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TTM Squeeze Screener [Pineify]TTM Squeeze Screener for Multiple Crypto Assets and Timeframes This advanced TradingView Pine script, TTM Squeeze Screener, helps traders scan multiple crypto symbols and timeframes simultaneously, unlocking new dimensions in momentum and volatility analysis. Key Features Screen up to 8 crypto symbols across 4 different timeframes in one pane TTM Squeeze indicator detects volatility contraction and expansion (“squeeze”) phases Momentum filter reveals potential breakout direction and strength Visual screener table for intuitive multi-asset monitoring Fully customizable for symbols and timeframes How It Works The heart of this screener is the TTM Squeeze algorithm—a hybrid volatility and momentum indicator leveraging Bollinger Bands, Keltner Channels, and linear momentum analysis. The script checks whether Bollinger Bands are “squeezed” inside Keltner Channels, flagging periods of low volatility primed for expansion. Once a squeeze is released, the included momentum calculation suggests the likely breakout direction. For each selected symbol and timeframe, the screener runs the TTM Squeeze logic, outputs “SQUEEZE” or “NO SQZ”, and tags momentum values. A table layout organizes the results, allowing rapid pattern recognition across symbols. Trading Ideas and Insights Spot multi-symbol volatility clusters—ideal for finding synchronized market moves Assess breakout potential and direction before entering trades Scalping and swing trading decisions are enhanced by cross-timeframe momentum filtering Portfolio managers can quickly identify which assets are about to move How Multiple Indicators Work Together This screener unites three essential concepts: Bollinger Bands : Measure volatility using standard deviation of price Keltner Channels : Define expected price range based on average true range (ATR) Momentum : Linear regression calculation to evaluate the direction and intensity after a squeeze By combining these, the indicator not only signals when volatility compresses and releases, but also adds directional context—filtering false signals and helping traders time entries and exits more precisely. Unique Aspects Multi-symbol, multi-timeframe architecture—optimized for crypto traders and market scanners Advanced table visualization—see all signals at a glance, minimizing cognitive overload Modular calculation functions—easy to adapt and extend for other asset classes or strategies Real-time, low-latency screening—built for actionable alerts on fast-moving markets How to Use Add the script to a TradingView chart (works on custom layouts) Select up to 8 symbols and 4 timeframes using input fields (defaults to BTCUSD, ETHUSD, etc.) Monitor the screener table; “SQUEEZE” highlights assets in potential breakout phase Use momentum values to judge if the squeeze is likely bullish or bearish Combine screener insights with manual chart analysis for optimal results Customization Symbols: Easily set any ticker for deep market scanning Timeframes: Adjust to match your trading horizon (scalping, swing, long-term) Indicator parameters: Refine Bollinger/Keltner/Momentum settings for sensitivity Visuals: Personalize table layout, color codes, and formatting for clarity Conclusion In summary, the TTM Squeeze Screener is a robust, original TradingView indicator designed for crypto traders who demand a sophisticated multi-symbol, multi-timeframe edge. Its combination of volatility and momentum analytics makes it ideal for catching explosive breakouts, managing risk, and scanning the market efficiently. Whether you’re a scalper or swing trader, this screener provides the insights needed to stay ahead of the curve.
Pine Script®指標
由Pineify提供
3
Seasonal Pattern DecoderSeasonal Pattern Decoder The Seasonal Pattern Decoder is a powerful tool designed for traders and analysts who want to uncover and leverage seasonal tendencies in financial markets. Instead of cluttering your chart with complex visuals, this indicator presents a clean, intuitive table that summarizes historical monthly performance, allowing you to spot recurring patterns at a glance. How It Works The indicator fetches historical monthly data for any symbol and calculates the percentage return for each month over a specified number of years. It then organizes this data into a comprehensive table, providing a clear, year-by-year and month-by-month breakdown of performance. Key Features Historical Performance Table: Displays monthly returns for up to a user-defined number of years, making it easy to compare performance across different periods. Color-Coded Heatmap: Each cell is colored based on the performance of the month. Strong positive returns are shaded in green, while strong negative returns are shaded in red, allowing for immediate visual analysis of monthly strength or weakness. Annual Summary: A "Σ" column shows the total percentage return for each full calendar year. AVG Row: Calculates and displays the average return for each month across all the years shown in the table. WR Row: Shows the "Win Rate" for each month, which is the percentage of time that month had a positive return. This is crucial for identifying high-probability seasonal trends. How to Use Add the "Seasonal Pattern Decoder" indicator to your chart. Note that it works best on Daily, Weekly, or Monthly timeframes. A warning message will be displayed on intraday charts. In the indicator settings, adjust the "Lookback Period" to control how many years of historical data you want to analyze. Use the "Show Years Descending" option to sort the table from the most recent year to the oldest. The "Heat Range" setting allows you to adjust the sensitivity of the color-coding to fit the volatility of the asset you are analyzing. This tool is ideal for confirming trading biases, developing seasonal strategies, or simply gaining a deeper understanding of an asset's typical behavior throughout the year. ## Disclaimer This indicator is designed as a technical analysis tool and should be used in conjunction with other forms of analysis and proper risk management. Past performance does not guarantee future results, and traders should thoroughly test any strategy before implementing it with real capital.
Pine Script®指標
由dchunt-stack提供
3
Volume Percentile Supertrend [BackQuant]Volume Percentile Supertrend A volatility and participation aware Supertrend that automatically widens or tightens its bands based on where current volume sits inside its recent distribution. The goal is simple: fewer whipsaws when activity surges, faster reaction when the tape is quiet. What it does Calculates a standard Supertrend framework from an ATR on a volume weighted price source. Measures current volume against its recent percentile and converts that context into a dynamic ATR multiplier. Widens bands when volume is unusually high to reduce chop. Tightens bands when volume is unusually low to catch turns earlier. Paints candles, draws the active Supertrend line and optional bands, and prints clear Long and Short signal markers. Why volume percentile Fixed ATR multipliers assume all bars are equal. They are not. When participation spikes, price swings expand and a static band gets sliced. Percentiles place the current bar inside a recent distribution. If volume is in the top slice, the Supertrend allows more room. If volume is in the bottom slice, it expects smaller noise and tightens. This keeps the same playbook usable across busy sessions and sleepy ones without constant manual retuning. How it works Volume distribution - A rolling window computes the Pth percentile of volume. Above that is flagged as high volume. A lower reference percentile marks quiet bars. Dynamic multiplier - Start from a Base Multiplier. If bar is high volume, scale it up by a function of volume-to-average and a Sensitivity knob. If bar is low volume, scale it down. Smooth the result with an EMA to avoid jitter. VWMA source - The price input for bands is a short volume weighted moving average of close. Heavy prints matter more. ATR envelope - Compute ATR on your length. UpperBasic = VWMA + Multiplier x ATR. LowerBasic = VWMA - Multiplier x ATR. Trailing logic - The final lines trail price so they only move in a direction that preserves Supertrend behavior. This prevents sudden flips from transient pokes. Direction and signals - Direction flips when price crosses through the relevant trailing line. SupertrendLong and SupertrendShort mark those flips. The plotted Supertrend is the active trailing side. Inputs and what they change Volume Lookback - Window for percentile and average. Larger window = stabler percentile, smaller = snappier. Volume Percentile Level - Threshold that defines high volume. Example 70 means top 30 percent of recent bars are treated as high activity. Volume Sensitivity - Gain from volume ratio to the dynamic multiplier. Higher = bands expand more when volume spikes. VWMA Source Length - Smoothing of the volume weighted price source for the bands. ATR Length - Standard ATR window. Larger = slower, smaller = quicker. Base Multiplier - Core band width before volume adjustment. Think of this as your neutral volatility setting. Multiplier Smoothing - EMA on the dynamic multiplier. Reduces back and forth changes when volume oscillates around the threshold. Show Supertrend on chart - Toggles the active line. Show Upper Lower Bands - Draws both sides even when inactive. Good for context. Paint candles according to Trend - Colors bars by trend direction. Show Long and Short Signals - Prints 𝕃 and 𝕊 markers at flips. Colors - Choose your long and short palette. Reading the plot Supertrend line - Thick line that hugs price from above in downtrends and from below in uptrends. Its distance breathes with volume. Bands - Optional upper and lower rails. Useful to see the inactive side and judge how wide the envelope is right now. Signals - 𝕃 prints when the trend flips long. 𝕊 prints when the trend flips short. Candle colors - Quick bias read at a glance when painting is enabled. Typical workflows Trend following - Use 𝕃 flips to initiate longs and ride while bars remain colored long and price respects the lower trailing line. Mirror for shorts with 𝕊 and the upper trailing line. During high volume phases the line will give more room, which helps stay in the move. Pullback adds - In an established trend, shallow tags toward the active line after a high volume expansion can be add points. The dynamic envelope adjusts to the session so your add distance is not fixed to a stale volatility regime. Mean reversion filter - In quiet tape the multiplier contracts and flips come earlier. If you prefer fading, watch for quick toggles around the bands when volume percentile remains low. In high volume, avoid fading into the widened line unless you have other strong reasons. Notes on behavior High volume bar: the percentile gate opens, volRatio > 1 powers up the multiplier through the Sensitivity lever, bands widen, fewer false flips. Low volume bar: multiplier contracts, bands tighten, flips can happen earlier which is useful when you want to catch regime changes in quiet conditions. Smoothing matters: both the price source (VWMA) and the multiplier are smoothed to keep structure readable while still adapting. Quick checklist If you see frequent chop and today feels busy: check that volume is above your percentile. Wider bands are expected. Consider letting the trend prove itself against the expanded line before acting. If everything feels slow and you want earlier entries: percentile likely marks low volume, so bands tighten and 𝕃 or 𝕊 can appear sooner. If you want more or fewer flips overall: adjust Base Multiplier first. If you want more reaction specifically tied to volume surges: raise Volume Sensitivity. If the envelope breathes too fast: raise Multiplier Smoothing. What the signals mean SupertrendLong - Direction changed from non-long to long. 𝕃 marker prints. The active line switches to support below price. SupertrendShort - Direction changed from non-short to short. 𝕊 marker prints. The active line switches to resistance above price. Trend color - Bars painted long or short help validate context for entries and management. Summary Volume Percentile Supertrend adapts the classic Supertrend to the day you are trading. Volume percentile sets the mood, sensitivity translates it into dynamic band width, and smoothing keeps it clean. The result is a single plot that aims to stay conservative when the tape is loud and act decisively when it is quiet, without you having to constantly retune settings.
