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Bayesian Trend Posterior [forexobroker]Bayesian Trend Posterior treats each bar as a Bernoulli observation (up vs not-up) and runs a Beta-Bernoulli sequential update over a sliding window. The posterior probability P(next bar up) = (alpha + u) / (alpha + beta + N), where u is the count of up-bars in the window. Schmitt hysteresis on the posterior locks bull or bear regimes, preventing chatter near 0.5. 🔶 ALGORITHM 1. Count up-bars u in the last N closes (close > close ). 2. Posterior mean = (alpha + u) / (alpha + beta + N) using Beta(alpha, beta) prior. 3. Hysteresis: regime locks to +1 when posterior >= upper threshold, locks to -1 when posterior <= lower threshold, holds otherwise. 4. Within a locked regime, an EMA cross provides the entry trigger so the indicator can fire multiple times during sustained trends. 🔶 SIGNAL LOGIC - Buy: bull regime locked AND close crosses pullback EMA up AND not already long AND cooldown elapsed AND barstate.isconfirmed. - Sell: bear regime locked AND close crosses pullback EMA down. - Position-lock state machine. 🔶 INPUTS - Posterior Window N (default 30) - Prior alpha (default 2.0) - Prior beta (default 2.0) - Upper Hysteresis (default 0.55) - Lower Hysteresis (default 0.45) - Pullback EMA Length (default 8) - Cooldown Bars (default 4) - Visual: dashboard, glow, EMA toggle, buy / sell colors 🔶 ALERTS BTP Buy, BTP Sell, BTP Any Signal, BTP Bull Lock, BTP Bear Lock, BTP High Posterior, BTP Low Posterior, BTP Cross 0.5, BTP Webhook JSON. 🔶 LIMITATIONS - Bernoulli simplification ignores bar size; a tiny up-bar contributes the same as a strong one. Pair with an ATR-aware filter for size-weighted posteriors. - Window N is the dominant tuning knob: smaller N reacts faster but flips more; larger N is steadier. - Prior alpha = beta = 2 is uninformative; users with strong directional bias can adjust. - Hysteresis prevents chatter but slightly delays regime detection vs threshold-only logic.
Pine Script® 인디케이터
forexobroker의
Anchored Volume Weighted Average Price | Astral Vision Anchored Volume Weighted Average Price | Astral Vision 🌠💠 The Volume Weighted Average Price anchored to a fixed date represents the average price at which every Bitcoin has changed hands since that moment, weighted by volume. Unlike a moving average which weights bars equally by time an anchored VWAP weights each bar by its trading activity, making it a true reflection of the average cost basis for all market participants who entered after the anchor point. When price trades above an anchored VWAP, the aggregate of participants since that anchor is in profit. When price trades below it, they are in loss. This makes anchored VWAPs among the most reliable dynamic support and resistance levels available, as they represent the price at which the largest volume of participants is either defending a gain or protecting against a loss. This indicator plots up to 16 simultaneous anchored VWAPs: one per calendar year from 2013 through 2025, plus three fully custom anchors at any user-defined date, all on the price chart with individual color control and labeled at the current bar. Calculation ⚙️ `VWAP = Cumulative(HLC3 × Volume) / Cumulative(Volume)` Accumulation begins on the first bar of the anchor year (or the exact timestamp for custom anchors) and runs continuously to the present bar. Each VWAP is computed independently, carrying its own cumulative price-volume and volume sums from its respective start date. Plots 📊 Up to 13 year-anchored VWAP lines (2013–2025), each with a dual-layer glow (linewidths 6/2, transparency 80/0) 3 custom timestamp-anchored VWAP lines with the same glow rendering Labeled endpoints at the current bar for every active VWAP, showing year or custom identifier Inputs 🎛️ `2013` through `2025` :individual toggles to enable each year-anchored VWAP, each with its own color picker `Custom 1 / 2 / 3`: toggles for three free-anchor VWAPs, each with a date/time input and color picker Colors 🎨 Each VWAP line has its own independent color, pre-assigned along a spectral progression from violet (2013) through the visible spectrum to yellow (2025), giving each cycle year a visually distinct identity at a glance. Custom anchors default to blue, yellow, and green with full override available. Purpose 🎯 Standard VWAP tools on TradingView anchor to the current session or a single user-defined point, offering no way to compare multiple historical anchors simultaneously. Traders who want to assess confluence across different cycle entry points must place and manage anchors manually, one at a time. This indicator solves that entirely: all major Bitcoin calendar years are available as one-click toggles, letting you layer any combination of historical cost bases onto the chart instantly. The custom anchors extend this to any structurally significant date (cycle lows, halving events, ETF approvals) without any manual drawing tool interaction. Confluence zones where multiple VWAPs converge are immediately visible and have historically acted as the strongest support and resistance levels in Bitcoin's price structure. Disclaimer ⭕️ It is not financial advice, not an investment recommendation, and not affiliated with any financial institution, research firm, or organization of any kind. All content is provided for educational and informational purposes only. Always conduct your own research before making any financial decision.
Pine Script® 인디케이터
AstralVision의
Rolling Sharpe Ratio Oscillator | Astral Vision Rolling Sharpe Ratio Oscillator | Astral Vision 🌠💠 The Sharpe Ratio measures risk-adjusted return: how much excess return is being generated per unit of volatility. Applied as a rolling oscillator to Bitcoin's daily log returns, it answers a question that neither price nor momentum indicators address: is the current appreciation being earned efficiently relative to the risk being taken, or is it a volatile, noisy move that consumes large drawdowns to produce modest gains? High rolling Sharpe values indicate sustained, low-volatility uptrends where return per unit of risk is structurally elevated, historically coinciding with the most efficient phases of Bitcoin's bull runs. Negative Sharpe values indicate periods where volatility exceeds returns, marking drawdowns and bear phases. This indicator plots the annualized rolling Sharpe as a smoothed oscillator with configurable thresholds, and back-projects those thresholds onto the price chart as dynamic levels representing the price that would produce each Sharpe extreme given current return and volatility conditions. Calculation ⚙️ `Log Return = log(close / close )` `Rolling Sharpe = (SMA(Log Return, length) / StdDev(Log Return, length)) × √365` The ratio is annualized by multiplying by the square root of 365, expressing it in standard annual terms. An EMA of configurable length is then applied to smooth the raw Sharpe before threshold evaluation and coloring. The price bands invert the Sharpe thresholds back to price space: `Band Price = close × exp(threshold × StdDev / √365 × length)` This produces a dynamic price level representing what price would need to be, given current volatility, to produce the specified Sharpe value. Plots 📊 Smoothed Sharpe oscillator line in the indicator panel, colored by regime or continuous gradient Overbought and oversold threshold lines Fill between oscillator and overbought threshold when breached (distribution zone) Fill between oscillator and oversold threshold when breached (accumulation zone) Dynamic overbought and oversold price bands on the price chart, EMA-smoothed Candle coloring on the price chart by regime or gradient Background highlight on the price chart when either threshold is active Inputs 🎛️ `Lookback Period (days)`: rolling window for mean and standard deviation of log returns (default 365) `Smoothing EMA Length`: EMA applied to the raw Sharpe before all output (default 30) `Oversold Threshold`: Sharpe level marking risk-adjusted accumulation extremes (default −1.5) `Overbought Threshold`: Sharpe level marking risk-adjusted distribution extremes (default 2.8) `Use Gradient Color`: toggles between continuous gradient coloring across the −2 to +2 range and discrete regime-based coloring Colors 🎨 5 Astral Vision presets + custom override. Default: Futura. In gradient mode, color transitions continuously from negative to positive across the Sharpe range. In discrete mode, positive color activates above the overbought threshold, negative below the oversold threshold, and neutral between them. Purpose 🎯 Standard momentum indicators like RSI and MACD measure price direction and speed, but are blind to whether that directional move is being achieved efficiently. A 30% Bitcoin rally with 80% annualized volatility carries very different risk-adjusted implications than the same rally with 40% volatility, yet both look identical on a price or momentum chart. The rolling Sharpe makes that distinction explicit. The price band back-projection eliminates the need to mentally translate Sharpe values into price context: the bands show directly on the chart what price level corresponds to each statistical extreme given current volatility, updating dynamically as the volatility regime evolves. The gradient coloring option provides a continuous read of risk-adjusted efficiency across the entire oscillator range, not just at binary threshold crossings. Disclaimer ⭕️ It is not financial advice, not an investment recommendation, and not affiliated with any financial institution, research firm, or organization of any kind. All content is provided for educational and informational purposes only. Always conduct your own research before making any financial decision.
