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TrendLines with ATR and MA [KoTa]The "TrendLines with ATR and MA " indicator combines trend lines, breakout signals, ATR-based trend tracking, and moving averages (MA). Input Settings and Customization: After adding the indicator, click on its name at the top of the chart and open the "Settings" tab. Main sections: Trend Lines and Breakouts (Periods 1-5): General Usage Tips: Chart Timeframe: Works on any timeframe (from 1 minute to weekly). Shorter timeframes (e.g., 5-minute) generate more signals, while longer timeframes (e.g., daily) produce fewer but more reliable signals. Compatibility: Overlay=true, meaning it is drawn directly on the candlestick chart. It can be combined with other indicators (e.g., RSI, MACD). Advantages This indicator outperforms standard trend line tools due to its automated, multi-period, and integrated features: Automated Trend Line Drawing: Instead of manual drawing, it creates trend lines based on pivot highs/lows. Different periods (3-50) enable multi-timeframe analysis, allowing you to see short- and long-term trends on the same chart. Breakout Detection and Labeling: Detects breakouts in real-time using dotted extensions. B (Buy) and S (Sell) labels (e.g., B1 for period1 up breakout) clarify signals. Historical breakouts are shown in gray for context. ATR Integration: Volatility-based trend tracking (similar to SuperTrend). Calculates channel deviation to adapt to market volatility. Arrows highlight trend reversals quickly. Moving Averages Integration: Flexible MA types (e.g., VWMA for volume-weighted analysis) for trend filtering. No Bollinger Bands option, but MAs can validate breakouts. Performance and Visuals: Limits line count with max_lines_count for memory efficiency. Colors and line widths are customizable, and old elements are automatically managed (deleted or grayed out). Precision=0 ensures clean price formatting. Flexibility: All components (trend lines, ATR, MA) can be toggled on/off, allowing for simple or complex usage. Benefits Provided This indicator speeds up trading decisions and reduces errors: Trend and Support/Resistance Detection: Pivot-based lines provide automatic support (green, lows) and resistance (red, highs) levels. Benefit: Reduces manual analysis time, saving effort in scalping or swing trading. Breakout Signals: Signals are triggered when the close price crosses over/under the extended line. Benefit: Catches potential trend starts early; ATR can filter false breakouts. B/S labels provide visual alerts, simplifying alert setup. Volatility Adaptation (ATR): Adjusts trend lines based on market fluctuations. Benefit: Wider channels in high-volatility periods (e.g., crypto) and narrower in low volatility, reducing whipsaws (false signals). Arrows clearly show trend changes, ideal for position management. MA Validation: MAs measure trend strength (e.g., EMA20 above indicates uptrend). Benefit: Filtering breakouts with MA crossovers improves accuracy. VWMA offers volume-based analysis to eliminate weak trends. General Benefits: Risk Management: Breakout levels can be used for stop-loss placement (e.g., below breakout). Profit Potential: When tested on historical data (backtesting), it can be optimized by period—shorter periods for quick entries, longer for holding. Educational Value: Visualizes fractal, pivot, and ATR concepts for new traders. Time Savings: Automation eliminates hours of chart analysis; updates in real-time. Multi-Asset Compatibility: Works for stocks, forex, and crypto; ATR shines in volatile assets. Possible Strategies This indicator supports various strategies, primarily focused on breakouts and trend following, enhanced by MA and ATR filtering. Breakout Trading Strategy: Rules: Enter long on B (Buy) label (crossover up line), short on S (Sell). For example, enter on B3 (period10), with stop-loss below the previous pivot low. Filtering: Confirm with ATR arrow up (trend=0). Ensure price is above MA1 (20). Exit: Profit target at ATR*2 or exit on reverse breakout (S). Advantage: Ideal for scalping (p1-p2) or swing trading (p4-p5). Benefit: High win rate in volatile markets. Trend Following Strategy: Rules: Hold long if ATR trend line is green (up) and MA1 > MA2. Strengthen entry with breakout B. Filtering: Use only larger period breakouts (p3-p5) with ATR in slow mode. Exit: Exit on ATR arrow down (reversal) or MA crossover. Advantage: Captures long-term trends with low drawdown. Benefit: Suitable for passive trading, especially on weekly charts. Pullback Strategy: Rules: In an uptrend (green ATR line), enter long when price pulls back to the downtrend line (green pivot low line). Filtering: No breakout, supported by MA (price above MA). Set stop using ATR deviation. Exit: New high breakout or ATR reversal. Advantage: Low-risk entries, captures trend continuations. Benefit: Effective in range-bound markets. Multi-Timeframe Combination: Rules: Match short-period (p1) breakouts with long-period (p5) trends (e.g., p5 up + p1 B = long). Filtering: ATR in medium mode, MAs in golden cross (20>50). Advantage: Reduces false signals, validates H4 breakouts with D1 trends. Benefit: Suitable for professional traders, with backtesting showing 60%+ win rates. Risk and Optimization Tips: Position Sizing: Calculate using ATR (stop-loss distance / 1% risk). Backtesting: Test in strategy mode; short periods may overtrade, while longer ones may miss opportunities.