Pine Script®指標
由BackQuant提供
Opening Candle Zone with ATR Bands by nkChartsThis indicator highlights the opening range of each trading session and projects dynamic ATR-based zones around it. Key Features Plots high and low levels of the opening candle for each new daily session. Extends these levels across the session, providing clear intraday support and resistance zones. Adds ATR-based offset bands above and below the opening range for volatility-adjusted levels. Customizable colors, ATR length, and multiplier for flexible use across markets and timeframes. Adjustable session history limit to control how many past levels remain on the chart. How to Use: The opening range high/low often acts as strong intraday support or resistance. The ATR bands give an adaptive volatility buffer, useful for breakout or mean-reversion strategies. Works on any market with clear session opens. This tool is designed for traders who want to combine session-based price action with volatility insights, helping identify potential breakouts, reversals, or consolidation areas throughout the day. ⚠️ Disclaimer: This indicator is for educational purposes only. It does not provide financial advice or guarantee profits. Always perform your own analysis before making trading decisions.
Pine Script®指標
由nkCharts提供
Z-Score Trend Channels [BackQuant]Z-Score Trend Channels A self-contained price-statistics framework that turns a rolling z-score into price channels, bias states, and trade markers. Run either trend-following or mean-reversion from the same tool with clear, on-chart context. What it is A rolling statistical map that measures how far price is from its recent average in standard-deviation units (z-score). Adaptive channels drawn in price space from fixed z thresholds, so the rails breathe with volatility. A simple trend proxy from z-score momentum to separate trending from ranging conditions. On-chart signals for pullback entries, stretched extremes, and practical exits. Core idea (plain English math) Rolling mean and volatility - Over a lookback you get the average price and its standard deviation. Z-score - How many standard deviations the current price is above or below its average: z = (price - mean) / stdev. z near 0 means near average; positive is above; negative is below. Noise control - An EMA smooths the raw z to reduce jitter and false flickers. Channels back in price - Fixed z levels are converted back to price to form the upper, lower, and extreme rails. Trend proxy - A smoothed change in z is used as a lightweight trend-strength line. Positive strength with positive z favors uptrend; negative strength with negative z favors downtrend. What you see on the chart Channels and fills - Mean, upper, lower, and optional extreme lines. The area mean->upper tints with the bearish color, mean->lower tints with the bullish color. Background tint (optional) - Soft green, red, or neutral based on detected trend state. Signals - Bullish Entry (triangle up) when z exits the oversold zone upward; Bearish Entry (triangle down) when z exits the overbought zone downward; Extreme markers (diamonds) at the extreme bands with a one-bar turn. Table - Current z, trend state, trend strength, distance to bands, market state tag, and a quick volatility regime label. Edge labels - MEAN, OB, and OS labels slightly projected forward with level values. Inputs you will actually use Z-Score Period - Lookback for mean and stdev. Larger = slower and steadier rails, smaller = more reactive. Smoothing Period - EMA on z. Lower = earlier but choppier flips; higher = later but cleaner. Price Source - Default hlc3. Choose close if you prefer session-close logic. Upper and Lower Thresholds - Default around +2.0 and -2.0. Tighten for more signals, widen for fewer and stronger. Extreme Upper and Lower - Deeper stretch guards, e.g., +/- 2.5. Strength Period - EMA on z momentum. Sets how fast the trend proxy flips. Trend Threshold - Minimum absolute z to accept a directional bias. Visual toggles - Channels, signals, background tint, stats table, colors, and optional last-bar trend label. How to use it: trend-following playbook Read the state - Uptrend when z > Trend Threshold and trend strength > 0. Downtrend when z < -Trend Threshold and trend strength < 0. Neutral otherwise. Entries - In an uptrend, prefer Bullish Entry signals that fire near the lower channel. In a downtrend, prefer Bearish Entry signals that fire near the upper channel. Stops - Conservative: beyond the extreme channel on your side. Tighter: just outside the standard band that framed the signal. Exits - For longs, exit or trim on a cross back through z = 0 or a clean tag of the upper threshold. For shorts, mirror with z = 0 up-cross or tag of the lower threshold. You can also reduce if trend strength flips against you. Adds - In strong trends, additional signals near your side’s band can be add points. Avoid adding once z hovers near the opposite band for several bars. How to use it: mean-reversion playbook Find stretch - Standard reversions: Bullish Entry when z leaves the oversold zone upward; Bearish Entry when z leaves the overbought zone downward. Aggressive reversions: Extreme markers at extreme bands with a one-bar turn. Entries - Take the signal as price exits the zone. Prefer setups where trend strength is near zero or tilting against the prior push. Targets - First target is the mean line. A runner can aim for the opposite standard channel if momentum keeps flipping. Stops - Outside the extreme band beyond your entry. If fading without extremes, place risk just beyond the opposite standard band. Filters - Optional: skip counter-trend fades against a very strong trend state unless your risk is tight and predefined. Reading the stats table Current Z-Score - Magnitude and sign of displacement now. Trend State - Uptrend, Downtrend, or Ranging. Trend Strength - Smoothed z momentum. Higher absolute values imply stronger directional conviction. Distance to Upper/Lower - Percent distance from price to each band, useful for sizing targets or judging room left. Market State - Overbought, Oversold, Extreme OB, Extreme OS, or Normal. Volatility Regime - High, Normal, or Low relative to recent distribution. Expect bands to widen in High and tighten in Low. Parameter guidance (conceptual) Z-Score Period - Choose longer for a structural mean, shorter for a reactive mean. Smoothing Period - Lower for earlier but noisier reads; higher for slower but steadier reads. Thresholds - Start around +/- 2.0. Tighten for scalping or quiet ranges. Widen for noisy or fast markets. Trend Threshold and Strength Period - Raise to avoid weak, transient bias. Lower to capture earlier regime shifts. Practical examples Trend pullback long - State shows Uptrend. Price tests the lower channel; z dips near or below the lower threshold; a Bullish Entry prints. Stop just below extreme lower; first target mean; keep a runner if trend strength stays positive. Mean-revert short - State is Ranging. z tags the extreme upper, an Extreme Bearish marker prints, then a Bearish Entry prints on the leave. Stop above extreme upper; target the mean; consider a runner toward the lower channel if strength turns negative. Potential Questions you might have Why z-score instead of fixed offsets - Because the bands adapt with volatility. When the tape gets quiet the rails tighten, when it runs hot the rails expand. Your entries stay normalized. Do I need both modes - No. Many users run only trend pullbacks or only mean-reversions. The tool lets you toggle what you need and keep the chart readable. Multi-timeframe workflow - A common approach is to set bias from a higher timeframe’s trend state and execute on a lower timeframe’s signals that align with it. Summary Z-Score Trend Channels gives you an adaptive mean, volatility-aware rails, a simple trend lens, and clear signals. Trade the trend by buying pullbacks in green and selling pullbacks in red, or fade stretched extremes back to the mean with defined risk. One framework, two strategies, consistent logic.
