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Dskyz (DAFE) GENESIS Dskyz (DAFE) GENESIS: Adaptive Quant, Real Regime Power Let’s be honest: Most published strategies on TradingView look nearly identical—copy-paste “open-source quant,” generic “adaptive” buzzwords, the same shallow explanations. I’ve even fallen into this trap with my own previously posted strategies. Not this time. What Makes This Unique GENESIS is not a black-box mashup or a pre-built template. It’s the culmination of DAFE’s own adaptive, multi-factor, regime-aware quant engine—built to outperform, survive, and visualize live edge in anything from NQ/MNQ to stocks and crypto. True multi-factor core: Volume/price imbalances, trend shifts, volatility compression/expansion, and RSI all interlock for signal creation. Adaptive regime logic: Trades only in healthy, actionable conditions—no “one-size-fits-all” signals. Momentum normalization: Uses rolling, percentile-based fast/slow EMA differentials, ALWAYS normalized, ALWAYS relevant—no “is it working?” ambiguity. Position sizing that adapts: Not fixed-lot, not naive—not a loophole for revenge trading. No hidden DCA or pyramiding—what you see is what you trade. Dashboard and visual system: Directly connected to internal logic. If it’s shown, it’s used—and nothing cosmetic is presented on your chart that isn’t quantifiable. 📊 Inputs and What They Mean (Read Carefully) Maximum Raw Score: How many distinct factors can contribute to regime/trade confidence (default 4). If you extend the quant logic, increase this. RSI Length / Min RSI for Shorts / Max RSI for Longs: Fine-tunes how “overbought/oversold” matters; increase the length for smoother swings, tighten floors/ceilings for more extreme signals. ⚡ Regime & Momentum Gates Min Normed Momentum/Score (Conf): Raise to demand only the strongest trends—your filter to avoid algorithmic chop. 🕒 Volatility & Session ATR Lookback, ATR Low/High Percentile: These control your system’s awareness of when the market is dead or ultra-volatile. All sizing and filter logic adapts in real time. Trading Session (hours): Easy filter for when entries are allowed; default is regular trading hours—no surprise overnight fills. 📊 Sizing & Risk Max Dollar Risk / Base-Max Contracts: All sizing is adaptive, based on live regime and volatility state—never static or “just 1 contract.” Control your max exposures and real $ risk. ATR will effect losses in high volatility times. 🔄 Exits & Scaling Stop/Trail/Scale multipliers: You choose how dynamic/flexible risk controls and profit-taking need to be. ATR-based, so everything auto-adjusts to the current market mode. Visuals That Actually Matter Dashboard (Top Right): Shows only live, relevant stats: scoring, status, position size, win %, win streak, total wins—all from actual trade engine state (not “simulated”). Watermark (Bottom Right): Momentum bar visual is always-on, regime-aware, reflecting live regime confidence and momentum normalization. If the bar is empty, you’re truly in no-momentum. If it glows lime, you’re riding the strongest possible edge. *No cosmetics, no hidden code distractions. Backtest Settings Initial capital: $10,000 Commission: Conservative, realistic roundtrip cost: 15–20 per contract (including slippage per side) I set this to $25 Slippage: 3 ticks per trade Symbol: CME_MINI:NQ1! Timeframe: 1 min (but works on all timeframes) Order size: Adaptive, 1–3 contracts No pyramiding, no hidden DCA Why these settings? These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for NQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions. Why It Wins While others put out “AI-powered” strategies with little logic or soul, GENESIS is ruthlessly practical. It is built around what keeps traders alive: - Context-aware signals, not just patterns - Tight, transparent risk - Inputs that adapt, not confuse - Visuals that clarify, not distract - Code that runs clean, efficient, and with minimal overfitting risk (try it on QQQ, AMD, SOL, etc. out of the box) Disclaimer (for TradingView compliance): Trading is risky. Futures, stocks, and crypto can result in significant losses. Do not trade with funds you cannot afford to lose. This is for educational and informational purposes only. Use in simulation/backtest mode before live trading. No past performance is indicative of future results. Always understand your risk and ownership of your trades. This will not be my last—my goal is to keep raising the bar until DAFE is a brand or I’m forced to take this private. Use with discipline, use with clarity, and always trade smarter. — Dskyz , powered by DAFE Trading Systems.