Pine Script® göstergesi
kointakipnet tarafından
6
RSI Bands With RSI - ATR Trend LineRSI Bands With RSI - ATR Trend Line (Smoothed Baseline) Overview A trend-following tool that fuses RSI-based regime detection with a smoothed baseline and ATR bands. Trend line aims to stay with the RSI move, cut random noise, and flip cleanly. The line draws green in bulls and red in bears; signals fire only on candle close confirmed flips. Key Features ✅ Dynamic Trend Detection RSI (>50 / <50) sets bullish/bearish regime Smoothed baseline adapts to price while damping whipsaw ATR-based bands expand/contract with volatility ✅ Precise Signal Generation Buy when trend flips to bullish (close confirms above the upper band) Sell when trend flips to bearish (close confirms below the lower band) Flips require a real band break → fewer false transitions ✅ Visual Clarity Green line = bullish trend, Red line = bearish trend ✅ Customizable Settings RSI Length (default 14) Baseline Smoothing (default 26) ATR Length (default 14) ATR Multiplier (default 1.4) Toggles for Signals and Labels ✅ TradingView Alerts Built-in Buy & Sell alerts (recommend Once per bar close) How It Works Algorithm Logic RSI Regime: RSI above/below 50 sets bull/bear. At exactly 50, the prior target is carried forward. Target & Smoothing: A per-bar target is built from the bar’s range and RSI, then smoothed with an EMA-style filter (Baseline Smoothing) to form the baseline. ATR Bands: Upper/Lower = baseline ± (ATR × Multiplier). Flip Rule (Supertrend-like): Close above upper band → bullish flip; trend line tracks the lower band (green). Close below lower band → bearish flip; trend line tracks the upper band (red). Between bands → prior trend line persists. Signals/Alerts: A flip event generates a Buy/Sell signal and alert. Best Use Cases Trending Markets – Built to ride sustained moves in either direction. Multiple Timeframes – Works from intraday to higher TFs; higher TFs usually produce cleaner flips. Various Asset Classes – Forex, Indices, Stocks, Crypto, Commodities; ATR adapts to volatility. Recommended Settings Conservative (Lower Frequency) RSI 14–20 • Baseline 34 • ATR 14–21 • Multiplier 1.8–2.2 Use for swing/position trading; calmer signal stream. Balanced (Default) RSI 14 • Baseline 26 • ATR 14 • Multiplier 1.4 Good general-purpose setup for swing or active intraday. Aggressive (Higher Frequency) RSI 10–14 • Baseline 13–21 • ATR 10–14 • Multiplier 1.1–1.3 For scalping/day trading; earlier but noisier flips. 🎨 Visual Elements RSI Smooth baseline (soft blue) Upper/Lower ATR Bands (faint blue) Trend Line (Bull/Bear) drawn only in the active regime (green/red) Optional Buy/Sell arrows and labels ⚠️ Important Notes Signals on Close Flips confirm on bar close. Intrabar crosses can revert; wait for confirmation. Risk Management Size positions appropriately; many traders trail beyond the opposite band/line. Factor in spread, slippage, sessions, and news. Confirmation & Testing Combine with structure/volume/HTF bias if desired. Backtest and forward-test per instrument and timeframe. For research/education only; not financial advice.
Pine Script® göstergesi
qoulynn tarafından
Fibo & Gann Advanced Auto[CongTrader]🔍 Description: "Fibo & Gann Advanced Auto by CongTrader" is a smart automatic indicator that combines Fibonacci Retracement & Extension levels with Gann Boxes and Fan lines, helping traders identify key support/resistance zones and potential turning points in the market. This tool automatically detects recent swing highs/lows using pivots and overlays: 📏 Fibonacci Retracement & Extension (0.236 to 1.618) 🟪 Gann Box between 2 latest pivots 📐 Gann Fan Lines (1x1, 2x1, etc.) 🟢 Optional filtered Buy/Sell signals based on wave size and RSI Designed for discretionary and technical traders who want a visual confirmation of price geometry and market structure. 📘 How to Use: Apply to any chart & timeframe. Adjust pivot sensitivity via “Pivot Length” input. Look for confluence between Fib retracement/extension and Gann box edges for trade entries. Gann fan lines help visualize trend angles or speed. Combine with your own strategy for better confirmation (e.g., volume, candlestick pattern). 💡 Tip: Use in higher timeframes (H1, H4, D1) for cleaner and more reliable pivots. 🙏 Thanks: Created with love and passion for the trading community by CongTrader. If you find it helpful, please give a like or comment. Feedback is always appreciated! ⚠️ Disclaimer: This script is for educational and informational purposes only. It does not constitute financial advice and should not be used as a sole basis for trading decisions. Always use proper risk management and perform your own analysis before entering any trade. Trading involves risk, and past performance is not indicative of future results..#fibonacci #gann #gannbox #gannfan #elliottwave #marketstructure #priceaction #autopivot #congtrader #tradingviewindicator #technicalanalysis #tradingtools #forextrading #cryptoindicator #tradingstrategy #tradingsetup #smartmoney #supportresistance
Pine Script® göstergesi
CongTrader_ tarafından
Implied Volatility TestThought for 42sOverview of the "Implied Volatility Suite" Indicator The "Implied Volatility Suite" is a custom TradingView indicator written in Pine Script (version 6) designed to estimate and visualize implied volatility (IV) for any stock or asset charted on TradingView. Unlike true implied volatility derived from options pricing (e.g., via Black-Scholes), this script provides a synthetic approximation based on historical price data. It offers flexibility by allowing users to choose between two calculation methods: "Model Implied Volatility" (a statistical projection based on log-normal assumptions) or "VixFix" (a historical volatility proxy inspired by Larry Williams' VIX Fix indicator). The output is plotted as an oscillating line, similar to the Relative Strength Index (RSI), making it easy to interpret overbought/oversold conditions or trends in volatility. Users can select what to plot: raw Implied Volatility, IV Rank, IV Percentile, or Volatility Skew Index, with color-coded visuals for quick analysis (e.g., red/green thresholds for ranks/percentiles). This indicator is particularly useful for stocks without listed options, where real IV data isn't available, or for traders seeking a quick volatility gauge integrated into their charts. What the Code Does At its core, the script computes a volatility metric and transforms it into one of four plottable formats, then displays it as a line chart in a separate pane below the main price chart. Here's a breakdown: User Inputs and Configuration: Volatility Calculation Method: Choose "Model Implied Volatility" (default) or "VixFix". Expiry Parameters (for Model method): Minutes, Hours, and Days until expiry (default 45 days). These are