Pine Script®指標
由BackQuant提供
MACD Josh MACD Study — Visual Crossover Tags Overview: This script displays MACD signals in a clear, visual way by showing: Histogram = EMA(Fast) − EMA(Slow) Signal = EMA(Histogram, Signal Length) It adds labels and arrows to help you see crossover events between the Histogram and the Signal line more easily. ⚠️ Disclaimer: This tool is for educational and research purposes only. It is not financial advice or an investment recommendation. Past performance does not guarantee future results. Users should make their own decisions and manage risk responsibly. Features Central Zero Line with Signal and Histogram plots Optional labels/arrows to highlight Histogram–Signal crossovers Alerts for crossover and crossunder events, integrated with TradingView’s alert system Standard adjustable inputs: Fast EMA, Slow EMA, Signal EMA How to Interpret (for study only) When the Histogram crosses above the Signal, a visual label/arrow marks a positive MACD event When the Histogram crosses below the Signal, a visual label/arrow marks a negative MACD event The “BUY/SELL” labels are visual study tags only — they do not represent trade instructions or recommendations Responsible Usage Tips Test across multiple timeframes and different assets Combine with higher-timeframe trend, support/resistance, or volume for confirmation Use alerts with caution, and always test in a demo environment first Technical Notes The script does not use future data and does not repaint signals once bars are closed Results depend on market conditions and may vary across assets and timeframes License & Credits Written in Pine Script® v5 for TradingView The indicator name shown on chart is for labeling purposes only and carries no implication of advice or solicitation
Pine Script®指標
由JOSHSniper4569提供
Options Max Pain Calculator [BackQuant]Options Max Pain Calculator A visualization tool that models option expiry dynamics by calculating "max pain" levels, displaying synthetic open interest curves, gamma exposure profiles, and pin-risk zones to help identify where market makers have the least payout exposure. What is Max Pain? Max Pain is the theoretical expiration price where the total dollar value of outstanding options would be minimized. At this price level, option holders collectively experience maximum losses while option writers (typically market makers) have minimal payout obligations. This creates a natural gravitational pull as expiration approaches. Core Features Visual Analysis Components: Max Pain Line: Horizontal line showing the calculated minimum pain level Strike Level Grid: Major support and resistance levels at key option strikes Pin Zone: Highlighted area around max pain where price may gravitate Pain Heatmap: Color-coded visualization showing pain distribution across prices Gamma Exposure Profile: Bar chart displaying net gamma at each strike level Real-time Dashboard: Summary statistics and risk metrics Synthetic Market Modeling** Since Pine Script cannot access live options data, the indicator creates realistic synthetic open interest distributions based on configurable market parameters including volume patterns, put/call ratios, and market maker positioning. How It Works Strike Generation: The tool creates a grid of option strikes centered around the current price. You can control the range, density, and whether strikes snap to realistic market increments. Open Interest Modeling: Using your inputs for average volume, put/call ratios, and market maker behavior, the indicator generates synthetic open interest that mirrors real market dynamics: Higher volume at-the-money with decay as strikes move further out Adjustable put/call bias to reflect current market sentiment Market maker inventory effects and typical short-gamma positioning Weekly options boost for near-term expirations Pain Calculation: For each potential expiry price, the tool calculates total option payouts: Call options contribute pain when finishing in-the-money Put options contribute pain when finishing in-the-money The strike with minimum total pain becomes the Max Pain level Gamma Analysis: Net gamma exposure is calculated at each strike using standard option pricing models, showing where hedging flows may be most intense. Positive gamma creates price support while negative gamma can amplify moves. Key Settings Basic Configuration: Number of Strikes: Controls grid density (recommended: 15-25) Days to Expiration: Time until option expiry Strike Range: Price range around current level (recommended: 8-15%) Strike Increment: Spacing between strikes Market Parameters: Average Daily Volume: Baseline for synthetic open interest Put/Call Volume Ratio: Market sentiment bias (>1.0 = bearish, <1.0 = bullish) It does not work if set to 1.0 Implied Volatility: Current option volatility estimate Market Maker Factors: Dealer positioning and hedging intensity Display Options: Model Complexity: Simple (line only), Standard (+ zones), Advanced (+ heatmap/gamma) Visual Elements: Toggle individual components on/off Theme: Dark/Light mode Update Frequency: Real-time or daily calculation Reading the Display Dashboard Table (Top Right): Current Price vs Max Pain Level Distance to Pain: Percentage gap (smaller = higher pin risk) Pin Risk Assessment: HIGH/MEDIUM/LOW based on proximity and time Days to Expiry and Strike Count Model complexity level Visual Elements: Red Line: Max Pain level where payout is minimized Colored Zone: Pin risk area around max pain Dotted Lines: Major strike levels (green = support, orange = resistance) Color Bar: Pain heatmap (blue = high pain, red = low pain/max pain zones) Horizontal Bars: Gamma exposure (green = positive, red = negative) Yellow Dotted Line: Gamma flip level where hedging behavior changes Trading Applications Expiration Pinning: When price is near max pain with limited time remaining, there's increased probability of gravitating toward that level as market makers hedge their positions. Support and Resistance: High open interest strikes often act as magnets, with max pain representing the strongest gravitational pull. Volatility Expectations: Above gamma flip: Expect dampened volatility (long gamma environment) Below gamma flip: Expect amplified moves (short gamma environment) Risk Assessment: The pin risk indicator helps gauge likelihood of price manipulation near expiry, with HIGH risk suggesting potential range-bound action. Best Practices Setup Recommendations Start with Model Complexity set to "Standard" Use realistic strike ranges (8-12% for most assets) Set put/call ratio based on current market sentiment Adjust implied volatility to match current levels Interpretation Guidelines: Small distance to pain + short time = high pin probability Large gamma bars indicate key hedging levels to monitor Heatmap intensity shows strength of pain concentration Multiple nearby strikes can create wider pin zones Update Strategy: Use "Daily" updates for cleaner visuals during trading hours Switch to "Every Bar" for real-time analysis near expiration Monitor changes in max pain level as new options activity emerges Important Disclaimers This is a modeling tool using synthetic data, not live market information. While the calculations are mathematically sound and the modeling realistic, actual market dynamics involve numerous factors not captured in any single indicator. Max pain represents theoretical minimum payout levels and suggests where natural market forces may create gravitational pull, but it does not guarantee price movement or predict exact expiration levels. Market gaps, news events, and changing volatility can override these dynamics. Use this tool as additional context for your analysis, not as a standalone trading signal. The synthetic nature of the data makes it most valuable for understanding market structure and potential zones of interest rather than precise price prediction. Technical Notes The indicator uses established option pricing principles with simplified implementations optimized for Pine Script performance. Gamma calculations use standard financial models while pain calculations follow the industry-standard definition of minimized option payouts. All visual elements use fixed positioning to prevent movement when scrolling charts, and the tool includes performance optimizations to handle real-time calculation without timeout errors.
Pine Script®指標
由BackQuant提供
23
Price Level Highlighter [ldlwtrades]This indicator is a minimalist and highly effective tool designed for traders who incorporate institutional concepts into their analysis. It automates the identification of key psychological price levels and adds a unique, dynamic layer of information to help you focus on the most relevant area of the market. Inspired by core principles of market structure and liquidity, it serves as a powerful visual guide for anticipating potential support and resistance. The core idea is simple: specific price points, particularly those ending in round numbers or common increments, often act as magnets or barriers for price. While many indicators simply plot static lines, this tool goes further by intelligently highlighting the single most significant level in real-time. This dynamic feature allows you to quickly pinpoint where the market is currently engaged, offering a clear reference point for your trading decisions. It reduces chart clutter and enhances your focus on the immediate price action. Features Customizable Price Range: Easily define a specific Start Price and End Price to focus the indicator on the most relevant area of your chart, preventing unnecessary clutter. Adjustable Increment: Change the interval of the lines to suit your trading style, from high-frequency increments (e.g., 10 points) for scalping to wider intervals (e.g., 50 or 100 points) for swing trading. Intelligent Highlighting: A key feature that automatically identifies and highlights the single horizontal line closest to the current market price with a distinct color and thickness. This gives you an immediate visual cue for the most relevant price level. Highly Customizabile: Adjust the line color, style, and width for both the main lines and the highlighted line to fit your personal chart aesthetic. Usage Apply the indicator to your chart. In the settings, input your desired price range (Start Price and End Price) to match the market you are trading. Set the Price Increment to your preferred density. Monitor the chart for the highlighted line. This is your active price level and a key area of interest. Combine this tool with other confirmation signals (e.g., order blocks, fair value gaps, liquidity pools) to build higher-probability trade setups. Best Practices Pairing: This tool is effective across all markets, including stocks, forex, indices, and crypto. It is particularly useful for volatile markets where price moves rapidly between psychological levels. Mindful Analysis: Use the highlighted level as a reference point for your analysis, not as a standalone signal. A break above or below this level can signify a shift in market control. Backtesting: Always backtest the indicator on your preferred market and timeframe to understand how it performs under different conditions.
Pine Script®指標
由ldlwtrades提供
Dynamic Stop Loss Optimizer [BackQuant]Dynamic Stop Loss Optimizer Overview Stop placement decides expectancy. This tool gives you three professional-grade, adaptive stop engines, ATR, Volatility, and Hybrid. So your exits scale with current conditions instead of guessing fixed ticks. It trails intelligently, redraws as the market evolves, and annotates the chart with clean labels/lines and a compact stats table. Pick the engine that fits the trade, or switch on the fly. What it does Calculates three adaptive stops in real time (ATR-based, Volatility-based, and Hybrid) and keeps them trailed as price makes progress. Shows exactly where your risk lives with on-chart levels, color-coded markers (long/short), and precise “Risk %” labels at the current bar. Surfaces context you actually use - current ATR, daily volatility, selected method, and the live stop level—in a tidy, movable table. Fires alerts on stop hits so you can automate exits or journal outcomes without staring at the screen. Why it matters Adaptive risk control: Stops expand in fast tape and tighten in quiet tape. You’re not punished for volatility; you’re aligned with it. Consistency across assets: The same playbook works whether you’re trading indexes, FX, crypto, or equities, because the engine normalizes to each symbol’s behavior. Cleaner decision-making: One chart shows your entry idea and its invalidation in the same breath. If price trespasses, you know it instantly. The three methods (choose your engine) 1) ATR Based “Structure-aware” distance This classic approach keys off Average True Range to set a stop just beyond typical bar-to-bar excursion. It adapts smoothly to changing ranges and respects swing structure. Use when: you want a steady, intuitive buffer that tracks trend legs without hugging price. See it in action: 2) Volatility Based “Behavior-aware” distance This engine derives stop distance from current return volatility (annualized, then scaled back down to the session). It reacts to regime shifts quickly and normalizes risk across symbols with very different prices. Use when: you want the stop to breathe with realized volatility and respond faster to heat-ups/cool-downs. See it in action: 3) Hybrid “Best of both worlds” The Hybrid blends the ATR and Volatility distances into one consensus level, then trails it intelligently. You get the structural common sense of ATR and the regime sensitivity of Vol. Use when: you want robust, all-weather behavior without micromanaging inputs. See it in action: How it trails Longs: The stop ratchets up with favorable movement and holds its ground on shallow pullbacks. If price closes back into the risk zone, the level refreshes to the newest valid distance. Shorts: Mirror logic ratchets down with trend, resists noise, and refreshes if price reclaims the zone. Hybrid trailing: Uses the blended distance and the same “no give-backs” principle to keep gains protected as structure builds. Reading the chart Markers: Circles = ATR stops, Crosses = Vol stops, Diamonds = Hybrid. Colors indicate long (red level under price) vs short (green level above price). Lines: The latest active stop is extended with a dashed line so you can see it at a glance. Labels: “Long SL / Short SL” shows the exact price and current risk % from the last close no math required. Table: ATR value, Daily Vol %, your chosen Method, the Current SL, and Risk %—all in one compact block that you can pin top-left/right/center. Quick workflow Define the idea: Long or Short, and which engine fits the tape (ATR, Vol, or Hybrid). Place and trail: Let the optimizer print the level; trail automatically as the move develops. Manage outcomes: If the line is tagged, you’re out clean. If it holds, you’ve contained heat while giving the trade room to work. Inputs you’ll actually touch Calculation Settings ATR Length / Multiplier: Controls the “structural” cushion. Volatility Length / Multiplier: Controls the “behavioral” cushion. Trading Days: 252 or 365 to keep the volatility math aligned with the asset’s trading calendar. Stop Loss Method ATR Based | Volatility Based | Hybrid : Switch engines instantly to fit the trade. Position Type Long | Short | Both : Show only what you need for the current strategy. Visual Settings Show ATR / Vol / Hybrid Stops: Toggle families on/off. Show Labels: Print price + Risk % at the live stop. Table Position: Park the metrics where you like. Coloring Long/Short/Hybrid colors: Set a palette that matches your theme and stands out on your background. Practical patterns to watch Trend-pullback continuation: The stop ratchets behind higher lows (long) or lower highs (short). If price tests the level and rejects, that’s your risk-defined continuation cue. Break-and-run: After a clean break, the Hybrid will usually sit slightly wider than pure Vol, use it to avoid getting shaken on the first retest. Range compression: When the ATR and Vol distances converge, the table will show small Risk %. That’s your green light to size up with the same dollar risk, or keep it conservative if you expect expansion. Alerts Long Stop Loss Hit : Notifies when price crosses below the live long stop. Short Stop Loss Hit : Notifies when price crosses above the live short stop. Why this feels “set-and-serious” You get a single look that answers three questions in real time: “Where’s my line in the sand?”, “How much heat am I taking right now?”, and “Is this distance appropriate for current conditions?” With ATR, Vol, and Hybrid in one tool, you can run the exact same playbook across symbols and regimes while keeping your chart clean and your risk explicit.