Pine Script® 인디케이터
AstralVision의
Blood Moons Spectrum | Astral Vision 🌑 Blood Moons ❤️‍🔥 | Astral Vision 🌠💠 A Blood Moon occurs during a total lunar eclipse, when Earth's shadow fully covers the Moon and the only light reaching it is refracted through Earth's atmosphere, filtering out shorter wavelengths and casting the Moon in deep red. These events follow predictable astronomical cycles and have historically captured significant cultural and psychological attention across civilizations. This indicator maps every Blood Moon and total lunar eclipse event from 2015 through 2029 onto the Bitcoin price chart, marking each event with a vertical line, a background highlight window, and a labeled annotation. The dataset includes named events (the 2015 Tetrad completion, the 2018 Super Blue Blood Moon, the 2018 record-length eclipse of the 21st century) alongside all standard Blood Moons, with duration and date displayed directly on the chart. Future events through 2029 are projected forward, making the indicator active across the current and next cycle. Calculation ⚙️ All event timestamps are hardcoded to their precise astronomical dates. The background highlight activates within a ±10-day window around each event, capturing the price behavior in the days immediately surrounding each eclipse. The label and line are rendered at the exact event date. No mathematical transformation is applied — the indicator is a temporal annotation layer mapped to astronomical data. Plots 📊 Vertical line at each Blood Moon date, extended across the full chart (toggleable) Background highlight on the price chart for a 10-day window around each event (toggleable) Label at each event bar displaying the event name, date, and eclipse duration (toggleable) Inputs 🎛️ `Show Background` toggles the ±10-day highlight window around each event `Plot Labels` toggles the annotation labels at each event date `Plot Lines` toggles the full-height vertical lines at each event date Colors 🎨 5 Astral Vision presets + custom override. Default: Inferno. Positive color applies to vertical lines and background highlights; negative color applies to label backgrounds. Purpose 🎯 Bitcoin price history contains a disproportionate number of notable moves, both tops and bottoms,in proximity to Blood Moon events, a pattern that has attracted consistent attention from on-chain analysts and cycle researchers. Whether the correlation reflects genuine market psychology, confirmation bias, or coincidence, the events are astronomically fixed and objectively dateable, making them worth tracking as potential behavioral anchors. This indicator provides the complete historical and forward-looking Blood Moon calendar overlaid directly on the price chart, eliminating the need to cross-reference external astronomical sources. The 10-day background window contextualizes price behavior in the event's immediate vicinity, and the duration annotation distinguishes short penumbral grazes from the long total eclipses that have historically drawn the most attention. Future events through 2029 allow the current cycle to be tracked against the same framework in real time. Disclaimer ⭕️ It is not financial advice, not an investment recommendation, and not affiliated with any financial institution, research firm, or organization of any kind. All content is provided for educational and informational purposes only. Always conduct your own research before making any financial decision.
Pine Script® 인디케이터
AstralVision의
Quarterly/Monthly/Weekly Performance | Astral Vision Quarterly/Monthly/Weekly Performance | Astral Vision 🌠💠 Price performance measured over fixed trailing windows (7, 30, and 90 bars) captures the momentum of Bitcoin's move at three structurally distinct timescales simultaneously. Weekly performance reflects short-term trend pressure; monthly performance captures the medium-term cycle direction; quarterly performance reveals whether the broader macro trend is accumulating or distributing. Reading all three in a single panel eliminates the need to switch timeframes to understand where momentum stands across the full temporal structure. This indicator plots trailing price performance as gradient-filled columns for each active window, with configurable overbought and oversold thresholds that identify statistically extreme moves. All three windows can be active simultaneously or independently, and each drives its own overlay on the price chart through candle coloring or background highlighting. Calculation ⚙️ `Performance = (close − close ) / close × 100` Where N is 7, 30, or 90 bars for weekly, monthly, and quarterly windows respectively. The result is a simple trailing percentage return expressed relative to the close N bars ago, with no smoothing applied — preserving the raw momentum read at each timescale. Plots 📊 Performance columns for each active window (weekly, monthly, quarterly) with gradient fill, opaque at the column tip, fading toward zero Zero baseline Overbought and oversold threshold lines for each active window Background highlight on the price chart when any active window's performance breaches a threshold (Background Color mode) Candle coloring on the price chart by the sign of the active window's performance (Plot Candle mode) Inputs 🎛️ `Overlay Mode`: Background Color, Plot Candle, or None for price chart output `Show Weekly / Monthly / Quarterly`: independent toggles for each performance window `Weekly OB / OS Threshold`: extreme levels for the 7-bar window (defaults +20 / −15) `Monthly OB / OS Threshold`: extreme levels for the 30-bar window (defaults +35 / −20) `Quarterly OB / OS Threshold`: extreme levels for the 90-bar window (defaults +50 / −30) Colors 🎨 5 Astral Vision presets + custom override. Default: Hermes. Positive color applies when performance is above zero; negative color applies when performance is below zero. Both the column fills and the price chart overlays follow the same coloring logic. Purpose 🎯 Standard momentum indicators process price through mathematical transformations (RSI, MACD, stochastic) that make their absolute values abstract and cycle-dependent. A trader looking for a direct answer to "how much has Bitcoin moved in the last month?" gets no clean output from any of those tools. This indicator answers that question directly with no transformation, keeping the output in percentage terms that are immediately interpretable. The three-window structure lets traders read weekly, monthly, and quarterly momentum in a single panel, identifying divergences between timescales, such as a strong monthly trend with an overextended weekly reading, that single-window indicators cannot surface. The threshold system identifies when a given trailing return has reached historically extreme levels for that window, providing a contextual signal layer on top of the raw performance read. Disclaimer ⭕️ It is not financial advice, not an investment recommendation, and not affiliated with any financial institution, research firm, or organization of any kind. All content is provided for educational and informational purposes only. Always conduct your own research before making any financial decision.