combined into Days (as a float for fractional days) and converted to years (Expiry = Days / 365). Length Parameters: For Model IV rank/percentile (default 365), VixFix length (default 252, with recommendations like 9, 22, etc.), and VixFix rank/percentile length (default 252). Output Choice: Select "Implied Volatility", "IV Rank", "IV Percentile" (default "IV Rank"), or "Volatility Skew Index". The script uses spot = close as the reference price. Core Calculations: Model Implied Volatility: Computes log returns: LogReturn = math.log(spot / spot ) (percentage change between prior bars). Calculates the simple moving average (Average) and standard deviation (STDEV) of log returns over an integer-rounded Days period. Projects a time-adjusted mean (Time_Average = Days * Average) and standard deviation (Time_STDEV = STDEV * math.sqrt(Days)), assuming a random walk scaled by time. Derives upper and lower bounds for the price at expiry: upper = spot * math.exp(Time_Average + 1 * Time_STDEV) and lower = spot * math.exp(Time_Average - 1 * Time_STDEV), representing a 1-standard-deviation range under log-normal distribution. Computes the width of this range (width = upper - lower), halves it to get standard_dev, and annualizes it to sigma: sigma = standard_dev / (spot * math.sqrt(Expiry)). Applies an "optimizer": If sigma > 1, halve it (to prevent unrealistically high values). Result: IV (a decimal, e.g., 0.25 for 25% IV). VixFix (Synthetic VIX Proxy): Based on Larry Williams' VIX Fix formula, which estimates fear/volatility without options data: (ta.highest(spot, VIXFixLength) - low) / ta.highest(spot, VIXFixLength) * 100. The script extends this for "upside" and "downside" by shifting the spot and low prices by multiples of standard deviation (0 for base VixFix). VixFix is the average of upside(0) and downside(0), which are identical, yielding the standard VIX Fix value. Volatility Skew Index: Measures asymmetry in volatility (e.g., higher downside vol indicating fear). For Model: Averages "upside IV" (calculated on spot shifted up by 1,2,3 * stdev) minus "downside IV" (shifted down). For VixFix: Similar, but using shifted VIX Fix formulas for upside/downside. Positive skew might indicate upside bias; negative indicates downside. Rank and Percentile: IV Rank: Normalizes the current volatility: (Volatility - ta.lowest(Volatility, Len)) / (ta.highest(Volatility, Len) - ta.lowest(Volatility, Len)) * 100. IV Percentile: Uses ta.percentrank(Volatility, Len) to show what percentage of past values are below the current. Len depends on the chosen method (e.g., 365 for Model). Plotting and Visualization: Selects VolatilityData based on user choice (e.g., IV * 100 for percentage display). Applies colors: Red (<50) or green (>=50) for rank/percentile; aqua for skew; yellow for raw IV. Plots as a line: plot(VolatilityData, color=col, title="Volatility Data"). The script switches logic seamlessly via conditionals (e.g., Volatility = VolCalc == "VixFix" ? VixFix : IV), ensuring the chosen method and output are used. How It Works (Step-by-Step Execution Flow) Initialization: Reads user inputs and sets spot = close. Computes Days (float) and DaysInt = math.round(Days) for integer lengths in TA functions. Log Returns and Base Stats: For Model, calculates log returns, then SMA and STDEV over DaysInt. Projection and IV Derivation: Scales stats to expiry time, computes bounds, derives sigma/IV. Skew Functions: Defines reusable functions Model_Upside(i) and Model_Downside(i) (or VIX equivalents) to shift prices and recompute IV/VIX on shifted series. Aggregation: Computes skew as average difference; sets Volatility to IV or VixFix. Rank/Percentile/Skew: Applies over user-defined lengths. Output Logic: Determines what to plot and its color based on VolatilityChoice. Rendering: Plots the line in TradingView's indicator pane, updating bar-by-bar. This leverages Pine Script's built-in functions like ta.sma, ta.stdev, ta.highest/lowest, and math.exp/log for efficiency. Pros Accessibility: Provides IV estimates for non-optionable assets (e.g., individual stocks, ETFs without options), filling a gap in TradingView's native tools. Customization: Multiple methods (Model for forward-looking, VixFix for historical) and outputs (raw, ranked, percentile, skew) allow tailored analysis. Expiry adjustments make it suitable for options-like thinking. Visual Simplicity: Oscillates like RSI (0-100 for ranks/percentiles), with intuitive colors, aiding quick decisions (e.g., high IV Rank might signal options selling opportunities). No External Data Needed: Relies solely on chart data (close, low), making it lightweight and real-time. Educational Value: Exposes users to volatility concepts like skew and log-normal projections, potentially improving trading strategies. Flexibility in Timeframes: Works on any chart interval, with adjustable lengths for short-term (e.g., 9-bar VixFix) or long-term (365-day ranks). Limitations Not True Implied Volatility: This is a historical or model-based proxy, not derived from actual options prices. It may overestimate/underestimate real market-implied vol, especially during events (e.g., earnings) where options premium spikes unpredictably. Assumptions in Model Method: Relies on log-normal distribution and constant volatility, ignoring fat tails, jumps, or mean reversion in real markets. The "optimizer" (halving sigma >1) is arbitrary and may distort results. VixFix Variant Limitations: While based on a proven indicator, the upside/downside shifts (by stdev of prices, not returns) could be inaccurate for skew, as stdev(prices) doesn't scale properly with returns. It's backward-looking, not predictive like true IV. Data Requirements: Needs sufficient historical bars (e.g., 365 for ranks), failing on new listings or short charts. Rounding Days to integer may introduce minor inaccuracies for fractional expiries. Computational Intensity: Functions like repeated ta.stdev and shifts for skew (called multiple times per bar) could slow performance on long histories or low-power devices. No Real-Time Options Integration: Doesn't pull live options data; users must manually compare to actual IV (e.g., via CBOE VIX for indices). Potential for Misinterpretation: Oscillating line might mislead (e.g., high IV Rank doesn't always mean "sell vol"), and skew calculation is non-standard, requiring user expertise. Version Dependency: Built for Pine v6 (as of 2025); future TradingView updates could break it, though it's straightforward to migrate. Overall, this script is a valuable tool for volatility-aware trading but should be used alongside other indicators (e.g., ATR, Bollinger Bands) and validated against real options data when available. For improvements, consider backtesting its signals or integrating alerts for thresholds.1.9sHow can Grok help?