Pine Script®指標
由BackQuant提供
2
FSVZO [Alpha Extract]A sophisticated volume-weighted momentum oscillator that combines Fourier smoothing with Volume Zone Oscillator methodology to deliver institutional-grade flow analysis and divergence detection. Utilizing advanced statistical filtering including ADF trend analysis and multi-dimensional volume dynamics, this indicator provides comprehensive market sentiment assessment through volume-price relationships with extreme zone detection and intelligent divergence recognition for high-probability reversal and continuation signals. 🔶 Advanced VZO Calculation Engine Implements enhanced Volume Zone Oscillator methodology using relative volume analysis combined with smoothed price changes to create momentum-weighted oscillator values. The system applies exponential smoothing to both volume and price components before calculating positive and negative momentum ratios with trend factor integration for market regime awareness. 🔶 Fourier-Based Smoothing Architecture Features advanced Fourier approximation smoothing using cosine-weighted calculations to reduce noise while preserving signal integrity. The system applies configurable Fourier length parameters with weighted sum normalization for optimal signal clarity across varying market conditions with enhanced responsiveness to genuine trend changes. // Fourier Smoothing Algorithm fourier_smooth(src, length) => sum = 0 weightSum = 0 for i = 0 to length - 1 weight = cos(2 * π * i / length) sum += src * weight weightSum += weight sum / weightSum 🔶 Intelligent Divergence Detection System Implements comprehensive divergence analysis using pivot point methodology with configurable lookback periods for both standard and hidden divergence patterns. The system validates divergence conditions through range analysis and provides visual confirmation through plot lines, labels, and color-coded identification for precise timing analysis. 15MIN 4H 12H 🔶 Flow Momentum Analysis Framework Calculates flow momentum by measuring oscillator deviation from its exponential moving average, providing secondary confirmation of volume flow dynamics. The system creates momentum-based fills and visual indicators that complement the primary oscillator analysis for comprehensive market flow assessment. 🔶 Extreme Zone Detection Engine Features sophisticated extreme zone identification at ±98 levels with specialized marker system including white X markers for signals occurring in extreme territory and directional triangles for potential reversal points. The system provides clear visual feedback for overbought/oversold conditions with institutional-level threshold accuracy. 🔶 Dynamic Visual Architecture Provides advanced visualization engine with bullish/bearish color transitions, dynamic fill regions between oscillator and signal lines, and flow momentum overlay with configurable transparency levels. The system includes flip markers aligned to color junction points for precise signal timing with optional bar close confirmation to prevent repainting. 🔶 ADF Trend Filtering Integration Incorporates Augmented Dickey-Fuller inspired trend filtering using normalized price statistics to enhance signal quality during trending versus ranging market conditions. The system calculates trend factors based on mean deviation and standard deviation analysis for improved oscillator accuracy across market regimes. 🔶 Comprehensive Alert System Features intelligent multi-tier alert framework covering bullish/bearish flow detection, extreme zone reversals, and divergence confirmations with customizable message templates. The system provides real-time notifications for critical volume flow changes and structural market shifts with exchange and ticker integration. 🔶 Performance Optimization Framework Utilizes efficient calculation methods with optimized variable management and configurable smoothing parameters to balance signal quality with computational efficiency. The system includes automatic pivot validation and range checking for consistent performance across extended analysis periods with minimal resource usage. This indicator delivers sophisticated volume-weighted momentum analysis through advanced Fourier smoothing and comprehensive divergence detection capabilities. Unlike traditional volume oscillators that focus solely on volume patterns, the FSVZO integrates volume dynamics with price momentum and statistical trend filtering to provide institutional-grade flow analysis. The system's combination of extreme zone detection, intelligent divergence recognition, and multi-dimensional visual feedback makes it essential for traders seeking systematic approaches to volume-based market analysis across cryptocurrency, forex, and equity markets with clearly defined reversal and continuation signals.
Pine Script®指標
由AlphaExtract提供
12
Session AnchorsDescription This indicator highlights the four main global trading sessions — London, New York AM, New York PM, and Asia — as color-coded boxes on the chart. Each session is defined by fixed start/end times (New York time) and dynamically updates with the evolving high and low during that interval. This provides a clear view of how volatility and structure shift as trading activity passes from one region to another. How to use • Works on any timeframe. • Toggle sessions on/off based on your trading hours. • Observe price behavior as one session closes and another opens. • Use session boxes as context for liquidity, volatility, and structure analysis. Originality This script delivers a clean, customizable visualization of global market hours and session ranges, avoiding extra overlays so traders can isolate session-based behavior without distraction. ⚠️ Disclaimer This indicator does not generate signals. It provides a structural mapping of global sessions for contextual analysis only.
Pine Script®指標
由theunlockedtrading提供
1
Weekly Session BreakThis indicator plots a vertical line at the end of the trading week (Friday) to mark the weekly session break. It is designed to be used on intraday charts (sub-1 hour timeframes). The line's appearance is fully customizable via the Inputs tab, allowing you to change its color, style (solid, dotted, or dashed), and thickness. Key Features: End-of-Week Marker: Accurately draws a vertical line on the last bar of the trading week. Timeframe Specific: Lines are only visible on intraday charts (1-minute to 59-minute timeframes) to prevent clutter on higher timeframes. Customizable: Adjust the line's color, style, and thickness from the Inputs menu.