Pine Script® 인디케이터
AstralVision의
Bitcoin CAGR Analysis | Astral Vision Bitcoin CAGR Analysis | Astral Vision 🌠💠 The Compound Annual Growth Rate expresses Bitcoin's return over any rolling window as an annualized percentage, normalizing for the length of the period being measured. Unlike raw percentage returns, CAGR makes every rolling window directly comparable regardless of its duration, a 6-month and a 2-year window both output an annualized rate, allowing the current growth pace to be read in consistent units across the entire price history. This indicator computes rolling CAGR over a configurable lookback, then offers two analytical layers. Raw CAGR plots the annualized return directly, revealing how Bitcoin's structural growth rate has evolved across cycles. Z-Score mode standardizes the CAGR against its own rolling distribution, identifying when the current annualized return is statistically extreme relative to historical norms, either overheated or deeply compressed. A slope-based trend mode colors by whether CAGR is accelerating or decelerating over a secondary lookback, independent of absolute level. Calculation ⚙️ `CAGR = (close / close )^(365 / days elapsed) − 1` Days elapsed is derived from the actual timestamp difference rather than a fixed bar count, ensuring accuracy regardless of gaps or non-trading days in the data. `Z-Score = (CAGR − SMA(CAGR, length)) / StdDev(CAGR, length)` In Trend mode, the slope is computed as the difference between the current value and its value N bars ago, coloring by whether the CAGR (or its Z-Score) is rising or falling irrespective of its absolute level. Plots 📊 CAGR or Z-Score line in the indicator panel, colored by active regime Zero baseline High and low threshold lines in Z-Score Extremes mode Fill between the signal line and the breached threshold in Z-Score Extremes mode Candle coloring on the price chart by active regime (Z-Score modes only) Background highlight on the price chart when a threshold is breached in Z-Score Extremes mode Inputs 🎛️ `Mode`: Raw CAGR (annualized return) or Z-Score (standardized CAGR) `Visualization`: Extremes (threshold-based coloring) or Trend (slope-based directional coloring) `Z-Score Length`: rolling window for both CAGR calculation and Z-Score normalization (default 730) `Threshold High`: Z-Score level marking overheated growth (default 3.0) `Threshold Low`: Z-Score level marking compressed or negative growth (default −1.5) `Slope Length`: bar offset used to compute CAGR acceleration in Trend mode (default 34) `Show Background`: toggles price chart background highlighting at Z-Score extremes Colors 🎨 5 Astral Vision presets + custom override. Default: Infinito. In Extremes mode, positive color activates below the low threshold and negative above the high threshold. In Trend mode, positive color applies when the signal is rising and negative when falling. Raw CAGR mode uses positive color throughout. Purpose 🎯 Raw price charts and standard momentum indicators express returns as absolute price levels or bounded oscillators, neither of which answers the question of what annualized return Bitcoin is currently delivering relative to its own historical pace. CAGR makes that question answerable directly. The Z-Score layer adds statistical context: rather than judging whether a 200% annualized return is "high" by intuition, the Z-Score places it in the distribution of all historical CAGR values over the same window, making the assessment rigorous and cycle-independent. The Trend visualization mode repurposes the same calculation as a momentum direction indicator, identifying inflection points in the growth rate before they become obvious in price. The two modes together cover both valuation positioning and tactical momentum within a single indicator. Disclaimer ⭕️ It is not financial advice, not an investment recommendation, and not affiliated with any financial institution, research firm, or organization of any kind. All content is provided for educational and informational purposes only. Always conduct your own research before making any financial decision.
Pine Script® 인디케이터
AstralVision의
USDT Market Cap Flow Z-Score | Astral Vision USDT Market Cap Flow | Astral Vision 🌠💠 Tether's market capitalization is a direct proxy for the total pool of stablecoin capital available to enter the crypto market. When USDT supply expands rapidly, new fiat liquidity is being minted and positioned for deployment into risk assets, a historically bullish condition for Bitcoin. When supply contracts or stagnates, capital is either being redeemed out of the ecosystem or sitting idle, reducing the available bid for BTC. This indicator measures the rolling change in USDT market cap over a configurable window, expressing how much new stablecoin liquidity has entered or exited the system in absolute terms or as a Z-Score relative to historical norms. Two analytical modes offer different reads on the same flow data: Valuation identifies whether the current flow is a positive or negative liquidity injection relative to thresholds, while Trend tracks whether the flow is accelerating or decelerating relative to its own short-term moving average. Calculation ⚙️ `MC Flow = USDT Market Cap − USDT Market Cap ` This measures the net change in stablecoin supply over the lookback period. In Z-Score mode, the flow is standardized against its own rolling mean and standard deviation: `Z-Score = (MC Flow − SMA(MC Flow, z_len)) / StdDev(MC Flow, z_len)` In Trend mode, a short SMA is applied to the display value and the signal colors by whether the raw value is above or below that average — indicating whether liquidity injection is accelerating or decelerating. Plots 📊 Flow line in the indicator panel, colored by active regime SMA of the flow in Trend mode Overbought and oversold threshold lines in Z-Score Valuation mode Fill between the flow line and zero baseline in Valuation mode (positive or negative regime) Candle coloring on the price chart by active regime Background highlight on the price chart when flow is negative (accumulation signal) or at Z-Score extremes Inputs 🎛️ `Rolling Window (days)`: lookback for the market cap change calculation (default 60) `SMA Length`: smoothing applied to the display value in Trend mode (default 30) `Show Background`: toggles price chart background highlighting `Data Mode`: Raw (absolute USD flow) or Z-Score (standardized flow) `Z-Score Lookback`: window for Z-Score normalization (default 200) `Overbought Threshold`: Z-Score level marking excessive inflow (default 2.0) `Oversold Threshold`: Z-Score level marking excessive outflow or contraction (default −2.0) `Mode`: Valuation (threshold-based regime coloring) or Trend (momentum direction relative to SMA) Colors 🎨 5 Astral Vision presets + custom override. Default: Hermes. In Valuation mode, positive color activates on negative flow (stablecoin contraction, potential accumulation signal) and negative color on positive flow above threshold (excess inflow, potential distribution signal). In Trend mode, positive color applies when flow is above its SMA and negative when below. Purpose 🎯 Most liquidity indicators either track BTC price directly or use broad stablecoin dominance, which conflates supply changes with price movements of the underlying assets. Neither isolates the actual flow of new capital entering the stablecoin ecosystem as a standalone signal. This indicator measures the source directly: the net change in Tether's total supply, which can only increase through new minting and decrease through redemption. The dual-mode structure allows traders to use the same data for both macro liquidity positioning (Z-Score Valuation, identifying historically extreme inflows or outflows) and short-term tactical reads (Trend, tracking whether the current liquidity injection is growing or shrinking). The Z-Score normalization makes the signal cycle-comparable regardless of the absolute growth in USDT supply across years. Disclaimer ⭕️ It is not financial advice, not an investment recommendation, and not affiliated with any financial institution, research firm, or organization of any kind. All content is provided for educational and informational purposes only. Always conduct your own research before making any financial decision.