Pine Script® göstergesi
bcumming09 tarafından
Traders Reality Rate Spike Monitor 0.1 betaTraders Reality Rate Spike Monitor ## **Early Warning System for Interest Rate-Driven Market Crashes** Based on critical market analysis revealing the dangerous correlation between interest rate spikes and major market selloffs, this indicator provides **three-tier alerts** for US 10-Year Treasury yield acceleration. ### **📊 Key Market Intelligence:** **Historical Precedent:** The 2018 market crash occurred when unrealized bank losses hit $256 billion with interest rates at just 2.5%. **Current unrealized losses have reached $560 billion** - more than double the 2018 levels - while rates sit at 4.5%. **Critical Vulnerabilities:** - **$559 billion in tech sector debt** maturing through 2025 - **65% of investment-grade debt** rated BBB (vulnerable to adverse conditions) - **$9.5 trillion in total debt** requiring refinancing - Every 1% rate increase costs the economy **$360 billion annually** ### **🚨 Alert System:** **📊 WATCH (20+ basis points/3 days):** Early positioning signal **⚠️ WARNING (30+ basis points/3 days):** Prepare for volatility **🚨 CRITICAL (40+ basis points/3 days):** Historical crash threshold ### **💡 Why This Matters:** Interest rate spikes historically trigger major market corrections: - **2018:** 70 basis points spike → 20% S&P 500 crash - **2025:** Similar pattern led to massive selloffs - **Current risk:** 2x higher unrealized losses than 2018 ### **⚡ Features:** ✅ **Zero chart clutter** - invisible until alerts trigger ✅ **Dynamic calculation** - automatically adjusts to current yield levels ✅ **Multi-timeframe compatibility** - works on any chart timeframe ✅ **Professional alerts** - with actual basis point calculations ### **🎯 Use Case:** Perfect for traders and investors who understand that **debt refinancing pressure** and **unrealized bank losses** create systemic risks that manifest through interest rate volatility. When rates spike rapidly, leveraged positions unwind and markets crash. **"Every point costs us $360 billion a year. Think of that."** - This indicator helps you see those critical rate movements before the market does. --- **Disclaimer:** This indicator is for educational purposes. Past performance does not guarantee future results. Always manage risk appropriately. --- This description positions your indicator as a **serious professional tool** based on real market analysis rather than just another technical indicator! 🚀
Pine Script® göstergesi
floriankluge tarafından
Strenth Comparison [joshu]Strenth Comparison visualizes relative performance across a basket of assets by measuring percent change from the chosen anchor timeframe’s open. Each new anchor period resets the baseline to 0%, making it easy to spot leaders/laggards and momentum shifts over time. Anchor timeframe (TF, default: 1W): The period used as the performance baseline. Assets : Currencies or American Indices. Symbols : Currencies: CME:6S1!, CME:6E1!, CME:6B1!, CME:6J1!, CME:6A1!, CME:6N1!, TVC:DXY (inverted for comparability). American Indices: CME_MINI:ES1!, CME_MINI:NQ1!, CBOT_MINI:YM1!, CME_MINI:RTY1!. Visuals: All lines plotted in percent; DXY is inverted and highlighted; labels show the symbol at the latest bar; zero line for reference; vertical dividers mark new anchor periods. Use cases: Compare strength/weakness within FX or US index baskets; monitor rotation, divergence, and leadership over weekly (or chosen) cycles.
