + Bullish RSI Divergence 2. "SELL Signal" - Liquidity Grab + Bearish RSI Divergence ═══════════════════════════════════════════════════════════════ 📈 RECOMMENDED SETTINGS BY TIMEFRAME 5-15 Min Charts: • Lookback: 10-15 • RSI Length: 14 • RSI Div Lookback: 3-5 1H-4H Charts: • Lookback: 20-30 • RSI Length: 14 • RSI Div Lookback: 5-7 Daily Charts: • Lookback: 30-50 • RSI Length: 14 • RSI Div Lookback: 7-10 ═══════════════════════════════════════════════════════════════ Good luck and trade safe! 🚀
Indicatore Pine Script®
di hassanejaz1
Aynet- True Wick Projector for Non-Standard ChartsTechnical Explanation: "Data Projection and Synchronization" This script is, at its core, a "data projection" tool. The fundamental technical problem it solves is compensating for the information loss that occurs when using different data visualization models. 1. The Core Problem: Information Loss Standard Charts (Time-Based): Normal candlesticks are time-based. Each candle represents a fixed time interval (like 1 hour or 1 day) and displays the complete Open, High, Low, and Close (OHLC) data for that period. The "wicks" show the volatility and the extreme price points (the High and Low). Non-Standard Charts (Price/Momentum-Based): Charts like Kagi, Renko, or Line Break filter out time. Their only concern is price movement. While one Renko box or Kagi line is forming, 10 or more time-based candles might have formed in the background. During this "noise filtering" process, the true high and low values (the wicks) from those underlying candles are lost. The problem is this: A trader looking at a non-standard chart cannot see how high or low the price actually went while that block or line was forming. This is a critical loss of information regarding market volatility, support/resistance levels, and price rejection. 2. The Technical Solution: A "Dual Data Stream" This script intelligently combines two different data streams to compensate for this information loss: Main Stream (Current Chart): The open and close data from your active Kagi, Renko, etc., chart. Secondary Stream (Projected Data): The high and low data from the underlying standard (time-based) chart. 3. The Code's Methodical Steps Step 1: Identifying the Data Source (syminfo...) This step precisely identifies the source for the secondary data stream. By using syminfo.prefix + ":" + syminfo.ticker (e.g., "NASDAQ:AAPL"), it guarantees that the data is pulled from the exact correct instrument and exchange. Step 2: Data Request & "Lookahead" Synchronization (request.security) This is the most critical part of the operation. request.security(...): This is the function Pine Script uses to pull data from another dataset (the secondary stream) onto the current chart. : This tells the function, "The only data I care about is the 'High' and 'Low' of the standard candle from that timeframe." lookahead = barmerge.lookahead_on (The Critical Key): This command solves the "time paradox." Normally (without this): request.security fetches data from the last completed bar. But as your Kagi bar is currently forming, the standard candle is also currently forming. This would cause the data to always be one bar behind (lag). With lookahead_on: This permits the script to "look ahead" at the data from the currently forming, incomplete standard bar. Because of this, as your Kagi bar moves, the true wick data is updated in real-time. This achieves real-time synchronization. Step 3: Visual Engineering (plotcandle) After the script retrieves the data, it must "draw" it. However, it only wants to draw the wicks, not the candle bodies. bodyTop and bodyBottom: First, it finds the top and bottom of the current Kagi bar's body (using math.max(open, close)). Plotting the Upper Wick (Green): It calls the plotcandle function and instructs it to draw a fake candle. It fixes this fake candle's Open, Low, and Close (open, low, close) values to the top of the Kagi bar's body (bodyTop). It only sets the High (high) value to the realHigh it fetched with request.security. The result: A wick is drawn from the bodyTop level up to the realHigh level, with no visible body. Plotting the Lower Wick (Red): It applies the reverse logic. It fixes the fake candle's Open, High, and Close values to the bottom of the Kagi bar's body (bodyBottom). It only sets the Low (low) value to the realLow. The result: A lower wick is drawn from bodyBottom down to realLow. Invisibility (color.new(color.white, 100)): In both plotcandle calls, the color (body color) and bordercolor are set to 100 transparency. This makes the "fake" candle bodies completely invisible, leaving only the colored wicks. Conclusion (Technical Summary) This script reclaims the volatility data (the wicks) that is naturally sacrificed by non-standard charts. It achieves this with technical precision by creating a secondary data stream using request.security and synchronizing it with zero lag using the lookahead_on parameter. Finally, it intelligently manipulates the plotcandle function (by creating invisible bodies) to project this lost data onto your Kagi/Renko chart as an "augmented reality" layer. This allows a trader to benefit from the clean, noise-filtered view of a non-standard chart without losing access to the full picture of market volatility.
Indicatore Pine Script®
di Aynet-London