Pine Script® 인디케이터
AstralVision의
Institutional Valuation PROInstitutional Relative Valuation Indicator This indicator is designed to measure whether an asset is relatively overvalued or undervalued compared to a benchmark market. For Forex markets, the indicator compares the selected currency pair against the US Dollar Index (DXY). For Metals, the indicator compares the selected metal against Gold Futures (GC1!). The model is based on: * Relative price strength * Statistical deviation * Mean reversion principles * Institutional relative valuation concepts How it works: 1. The indicator calculates the relationship between the asset and its benchmark. 2. It measures the historical average behavior over a selected lookback period. 3. It then calculates how far the current price relationship deviates from its normal range. The result is a valuation score that helps identify: * Overvalued conditions * Undervalued conditions * Fair value areas * Extreme market extensions Key Features: * USD-based valuation model for FX * Gold-based valuation model for Metals * Smooth institutional-style valuation curves * Professional premium/discount zones * Overvaluation and undervaluation levels * Optional benchmark visibility controls * Mean reversion focused framework This indicator is not designed as a traditional momentum tool like RSI or MACD. Instead, it focuses on relative market valuation and statistical market positioning, similar to concepts used in institutional macro and relative-value trading.
Pine Script® 인디케이터
Gabriel131101의
Local Linear Slope Network [forexobroker]Local Linear Slope Network runs four `ta.linreg` regressions at windows 10/20/40/80, computes each line's slope sign per bar, and only fires signals when at least N slopes agree AND the previous bar did NOT yet have agreement. A clean fractal trend-confirmation entry — most trend indicators use one length; this one votes across four. 🔶 ALGORITHM For each window n in {10, 20, 40, 80}: 1. linreg_n = ta.linreg(close, n, 0) 2. slope_n = linreg_n − linreg_n 3. slope-sign vote: count how many slopes are > 0 (upCount) and how many are < 0 (dnCount) 4. Agreement edge: at least N slopes agree AND previous bar agreement was below the same threshold The "agreement edge" requirement gates the signal to a single bar at the regime change, not a stream of confirmations. 🔶 SIGNAL LOGIC - Buy: upCount ≥ N AND previous bar upCount < N AND cooldown AND barstate.isconfirmed - Sell: dnCount ≥ N AND previous bar dnCount < N AND cooldown AND barstate.isconfirmed 🔶 INPUTS - Window 1/2/3/4 (defaults 10/20/40/80 — dyadic spacing) - Min Slopes Agreeing (default 3 of 4) - Signal Cooldown (default 8) - Visual toggles for slowest line, dashboard, glow, colors 🔶 ALERTS LLN Buy / Sell, Any Signal, Full Bull (4/4), Full Bear (4/4), Fast Pair Up/Dn, Webhook JSON. 🔶 LIMITATIONS - ta.linreg internally is OLS regression — robust but assumes linear local trend. Works well on liquid trending instruments. - Slope is computed as endpoint difference (linreg − linreg ) — sensitive to outlier bars. - Slowest window (80 default) sets warmup. - The dyadic spacing (10/20/40/80) is opinionated; tighter/wider spacings change signal frequency drastically.
Pine Script® 인디케이터
forexobroker의
Bitcoin/USDT Dominance Ratio | Astral Vision Bitcoin/USDT Dominance Ratio | Astral Vision 🌠💠 USDT dominance measures the share of total crypto market capitalization held in Tether. When USDT dominance is high, capital is parked in stablecoins: risk appetite is low and dry powder is accumulating. When USDT dominance is low, capital has rotated into risk assets: stablecoin supply relative to the market has been deployed. Dividing Bitcoin's price by USDT dominance produces a ratio that amplifies both conditions: it rises when BTC appreciates while stablecoin dominance contracts (maximum risk-on), and falls when BTC depreciates while stablecoin dominance expands (maximum risk-off). The ratio acts as a liquidity-adjusted price: a measure of how much Bitcoin is worth relative to the available pool of sidelined capital. Calculation ⚙️ `Ratio = BTC Price / USDT Dominance (%)` Both the ratio candles and the price chart candles are colored identically by the same threshold logic, so the regime read is simultaneously visible in the indicator panel and on the price chart without switching focus. Plots 📊 Ratio candles in the indicator panel, colored by active regime Oversold threshold line (positive color) and overbought threshold line (negative color) Price chart candle coloring by the same regime logic Background highlight on the price chart when either threshold is breached Inputs 🎛️ `Oversold Threshold`: ratio level below which the signal enters accumulation territory (default 2100) `Overbought Threshold`: ratio level above which the signal enters distribution territory (default 27000) Colors 🎨 5 Astral Vision presets + custom override. Default: Infinito. Positive color activates below the oversold threshold; negative color activates above the overbought threshold. Purpose 🎯 Tracking BTC price and USDT dominance as separate charts requires constant context-switching and leaves the relationship between the two implicit. Most dominance indicators plot stablecoin share in isolation with no connection to price magnitude, while raw BTC price charts carry no information about the liquidity environment surrounding each move. This indicator fuses the two into a single ratio that makes the liquidity context inseparable from price. A BTC rally with contracting USDT dominance reads as a structurally stronger move than the same price gain with stable or rising stablecoin dominance and this indicator makes that difference directly visible through threshold crossings, candle color, and background regime highlighting on the price chart. Disclaimer ⭕️ It is not financial advice, not an investment recommendation, and not affiliated with any financial institution, research firm, or organization of any kind. All content is provided for educational and informational purposes only. Always conduct your own research before making any financial decision.
Pine Script® 인디케이터
AstralVision의
HAP + Sniper Combined trend regime filtering with normalized price positioning. The first component, the EMA Cage, is built using three exponential moving averages (14, 50, and 100 periods). It defines dynamic trend zones based on the relative alignment of short, medium, and long-term EMAs. When the EMAs are aligned upward or downward, the structure highlights directional trend phases through adaptive coloring and band visualization. The second component, the Sniper Band, transforms price behavior into normalized oscillatory values using both range-based and mean-reversion calculations. It compares short-term price distribution against a smoothed percentage deviation from a moving average. These two normalized signals are then mapped back onto the price scale to create a structured dual-band system. The interaction between these two lines defines market state: When both normalized components converge closely, it indicates equilibrium or compression zones. When separation increases, it reflects directional expansion and trend development. Color transitions represent relative dominance between the two normalized measures. This combined structure is designed to visualize both trend direction (EMA Cage) and internal price pressure (Sniper Band) within the same framework, enabling clearer identification of market phases such as consolidation, expansion, and directional bias shifts.