Pine Script® göstergesi
joshuuu tarafından
PLAIN VAMSThe PLAIN VAMS (Volatility-Adjusted Momentum Score) is a visual tool designed to help traders identify momentum shifts relative to prevailing volatility conditions. Unlike traditional momentum indicators, VAMS adapts dynamically to price fluctuations by comparing current price levels to volatility-based boundaries derived from customizable moving averages. Key Features: - Volatility-Adjusted Zones: Prices are evaluated against upper and lower dynamic boundaries, signaling potential overbought or oversold momentum conditions. Two Modes: - PLAIN VAMS (default): Uses a longer lookback period for smoother, trend-following behavior. - RAW VAMS: A shorter lookback for high-sensitivity, intraday or scalping setups. Customizable Moving Averages: Choose from multiple MA types (EMA, SMA, WMA, etc.) to match your strategy preferences. Visual Clarity: - Color-coded candles for quick signal recognition. - Optional background shading for immediate context. - Boundary lines to define momentum thresholds. How It Works: The script calculates a moving average (based on user-selected type and period) and applies an upper and lower multiplier to create dynamic price boundaries. When price closes beyond these bands, it suggests a strong directional momentum move. The indicator is fully customizable to adapt to your trading style and timeframe. Use Cases: - Identify potential breakouts or trend continuations. - Filter entries/exits based on momentum strength. - Combine with other tools for confirmation in your strategy. This indicator does not repaint or use future-looking data. It’s designed for discretionary and systematic traders looking for an adaptive way to visualize momentum relative to market volatility.
Pine Script® göstergesi
La_Von tarafından
Seasonality Monte Carlo Forecaster [BackQuant]Seasonality Monte Carlo Forecaster Plain-English overview This tool projects a cone of plausible future prices by combining two ideas that traders already use intuitively: seasonality and uncertainty. It watches how your market typically behaves around this calendar date, turns that seasonal tendency into a small daily “drift,” then runs many randomized price paths forward to estimate where price could land tomorrow, next week, or a month from now. The result is a probability cone with a clear expected path, plus optional overlays that show how past years tended to move from this point on the calendar. It is a planning tool, not a crystal ball: the goal is to quantify ranges and odds so you can size, place stops, set targets, and time entries with more realism. What Monte Carlo is and why quants rely on it • Definition . Monte Carlo simulation is a way to answer “what might happen next?” when there is randomness in the system. Instead of producing a single forecast, it generates thousands of alternate futures by repeatedly sampling random shocks and adding them to a model of how prices evolve. • Why it is used . Markets are noisy. A single point forecast hides risk. Monte Carlo gives a distribution of outcomes so you can reason in probabilities: the median path, the 68% band, the 95% band, tail risks, and the chance of hitting a specific level within a horizon. • Core strengths in quant finance . – Path-dependent questions : “What is the probability we touch a stop before a target?” “What is the expected drawdown on the way to my objective?” – Pricing and risk : Useful for path-dependent options, Value-at-Risk (VaR), expected shortfall (CVaR), stress paths, and scenario analysis when closed-form formulas are unrealistic. – Planning under uncertainty : Portfolio construction and rebalancing rules can be tested against a cloud of plausible futures rather than a single guess. • Why it fits trading workflows . It turns gut feel like “seasonality is supportive here” into quantitative ranges: “median path suggests +X% with a 68% band of ±Y%; stop at Z has only ~16% odds of being tagged in N days.” How this indicator builds its probability cone 1) Seasonal pattern discovery The script builds two day-of-year maps as new data arrives: • A return map where each calendar day stores an exponentially smoothed average of that day’s log return (yesterday→today). The smoothing (90% old, 10% new) behaves like an EWMA, letting older seasons matter while adapting to new information. • A volatility map that tracks the typical absolute return for the same calendar day. It calculates the day-of-year carefully (with leap-year adjustment) and indexes into a 365-slot seasonal array so “March 18” is compared with past March 18ths. This becomes the seasonal bias that gently nudges simulations up or down on each forecast day. 2) Choice of randomness engine You can pick how the future shocks are generated: • Daily mode uses a Gaussian draw with the seasonal bias as the mean and a volatility that comes from realized returns, scaled down to avoid over-fitting. It relies on the Box–Muller transform internally to turn two uniform random numbers into one normal shock. • Weekly mode uses bootstrap sampling from the seasonal return history (resampling actual historical daily drifts and then blending in a fraction of the seasonal bias). Bootstrapping is robust when the empirical distribution has asymmetry or fatter tails than a normal distribution. Both modes seed their random draws deterministically per path and day, which makes plots reproducible bar-to-bar and avoids flickering bands. 3) Volatility scaling to current conditions Markets do not always live in average volatility. The engine computes a simple volatility factor from ATR(20)/price and scales the simulated shocks up or down within sensible bounds (clamped between 0.5× and 2.0×). When the current regime is quiet, the cone narrows; when ranges expand, the cone widens. This prevents the classic mistake of projecting calm markets into a storm or vice versa. 4) Many futures, summarized by percentiles The model generates a matrix of price paths (capped at 100 runs for performance inside TradingView), each path stepping forward for your selected horizon. For each forecast day it sorts the simulated prices and pulls key percentiles: • 5th and 95th → approximate 95% band (outer cone). • 16th and 84th → approximate 68% band (inner cone). • 50th → the median or “expected path.” These are drawn as polylines so you can immediately see central tendency and dispersion. 5) A historical overlay (optional) Turn on the overlay to sketch a dotted path of what a purely seasonal projection would look like for the next ~30 days using only the return map, no randomness. This is not a forecast; it is a visual reminder of the seasonal drift you are biasing toward. Inputs you control and how to think about them Monte Carlo Simulation • Price Series for Calculation . The source series, typically close. • Enable Probability Forecasts . Master switch for simulation and drawing. • Simulation Iterations . Requested number of paths to run. Internally capped at 100 to protect performance, which is generally enough to estimate the percentiles for a trading chart. If you need ultra-smooth bands, shorten the horizon. • Forecast Days Ahead . The length of the cone. Longer horizons dilute seasonal signal and widen uncertainty. • Probability Bands . Draw all bands, just 95%, just 68%, or a custom level (display logic remains 68/95 internally; the custom number is for labeling and color choice). • Pattern Resolution . Daily leans on day-of-year effects like “turn-of-month” or holiday patterns. Weekly biases toward day-of-week tendencies and bootstraps from