Strategi Pine Script®
oleh DskyzInvestments
5
FMCB – Ultimate Quant StrategyA Proprietary Long-Term Alpha Model for Institutional-Grade Index Exposure Overview FMCB (Fractal Momentum Compression Breakout) is a high-performance, long-term trading strategy exclusively optimized for SPX500 and E-mini S&P 500 Futures (ES). It is designed to capture large directional moves by identifying the precise moment when fractal compression, volume exhaustion, and momentum inflection converge—often ahead of major institutional moves. This strategy was born out of a personal frustration with unreliable retail signals and short-term noise. After years of development and live market testing, FMCB has demonstrated high win consistency and asymmetric reward-to-risk performance in trending environments. Core Philosophy At its heart, FMCB is a volatility-sensing, breakout-driven strategy that leverages a multi-layered system of: RSI Momentum Thresholds Dynamic Fractal Compression Windows Volume Spike Confirmation Breakout Range Expansion Filters ATR-based Risk Positioning These signals are not used in isolation. Instead, they are fused into a cohesive decision framework that only triggers trades when multiple market forces align—minimizing whipsaws and false positives. Why SPX500 and ES Futures Only? FMCB is deeply calibrated for the microstructure and volatility rhythm of US large-cap index futures. The SPX500 and ES markets demonstrate predictable breakout behavior and institutional footprint patterns, making them ideal for this strategy. It is not recommended for FX, crypto, or commodities, where the volatility curves and liquidity cycles differ substantially. Key Components 1. RSI Momentum Filter RSI Length: 12 Buy zone: Above 65 Sell zone: Below 35 Used to gauge exhaustion in directional bias 2. Breakout Window Customizable from 10 to 50 bars Measures high-low range compression before a move Only enters trades when the current range is narrower than X% of prior N bars 3. Volume Spike Multiplier Filters breakout traps by requiring volume to exceed average by a factor of 2.0 Helps detect real participation behind price 4. ATR-Based Stop Sizing Risk is dynamically sized as a function of ATR Ensures risk remains sustainable and adapts to market volatility 5. Equity Allocation Engine Built-in dynamic position sizing to adjust exposure based on equity curve slope Designed for compounding long-term results without over-leverage How to Use Apply only on SPX500 or ES Futures charts on 1H, 4H, or Daily timeframes. Load default settings before tweaking for optimization. Use a minimum account capital of $10,000 USD, with 1–2% max equity risk per trade. Allow a large dataset (100+ trades) for statistically meaningful results. View trades in strategy tester with realistic slippage (1 tick) and $2.50 per-contract commission (ES). Backtesting Notes Commission: $2.50 per contract Slippage: 1 Initial Capital: $10,000 Default Position Size: 100% of allocated capital (position scaling is adaptive) This strategy does not overtrade. It enters when conviction is high, typically a few times per month per instrument. Its edge is not frequency—it is precision. What Makes FMCB Original FMCB does not rely on generic crossovers, MA triggers, or candle patterns. It uses a multi-layered, signal fusion model that compresses multiple dimensions (price, volume, volatility, and momentum) into a single trigger point. This makes it especially suitable for institutional swing systems, hedge fund models, and long-term prop firm accounts. Unlike many scripts on TradingView, FMCB was not built for quick thrills or backtest fantasies—it was designed to deploy capital in real markets and generate reliable returns with controlled risk. Disclaimer This strategy is provided for educational and informational purposes only. Historical performance does not guarantee future returns. Always use proper risk management. Final Thoughts The markets don’t reward noise. They reward conviction backed by logic, discipline, and timing. FMCB was developed with this truth in mind. If you're serious about mastering the SPX500 or ES and want a quant-tested, low-noise, high-conviction breakout strategy, FMCB might just be the edge you're looking for. Let the world know: FMCB is live.
Strategi Pine Script®
oleh Wavervanir_International_LLC
REVELATIONS (VoVix - PoC) REVELATIONS (VoVix - POC): True Regime Detection Before the Move Let’s not sugarcoat it: Most strategies on TradingView are recycled—RSI, MACD, OBV, CCI, Stochastics. They all lag. No matter how many overlays you stack, every one of these “standard” indicators fires after the move is underway. The retail crowd almost always gets in late. That’s never been enough for my team, for DAFE, or for anyone who’s traded enough to know the real edge vanishes by the time the masses react. How is this different? REVELATIONS (VoVix - POC) was engineered from raw principle, structured to detect pre-move regime change—before standard technicals even light up. We built, tested, and refined VoVix to answer one hard question: What if you could see the spike before the trend? Here’s what sets this system apart, line-by-line: o True volatility-of-volatility mathematics: It’s not just "ATR of ATR" or noise smoothing. VoVix uses normalized, multi-timeframe v-vol spikes, instantly detecting orderbook stress and "outlier" market events—before the chart shows them as trends. o Purist regime clustering: Every trade is enabled only during coordinated, multi-filter regime stress. No more signals in meaningless chop. o Nonlinear entry logic: No trade is ever sent just for a “good enough” condition. Every entry fires only if every requirement is aligned—local extremes, super-spike threshold, regime index, higher timeframe, all must trigger in sync. o Adaptive position size: Your contracts scale up with event strength. Tiny size during nominal moves, max leverage during true regime breaks—never guesswork, never static exposure. o All exits governed by regime decay logic: Trades are closed not just on price targets but at the precise moment the market regime exhausts—the hardest part of systemic trading, now solved. How this destroys the lag: Standard indicators (RSI, MACD, OBV, CCI, and even most “momentum” overlays) simply tell you what already happened. VoVix triggers as