Pine Script® 인디케이터
onderarslantas107의
Index Futures Position Size Calculator with valuesA simple, free position size calculator for CME index futures traders. Click Entry, click Stop Loss, pick your asset, get your contract size instantly. Built for fast NY session execution — no spreadsheets, no manual maths, no noise. ═══════════════════════════════════ ✦ SUPPORTED INSTRUMENTS MNQ · MES · NQ · ES — all CME tick values hardcoded. No manual lookup, no mistakes. ═══════════════════════════════════ ✦ FEATURES → One-click Entry and Stop Loss directly on the chart → Auto 1-handle SL buffer — stop shifts 1 full point beyond your click, protecting against wick hunts → Asset dropdown — correct tick value loads automatically, zero manual entry → Smart rounding — fractional contracts of 0.75 or higher round up, otherwise round down → Green Entry line and Red SL line — both start at your exact click and extend right → Price labels on both lines — confirm your exact adjusted levels instantly → Direction arrow — ▲ Buy or ▼ Sell auto-detected from your Entry and SL position → Live dark panel — asset name, contract size, real USD risk and stop distance, all updating in real time ═══════════════════════════════════ ✦ HOW TO USE Add to chart → click Entry → click Stop Loss → pick asset → set Account Size and Risk %. Read your size from the top-right panel. Three clicks and you are sized. ═══════════════════════════════════ ✦ PROP FIRM CHALLENGE SIZING Two clean methods to work within your max drawdown limit. Method 1 — Loss budget split Divide your max loss by how many consecutive losses you can afford. Enter that result as Account Size with Risk at 100%. Example: $2,000 max loss ÷ 5 losses → Account Size $400, Risk 100% Method 2 — Direct percentage Enter your full max loss as Account Size and set your per-trade risk percentage directly. Example: $2,000 max loss, 20% per trade → Account Size $2,000, Risk 20% Both give the same result — use whichever feels natural. ═══════════════════════════════════ ✦ HOW THIS WAS BUILT Developed step by step through real trading feedback, not theory. Started as a basic calculator with manual tick inputs. Then came the asset dropdown with hardcoded CME values, smart rounding, exact click-point line rendering, the auto 1-handle SL buffer with price labels, real-time USD risk display, stop distance row, and finally a full dark panel redesign with colour-coded values and direction detection. Every feature exists because a real trade needed it. ═══════════════════════════════════ ✦ A NOTE FROM THE AUTHOR Built together with Claude AI through real iterative development. Sharing it free because clean tools should not be locked behind paywalls. No Discord, no course, no affiliate links, nothing to buy. Copy it, modify it, build something better — it is yours. ═══════════════════════════════════ ✦ DISCLAIMER Educational tool only. I do not take any responsibility when you use this indicator in your trading — always check the calculations before use. Futures trading carries substantial risk of loss. Not financial advice. Built with ❤️ by REDz and Claude
Pine Script® 인디케이터
Green_Room의
NQ HMA Midday StrategyThe Story Behind This Strategy This strategy didn't come from a quick backtest or a weekend project. It's the result of months of systematic research across multiple strategy families (DVD, Zscore, HMA) on both NQ and ES futures. My Research Process: I started with six strategy families and ran extensive backtests spanning from 2019 through April 2025, followed by recent validation from 2025 through April 2026. My goal wasn't to maximize historical PnL - it was to identify robust strategies with better drawdown behavior, stronger profit factors, and more stable portfolio-level risk/reward. After evaluating hundreds of parameter combinations and multiple objective functions, I narrowed down to two core NQ candidates. This HMA Midday strategy emerged as one of them because it showed: Strong recent performance (2025-2026: $16,865 profit, 1.53 profit factor) Reasonable drawdown characteristics ($8,940 max drawdown) Clean portfolio behavior when combined with other strategies Better risk-adjusted returns than the baseline HMA version What This Strategy Actually Does: It's a momentum-based system using Hull Moving Averages, EMAs, and Rate of Change to identify trade setups during specific time windows (11:00-15:45 ET trading, 10:30-13:00 ET entries). I added the one-trade-per-day limit after observing that multiple daily entries often degraded risk-adjusted returns. The Honest Truth: This is still a research strategy, not a live-trading system I have a Python version with walk-forward optimization that I use to tune parameters when market regimes change Parameters should be re-optimized periodically - they're not set-and-forget The strategy works best as part of a portfolio, not in isolation Past performance (2019-2026) doesn't guarantee future results Why I'm Publishing It: To share the methodology and code structure with the community. The approach - combining trend indicators with momentum filters, time windows, and ATR-based risk management - is worth studying even if you don't trade this exact configuration. Developer: QuantByBoji Status: Research candidate, not live-trading recommendation
Pine Script™ 전략
QuantByBoji의
XAUUSD Session Range [MatsukazeAlgo]🇬🇧 ENGLISH A session analysis tool optimized for Gold (XAUUSD). Surfaces the relationship between Asia, London, and NY sessions, classifies the daily regime, and shows how NY historically behaves within that context. Built for traders who use ICT-influenced or session-based frameworks. Concepts The 25% Level — Most session-based tools use the midpoint (50%) of a range as the key level. The 25% level is different: it marks the directional commitment zone. On a bullish session, the upper 25% of the body is where price proved it was willing to close strong. If a subsequent session penetrates this zone and recovers, it signals that the directional conviction still holds. If it fails to recover, the structure has shifted. This is the foundation of the wick interaction statistics in the table. Regime Classification — Every trading day, the Asia→London relationship falls into one of five structural patterns. "London Engulfs Asia" means London broke both Asia's high and low — a sign of strong directional intent. "Inside" means London stayed within Asia's range — a compression pattern. The regime determines which historical statistics are shown, because NY behaves differently under each structure. Asia Sweep — On Gold, London frequently takes out Asia's high or low before reversing. This is a liquidity grab: stop orders clustered above/below the Asia range get triggered, providing fuel for the real move. The indicator tracks how often this sweep predicts NY's direction. DXY Inverse Correlation — Gold and the US Dollar Index typically move in opposite directions. When DXY falls, Gold tends to rise. The indicator tracks this correlation historically and displays today's DXY direction as a macro bias filter. How It Works 1. Session Tracking: Asia (18:00–02:00 ET), London (02:00–08:00 ET), and NY (08:00–17:00 ET) OHLC are tracked live and displayed as composite candlesticks to the right of the chart. 