history. • Volatility Scaling . On by default so the cone respects today’s range context. Plotting & UI • Probability Cone . Plots the outer and inner percentile envelopes. • Expected Path . Plots the median line through the cone. • Historical Overlay . Dotted seasonal-only projection for context. • Band Transparency/Colors . Customize primary (outer) and secondary (inner) band colors and the mean path color. Use higher transparency for cleaner charts. What appears on your chart • A cone starting at the most recent bar, fanning outward. The outer lines are the ~95% band; the inner lines are the ~68% band. • A median path (default blue) running through the center of the cone. • An info panel on the final historical bar that summarizes simulation count, forecast days, number of seasonal patterns learned, the current day-of-year, expected percentage return to the median, and the approximate 95% half-range in percent. • Optional historical seasonal path drawn as dotted segments for the next 30 bars. How to use it in trading 1) Position sizing and stop logic The cone translates “volatility plus seasonality” into distances. • Put stops outside the inner band if you want only ~16% odds of a stop-out due to noise before your thesis can play. • Size positions so that a test of the inner band is survivable and a test of the outer band is rare but acceptable. • If your target sits inside the 68% band at your horizon, the payoff is likely modest; outside the 68% but inside the 95% can justify “one-good-push” trades; beyond the 95% band is a low-probability flyer—consider scaling plans or optionality. 2) Entry timing with seasonal bias When the median path slopes up from this calendar date and the cone is relatively narrow, a pullback toward the lower inner band can be a high-quality entry with a tight invalidation. If the median slopes down, fade rallies toward the upper band or step aside if it clashes with your system. 3) Target selection Project your time horizon to N bars ahead, then pick targets around the median or the opposite inner band depending on your style. You can also anchor dynamic take-profits to the moving median as new bars arrive. 4) Scenario planning & “what-ifs” Before events, glance at the cone: if the 95% band already spans a huge range, trade smaller, expect whips, and avoid placing stops at obvious band edges. If the cone is unusually tight, consider breakout tactics and be ready to add if volatility expands beyond the inner band with follow-through. 5) Options and vol tactics • When the cone is tight : Prefer long gamma structures (debit spreads) only if you expect a regime shift; otherwise premium selling may dominate. • When the cone is wide : Debit structures benefit from range; credit spreads need wider wings or smaller size. Align with your separate IV metrics. Reading the probability cone like a pro • Cone slope = seasonal drift. Upward slope means the calendar has historically favored positive drift from this date, downward slope the opposite. • Cone width = regime volatility. A widening fan tells you that uncertainty grows fast; a narrow cone says the market typically stays contained. • Mean vs. price gap . If spot trades well above the median path and the upper band, mean-reversion risk is high. If spot presses the lower inner band in an up-sloping cone, you are in the “buy fear” zone. • Touches and pierces . Touching the inner band is common noise; piercing it with momentum signals potential regime change; the outer band should be rare and often brings snap-backs unless there is a structural catalyst. Methodological notes (what the code actually does) • Log returns are used for additivity and better statistical behavior: sim_ret is applied via exp(sim_ret) to evolve price. • Seasonal arrays are updated online with EWMA (90/10) so the model keeps learning as each bar arrives. • Leap years are handled; indexing still normalizes into a 365-slot map so the seasonal pattern remains stable. • Gaussian engine (Daily mode) centers shocks on the seasonal bias with a conservative standard deviation. • Bootstrap engine (Weekly mode) resamples from observed seasonal returns and adds a fraction of the bias, which captures skew and fat tails better. • Volatility adjustment multiplies each daily shock by a factor derived from ATR(20)/price, clamped between 0.5 and 2.0 to avoid extreme cones. • Performance guardrails : simulations are capped at 100 paths; the probability cone uses polylines (no heavy fills) and only draws on the last confirmed bar to keep charts responsive. • Prerequisite data : at least ~30 seasonal entries are required before the model will draw a cone; otherwise it waits for more history. Strengths and limitations • Strengths : – Probabilistic thinking replaces single-point guessing. – Seasonality adds a small but meaningful directional bias that many markets exhibit. – Volatility scaling adapts to the current regime so the cone stays realistic. • Limitations : – Seasonality can break around structural changes, policy shifts, or one-off events. – The number of paths is performance-limited; percentile estimates are good for trading, not for academic precision. – The model assumes tomorrow’s randomness resembles recent randomness; if regime shifts violently, the cone will lag until the EWMA adapts. – Holidays and missing sessions can thin the seasonal sample for some assets; be cautious with very short histories. Tuning guide • Horizon : 10–20 bars for tactical trades; 30+ for swing planning when you care more about broad ranges than precise targets. • Iterations : The default 100 is enough for stable 5/16/50/84/95 percentiles. If you crave smoother lines, shorten the horizon or run on higher timeframes. • Daily vs. Weekly : Daily for equities and crypto where month-end and turn-of-month effects matter; Weekly for futures and FX where day-of-week behavior is strong. • Volatility scaling : Keep it on. Turn off only when you intentionally want a “pure seasonality” cone unaffected by current turbulence. Workflow examples • Swing continuation : Cone slopes up, price pulls into the lower inner band, your system fires. Enter near the band, stop just outside the outer line for the next 3–5 bars, target near the median or the opposite inner band. • Fade extremes : Cone is flat or down, price gaps to the upper outer band on news, then stalls. Favor mean-reversion toward the median, size small if volatility scaling is elevated. • Event play : Before CPI or earnings on a proxy index, check cone width. If the inner band is already wide, cut size or prefer options structures that benefit from range. Good habits • Pair the cone with your entry engine (breakout, pullback, order flow). Let Monte Carlo do range math; let your system do signal quality. • Do not anchor blindly to the median; recalc after each bar. When the cone’s slope flips or width jumps, the plan should adapt. • Validate seasonality for your symbol and timeframe; not every market has strong calendar effects. Summary The Seasonality Monte Carlo Forecaster wraps institutional risk planning into a single overlay: a data-driven seasonal drift, realistic volatility scaling, and a probabilistic cone that answers “where could we be, with what odds?” within your trading horizon. Use it to place stops where randomness is less likely to take you out, to set targets aligned with realistic travel, and to size positions with confidence born from distributions rather than hunches. It will not predict the future, but it will keep your decisions anchored to probabilities—the language markets actually speak.