price structure transitions—anyone running these generic scripts will trade behind the move while VoVix gets in as stress emerges. Real alpha comes from anticipation, not confirmation. The visuals only show what matters: Top right, you get a live, live quant dashboard—regime index, current position size, real-time performance (Sharpe, Sortino, win rate, and wins). Bottom right: a VoVix "engine bar" that adapts live with regime stress. Everything you see is a direct function of logic driving this edge—no cosmetics, no fake momentum. Inputs/Signals—explained carefully for clarity: o ATR Fast Length & ATR Slow Length: These are the heart of VoVix’s regime sensing. Fast ATR reacts to sharp volatility; Slow ATR is stability baseline. Lower Fast = reacts to every twitch; higher Slow = requires more persistent, “real” regime shifts. Tip: If you want more signals or faster markets, lower ATR Fast. To eliminate noise, raise ATR Slow. o ATR StdDev Window: Smoothing for volatility-of-volatility normalization. Lower = more jumpy, higher = only the cleanest spikes trigger. Tip: Shorten for “jumpy” assets, raise for indices/futures. o Base Spike Threshold: Think of this as your “minimum event strength.” If the current move isn’t volatile enough (normalized), no signal. Tip: Higher = only biggest moves matter. Lower for more signals but more potential noise. o Super Spike Multiplier: The “are you sure?” test—entry only when the current spike is this multiple above local average. Tip: Raise for ultra-selective/swing-trading; lower for more active style. Regime & MultiTF: o Regime Window (Bars): How many bars to scan for regime cluster “events.” Short for turbo markets, long for big swings/trends only. o Regime Event Count: Only trade when this many spikes occur within the Regime Window—filters for real stress, not isolated ticks. Tip: Raise to only ever trade during true breakouts/crashes. o Local Window for Extremes: How many bars to check that a spike is a local max. Tip: Raise to demand only true, “clearest” local regime events; lower for early triggers. o HTF Confirm: Higher timeframe regime confirmation (like 45m on an intraday chart). Ensures any event you act on is visible in the broader context. Tip: Use higher timeframes for only major moves; lower for scalping or fast regimes. Adaptive Sizing: o Max Contracts (Adaptive): The largest size your system will ever scale to, even on extreme event. Tip: Lower for small accounts/conservative risk; raise on big accounts or when you're willing to go big only on outlier events. o Min Contracts (Adaptive): The “toe-in-the-water.” Smallest possible trade. Tip: Set as low as your broker/exchange allows for safety, or higher if you want to always have meaningful skin in the game. Trade Management: o Stop %: Tightness of your stop-loss relative to entry. Lower for tighter/safer, higher for more breathing room at cost of greater drawdown. o Take Profit %: How much you'll hold out for on a win. Lower = more scalps. Higher = only run with the best. o Decay Exit Sensitivity Buffer: Regime index must dip this far below the trading threshold before you exit for “regime decay.” Tip: 0 = exit as soon as stress fails, higher = exits only on stronger confirmation regime is over. o Bars Decay Must Persist to Exit: How long must decay be present before system closes—set higher to avoid quick fades and whipsaws. Backtest Settings Initial capital: $10,000 Commission: Conservative, realistic roundtrip cost: 15–20 per contract (including slippage per side) I set this to $25 Slippage: 3 ticks per trade Symbol: CME_MINI:NQ1! Timeframe: 1 min (but works on all timeframes) Order size: Adaptive, 1–3 contracts No pyramiding, no hidden DCA Why these settings? These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for NQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions. Tip: Set to 1 for instant regime exit; raise for extra confirmation (less whipsaw risk, exits held longer). ________________________________________ Bottom line: Tune the sensitivity, selectivity, and risk of REVELATIONS by these inputs. Raise thresholds and windows for only the best, most powerful signals (institutional style); lower for activity (scalpers, fast cryptos, signals in constant motion). Sizing is always adaptive—never static or martingale. Exits are always based on both price and regime health. Every input is there for your control, not to sell “complexity.” Use with discipline, and make it your own. This strategy is not just a technical achievement: It’s a statement about trading smarter, not just more. * I went back through the code to make sure no the strategy would not suffer from repainting, forward looking, or any frowned upon loopholes. Disclaimer: Trading is risky and carries the risk of substantial loss. Do not use funds you aren’t prepared to lose. This is for research and informational purposes only, not financial advice. Backtest, paper trade, and know your risk before going live. Past performance is not a guarantee of future results. Expect more: We’ll keep pushing the standard, keep evolving the bar until “quant” actually means something in the public code space. Use with clarity, use with discipline, and always trade your edge. — Dskyz , for DAFE Trading Systems
Strategi Pine Script®
oleh DskyzInvestments
2
±1% Close BandsBreaking Bad - Walt vs. Jesse Scene: Walter (Bryan Cranston) rages at Jesse (Aaron Paul) over Krazy-8 and Jesse's habit. BUY THE SERIES: www.fandangonow.com Watch the best Breaking Bad scenes: • Breaking Bad | TV Scenes | Rotten Tom... US Air Date: 2008 Network: AMC Starring: Aaron Paul, Bryan Cranston Director: Adam Bernstein © Sony ► Learn more about this show on Rotten Tomatoes: www.rottentomatoes.com #BreakingBad What to Watch Next: ► Certified Fresh TV: bit.ly ► Top TV Dramas: bit.ly ► Most Anticipated Shows: bit.ly ► TV Shows by Channel & Streaming Platform: bit.ly More Rotten Tomatoes: ► Subscribe to ROTTEN TOMATOES TV: bit.ly ► Subscribe to the ROTTEN TOMATOES NEWSLETTER: www.rottentomatoes.com ► Follow us on TWITTER: bit.ly ► Like us on FACEBOOK: bit.ly ► Follow us on INSTAGRAM: bit.ly Rotten Tomatoes TV delivers Fresh TV at a click! Subscribe now for the best trailers, clips, sneak peeks, and binge guides for shows you love and the upcoming series and TV movies that should be on your radar.