2. 25% Level: For each completed session, a direction-aware level is calculated at the upper or lower 25% of the candle body. This marks where price delivery shifts from neutral to committed. 3. Regime Classification: At NY open, the indicator classifies the Asia-to-London relationship into one of five regimes: London Engulfs Asia, Asia Engulfs London, London Partial Up, London Partial Down, or Inside. 4. Stats Table: Historical NY behaviour is filtered by today's regime. NY bullish probability, London High/Low take rates, wick interaction with the London 25% level, and more. Gold-Specific Features Psychological Level Confluence — $50/$100 round-number levels are automatically plotted near price. When a psychological level aligns with a session's 25% level, a ★ CONFL marker appears. Gold respects round numbers. Confluence = higher probability zone. Asia Sweep Statistics — Tracks when London sweeps Asia's high or low, then measures NY's directional response. The stats table shows "Asia H Swept → NY Bull" and "Asia L Swept → NY Bear" probabilities. A core ICT Gold pattern that the original NQ-focused version didn't capture. DXY Inverse Correlation — Real-time DXY direction display in the TODAY section, with historical inverse correlation percentage in the GOLD ANALYSIS section. London Fix Marker — Vertical line at 15:00 GMT (10:00 ET) marking the London Gold Fix. One of the most significant intraday price events for Gold. Range in Pips — Session ranges displayed in pips (Gold standard) rather than points. Togglable in settings. Session Open Markers — Vertical lines at Asia / London / NY open times with configurable colour, style, and labels. These mark session boundaries. They are not trade signals. Alerts 5 alert types: Regime Confirmed (fires at NY open), NY Touches London 25%, London High Taken, London Low Taken, Psych Level Confluence. Set alerts and walk away. Input Reference Setup — Show Session Candle Panel: master toggle for the composite candlestick display. Show Chart Lines: master toggle for H/M/L/O and 25% lines on the chart. Asia / London / NY Session — Each session group contains: Show Candle (on/off), Session Open Line (vertical marker at session start with colour, style, width, and label toggle), H/M/L/O Lines (individual toggles for High, Mid, Low, Open with shared colour, style, width), 25% Level (colour, style, width for the directional commitment line). London Session — additionally includes London Fix Line (vertical marker at 15:00 GMT) and Fix Label toggle, both defaulting to line on / label off. Gold Settings — Psychological Levels: toggle $100 and $50 levels independently with separate transparency. Confluence Distance ($): how close a psych level must be to a 25% level to trigger the ★ marker (default 3.0). DXY Direction: toggle the DXY display in the stats table. Range in Pips: switch between pip display (Gold standard, 1 pip = $0.10) and point display. Stats Table — Show Table, Position (9 positions), Text Size (Tiny/Small/Normal), Text Colour, Title Colour. Lookback: number of historical sessions used for percentage calculations (default 252, roughly one trading year). Alerts — Individual toggles for each of the 5 alert conditions. All default to on. Conclusion XAUUSD Session Range gives Gold traders a structured, data-driven view of how the three major sessions interact. Instead of guessing whether NY will continue or reverse London's move, the stats table shows what happened historically under today's exact regime. The Gold-specific additions — psychological level confluence, Asia sweep tracking, and DXY correlation — layer institutional context that generic session tools miss. Every element is independently configurable and colour-customizable. Recommended timeframe: 1min–15min on XAUUSD. --- Based on Session Range Candles + 25% Level by lucymatos . This version adds Gold psychological level confluence, Asia sweep statistics, DXY inverse correlation, London Fix marker, pip display, alert conditions, and MatsukazeAlgo colour palette. --- 🇯🇵 日本語 ゴールド（XAUUSD）に特化したセッション分析ツールです。東京・ロンドン・NYの3セッション構造を分析し、日々のレジームを分類、NYが過去どのように動いたかを統計的に表示します。ICTやセッションベースのフレームワークを使うトレーダー向け。 コンセプト 25%レベル — 多くのセッションツールはレンジの中間点（50%）を基準にします。25%レベルは異なります。方向性のコミットメントゾーンを示します。強気セッションでは、ボディの上位25%は「価格が強く引けることを証明した場所」です。後続のセッションがこのゾーンに侵入して回復すれば、方向性の確信が継続しています。回復しなければ、構造が変化したということです。テーブルのウィック相互作用統計の基盤です。 レジーム分類 — 毎日、東京→ロンドンの関係が5つの構造パターンのいずれかに分類されます。「London Engulfs Asia」はロンドンが東京の高値と安値の両方を突破したことを意味し、強い方向性の意図を示します。「Inside」はロンドンが東京のレンジ内に留まったことを意味する圧縮パターンです。レジームによって表示される統計が変わります。各構造の下でNYの挙動が異なるためです。 東京スイープ — ゴールドでは、ロンドンが東京の高値/安値を取ってから反転することが頻繁にあります。流動性の掃き出しです。東京レンジの上下に集まったストップオーダーがトリガーされ、本当の動きの燃料になります。このスイープがNYの方向をどの程度予測するかを追跡します。 DXY逆相関 — ゴールドとドルインデックスは通常逆方向に動きます。DXYが下落するとゴールドは上昇する傾向があります。過去の相関率を統計的に追跡し、今日のDXY方向をマクロバイアスフィルターとして表示します。 仕組み 1. セッション追跡：東京（18:00–02:00 ET）、ロンドン（02:00–08:00 ET）、NY（08:00–17:00 ET）のOHLCをリアルタイム追跡。合成ローソク足としてチャート右側に表示。 2. 25%レベル：完了したセッションのローソク足ボディの方向に応じた25%レベルを計算。価格が中立からコミットに切り替わるゾーン。 3. レジーム分類：NYオープン時に、東京→ロンドンの関係を5つのレジームに分類（ロンドンが東京を包み込む、東京がロンドンを包み込む、ロンドン上方部分突破、ロンドン下方部分突破、インサイド）。 4. 統計テーブル：今日のレジームでフィルタリングされたNYの過去の挙動を表示。NY強気確率、ロンドン高値/安値テイク率、ロンドン25%レベルとのウィック相互作用統計など。 ゴールド専用機能 心理的価格帯の合流 — $50/$100のラウンドナンバーを価格付近に自動表示。セッションの25%レベルと心理的価格が近接すると★ CONFLマーカーが出現。ゴールドはラウンドナンバーを強くリスペクトします。合流 = 高確率ゾーン。 東京スイープ統計 — ロンドンが東京の高値/安値をスイープした後、NYがどの方向に動くかの確率を統計テーブルに表示。元のNQ向けバージョンにはなかったICTゴールドの重要パターン。 DXY逆相関 — TODAY欄にDXY方向のリアルタイム表示。GOLD ANALYSIS欄に過去の逆相関率を表示。 ロンドンフィックスマーカー — 15:00 GMT（10:00 ET）に縦線を表示。