Pine Script®指標
由emini_watch提供
1
Key Levels: Daily, Weekly, Monthly [BackQuant]Key Levels: Daily, Weekly, Monthly Map the market’s “memory” in one glance—yesterday’s range, this week’s chosen day high/low, and D/W/M opens—then auto-clean levels once they break. What it does This tool plots three families of high-signal reference lines and keeps them tidy as price evolves: Chosen Day High/Low (per week) — Pick a weekday (e.g., Monday). For each past week, the script records that day’s session high and low and projects them forward for a configurable number of bars. These act like “memory levels” that price often revisits. Daily / Weekly / Monthly Opens — Plots the opening price of each new day, week, and month with separate styling. These opens frequently behave like magnets/flip lines intraday and anchors for regime on higher timeframes. Auto-pruning — When price breaks a stored level, the script can automatically remove it to reduce clutter and refocus you on still-active lines. See: (broken levels removed). Why these levels matter Liquidity pockets — Prior day’s high/low and the daily open concentrate stops and pending orders. Mapping them quickly reveals likely sweep or fade zones. Example: previous day highs + daily open highlighting liquidity: Context & regime — Monthly opens frame macro bias; trading above a rising cluster of monthly opens vs. below gives a clean top-down read. Example: monthly-only “macro outlook” view: Cleaner charts — Auto-remove broken lines so you focus on what still matters right now. What it plots (at a glance) Past Chosen Day High/Low for up to N prior weeks (your choice), extended right. Current Daily Open , Weekly Open , and Monthly Open , each with its own color, label, and forward extension. Optional short labels (e.g., “Mon High”) or full labels (with week/month info). How breaks are detected & cleaned You control both the evidence and the timing of a “break”: Break uses — Choose Close (more conservative) or Wick (more sensitive). Inclusive? — If enabled, equality counts (≥ high or ≤ low). If disabled, you need a strict cross. Allow intraday breaks? — If on, a level can break during the tracked day; if off, the script only counts breaks after the session completes. Remove Broken Levels — When a break is confirmed, the line/label is deleted automatically. (See the demo: ) Quick start Pick a Day of Week to Track (e.g., Monday). Set how many weeks back to show (e.g., 8–10). Choose how far to extend each family (bars to the right for chosen-day H/L and D/W/M opens). Decide if a break uses Close or Wick , and whether equality counts. Toggle Remove Broken Levels to keep the chart clean automatically. Tips by use-case Intraday bias — Watch the Daily Open as a magnet/flip. If price gaps above and holds, pullbacks to the daily open often decide direction. Pair with last day’s high/low for sweep→reversal or true breakout cues. See: Weekly structure — Track the week’s chosen day (e.g., Monday) high/low across prior weeks. If price stalls near a cluster of old “Monday Highs,” look for sweep/reject patterns or continuation on reclaim. Macro regime — Hide daily/weekly lines and keep only Monthly Opens to read bigger cycles at a glance (BTC/crypto especially). Example: Customization Use wicks or bodies for highs/lows (wicks capture extremes; bodies are stricter). Line style & thickness — solid/dashed/dotted, width 1–5, plus global transparency. Labels — Abbreviated (“Mon High”, “D Open”) or full (month/week/day info). Color scheme — Separate colors for highs, lows, and each of D/W/M opens. Capacity controls — Set how many daily/weekly/monthly opens and how many weeks of chosen-day H/L to keep visible. What’s under the hood On your selected weekday, the script records that session’s true high and true low (using wicks or body-based extremes—your choice), then projects a horizontal line forward for the next bars. At each new day/week/month , it records the opening price and projects that line forward as well. Each bar, the script checks your “break” rules; once broken, lines/labels are removed if auto-cleaning is on. Everything updates in real time; past levels don’t repaint after the session finishes. Recommended presets Day trading — Weeks back: 6–10; extend D/W opens: 50–100 bars; Break uses: Close ; Inclusive: off; Auto-remove: on. Swing — Fewer daily opens, more weekly opens (2–6), and 8–12 weeks of chosen-day H/L. Macro — Show only Monthly Opens (1–6 months), dashed style, thicker lines for clarity. Reading the examples Broken lines disappear — decluttering in action: Macro outlook — monthly opens as cycle rails: Liquidity map — previous day highs + daily open: Final note These are not “signals”—they’re reference points that many participants watch. By standardising how you draw them and automatically clearing the ones that no longer matter, you turn a noisy chart into a focused map: where liquidity likely sits, where price memory lives, and which lines are still in play.
Pine Script®指標
由BackQuant提供
6
Quantile Regression Bands [BackQuant]Quantile Regression Bands Tail-aware trend channeling built from quantiles of real errors, not just standard deviations. What it does This indicator fits a simple linear trend over a rolling lookback and then measures how price has actually deviated from that trend during the window. It then places two pairs of bands at user-chosen quantiles of those deviations (inner and outer). Because bands are based on empirical quantiles rather than a symmetric standard deviation, they adapt to skewed and fat-tailed behaviour and often hug price better in trending or asymmetric markets. Why “quantile” bands instead of Bollinger-style bands? Bollinger Bands assume a (roughly) symmetric spread around the mean; quantiles don’t—upper and lower bands can sit at different distances if the error distribution is skewed. Quantiles are robust to outliers; a single shock won’t inflate the bands for many bars. You can choose tails precisely (e.g., 1%/99% or 5%/95%) to match your risk appetite. How it works (intuitive) Center line — a rolling linear regression approximates the local trend. Residuals — for each bar in the lookback, the indicator looks at the gap between actual price and where the line “expected” price to be. Quantiles — those gaps are sorted; you select which percentiles become your inner/outer offsets. Bands — the chosen quantile offsets are added to the current end of the regression line to draw parallel support/resistance rails. Smoothing — a light EMA can be applied to reduce jitter in the line and bands. What you see Center (linear regression) line (optional). Inner quantile bands (e.g., 25th/75th) with optional translucent fill. Outer quantile bands (e.g., 1st/99th) with a multi-step gradient to visualise “tail zones.” Optional bar coloring: bars trend-colored by whether price is rising above or falling below the center line. Alerts when price crosses the outer bands (upper or lower). How to read it Trend & drift — the slope of the center line is your local trend. Persistent closes on the same side of the center line indicate directional drift. Pullbacks — tags of the inner band often mark routine pullbacks within trend. Reaction back to the center line can be used for continuation entries/partials. Tails & squeezes — outer-band touches highlight statistically rare excursions for the chosen window. Frequent outer-band activity can signal regime change or volatility expansion. Asymmetry — if the upper band sits much further from the center than the lower (or vice versa), recent behaviour has been skewed. Trade management can be adjusted accordingly (e.g., wider take-profit upslope than downslope). A simple trend interpretation can be derived from the bar colouring Good use-cases Volatility-aware mean reversion — fade moves into outer bands back toward the center when trend is flat. Trend participation — buy pullbacks to the inner band above a rising center; flip logic for shorts below a falling center. Risk framing — set dynamic stops/targets at quantile rails so position sizing respects recent tail behaviour rather than fixed ticks. Inputs (quick guide) Source — price input used for the fit (default: close). Lookback Length — bars in the regression window and residual sample. Longer = smoother, slower bands; shorter = tighter, more reactive. Inner/Outer Quantiles (τ) — choose your “typical” vs “tail” levels (e.g., 0.25/0.75 inner, 0.01/0.99 outer). Show toggles — independently toggle center line, inner bands, outer bands, and their fills. Colors & transparency — customize band and fill appearance; gradient shading highlights the tail zone. Band Smoothing Length — small EMA on lines to reduce stair-step artefacts without meaningfully changing levels. Bar Coloring — optional trend tint from the center line’s momentum. Practical settings Swing trading — Length 75–150; inner τ = 0.25/0.75, outer τ = 0.05/0.95. Intraday — Length 50–100 for liquid futures/FX; consider 0.20/0.80 inner and 0.02/0.98 outer in high-vol assets. Crypto — Because of fat tails, try slightly wider outers (0.01/0.99) and keep smoothing at 2–4 to tame weekend jumps. Signal ideas Continuation — in an uptrend, look for pullback into the lower inner band with a close back above the center as a timing cue. Exhaustion probe — in ranges, first touch of an outer band followed by a rejection candle back inside the inner band often precedes mean-reversion swings. Regime shift — repeated closes beyond an outer band or a sharp re-tilt in the center line can mark a new trend phase; adjust tactics (stop-following along the opposite inner band). Alerts included “Price Crosses Upper Outer Band” — potential overextension or breakout risk. “Price Crosses Lower Outer Band” — potential capitulation or breakdown risk. Notes The fit and quantiles are computed on a fixed rolling window and do not repaint; bands update as the window moves forward. Quantiles are based on the recent distribution; if conditions change abruptly, expect band widths and skew to adapt over the next few bars. Parameter choices directly shape behaviour: longer windows favour stability, tighter inner quantiles increase touch frequency, and extreme outer quantiles highlight only the rarest moves. Final thought Quantile bands answer a simple question: “How unusual is this move given the current trend and the way price has been missing it lately?” By scoring that question with real, distribution-aware limits rather than one-size-fits-all volatility you get cleaner pullback zones in trends, more honest “extreme” tags in ranges, and a framework for risk that matches the market’s recent personality.