Penunjuk Pine Script®
oleh danielsong2401
Deviation over Deviation (DoD) (DAFE) Deviation over Deviation (DoD) Let’s call it out: The vast majority of “volatility” tools on TradingView are just new wrappers on old math—ATR, bands, and basic deviation, all chasing the same tired after-the-fact moves. They’re built to describe the aftermath, not the ignition. If you’re still relying on these, you’re trading in the rearview mirror while the real edge is already gone. That’s not our game, and it shouldn’t be yours. Deviation over Deviation (DoD) is built for one purpose: To expose the hidden regime shifts—the moments when volatility itself becomes volatile, when the market’s “normal” deviation is no longer normal, and when the next move is about to erupt. This isn’t just another overlay. This is a quant-grade anomaly detector, engineered to show you the probability surface before the crowd even knows it’s changed. What sets this apart: Deviation over Deviation (DoD): Not just “how much did price move,” but “how unusual is the current volatility compared to its own history?” This is the Z-score of Z-scores—a true rarity detector for market stress, lull, or impending breakout. VoVix Integration: Select VoVix as your source and you’re not just tracking price, but the volatility of volatility—the same math that powers institutional regime models. This is the edge that front-runs the move, not follows it. Multi-Timeframe Comparative Engine: Instantly compare current and higher timeframe DoD Z-scores. See when the micro and macro regimes align—or when they’re about to collide. Professional, Adaptive Dashboard: No cosmetic fluff, always showing you the real quant state: current DoD Z, HTF DoD Z, and regime warnings. Every color, every plot, every signal is a direct function of the logic—no distractions, no lag. How this destroys the lag: Standard deviation, ATR, and “volatility bands” are always late. They tell you what just happened. DoD and VoVix show you when the nature of volatility itself is changing—when the market is about to leave the old regime behind. This is the difference between trading the past and trading the future. Inputs/Signals—explained for clarity: Deviation Lookback & DoD Lookback: Control the sensitivity and selectivity of the regime detector. Shorter = more signals, longer = only the rarest events. Source Selection: Choose from price, volume, volatility, or VoVix. Each source gives you a different lens on market stress. VoVix is for those who want to see the “regime quake” before the aftershocks. HTF (Comparative Timeframe): Set your higher timeframe for macro regime confirmation. When both DoD Z-scores align, you’re seeing a true market inflection. VoVix Parameters: Fine-tune the volatility-of-volatility engine for your market. Lower ATR Fast = more responsive; higher ATR Slow = more selective. Adjust for your asset, your timeframe, your edge. Bottom line: This isn’t just another “volatility” script. This is a regime anomaly detector, built for traders who want to anticipate, not react. Every input is there for a reason. Every plot is a direct readout of the quant logic. Use it to filter your entries, to time your exits, or to simply see the market’s hidden structure in real time. Disclaimer: Trading is risky. This script is for research and informational purposes only, not financial advice. Backtest, paper trade, and know your risk before going live. Past performance is not a guarantee of future results. *Updated the Dashboard/Metrics Display for better visibility Use with discipline. Trade your edge. — Dskyz, for DAFE Trading Systems
Penunjuk Pine Script®
oleh DskyzInvestments
(DAFE) DEVMA - Crossover (Deviation Moving Average) (DAFE) DEVMA - Crossover (Deviation Moving Average) Let’s keep pushing the edge. After the breakthrough of Deviation over Deviation (DoD)—which gave traders a true lens into volatility’s hidden regime shifts—many asked: “What’s next?” The answer is DEVMA: a crossover engine built not on price, but on the heartbeat of the market itself. Why is this different? DEVMA isn’t just a moving average crossover. It’s a regime detector that tracks the expansion and contraction of deviation—giving you a real-time readout of when the market’s energy is about to shift. This is the next step for anyone who wants to anticipate volatility, not just react to it. What sets DEVMA apart: Volatility-First Logic:Both fast and slow lines are moving averages of deviation, not price. You’re tracking the market’s “energy,” not just its direction. This is the quant edge that most scripts miss. Regime-Colored Lines: The fast and slow DEVMA lines change color in real time—green/aqua for expansion, maroon/orange for contraction—so you can see regime shifts at a glance. Quant-Pro Visuals: Subtle glow, clean cross markers, and a minimalist dashboard keep your focus on what matters: the regime, not the noise. Static Regime Thresholds: Reference lines at 1.5 and 0.5 (custom colors) give you instant context for “normal” vs. “extreme” volatility states. No Price Chasing: This isn’t about following price. It’s about anticipating the next volatility regime—before the crowd even knows what’s coming. How this builds on DoD: DoD showed you when volatility itself was about to change. DEVMA takes that insight and turns it into a crossover engine—so you can see, filter, and act on regime shifts in real time. If DoD was the radar, DEVMA is the navigation system. Inputs/Signals—explained for clarity: Deviation Lookback: Controls the sensitivity of the regime detector. Shorter = more signals, longer = only the rarest events. Fast/Slow DEVMA Lengths: Fine-tune how quickly the regime lines react. Fast for scalping, slow for swing trading. Source Selection: Choose from price, volume, volatility, or VoVix. Each source gives you a different lens on market stress. VoVix is for those who want to see the “regime quake” before the aftershocks. VoVix Parameters: Fine-tune the volatility-of-volatility engine for your market. Lower ATR Fast = more responsive; higher ATR Slow = more selective. Bottom line: DEVMA is for those who want to see the market’s heartbeat, not just its shadow. Use it to filter your trades, time your entries, or simply understand the market’s true rhythm. Every input is there for a reason. Every plot is a direct readout of the quant logic. Use with discipline, and make it your own. Disclaimer: Trading is risky. This script is for research and informational purposes only, not financial advice. Backtest, paper trade, and know your risk before going live. Past performance is not a guarantee of future results. *Updated the Dashboard/Metrics Display for better visibility Use with discipline. Trade your edge. — Dskyz, for DAFE Trading Systems
Penunjuk Pine Script®
oleh DskyzInvestments
Futures Scalping Signal by AK_Trades – RISK PROTECTED MODEFutures Scalping Signal by AK_Trades – RISK PROTECTED MODE This precision-built scalping indicator is designed for futures traders who demand clarity, speed, and protection. ✅ Smart Signal Logic: Based on UT Bot ATR trailing stop logic Requires minimum price movement for confirmation Prevents repeated signals in the same direction using trend memory ✅ Visuals That Guide You, Not Distract: Clear Buy/Sell signals labeled on the chart Dynamic support or resistance line always visible Price-tagged signal entries (Buy @, Sell @) ✅ Candlestick Awareness: Highlights key patterns: Engulfing, Doji, Hammer, Shooting Star Patterns are visual only — no interference with signal flow ✅ Trend Label: Clean top-right corner label updates periodically to guide sentiment ⚠️ Disclaimer: This tool is for educational purposes only. No financial advice is provided. Use at your own risk. Built by @AK_Trades to help scalpers trade smarter, not harder.