ゴールドの最も重要な日中イベントの一つ。 pips表示 — セッションレンジをゴールド標準のpips単位で表示。設定で切替可能。 セッション開始マーカー — 東京/ロンドン/NYの開始時刻に縦線を表示。セッション境界のマーカーであり、売買シグナルではありません。色・スタイル・ラベルは設定で変更可能。 アラート 5種類：レジーム確定（NYオープン時）、NY 25%タッチ、ロンドン高値突破、ロンドン安値割れ、心理的価格合流。アラートを設定してチャートから離れられます。 入力パラメータ 設定 — セッションキャンドルパネル表示：合成ローソク足のマスタートグル。チャートライン表示：H/M/L/Oと25%ラインのマスタートグル。 東京/ロンドン/NYセッション — 各グループ：キャンドル表示、セッション開始ライン（色・スタイル・太さ・ラベル）、H/M/L/Oライン（High/Mid/Low/Openの個別トグル、共有色・スタイル・太さ）、25%レベル（色・スタイル・太さ）。 ロンドンセッション — 追加でロンドンフィックスライン（15:00 GMT）とラベルトグル。デフォルトはラインON / ラベルOFF。 ゴールド設定 — 心理的価格帯：$100と$50レベルを個別にトグル、透明度別設定。合流距離（$）：★マーカーのトリガー距離（デフォルト3.0）。DXY方向：統計テーブルのDXY表示トグル。pips表示：pip表示（1 pip = $0.10）とポイント表示の切替。 統計テーブル — テーブル表示、位置（9か所）、文字サイズ（Tiny/Small/Normal）、文字色、タイトル色。ルックバック：統計計算に使用する過去のセッション数（デフォルト252、約1取引年分）。 アラート — 5種類のアラート条件それぞれに個別トグル。すべてデフォルトON。 まとめ XAUUSD Session Rangeは、ゴールドトレーダーに3セッションの相互作用をデータに基づいて分析する構造化されたビューを提供します。NYがロンドンの動きを継続するか反転するかを推測する代わりに、今日のレジームの下で過去に何が起きたかを統計テーブルで確認できます。心理的価格帯の合流、東京スイープ追跡、DXY相関というゴールド固有の機能は、汎用的なセッションツールでは見えない機関投資家の文脈を重ねます。すべての要素は独立して設定・色変更が可能です。 推奨時間足：1分〜15分（XAUUSD） --- Based on Session Range Candles + 25% Level by lucymatos . 心理的価格帯の合流検出、東京スイープ統計、DXY逆相関、ロンドンフィックスマーカー、pips表示、アラート、MatsukazeAlgoカラーパレットを追加。
Pine Script® 인디케이터
MatsukazeAlgo의
Takas Laguerre + TRIX +/- (Onder Edition Final)Takas Laguerre + TRIX +/- (Onder Edition Final) is a multi-factor momentum and volatility-based oscillator designed to analyze trend strength, directional pressure, and short-term reversal conditions. The indicator combines four independent analytical components: 🔹 Volatility Pressure (WVF-style Fear Model) A volatility-weighted structure derived from the relationship between price highs and lows over a defined lookback period. It is used to approximate short-term market stress and expansion phases. 🔹 TRIX Momentum Core A triple-smoothed exponential moving average system is used to generate a momentum oscillator. The difference between the final smoothed value and its prior value defines directional momentum (TRIX momentum). An additional strength filter compares momentum magnitude against its historical average to identify stronger trend phases. 🔹 Stochastic Reversal Signals A smoothed stochastic oscillator is used to detect short-term reversal conditions. Crossovers between %K and %D are used as timing triggers for potential directional shifts. 🔹 ADX Trend Strength Filter A directional movement-based ADX implementation measures trend strength and filters out weak or non-trending market conditions. Only signals occurring in higher trend-strength environments are considered valid. 📊 Signal Logic Bullish (+ Signal) occurs when: Stochastic %K crosses above %D ADX indicates sufficient trend strength TRIX momentum is positive Momentum strength exceeds its adaptive threshold Bearish (- Signal) occurs when: Stochastic %K crosses below %D ADX confirms trend presence TRIX momentum is negative Momentum strength confirms directional expansion 📈 Visualization The histogram represents TRIX momentum around a zero baseline, highlighting directional expansion and contraction phases. Color intensity reflects momentum strength conditions. Signal markers are plotted at the zero level to indicate potential directional shifts under confirmed trend conditions. ⚙️ Purpose This indicator is designed to combine momentum structure, volatility pressure, and trend confirmation into a single analytical framework for improved market phase recognition and timing precision.
Pine Script® 인디케이터
onderarslantas107의
Futures/Cash/ETF Levels Converter - ES/SPX/SPY and NQ/NDX/QQQFutures / Cash / ETF Levels Converter This indicator displays a real-time conversion table that maps cash index levels to their equivalent futures and ETF prices — helping you instantly read levels across instruments without doing the math manually. Supports two modes, switchable directly from the settings: ES / SPX / SPY — S&P 500 complex NQ / NDX / QQQ — Nasdaq 100 complex Since all prices are fetched via request.security, the indicator works correctly on any chart symbol — you don't need to be on the ES or NQ chart for it to display accurate values. Key features: Live basis (Futures − Cash) with configurable update frequency (1m, 2m, 3m, 5m, 10m, 15m, 30m, 1h, Daily) Adjustable row step and number of rows above/below current price Nearest price row highlighting (toggleable) Fully customizable column layout — choose the position of each column independently (Cash, Futures, ETF, Δ Basis) Show/hide controls for the ETF column, Δ Basis column, and Basis Info row Table position (Top/Bottom, Left/Right) and full color customization Free to use. Feedback and suggestions are welcome.
Pine Script® 인디케이터
rix_serk의
Bootstrap Confidence Break [forexobroker]Bootstrap Confidence Break flags bars whose return falls outside a 90 percent confidence interval on the rolling mean return. The CI uses the standard-error formulation that is asymptotically equivalent to the percentile bootstrap when N >= 30, but is fully deterministic — no random number generation, no repainting. Signals fire on EMA cross when the move is statistically significant. 🔶 ALGORITHM 1. r = close - close (single-bar return). 2. mu = sma(r, N); sd = stdev(r, N); se = sd / sqrt(N). 3. CI high = mu + 1.645 * se; CI low = mu - 1.645 * se (90 percent two-sided). 4. Outside-up regime when r > CI_high; outside-down when r < CI_low. 🔶 SIGNAL LOGIC - Buy: outside-up AND close crosses EMA up AND not already long AND cooldown elapsed AND barstate.isconfirmed. - Sell: outside-down AND close crosses EMA down. - Position-lock state machine. 🔶 INPUTS - Return Window (default 40) - Pullback EMA Length (default 8) - Cooldown Bars (default 4) - Visual: dashboard, glow, EMA toggle, buy / sell colors 🔶 ALERTS BCB Buy, BCB Sell, BCB Any Signal, BCB Outside Up, BCB Outside Down, BCB EMA Up, BCB EMA Down, BCB 2-Sigma, BCB Webhook JSON. 🔶 LIMITATIONS - Standard-error CI assumes approximately normal returns; heavy-tailed distributions widen the true tail risk and make this more conservative than a true percentile bootstrap. - 90 percent interval is a reasonable default; adjust the multiplier (1.645) for stricter or looser cutoffs by editing the script. - Signal cadence depends entirely on volatility regime; quiet markets produce few outside-CI bars. - Combining CI break with EMA cross dampens whipsaws but slightly delays entry vs raw CI break.