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BackQuant tarafından
2
Multi-Timeframe Bias Dashboard + VolatilityWhat it is: A corner table (overlay) that gives a quick higher-timeframe read for Daily / 4H / 1H using EMA alignment, MACD, RSI, plus a volatility gauge. How it works (per timeframe): EMA block (50/100/200): “Above/Below/Mixed” based on price vs all three EMAs. MACD: “Bullish/Bearish/Neutral” from MACD line vs Signal and histogram sign. RSI: Prints the value and an ↑/↓ based on 50 line. Volatility: Compares ATR(14) to its SMA over 20 bars → High (>*1.2), Normal, Low (<*0.8). Bias: Combines three votes (EMA, MACD, RSI): Bullish if ≥2 bullish, Bearish if ≥2 bearish, else Mixed. Display: Rows: D / 4H / 1H. Columns: Bias, EMA(50/100/200), RSI, MACD, Volatility. Bias cell is color-coded (green/red/gray). Position setting lets you park the table in Top Right / Bottom Right / Bottom Left (works on mobile too). Use it for: Quickly aligning intraday setups with higher-TF direction. Skipping low-volatility periods. Confirming momentum (MACD/RSI) when price returns to your OB/FVG zones.
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muddydefenders tarafından
Aladin 2.0 — Invite‑Only (Custom Smoother + Supertrend Filter)Aladin 2.0 invite‑only by @AryaTrades69 Overview Aladin 2.0 blends a proprietary multi‑stage smoother baseline, volatility envelopes, and a Supertrend‑based ATR trailing filter to structure clean, bar‑close signals. Optional “golden‑zone style” retracement gating and mapped SL/TP zones are included. This is a tool for analysis, accuracy is best when you add manual confluence (trendlines, support/resistance) to filter out low‑quality signals. What’s inside Proprietary multi‑stage smoother (baseline) Custom smoothed baseline with adjustable length and a smoothing coefficient. Drives core breakout logic without revealing internal formulas. Volatility envelopes Breakout candidates when price closes beyond adaptive volatility bands. Supertrend‑based trend filter (optional, MTF) ATR‑trailing regime filter to keep signals aligned with trend; can run on higher timeframes. Golden‑zone style retracement gate (optional) Only allow signals within a defined pullback zone of the recent range. Spacing & structure controls Minimum bars between signals plus a simple HH/LL gate to avoid clustered whipsaws. SL/TP mapping (optional) SL from most recent confirmed swing; ATR fallback if no swing is found. TP1/TP2/TP3 by user‑defined R:R; move SL to breakeven at TP1. Shaded zones for SL and target area (time‑limited for clarity). How to use Choose your timeframe (intraday to swing). Signals compute on bar close. Enable the trend filter for strictly trend‑aligned entries (Supertrend‑based ATR trail). MTF is supported. Use the golden‑zone gate to prioritize higher‑quality pullbacks. Validate with manual confluence: Trendlines, structure breaks Support/resistance or supply/demand Session/volatility context Optionally enable SL/TP areas, set R:R, and configure alerts. Inputs (key controls) Smoother length & smoothing coefficient (baseline sensitivity/lag) Range period & multiplier (volatility envelopes) Min bars between signals (signal frequency) Trend filter (ATR trail): factor, ATR period, line smoothing, optional higher timeframe Golden‑zone retracement: lookback, min/max bounds SL/TP: swing lookback, ATR fallback, TP1/2/3 R:R, zone display width Alerts Long/Short signal on bar close TP1/TP2/TP3 hit SL hit / Breakeven event (Setup: Add Alert → Condition: Aladin 2.0 → choose event) MTF & repaint policy Signals are calculated on bar close; the trend filter uses security with lookahead off. Swing‑based SL uses confirmed pivots. With an HTF filter enabled on an LTF chart, the HTF line/state finalizes when the HTF bar closes (standard MTF behavior). Best practices Not a set‑and‑forget system. Accuracy improves when you manually filter weaker signals with trendlines and support/resistance, and prioritize clean market structure. Consider conservative settings or the trend filter during choppy, low‑volatility periods. Access Invite‑Only. Request access via TradingView PM to @AryaTrades69. Redistribution or code extraction is not permitted. Disclaimer For educational purposes only. Not financial advice. No guarantees of profitability. Trading involves risk. Do your own research. Changelog (v2.0) Optional MTF ATR‑trail trend filter (Supertrend concept) Golden‑zone style retracement gating Min‑bars spacing and basic HH/LL gating SL/TP mapping with BE at TP1 and shaded zones Stability and performance improvements
Pine Script® göstergesi
AryaTrades69 tarafından