Penunjuk Pine Script®
oleh adeelk714
1
Harmony in Havoc - The Entropy of VoVix Harmony in Havoc – The Entropy of VoVix There are moments in the market when chaos and order are not opposites, but partners in a dance. Harmony in Havoc is not just an indicator—it’s a window into that dance. Most tools try to tame the market by smoothing it, boxing it in, or chasing after what’s already happened. This script does the opposite: it listens for the music beneath the noise, the rare moments when volatility and unpredictability align, and the market’s next movement is about to begin. What is Harmony in Havoc? VoVix Spike: The pulse of volatility-of-volatility. Not just how much the market is moving, but how violently its own heartbeat is changing. Entropy: A real-time measure of surprise. When entropy is high, the market is not just moving—it’s breaking its own patterns, rewriting its own rules. Progression Bar & Status: The yellow bar is your visual gauge of tension. As it fills, the market is winding up. Wait: The world is calm. Get ready!: The storm is building. Take Action!!: The probability of a regime eruption is at its peak. Yellow Background: When the background glows, the market is at its most unstable—this is not a buy or sell signal, but a quant alert. How does it work? Every tick, Harmony in Havoc measures the distance between the market’s current volatility and its own unpredictability. When the VoVix spike approaches or exceeds the entropy threshold, the system knows: “This is the moment when the improbable becomes possible.” Why is this different? It doesn’t tell you what to do. It doesn’t chase price. It doesn’t care about trends, bands, or the past. Instead, it gives you a quantitative sense of anticipation—a way to see when the market is most likely to break from its own history, and when the edge is at its sharpest. How to use it: Watch for the yellow background and “Take Action!!” status. Use it as a regime filter, a volatility dashboard, or a warning system for your own strategies. Tune the inputs for your asset and timeframe—make it your own. Inputs—explained for you: VoVix Fast/Slow ATR & Stdev: Control how sensitive the system is to volatility shocks. Lower = more signals, higher = only the rarest events. Entropy Window & Bins: Control how “surprised” the entropy engine is by current volatility. Shorter window = more responsive, more bins = finer detail. Show/Hide Controls: Toggle the VoVix spike, entropy line, and their glows to customize your visual experience. Bottom line: This is not a buy or sell script. This is a quant regime detector for those who want to feel the market’s tension—to sense when harmony and havoc are about to collide. Disclaimer: Trading is risky. This script is for research and informational purposes only, not financial advice. Backtest, paper trade, and know your risk before going live. Past performance is not a guarantee of future results. *I've only tested this on 1 and 5 min frames. Use with discipline. Trade your edge. — Dskyz, for DAFE Trading Systems 3 days ago Release Notes * Now mobile friendly. I've added a toggle to switch the dashboard on/off, and added a mobile information line that shows the same information on the dashboard. This is to allow the script to stay visually in balance and this also has a toggle. * Background color added that coresponds with Buy or Sell areas.
Penunjuk Pine Script®
oleh DskyzInvestments
Granger Causality Flow IndicatorGranger Causality Flow Indicator (GC Flow) █ OVERVIEW The Granger Causality Flow Indicator (GC Flow) attempts to quantify the potential predictive relationship between two user-selected financial instruments (Symbol X and Symbol Y). In essence, it explores whether the past values of one series (e.g., Symbol X) can help explain the current value of another series (e.g., Symbol Y) better than Y's own past values alone. This indicator provides a "Granger Causality Score" (GC Score) for both directions (X → Y and Y → X). A higher score suggests a stronger statistical linkage where one series may lead or influence the other. The indicator visualizes this "flow" of potential influence through background colors and on-chart text. Important Note: "Granger Causality" does not imply true economic or fundamental causation. It is a statistical concept indicating predictive power or information flow. This implementation also involves simplifications (notably, using AR(1) models) due to the complexities of full Vector Autoregression (VAR) models in Pine Script®. █ HOW IT WORKS The indicator's methodology is based on comparing the performance of Autoregressive (AR) models: 1. Data Preprocessing: Fetches historical close prices for two user-defined symbols (X and Y). Optionally applies first-order differencing (`price - price `) to the series. Differencing is a common technique to achieve a proxy for stationarity, which is an underlying assumption for Granger Causality tests. Non-stationary series can lead to spurious correlations. 2. Autoregressive (AR) Models (Simplified to AR(1)): Due to Pine Script's current limitations for complex multivariate time series models, this indicator uses simplified AR(1) models (where the current value is predicted by its immediately preceding value). Restricted Model (for Y → Y): Predicts the target series (e.g., Y) using only its own past value (Y ). `Y = c_R + a_R * Y + residuals_R` The variance of `residuals_R` (Var_R) is calculated. Unrestricted Model (Proxy for X → Y): To test if X Granger-causes Y, the indicator examines if the past values of X (X ) can explain the residuals from the restricted model of Y. `residuals_R = c_UR' + b_UR * X + residuals_UR` The variance of these final `residuals_UR` (Var_UR) is calculated. The same process is repeated to test if Y Granger-causes X. 3. Granger Causality (GC) Score Calculation: The GC Score quantifies the improvement in prediction from adding the other series' past values. It's calculated as: `GC Score = 1 - (Var_UR / Var_R)` A score closer to 1 suggests that the "causing" series significantly reduces the unexplained variance of the "target" series (i.e., Var_UR is much smaller than Var_R), indicating stronger Granger causality. A score near 0 (or capped at 0 if Var_UR >= Var_R) suggests little to no improvement in prediction. The score is calculated over a rolling `Calculation Window`. Pine Script® Snippet (Conceptual GC Score Logic): // Conceptual representation of GC Score calculation // var_R: Variance of residuals when Y is predicted by Y // var_UR: Variance of residuals when Y's AR(1) residuals are predicted by X score = 0.0 if var_R > 1e-9 // Avoid division by zero score := 1.0 - (var_UR / var_R) score := score < 0 ? 