Pine Script®指標
由BackQuant提供
1
Cumulative Returns by Session [BackQuant]Cumulative Returns by Session What this is This tool breaks the trading day into three user-defined sessions and tracks how much each session contributes to return, volatility, and volume. It then aggregates results over a rolling window so you can see which session has been pulling its weight, how streaky each session has been, and how sessions relate to one another through a compact correlation heatmap. We’ve also given the functionality for the user to use a simplified table, just by switching off all settings they are not interested in. How it works 1) Session segmentation You define APAC, EU, and US sessions with explicit hours and time zones. The script detects when each session starts and ends on every intraday bar and records its open, intraday high and low, close, and summed volume. 2) Per-session math At each session end the script computes: Return — either Percent: (Close−Open)÷Open×100(Close − Open) ÷ Open × 100(Close−Open)÷Open×100 or Points: (Close−Open)(Close − Open)(Close−Open), based on your selection. Volatility — either Range: (High−Low)÷Open×100(High − Low) ÷ Open × 100(High−Low)÷Open×100 or ATR scaled by price: ATR÷Open×100ATR ÷ Open × 100ATR÷Open×100. Volume — total volume transacted during that session. 3) Storage and lookback Each day’s three session stats are stored as a row. You choose how many recent sessions to keep in memory. The script then: Builds cumulative returns for APAC, EU, US across the lookback. Computes averages, win rates, and a Sharpe-like ratio avgreturn÷avgvolatilityavg return ÷ avg volatilityavgreturn÷avgvolatility per session. Tracks streaks of positive or negative sessions to show momentum. Tracks drawdowns on cumulative returns to show worst runs from peak. Computes rolling means over a short window for short-term drift. 4) Correlation heatmap Using the stored arrays of session returns, the script calculates Pearson correlations between APAC–EU, APAC–US, and EU–US, and colors the matrix by strength and sign so you can spot coupling or decoupling at a glance. What it plots Three lines: cumulative return for APAC, EU, US over the chosen lookback. Zero reference line for orientation. A statistics table with cumulative %, average %, positive session rate, and optional columns for volatility, average volume, max drawdown, current streak, return-to-vol ratio, and rolling average. A small correlation heatmap table showing APAC, EU, US cross-session correlations. How to use it Pick the asset — leave Custom Instrument empty to use the chart symbol, or point to another symbol for cross-asset studies. Set your sessions and time zones — defaults approximate APAC, EU, and US hours, but you can align them to exchange times or your workflow. Choose calculation modes — Percent vs Points for return, Range vs ATR for volatility. Points are convenient for futures and fixed-tick assets, Percent is comparable across symbols. Decide the lookback — more sessions smooths lines and stats; fewer sessions makes the tool more reactive. Toggle analytics — add volatility, volume, drawdown, streaks, Sharpe-like ratio, rolling averages, and the correlation table as needed. Why session attribution helps Different sessions are driven by different flows. Asia often sets the overnight tone, Europe adds liquidity and direction changes, and the US session can dominate range expansion. Separating contributions by session helps you: Identify which session has been the main driver of net trend. Measure whether volatility or volume is concentrated in a specific window. See if one session’s gains are consistently given back in another. Adapt tactics: fade during a mean-reverting session, press during a trending session. Reading the tables Cumulative % — sum of session returns over the lookback. The sign and slope tell you who is carrying the move. Avg Return % and Positive Sessions % — direction and hit rate. A low average but high hit rate implies many small moves; the reverse implies occasional big swings. Avg Volatility % — typical intrabars range for that session. Compare with Avg Return to judge efficiency. Return/Vol Ratio — return per unit of volatility. Higher is better for stability. Max Drawdown % — worst cumulative give-back within the lookback. A quick way to spot riskiness by session. Current Streak — consecutive up or down sessions. Useful for mean-reversion or regime awareness. Rolling Avg % — short-window drift indicator to catch recent turnarounds. Correlation matrix — green clusters indicate sessions tending to move together; red indicates offsetting behavior. Settings overview Basic Number of Sessions — how many recent days to include. Custom Instrument — analyze another ticker while staying on your current chart. Session Configuration and Times Enable or hide APAC, EU, US rows. Set hours per session and the specific time zone for each. Calculation Methods Return Calculation — Percent or Points. Volatility Calculation — Range or ATR; ATR Length when applicable. Advanced Analytics Correlation, Drawdown, Momentum, Sharpe-like ratio, Rolling Statistics, Rolling Period. Display Options and Colors Show Statistics Table and its position. Toggle columns for Volatility and Volume. Pick individual colors for each session line and row accents. Common applications Session bias mapping — find which window tends to trend in your market and plan exposure accordingly. Strategy scheduling — allocate attention or risk to the session with the best return-to-vol ratio. News and macro awareness — see if correlation rises around central bank cycles or major data releases. Cross-asset monitoring — set the Custom Instrument to a driver (index future, DXY, yields) to see if your symbol reacts in a particular session. Notes This indicator works on intraday charts, since sessions are defined within a day. If you change session clocks or time zones, give the script a few bars to accumulate fresh rows. Percent vs Points and Range vs ATR choices affect comparability across assets, so be consistent when comparing symbols. Session context is one of the simplest ways to explain a messy tape. By separating the day into three windows and scoring each one on return, volatility, and consistency, this tool shows not just where price ended up but when and how it got there. Use the cumulative lines to spot the steady driver, read the table to judge quality and risk, and glance at the heatmap to learn whether the sessions are amplifying or canceling one another. Adjust the hours to your market and let the data tell you which session deserves your focus.
Pine Script®指標
由BackQuant提供
Deadband Hysteresis Supertrend [BackQuant]Deadband Hysteresis Supertrend A two-stage trend tool that first filters price with a deadband baseline, then runs a Supertrend around that baseline with optional flip hysteresis and ATR-based adverse exits. What this is A hybrid of two ideas: Deadband Hysteresis Baseline that only advances when price pulls far enough from the baseline to matter. This suppresses micro noise and gives you a stable centerline. Supertrend bands wrapped around that baseline instead of raw price. Flips are further gated by an extra margin so side changes are more deliberate. The goal is fewer whipsaws in chop and clearer regime identification during trends. How it works (high level) Deadband step — compute a per-bar “deadband” size from one of four modes: ATR, Percent of price, Ticks, or Points. If price deviates from the baseline by more than this amount, move the baseline forward by a fraction of the excess. If not, hold the line. Centered Supertrend — build upper and lower bands around the baseline using ATR and a user factor. Track the usual trailing logic that tightens a band while price moves in its favor. Flip hysteresis — require price to exceed the active band by an extra flip offset × ATR before switching sides. This adds stickiness at the boundary. Adverse exit — once a side is taken, trigger an exit if price moves against the entry by K × ATR . If you would like to check out the filter by itself: What it plots DBHF baseline (optional) as a smooth centerline. DBHF Supertrend as the active trailing band. Candle coloring by trend side for quick read. Signal markers 𝕃 and 𝕊 at flips plus ✖ on adverse exits. Inputs that matter Price Source — series being filtered. Close is typical. HL2 or HLC3 can be steadier. Deadband mode — ATR, Percent, Ticks, or Points. This defines the “it’s big enough to matter” zone. ATR Length / Mult (DBHF) — only used when mode = ATR. Larger values widen the do-nothing zone. Percent / Ticks / Points — alternatives to ATR; pick what fits your market’s convention. Enter Mult — scales the deadband you must clear before the baseline moves. Increase to filter more noise. Response — fraction of the excess applied to baseline movement. Higher responds faster; lower is smoother. Supertrend ATR Period & Factor — traditional band size controls; higher factor widens and flips less often. Flip Offset ATR — extra ATR buffer required to flip. Useful in choppy regimes. Adverse Stop K·ATR — per-trade danger brake that forces an exit if price moves K×ATR against entry. UI — toggle baseline, supertrend, signals, and bar painting; choose long and short colors. How to read it Green regime — candles painted long and the Supertrend running below price. Pullbacks toward the baseline that fail to breach the opposite band often resume higher. Red regime — candles painted short and the Supertrend running above price. Rallies that cannot reclaim the band may roll over. Frequent side swaps — reduce sensitivity by increasing Enter Mult, using ATR mode, raising the Supertrend factor, or adding Flip Offset ATR. Use cases Bias filter — allow entries only in the direction of the current side. Use your preferred triggers inside that bias. Trailing logic — treat the active band as a dynamic stop. If the side flips or an adverse K·ATR exit prints, reduce or close exposure. Regime map — on higher timeframes, the combination baseline + band produces a clean up vs down template for allocation decisions. Tuning guidance Fast markets — ATR deadband, modest Enter Mult (0.8–1.2), response 0.2–0.35, Supertrend factor 1.7–2.2, small Flip Offset (0.2–0.5 ATR). Choppy ranges — widen deadband or raise Enter Mult, lower response, and add more Flip Offset so flips require stronger evidence. Slow trends — longer ATR periods and higher Supertrend factor to keep you on side longer; use a conservative adverse K. Included alerts DBHF ST Long — side flips to long. DBHF ST Short — side flips to short. Adverse Exit Long / Short — K·ATR stop triggers against the current side. Strengths Deadbanded baseline reduces micro whipsaws before Supertrend logic even begins. Flip hysteresis adds a second layer of confirmation at the boundary. Optional adverse ATR stop provides a uniform risk cut across assets and regimes. Clear visuals and minimal parameters to adjust for symbol behavior. Putting it together Think of this tool as two decisions layered into one view. The deadband baseline answers “does this move even count,” then the Supertrend wrapped around that baseline answers “if it counts, which side should I be on and where do I flip.” When both parts agree you tend to stay on the correct side of a trend for longer, and when they disagree you get an early warning that conditions are changing. When the baseline bends and price cannot reclaim the opposite band , momentum is usually continuing. Pullbacks into the baseline that stall before the far band often resolve in trend. When the baseline flattens and the bands compress , expect indecision. Use the Flip Offset ATR to avoid reacting to the first feint. Wait for a clean band breach with follow through. When an adverse K·ATR exit prints while the side has not flipped , treat it as a risk event rather than a full regime change. Many users cut size, re-enter only if the side reasserts, and let the next flip confirm a new trend. Final thoughts Deadband Hysteresis Supertrend is best read as a regime lens. The baseline defines your tolerance for noise, the bands define your trailing structure, and the flip offset plus adverse ATR stop define how forgiving or strict you want to be at the boundary. On strong trends it helps you hold through shallow shakeouts. In choppy conditions it encourages patience until price does something meaningful. Start with settings that reflect the cadence of your market, observe how often flips occur, then nudge the deadband and flip offset until the tool spends most of its time describing the move you care about rather than the noise in between.