Pine Script® 인디케이터
forexobroker의
GBM Projection Cone (Ito)GBM Projection Cone (Itō) A geometric Brownian motion probability cone derived analytically from Itō's lemma — no random simulation required, no path-to-path variance, identical output on every reload. The cone shows where price should be in the future under a GBM model fitted to the recent log-return distribution. The output is three concentric ±σ bands (68%, 95%, 99.7%), the arithmetic-mean path, and the Itō-corrected median path. The visible gap between mean and median is the Jensen gap — the systematic divergence that pure-arithmetic forecasting hides and lognormal compounding requires you to acknowledge. How it works Applying Itō's lemma to f(S, t) = ln(S): d(ln S) = (μ − σ²/2) dt + σ dW so under GBM the log-price is normally distributed: ln(S_t) ~ N(ln S₀ + (μ − σ²/2)·t, σ²·t) Drift μ and volatility σ are estimated from the most recent N bars of log-returns (sample mean and sample standard deviation). Percentile bands at ±kσ come straight out of the normal CDF in log-space and exponentiate back to price-space, giving the asymmetric cone characteristic of GBM. Two center lines are computed because they answer different questions: Arithmetic mean path — E = S₀·exp(μ·t). The ensemble average across all GBM paths. Itō-corrected median path — S₀·exp((μ − σ²/2)·t). The most probable single trajectory. The mean is always above the median by Jensen's inequality, with the gap widening as volatility rises. Both are plotted so the gap is always visible. An optional Monte Carlo overlay simulates independent GBM paths via Box-Muller normal sampling. It's there for pedagogical comparison against the closed form, not for production analysis — Monte Carlo paths re-roll on every reload. Off by default. How to read it The cone shows the analytical confidence regions of the projected price distribution: ±1σ (68.3%) — the central body of likely outcomes ±2σ (95.4%) — out to the edge of normal-regime expectations ±3σ (99.7%) — beyond which an excursion would be unusually extreme under the assumed GBM dynamics Inner bands are drawn thicker and more saturated; outer bands are thin and translucent. Endpoint labels at the right edge mark the projected price at each ±σ level at the cone's terminal bar. The two center paths — mean (default amber) and median (default off-white) — diverge as time and volatility accumulate. Reading the divergence: a wide Jensen gap means the asset is in a high-volatility regime where ensemble-average forecasts overstate where any individual trajectory is likely to land. The median is the more honest answer for a single realised path. The bottom-right parameter table reports estimated μ, σ, the Itō correction (−σ²/2), and the resulting Itō drift (μ − σ²/2). When the Itō drift turns negative while μ is still positive, volatility drag is overwhelming directional drift — the asset is positive-EV in expectation but negative-EV in the most-probable case. Inputs Estimation window — bars used to estimate μ and σ from observed log-returns. Default 20. Smaller windows track the recent regime; larger smooth out noise. Projection bars — how many bars ahead to project. Default 20. Cone width grows with σ√t — longer horizons fan out faster under high volatility. Bands — toggle ±1σ, ±2σ, ±3σ independently. Defaults: 1σ and 2σ on, 3σ off. Mean path — show the arithmetic expected-value path. Default on. Median path — show the Itō-corrected median path. Default on. Endpoint labels — price labels at the right edge of each band. Default on. Parameter table — bottom-right μ/σ/Itō readout. Default on. Monte Carlo overlay — draw N random GBM realisations for comparison. Default off, non-deterministic. Path count — number of MC paths when overlay is on. Default 20. Colors — cone, mean path, median path. Built-in alerts Volatility spike — σ rises above 1.5× its rolling average Drift turned negative — μ crosses below zero Drift turned positive — μ crosses above zero Itō drift crossed below zero — μ − σ²/2 turns negative (volatility drag now outpaces drift) Itō drift crossed above zero — μ − σ²/2 recovers above zero The Itō-drift alerts are the more practically useful pair. A positive arithmetic μ with negative Itō drift describes the textbook scenario where a volatile asset has positive expected return but a negative typical return — the regime where naïve EV calculations mislead position sizing. Notes GBM is a model. Real returns aren't truly lognormal — they exhibit fat tails, autocorrelation, and volatility clustering that GBM's i.i.d. assumption can't capture. The cone is calibrated to what the recent N bars would project forward if returns continued behaving as estimated; the more the underlying violates the model's assumptions, the less the cone reflects realised probabilities. That said, GBM remains useful as a baseline. Most options-pricing intuition, microstructure tooling, and risk-management frameworks assume GBM-like dynamics. The cone gives you the model's own opinion about where price is likely to go — informative even when the model is wrong, because the direction and magnitude of disagreement between cone and realised price is itself signal. The closed-form derivation is deterministic on purpose. Two reloads of the same chart produce identical cones; two reloads with the Monte Carlo overlay produce visibly different paths. For production analysis, leave Monte Carlo off. To teach yourself how MC converges to the closed form, turn it on and watch the random paths fill the bands as you increase path count. The Itō correction (−σ²/2) is small for low-volatility assets and dominant for high-volatility ones. On a daily chart of a major equity index it's a fraction of a basis point per day; on a high-frequency crypto chart it can outweigh the directional drift entirely. The parameter table makes this visible. This is a diagnostic tool, not a signal generator. It tells you what GBM thinks the next N bars look like. Five years of work on a trading system left me with dozens of indicators that ultimately didn't earn a place in the final build. They're not failures — they're tools that solved problems I no longer needed solved. So instead of shelving them, I'm publishing the majority of them open-source. If you're a discretionary trader, take what's useful. If you're a systems builder, the source is yours to dissect, modify, and improve. The best return on five years of work is for it to keep working — for someone. If you use this script — or part of it — in your own work, please credit the original with a link back to my profile. Note: these indicators have been updated to Pine Script v6 — some manually, some with AI assistance.
Pine Script® 인디케이터
TradeSymbiotic의
iFCPO MYR ContextiFCPO MYR Context — USDMYR strength gauge + 30-day FCPO↔USDMYR correlation flag for Bursa Crude Palm Oil Futures. WHY IT MATTERS The Malaysian ringgit drives FCPO export competitiveness. Soft MYR (USDMYR rising) makes Malaysian palm oil cheaper for foreign buyers — bullish FCPO. Strong MYR (USDMYR falling) hurts exporters — bearish FCPO. But the FCPO/MYR relationship isn't always live: when correlation is decoupled (|r| < 0.3), the MYR signal is noise. This indicator gauges both USDMYR strength AND tells you when to listen. HOW TO USE - USDMYR > 30-day MA by +0.5%: Soft MYR — FCPO tailwind (bullish bias) - USDMYR < 30-day MA by −0.5%: Strong MYR — FCPO headwind (bearish bias) - |corr| > 0.5: Relationship is live — apply MYR bias - |corr| < 0.3: Decoupled — IGNORE the MYR signal entirely This is a SIZE / SL MODIFIER — it adjusts conviction, not entries. Pair with iFCPO Wick Hunter (entries) + iFCPO Regime Meter (regime) + iFCPO Session Law (timing). KPIs - Lookback: 30 daily bars (configurable) - Strong correlation threshold: |r| ≥ 0.5 - Default symbol: FX_IDC:USDMYR (free TV symbol) OUTPUTS USDMYR daily, % deviation vs 30-day MA, 30-day FCPO↔USDMYR correlation, color-graded line (green soft / red strong / grey neutral), full status table top-right (USDMYR, deviation %, correlation strength, bias, pair-with). Open-source. Part of the iFCPO free hero stack.
Pine Script® 인디케이터
TraderJalanan_의
iFCPO Soyoil SpreadiFCPO Soyoil Spread — z-score divergence between FCPO (Bursa Crude Palm Oil Futures) and CBOT soybean oil (ZL/BO). WHY IT MATTERS FCPO and soybean oil are 0.85+ correlated long-run (substitute oils in the global vegetable-oil complex). When the FCPO/BO ratio z-score blows out beyond ±2σ over a 50-day lookback, FCPO is statistically rich or cheap vs the global benchmark. Mean-reversion bias kicks in. HOW TO USE - z > +2: FCPO over-extended vs BO — bias short / fade longs - z < −2: FCPO cheap vs BO — bias long / fade shorts - |z| < 1: ignore — pairs are tracking normally - 1 < |z| < 2: stretched, watch for reversal This is a CONTEXT layer — it modifies conviction. NEVER trade z alone. Pair with iFCPO Wick Hunter (entries) + iFCPO Regime Meter (regime) + iFCPO Session Law (timing). KPIs - Lookback: 50 daily bars (configurable) - Extreme threshold: ±2σ (configurable) - Symbol: CBOT:ZL1! (TradingView's continuous front-month soybean oil) OUTPUTS Dimensionless ratio z (FCPO close / BO close), mean / ±1σ / ±2σ hlines, color-graded line (red rich / green cheap / amber stretched), tinted background at extremes, full status table top-right (FCPO, BO, z, state, pair-with). Open-source. Part of the iFCPO free hero stack.
Pine Script® 인디케이터
TraderJalanan_의