0 : score // Ensure score is not negative 4. Determining Causal Flow: The calculated GC Scores for X → Y and Y → X are compared against a user-defined `Significance Threshold for GC Score`. If GC_X→Y > threshold AND GC_Y→X > threshold: Bidirectional flow. If GC_X→Y > threshold only: X → Y flow. If GC_Y→X > threshold only: Y → X flow. Otherwise: No significant flow. █ HOW TO USE IT Interpreting the Visuals: Background Color: Green: Indicates X → Y (Symbol 1 potentially leads Symbol 2). Orange: Indicates Y → X (Symbol 2 potentially leads Symbol 1). Blue: Indicates Bidirectional influence. Gray: No significant Granger causality detected based on the threshold. Data Window Plots: The actual GC Scores for X → Y (blue) and Y → X (red) are plotted and visible in TradingView's Data Window. A dashed gray line shows your `Significance Threshold`. On-Chart Table (Last Bar): Displays the currently detected causal direction text (e.g., "BTCUSDT → QQQ"). Potential Applications: Intermarket Analysis: Explore potential lead-lag relationships between different asset classes (e.g., commodities and equities, bonds and currencies). Pair Trading Components: Identify if one component of a potential pair tends to lead the other. Confirmation Tool: Use alongside other analyses to see if a move in one asset might foreshadow a move in another. Considerations: Symbol Choice: Select symbols that have a plausible economic or market relationship. Stationarity: Granger Causality tests ideally require stationary time series. The `Use Differencing` option is a simple proxy. True stationarity testing is complex. Non-stationary data can yield misleading results. Lag Order (p): This indicator is fixed at p=1 due to Pine Script® limitations. In rigorous analysis, selecting the optimal lag order is crucial. Calculation Window: Shorter windows are more responsive but may be noisier. Longer windows provide smoother scores but lag more. Significance Threshold: Adjust this based on your desired sensitivity for detecting causal links. There's no universally "correct" threshold; it depends on the context and noise level of the series. █ INPUTS Symbol 1 (X): The first symbol in the analysis. Symbol 2 (Y): The second symbol (considered the target when testing X → Y). Use Differencing: If true, applies first-order differencing to both series as a proxy for stationarity. Calculation Window (N): Lookback period for AR model coefficient estimation and variance calculations. Lag Order (p): Currently fixed at 1. This defines the lag used (e.g., X , Y ) in the AR models. Significance Threshold for GC Score: A value between 0.01 and 0.99. The calculated GC Score must exceed this to be considered significant. █ VISUALIZATION Background Color: Dynamically changes based on the detected Granger causal flow (Green for X → Y, Orange for Y → X, Blue for Bidirectional, Gray for None). GC Scores (Data Window): Blue Plot: GC Score for X → Y. Red Plot: GC Score for Y → X. Significance Threshold Line: A dashed gray horizontal line plotted at the level of your input threshold. On-Chart Table: Displayed on the top-right (on the last bar), showing the current causal direction text. █ ALERTS The indicator can generate alerts for: Emergence of X → Y causality. Emergence of Y → X causality. General change or cessation of a previously detected causal relationship. █ IMPORTANT DISCLAIMERS & LIMITATIONS Correlation vs. Causation: Granger causality measures predictive power, not true underlying economic causation. A strong GC Score doesn't prove one asset *causes* another to move, only that its past values improve predictions. Stationarity Assumption: While differencing is offered, it's a simplified approach. Non-stationary data can lead to spurious (false) Granger causality detection. Model Simplification (AR(1)): This script uses AR(1) models for simplicity. Real-world relationships can involve more complex dynamics and higher lag orders. The fixed lag of p=1 is a significant constraint. Sensitivity to Parameters: Results can be sensitive to the chosen symbols, calculation window, differencing option, and significance threshold. No Statistical Significance Testing (p-values): This indicator uses a direct threshold on the GC Score itself, not a formal statistical test (like an F-test producing p-values) typically found in econometric software. Use this indicator as an exploratory tool within a broader analytical framework. Do not rely on it as a standalone basis for trading decisions. █ CREDITS & LICENSE Author: mastertop ( Twitter: x.com ) Version: 1.0 (Released: 2025-05-08) This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org © mastertop, 2025
Penunjuk Pine Script®
oleh MASTERTOP_ASTRAY
Adaptive Hurst Exponent Regime FilterAdaptive Hurst Exponent Regime Filter (AHERF) █ OVERVIEW The Adaptive Hurst Exponent Regime Filter (AHERF) is designed to identify the prevailing market regime—be it Trending, Mean-Reverting, or a Random Walk/Transition phase. While the Hurst Exponent is a well-known tool for this purpose, AHERF introduces a key innovation: an adaptive threshold . Instead of relying solely on the traditional fixed 0.5 Hurst value, this indicator's threshold dynamically adjusts based on current market volatility, aiming to provide more nuanced and responsive regime classifications. This tool can assist traders in: Gauging the current character of the market. Tailoring trading strategies to the identified regime (e.g., deploying trend-following systems in Trending markets or mean-reversion tactics in Mean-Reverting conditions). Filtering out trades that may be counterproductive to the dominant market behavior. █ HOW IT WORKS The indicator operates through the following key calculations: 1. Hurst Exponent Calculation: The script computes an approximate Hurst Exponent (H). It utilizes log price changes as its input series. The `calculateHurst` function implements a variance scaling approach: It defines three sub-periods based on the main `Hurst Lookback