Pine Script®指標
由BackQuant提供
8
Deadband Hysteresis Filter [BackQuant]Deadband Hysteresis Filter What this is This tool builds a “debounced” price baseline that ignores small fluctuations and only reacts when price meaningfully departs from its recent path. It uses a deadband to define how much deviation matters and a hysteresis scheme to avoid rapid flip-flops around the decision boundary. The baseline’s slope provides a simple trend cue, used to color candles and to trigger up and down alerts. Why deadband and hysteresis help They filter micro noise so the baseline does not react to every tiny tick. They stabilize state changes. Hysteresis means the rule to start moving is stricter than the rule to keep holding, which reduces whipsaw. They produce a stepped, readable path that advances during sustained moves and stays flat during chop. How it works (conceptual) At each bar the script maintains a running baseline dbhf and compares it to the input price p . Compute a base threshold baseTau using the selected mode (ATR, Percent, Ticks, or Points). Build an enter band tauEnter = baseTau × Enter Mult and an exit band tauExit = baseTau × Exit Mult where typically Exit Mult < Enter Mult . Let diff = p − dbhf . If diff > +tauEnter , raise the baseline by response × (diff − tauEnter) . If diff < −tauEnter , lower the baseline by response × (diff + tauEnter) . Otherwise, hold the prior value. Trend state is derived from slope: dbhf > dbhf → up trend, dbhf < dbhf → down trend. Inputs and what they control Threshold mode ATR — baseTau = ATR(atrLen) × atrMult . Adapts to volatility. Useful when regimes change. Percent — baseTau = |price| × pctThresh% . Scale-free across symbols of different prices. Ticks — baseTau = syminfo.mintick × tickThresh . Good for futures where tick size matters. Points — baseTau = ptsThresh . Fixed distance in price units. Band multipliers and response Enter Mult — outer band. Price must travel at least this far from the baseline before an update occurs. Larger values reject more noise but increase lag. Exit Mult — inner band for hysteresis. Keep this smaller than Enter Mult to create a hold zone that resists small re-entries. Response — step size when outside the enter band. Higher response tracks faster; lower response is smoother. UI settings Show Filtered Price — plots the baseline on price. Paint candles — colors bars by the filtered slope using your long/short colors. How it can be used Trend qualifier — take entries only in the direction of the baseline slope and skip trades against it. Debounced crossovers — use the baseline as a stabilized surrogate for price in moving-average or channel crossover rules. Trailing logic — trail stops a small distance beyond the baseline so small pullbacks do not eject the trade. Session aware filtering — widen Enter Mult or switch to ATR mode for volatile sessions; tighten in quiet sessions. Parameter interactions and tuning Enter Mult vs Response — both govern sensitivity. If you see too many flips, increase Enter Mult or reduce Response. If turns feel late, do the opposite. Exit Mult — widening the gap between Enter and Exit expands the hold zone and reduces oscillation around the threshold. Mode choice — ATR adapts automatically; Percent keeps behavior consistent across instruments; Ticks or Points are useful when you think in fixed increments. Timeframe coupling — on higher timeframes you can often lower Enter Mult or raise Response because raw noise is already reduced. Concrete starter recipes General purpose — ATR mode, atrLen=14 , atrMult=1.0–1.5 , Enter=1.0 , Exit=0.5 , Response=0.20 . Balanced noise rejection and lag. Choppy range filter — ATR mode, increase atrMult to 2.0, keep Response≈0.15 . Stronger suppression of micro-moves. Fast intraday — Percent mode, pctThresh=0.1–0.3 , Enter=1.0 , Exit=0.4–0.6 , Response=0.30–0.40 . Quicker turns for scalping. Futures ticks — Ticks mode, set tickThresh to a few spreads beyond typical noise; start with Enter=1.0 , Exit=0.5 , Response=0.25 . Strengths Clear, explainable logic with an explicit noise budget. Multiple threshold modes so the same tool fits equities, futures, and crypto. Built-in hysteresis that reduces flip-flop near the boundary. Slope-based coloring and alerts that make state changes obvious in real time. Limitations and notes All filters add lag. Larger thresholds and smaller response trade faster reaction for fewer false turns. Fixed Points or Ticks can under- or over-filter when volatility regime shifts. ATR adapts, but will also expand bands during spikes. On extremely choppy symbols, even a well tuned band will step frequently. Widen Enter Mult or reduce Response if needed. This is a chart study. It does not include commissions, slippage, funding, or gap risks. Alerts DBHF Up Slope — baseline turns from down to up on the latest bar. DBHF Down Slope — baseline turns from up to down on the latest bar. Implementation details worth knowing Initialization sets the baseline to the first observed price to avoid a cold-start jump. Slope is evaluated bar-to-bar. The up and down alerts check for a change of slope rather than raw price crossings. Candle colors and the baseline plot share the same long/short palette with transparency applied to the line. Practical workflow Pick a mode that matches how you think about distance. ATR for volatility aware, Percent for scale-free, Ticks or Points for fixed increments. Tune Enter Mult until the number of flips feels appropriate for your timeframe. Set Exit Mult clearly below Enter Mult to create a real hold zone. Adjust Response last to control “how fast” the baseline chases price once it decides to move. Final thoughts Deadband plus hysteresis gives you a principled way to “only care when it matters.” With a sensible threshold and response, the filter yields a stable, low-chop trend cue you can use directly for bias or plug into your own entries, exits, and risk rules.
Pine Script®指標
由BackQuant提供
10
Martingale Strategy Simulator [BackQuant]Martingale Strategy Simulator Purpose This indicator lets you study how a martingale-style position sizing rule interacts with a simple long or short trading signal. It computes an equity curve from bar-to-bar returns, adapts position size after losing streaks, caps exposure at a user limit, and summarizes risk with portfolio metrics. An optional Monte Carlo module projects possible future equity paths from your realized daily returns. What a martingale is A martingale sizing rule increases stake after losses and resets after a win. In its classical form from gambling, you double the bet after each loss so that a single win recovers all prior losses plus one unit of profit. In markets there is no fixed “even-money” payout and returns are multiplicative, so an exact recovery guarantee does not exist. The core idea is unchanged: Lose one leg → increase next position size Lose again → increase again Win → reset to the base size The expectation of your strategy still depends on the signal’s edge. Sizing does not create positive expectancy on its own. A martingale raises variance and tail risk by concentrating more capital as a losing streak develops. What it plots Equity – simulated portfolio equity including compounding Buy & Hold – equity from holding the chart symbol for context Optional helpers – last trade outcome, current streak length, current allocation fraction Optional diagnostics – daily portfolio return, rolling drawdown, metrics table Optional Monte Carlo probability cone – p5, p16, p50, p84, p95 aggregate bands Model assumptions Bar-close execution with no slippage or commissions Shorting allowed and frictionless No margin interest, borrow fees, or position limits No intrabar moves or gaps within a bar (returns are close-to-close) Sizing applies to equity fraction only and is capped by your setting All results are hypothetical and for education only. How the simulator applies it 1) Directional signal You pick a simple directional rule that produces +1 for long or −1 for short each bar. Options include 100 HMA slope, RSI above or below 50, EMA or SMA crosses, CCI and other oscillators, ATR move, BB basis, and more. The stance is evaluated bar by bar. When the stance flips, the current trade ends and the next one starts. 2) Sizing after losses and wins Position size is a fraction of equity: Initial allocation – the starting fraction, for example 0.15 means 15 percent of equity Increase after loss – multiply the next allocation by your factor after a losing leg, for example 2.00 to double Reset after win – return to the initial allocation Max allocation cap – hard ceiling to prevent runaway growth At a high level the size after k consecutive losses is alloc(k) = min( cap , base × factor^k ) . In practice the simulator changes size only when a leg ends and its PnL is known. 3) Equity update Let r_t = close_t / close_{t-1} − 1 be the symbol’s bar return, d_{t−1} ∈ {+1, −1} the prior bar stance, and a_{t−1} the prior bar allocation fraction. The simulator compounds: eq_t = eq_{t−1} × (1 + a_{t−1} × d_{t−1} × r_t) . This is bar-based and avoids intrabar lookahead. Costs, slippage, and borrowing costs are not modeled. Why traders experiment with martingale sizing Mean-reversion contexts – if the signal often snaps back after a string of losses, adding size near the tail of a move can pull the average entry closer to the turn Behavioral or microstructure edges – some rules have modest edge but frequent small whipsaws; size escalation may shorten time-to-recovery when the edge manifests Exploration and stress testing – studying the relationship between streaks, caps, and drawdowns is instructive even if you do not deploy martingale sizing live Why martingale is dangerous Martingale concentrates capital when the strategy is performing worst. The main risks are structural, not cosmetic: Loss streaks are inevitable – even with a 55 percent win rate you should expect multi-loss runs. The probability of at least one k-loss streak in N trades rises quickly with N. Size explodes geometrically – with factor 2.0 and base 10 percent, the sequence is 10, 20, 40, 80, 100 (capped) after five losses. Without a strict cap, required size becomes infeasible. No fixed payout – in gambling, one win at even odds resets PnL. In markets, there is no guaranteed bounce nor fixed profit multiple. Trends can extend and gaps can skip levels. Correlation of losses – losses cluster in trends and in volatility bursts. A martingale tends to be largest just when volatility is highest. Margin and liquidity constraints – leverage limits, margin calls, position limits, and widening spreads can force liquidation before a mean reversion occurs. Fat tails and regime shifts – assumptions of independent, Gaussian returns can understate tail risk. Structural breaks can keep the signal wrong for much longer than expected. The simulator exposes these dynamics in the equity curve, Max Drawdown, VaR and CVaR, and via Monte Carlo sketches of forward uncertainty. Interpreting losing streaks with numbers A rough intuition: if your per-trade win probability is p and loss probability is q=1−p , the chance of a specific run of k consecutive losses is q^k . Over many trades, the chance that at least one k-loss run occurs grows with the number of opportunities. As a sanity check: If p=0.55 , then q=0.45 . A 6-loss run has probability q^6 ≈ 0.008 on any six-trade window. Across hundreds of trades, a 6 to 8-loss run is not rare. If your size factor is 1.5 and your base is 10 percent, after 8 losses the requested size is 10% × 1.5^8 ≈ 25.6% . With factor 2.0 it would try to be 10% × 2^8 = 256% but your cap will stop it. The equity curve will still wear the compounded drawdown from the sequence that led to the cap. This is why the cap setting is central. It does not remove tail risk, but it prevents the sizing rule from demanding impossible positions Note: The p and q math is illustrative. In live data the win rate and distribution can drift over time, so real streaks can be longer or shorter than the