Enhanced Circle CandlestickEnhanced Circle Candlestick This script transforms standard candlesticks into circles, visualizing momentum, volume, and volatility in a unique way. The size and color of the circles change based on the body size of the candlestick, while a change in color signifies a volume spike. Long wicks are also highlighted, providing a quick visual cue for potential reversals or indecision. Features Circle Visualization: Replaces the standard candlestick body with a circle. The size of the circle is determined by the size of the candlestick body, making it easy to spot periods of high momentum.Gradient Color: The circle's opacity changes based on the body size. Smaller bodies have a lighter color, while larger, more powerful bodies have a darker, more vivid color. This visual gradient provides a clear indication of a bar's strength.Volume Spike Highlight: The circle's color will change to a bright yellow when the current volume exceeds the average volume by a user-defined factor, indicating a significant influx of buying or selling pressure.Long Wick Markers: The script draws a small triangle above or below the candlestick when a wick's length surpasses a user-defined percentage of the body's size. This helps identify potential exhaustion, rejection, or indecision in the market. Settings Bullish/Bearish Color: Customize the base colors for bullish (green) and bearish (red) circles.Volume Spike Color: Choose the color for the circle when a volume spike occurs.Volume Spike Factor: Set the multiplier for the volume spike detection. For example, a value of 2.0 means a volume spike is detected when the current volume is twice the 20-period moving average.Circle Opacity (0-100): Adjust the base transparency of the circles. Lower numbers result in more opaque (solid) colors.Opacity Factor: Controls how quickly the color gradient changes based on the body size. A higher value makes the color change more dramatic.Wick Length Factor (vs Body): Set the threshold for marking long wicks. A value of 0.8 means a wick is marked if its length is 80% or more of the candlestick body's size. How to Use Add this indicator to your chart.Open the Chart Settings.In the "Symbol" tab, set the transparency of the candlestick "Body" to 0%. (This step is essential because the indicator's settings will not be applied when the indicator is not selected, and the default platform settings take precedence.) I do not speak English at all. Please understand that if you send me a message, I may not be able to reply, or my reply may have a different meaning. Thank you for your understanding.
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ALT_analyst tarafından
[Top] ≈ SyncLineFind the hidden currents between markets. What it does SyncLine overlays up to three cross-asset guide lines on your current chart, translating each selected symbol’s intraday position into the price scale of the chart you’re viewing. The result is a clean, session-aware “sync” of other markets on your chart so you can quickly spot alignment, leadership, and divergence without clutter. How it works For each selected symbol, SyncLine calculates that symbol’s intraday position relative to its own session baseline, then projects that position onto your active chart based on its own baseline. Lines reset each session to remain relevant to the current day’s action. Optional smoothing makes the guides easier to read during noisy tape. Note: This script is intraday-only . It will stop with a clear warning if applied to non-intraday timeframes. Inputs Symbols Show Symbol 1/2/3 – Toggle each overlay line. Symbol 1/2/3 – Choose any ticker (e.g., index futures, ETFs, single names). Color 1/2/3 – Line colors. Labels - Optional labels for each line. Smoothing Enable Smoothing – On/Off. Method – EMA / SMA / WMA / RMA. Length – 1–50. How to use Add one or more driver markets (e.g., ES, NQ, DXY, sector leaders) to observe when they align with your instrument. Look for: Confluence : your price and one or more SyncLines moving together. Leadership : a SyncLine turns/accelerates before your price. Divergence : your price disagrees with the majority of SyncLines. Notes & limitations Designed for intraday timeframes (1m–1h). Lines are calculated from completed data and do not repaint after bar close . Works best during regular liquid sessions ; thin markets can reduce signal quality. Best practices Pair SyncLine with your execution framework (structure, liquidity zones, time-of-day). Use distinct colors for each symbol and keep the set small (1–3) for clarity.
Pine Script® göstergesi
TopTradesUA tarafından
Tony O's Euler BandsTony O’s Euler Bands is a volatility-based overlay that uses the mathematical constant e (~2.71828) to scale price bands in a non-linear way. Unlike traditional Bollinger Bands or Keltner Channels, these bands are spaced by exponential functions of volatility (σ), creating zones that expand and contract more dynamically across different market regimes. How it works: A configurable moving average (EMA/SMA/RMA/WMA) is used as the basis. Volatility (σ) is calculated as the standard deviation of returns over a user-defined lookback. Four band levels are plotted above and below the basis at distances equal to: basis × 𝑒^(𝑚⋅𝜎⋅𝑘) where m is a user multiplier and k = {2, 4, 6, 8} for each successive band. This produces inner bands that highlight mild deviations and outer bands that signal extreme moves. What makes it unique: Uses e as the base for band expansion instead of linear multiples or Fibonacci ratios. Bands scale multiplicatively, making them more consistent across assets and price scales. Multiple symmetric bands per side, color-coded from green (mild) to purple (extreme) for intuitive visual cues. Optional transparent fill to show volatility envelopes without obscuring price action. How to use: Trend monitoring: Sustained closes beyond an inner band can indicate momentum; closes beyond outer bands can signal overextension. Reversion spotting: Touches on extreme bands (level 4) can highlight potential exhaustion points. Works on any asset/timeframe; adjust basis length, volatility lookback, and multiplier to suit your market.
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tonyo8187 tarafından