Period`. It calculates the standard deviation of the input series over these sub-periods. The Hurst Exponent is then estimated from the slope of a log-log regression between the standard deviations and their respective sub-period lengths. A simplified calculation using the first and last sub-periods is performed: `H = (log(StdDev3) - log(StdDev1)) / (log(N3) - log(N1))`. Theoretically, a Hurst Exponent: H > 0.5 suggests persistence (trending behavior). H < 0.5 suggests anti-persistence (mean-reverting behavior). H ≈ 0.5 suggests a random walk (unpredictable movement). Pine Script® Snippet (Hurst Calculation Call): float logPriceChange = math.log(close) - math.log(close ); // ... ensure logPriceChange is not na on first bar ... float hurstValue = calculateHurst(logPriceChange, hurstLookbackInput); 2. Volatility Proxy Calculation: To enable the adaptive nature of the threshold, a volatility proxy is calculated. Users can select the `Volatility Metric` to be either: Average True Range (ATR), normalized by the closing price. Standard Deviation (StdDev) of simple price returns. This proxy quantifies the current degree of price activity or fluctuation in the market. Pine Script® Snippet (Volatility Proxy Call): float volatilityProxy = getVolatilityProxy(volatilityMetricInput, volatilityLookbackInput); 3. Adaptive Threshold Calculation: This is the core of AHERF's adaptability. Instead of a static 0.5 line as the sole determinant, the script computes a dynamic threshold. The adaptive threshold is calculated as: `0.5 + (Threshold Sensitivity * Volatility Proxy)`. This means the threshold starts at the baseline 0.5 level and then adjusts upwards or downwards based on the current `volatilityProxy` scaled by the `Threshold Sensitivity (k)` input. Pine Script® Snippet (Adaptive Threshold Calculation): float adaptiveThreshold = 0.5 + sensitivityInput * nz(volatilityProxy, 0.0); 4. Regime Identification: The prevailing market regime is determined by comparing the `hurstValue` to this `adaptiveThreshold`, incorporating a `Threshold Buffer` to reduce noise and clearly delineate zones: Trending: `hurstValue > adaptiveThreshold + bufferInput` Mean-Reverting: `hurstValue < adaptiveThreshold - bufferInput` Random/Transition: Otherwise (Hurst value is within the buffer zone around the adaptive threshold). Pine Script® Snippet (Regime Determination Logic): if not na(hurstValue) and not na(adaptiveThreshold) if hurstValue > adaptiveThreshold + bufferInput currentRegimeColor := TRENDING_COLOR regimeText := "Trending" else if hurstValue < adaptiveThreshold - bufferInput currentRegimeColor := MEAN_REVERTING_COLOR regimeText := "Mean-Reverting" // else remains Random/Transition █ HOW TO USE IT Interpreting the Visuals: Observe the plotted `Hurst Exponent (H)` line (White) relative to the `Adaptive Threshold` line (Orange). The background color provides an immediate indication of the current regime: Green for Trending, Red for Mean-Reverting, and Gray for Random/Transition. The fixed `0.5 Level` (Dashed Gray) is plotted for reference against traditional Hurst interpretation. Labels "T", "M", and "R" appear below bars to signal new entries into Trending, Mean-Reverting, or Random/Transition regimes, respectively. Inputs Customization: Hurst Exponent Calculation Hurst Lookback Period: Defines the number of bars used for the Hurst Exponent calculation. Longer periods generally yield smoother Hurst values, reflecting longer-term market memory. Shorter periods are more responsive. Adaptive Threshold Settings Volatility Metric: Choose "ATR" or "StdDev" to drive the adaptive threshold. Experiment to see which best suits the asset. Volatility Lookback: The lookback period for the selected volatility metric. Threshold Sensitivity (k): A crucial multiplier determining how strongly volatility influences the adaptive threshold. Higher values mean volatility has a greater impact, potentially widening or shifting the regime bands more significantly. Threshold Buffer: Creates a neutral zone around the adaptive threshold. This helps prevent overly frequent regime shifts due_to minor Hurst fluctuations. █ ORIGINALITY AND USEFULNESS The AHERF indicator distinguishes itself by: Implementing an adaptive threshold mechanism for Hurst Exponent analysis. This threshold dynamically responds to changes in market volatility, offering a more flexible approach than a fixed 0.5 reference, potentially leading to more contextually relevant regime detection. Providing clear, at-a-glance visualization of market regimes through background coloring and distinct plot shapes. Offering user-configurable parameters for both the Hurst calculation and the adaptive threshold components, allowing for tuning across various assets and timeframes. Traders can leverage AHERF to better align their chosen strategies with the prevailing market character, potentially enhancing trade filtering and decision-making processes. █ VISUALIZATION The indicator plots the following in a separate pane: Hurst Exponent (H): A white line representing the calculated Hurst value. Adaptive Threshold: An orange line representing the dynamic threshold. Fixed 0.5 Level: A dashed gray horizontal line for traditional Hurst reference. Background Color: Changes based on the identified regime: Green: Trending regime. Red: Mean-Reverting regime. Gray: Random/Transition regime. Regime Entry Shapes: Plotted below the price bars (forced overlay for visibility): "T" (Green Label): Signals entry into a Trending regime. "M" (Teal Label): Signals entry into a Mean-Reverting regime. "R" (Cyan Label): Signals entry into a Random/Transition regime. █ ALERTS The script provides alert conditions for changes in the market regime: Regime Shift to Trending: Triggers when the Hurst Exponent crosses above the adaptive threshold into a Trending state. Regime Shift to Mean-Reverting: Triggers when the Hurst Exponent crosses below the adaptive threshold into a Mean-Reverting state. Regime Shift to Random/Transition: Triggers when the Hurst Exponent enters the Random/Transition zone around the adaptive threshold. These can be configured directly from the TradingView alerts panel. █ NOTES & DISCLAIMERS The Hurst Exponent calculation is an approximation; various methods exist, each with its nuances. The performance and relevance of the identified regimes can differ across financial instruments and timeframes. Parameter tuning is recommended. This indicator is intended as a decision-support tool and should not be the sole basis for trading decisions. Always integrate its signals within a broader analytical framework. Past performance of any trading system or indicator, including those derived from AHERF, is not indicative of future results. █ CREDITS & LICENSE Author: mastertop ( Twitter: x.com ) Color Palette: Uses the `MaterialPalette` library by MASTERTOP_ASTRAY. This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org © mastertop, 2025
Penunjuk Pine Script®
oleh MASTERTOP_ASTRAY
PORTFOLIO TABLE Full [Titans_Invest]PORTFOLIO TABLE Full This is a complete table for monitoring your assets or cryptocurrencies in your SPOT wallet without needing to access your broker’s website or app. ⯁ HOW TO USE THIS TABLE❓ Simply select the asset and enter the amount you hold. The table will display the value of each asset and the total value of your portfolio. You can monitor up to 19 assets in real time. ⯁ CONVERT VALUES You can also enable and select a currency for conversion. For example, cryptocurrencies are calculated in US dollars by default, but you can choose euros as the conversion currency. The values originally in dollars will then be displayed in euros. ⯁ TRACK THE DAILY VARIATION OF YOUR PORTFOLIO You’ll be able to monitor your portfolio’s raw daily variation in real time. 🔶 Track your Portfolio in real time: 🔶 Add your local Currency to Convert Values: 🔶 Follow your Portfolio Live: ___________________________________________________________ 📜 SCRIPT : PORTFOLIO TABLE Full 🎴 Art by  : @Titans_Invest & @DiFlip 👨‍💻 Dev by : @Titans_Invest & @DiFlip 🎑 Titans Invest — The Wizards Without Gloves 🧤 ✨ Enjoy! ___________________________________________________________ o Mission 🗺 • Inspire Traders to manifest Magic in the Market. o Vision 𐓏 • To elevate collective Energy 𐓷𐓏
Penunjuk Pine Script®
oleh Titans_Invest
BPCO Z-ScoreBPCO Z-Score with Scaled Z-Value and Table Description: This custom indicator calculates the Z-Score of a specified financial instrument (using the closing price as a placeholder for the BPCO value), scales the Z-Score between -2 and +2 based on user-defined thresholds, and displays it in a table for easy reference. The indicator uses a simple moving average (SMA) and standard deviation to calculate the original Z-Score, and then scales the Z-Score within a specified range (from -2 to +2) based on the upper and lower thresholds set by the user. Additionally, the scaled Z-Score is displayed in a separate table on the right side of the chart, providing a clear, numerical value for users to track and interpret. Key Features: BPCO Z-Score: Calculates the Z-Score using a simple moving average and standard deviation over a user-defined window (default: 365 days). This provides a measure of how far the current price is from its historical average in terms of standard deviations. Scaled Z-Score: The original Z-Score is then scaled between -2 and +2, based on the user-specified upper and lower thresholds. The thresholds default to 3.5 (upper) and -1.5 (lower), and can be adjusted as needed. Threshold Bands: Horizontal lines are plotted on the chart to represent the upper and lower thresholds. These help visualize when the Z-Score crosses critical levels, indicating potential market overbought or oversold conditions. Dynamic Table Display: The scaled Z-Score is shown in a dynamic table at the top-right of the chart, providing a convenient reference for traders. The table updates automatically as the Z-Score fluctuates. How to Use: Adjust Time Window: The "Z-Score Period (Days)" input allows you to adjust the time period used for calculating the moving average and standard deviation. By default, this is set to 365 days (1 year), but you can adjust this depending on your analysis needs. Set Upper and Lower Thresholds: Use the "BPCO Upper Threshold" and "BPCO Lower Threshold" inputs to define the bands for your Z-Score. The default values are 3.5 for the upper band and -1.5 for the lower band, but you can adjust them based on your strategy. Interpret the Z-Score: The Z-Score provides a standardized measure of how far the current price (or BPCO value) is from its historical mean, relative to the volatility. A value above the upper threshold (e.g., 3.5) may indicate overbought conditions, while a value below the lower threshold (e.g., -1.5) may indicate oversold conditions. Use the Scaled Z-Score: The scaled Z-Score is calculated based on the original Z-Score, but it is constrained to a range between -2 and +2. When the BPCO value hits the upper threshold (3.5), the scaled Z-Score will be +2, and when it hits the lower threshold (-1.5), the scaled Z-Score will be -2. This gives you a clear, easy-to-read value to interpret the market's condition. Data Sources: BPCO Data: In this indicator, the BPCO value is represented by the closing price of the asset. The calculation of the Z-Score and scaled Z-Score is based on this price data, but you can modify it to incorporate other data streams as needed (e.g., specific economic indicators or custom metrics). Indicator Calculation: The Z-Score is calculated using the following formulas: Mean (SMA): A simple moving average of the BPCO (close price) over the selected period (365 days by default). Standard Deviation (Std): The standard deviation of the BPCO (close price) over the same period. Z-Score: (Current BPCO - Mean) / Standard Deviation Scaled Z-Score: The Z-Score is normalized to fall within a specified range (from -2 to +2), based on the upper and lower threshold inputs. Important Notes: Customization: The indicator allows users to adjust the period (window) for calculating the Z-Score, as well as the upper and lower thresholds to suit different timeframes and trading strategies. Visual Aids: Horizontal lines are drawn to represent the upper and lower threshold levels, making it easy to visualize when the Z-Score crosses critical levels. Limitations: This indicator relies on historical price data (or BPCO) and assumes that the standard deviation and mean are representative of future price behavior. It does not account for potential market shifts or extreme events that may fall outside historical norms.
Penunjuk Pine Script®
oleh simonweisser_business