simple q^k intuition suggests.. Using the simulator productively Parameter studies Start with conservative settings. Increase one element at a time and watch how the equity, Max Drawdown, and CVaR respond. Initial allocation – lower base reduces volatility and drawdowns across the board Increase factor – set modestly above 1.0 if you want the effect at all; doubling is aggressive Max cap – the most important brake; many users keep it between 20 and 50 percent Signal selection Keep sizing fixed and rotate signals to see how streak patterns differ. Trend-following signals tend to produce long wrong-way streaks in choppy ranges. Mean-reversion signals do the opposite. Martingale sizing interacts very differently with each. Diagnostics to watch Use the built-in metrics to quantify risk: Max Drawdown – worst peak-to-trough equity loss Sharpe and Sortino – volatility and downside-adjusted return VaR 95 percent and CVaR – tail risk measures from the realized distribution Alpha and Beta – relationship to your chosen benchmark If you would like to check out the original performance metrics script with multiple assets with a better explanation on all metrics please see Monte Carlo exploration When enabled, the forecast draws many synthetic paths from your realized daily returns: Choose a horizon and a number of runs Review the bands: p5 to p95 for a wide risk envelope; p16 to p84 for a narrower range; p50 as the median path Use the table to read the expected return over the horizon and the tail outcomes Remember it is a sketch based on your recent distribution, not a predictor Concrete examples Example A: Modest martingale Base 10 percent, factor 1.25, cap 40 percent, RSI>50 signal. You will see small escalations on 2 to 4 loss runs and frequent resets. The equity curve usually remains smooth unless the signal enters a prolonged wrong-way regime. Max DD may rise moderately versus fixed sizing. Example B: Aggressive martingale Base 15 percent, factor 2.0, cap 60 percent, EMA cross signal. The curve can look stellar during favorable regimes, then a single extended streak pushes allocation to the cap, and a few more losses drive deep drawdown. CVaR and Max DD jump sharply. This is a textbook case of high tail risk. Strengths Bar-by-bar, transparent computation of equity from stance and size Explicit handling of wins, losses, streaks, and caps Portable signal inputs so you can A–B test ideas quickly Risk diagnostics and forward uncertainty visualization in one place Example, Rolling Max Drawdown Limitations and important notes Martingale sizing can escalate drawdowns rapidly. The cap limits position size but not the possibility of extended adverse runs. No commissions, slippage, margin interest, borrow costs, or liquidity limits are modeled. Signals are evaluated on closes. Real execution and fills will differ. Monte Carlo assumes independent draws from your recent return distribution. Markets often have serial correlation, fat tails, and regime changes. All results are hypothetical. Use this as an educational tool, not a production risk engine. Practical tips Prefer gentle factors such as 1.1 to 1.3. Doubling is usually excessive outside of toy examples. Keep a strict cap. Many users cap between 20 and 40 percent of equity per leg. Stress test with different start dates and subperiods. Long flat or trending regimes are where martingale weaknesses appear. Compare to an anti-martingale (increase after wins, cut after losses) to understand the other side of the trade-off. If you deploy sizing live, add external guardrails such as a daily loss cut, volatility filters, and a global max drawdown stop. Settings recap Backtest start date and initial capital Initial allocation, increase-after-loss factor, max allocation cap Signal source selector Trading days per year and risk-free rate Benchmark symbol for Alpha and Beta UI toggles for equity, buy and hold, labels, metrics, PnL, and drawdown Monte Carlo controls for enable, runs, horizon, and result table Final thoughts A martingale is not a free lunch. It is a way to tilt capital allocation toward losing streaks. If the signal has a real edge and mean reversion is common, careful and capped escalation can reduce time-to-recovery. If the signal lacks edge or regimes shift, the same rule can magnify losses at the worst possible moment. This simulator makes those trade-offs visible so you can calibrate parameters, understand tail risk, and decide whether the approach belongs anywhere in your research workflow.
Pine Script®指標
由BackQuant提供
ATR% | Volatility NormalizerThis indicator measures true volatility by expressing the Average True Range (ATR) as a percentage of price. Unlike basic ATR plots, which show raw values, this version normalizes volatility to make it directly comparable across instruments and timeframes. How it works: Uses True Range (High–Low plus gaps) to capture actual market movement. Normalizes by dividing ATR by the chosen price base (default: Close). Multiplies by 100 to output a clean ATR% line. Smoothing is flexible: choose from RMA, SMA, EMA, or WMA. Optional Feature: For comparison, you can toggle an auxiliary line showing the average absolute close-to-close % move, highlighting the difference between simplified and true volatility. Why use it: Track regime shifts: identify when volatility expands or contracts in % terms. Compare volatility across different markets (equities, crypto, forex, commodities). Integrate into risk management: position sizing, stop placement, or volatility filters for entries. Interpretation: Rising ATR% → expanding volatility, potential breakouts or unstable ranges. Falling ATR% → contracting volatility, possible consolidation or range-bound conditions. Sudden spikes → market “shocks” worth paying attention to.
Pine Script®指標
由maulikns提供
Liquidity Swing Points [BackQuant]Liquidity Swing Points This tool marks recent swing highs and swing lows and turns them into persistent horizontal “liquidity” levels. These are places where resting orders often accumulate, such as stop losses above prior highs and below prior lows. The script detects confirmed pivots, records their prices, draws lines and labels, and manages their lifecycle on the chart so you can monitor potential sweep or breakout zones without manual redrawing. What it plots LQ-H at confirmed swing highs LQ-L at confirmed swing lows Horizontal levels that can optionally extend into the future Timed removal of old levels to keep the chart clean Each level stores its price, the bar where it was created, its type (high or low), plus a label and a line reference for efficient updates. How it works Pivot detection A swing high is confirmed when the highest high has swing_length bars on both sides that are lower. A swing low is confirmed when the lowest low has swing_length bars on both sides that are higher. Pivots are only marked after they are confirmed, so they do not repaint. Level creation When a pivot confirms, the script records the price and the creation bar (offset by the right lookback). A new line is plotted at that price, labeled LQ-H or LQ-L. Rendering and extension Levels can be drawn to the most recent bar only or extended to the right for forward reference. Label size and line color/transparency are configurable. Lifecycle management On each confirmed bar, the script checks level age. Levels older than a chosen bar count are removed automatically to reduce clutter. How it can be used Liquidity sweeps: Watch for price to probe beyond a level then close back inside. That behavior often signals a potential fade back into the prior range. Breakout validation: If price pushes through a level and holds on closes, traders may treat that as continuation. Retests of the level from the other side can serve as structure checks. Context for entries and exits: Use nearby LQ-H or LQ-L as reference for stop placement or partial-take zones, especially when other tools agree. Multi-timeframe mapping: Plot swing points on higher timeframes, then drill down to time entries on lower timeframes as price interacts with those levels. Why liquidity levels matter Prior swing points are focal areas where many strategies set stops or pending orders. Price often revisits these zones, either to “sweep” resting liquidity before reversing, or to absorb it and trend. Marking these areas objectively helps frame scenarios like failed breaks, successful breakouts, and retests, and it reduces the subjectivity of eyeballing structure. Settings to know Swing Detection Length (swing_length), Controls sensitivity. Lower values find more local swings. Higher values find more significant ones. Bars until removal (removeafter), Deletes levels after a fixed number of bars to prevent buildup. Extend Levels Right (extend_levels), Keeps levels projected into the future for easier planning. Label Size (label_size), Choose tiny to large for chart readability. One color input controls both high and low levels with transparency for context. Strengths Objective marking of recent structure without hand drawing No repaint after confirmation since pivots are locked once the right lookback completes Lightweight and fast with simple lifecycle management Clear visuals that integrate well with any price-action workflow Practical tips For scalping: use smaller swing_length to capture more granular liquidity. Keep removeafter short to avoid clutter. For swing trading: increase swing_length so only more meaningful levels remain. Consider extending levels to the right for planning. Combine with time-of-day filters, ATR for stop sizing, or a separate trend filter to bias trades taken at the levels. Keep screenshots focused: one image showing a sweep and reversal, another showing a clean breakout and retest. Limitations and notes Levels appear after confirmation, so they are delayed by swing_length bars. This is by design to avoid repainting. On very noisy or illiquid symbols, you may see many nearby levels. Increasing swing_length and shortening removeafter helps. The script does not assess volume or session context. Consider pairing with volume or session tools if that is part of your process.
Pine Script®指標
由BackQuant提供
7
Adaptive Valuation [BackQuant]Adaptive Valuation What this is A composite, zero-centered oscillator that standardizes several classic indicators and blends them into one “valuation” line. It computes RSI, CCI, Demarker, and the Price Zone Oscillator, converts each to a rolling z-score, then forms a weighted average. Optional smoothing, dynamic overbought and oversold bands, and an on-chart table make the inputs and the final score easy to inspect. How it works Components • RSI with its own lookback. • CCI with its own lookback. • DM (Demarker) with its own lookback. • PZO (Price Zone Oscillator) with its own lookback. Standardization via z-score Each component is transformed using a rolling z-score over lookback bars: z = (value − mean) ÷ stdev , where the mean is an EMA and the stdev is rolling. This puts all inputs on a comparable scale measured in standard deviations. Weighted blend The z-scores are combined with user weights w_rsi, w_cci, w_dm, w_pzo to produce a single valuation series. If desired, it is then smoothed with a selected moving average (SMA, EMA, WMA, HMA, RMA, DEMA, TEMA, LINREG, ALMA, T3). ALMA’s sigma input shapes its curve. Dynamic thresholds (optional) Two ways to set overbought and oversold: • Static : fixed levels at ob_thres and os_thres . • Dynamic : ±k·σ bands, where σ is the rolling standard deviation of the valuation over dynLen . Bands can be centered at zero or around the valuation’s rolling mean ( centerZero ). Visualization and UI • Zero line at 0 with gradient fill that darkens as the valuation moves away from 0. • Optional plotting of band lines and background highlights when OB or OS is active. • Optional candle and background coloring driven by the valuation. • Summary table showing each component’s current z-score, the final score, and a compact status. How it can be used • Bias filter : treat crosses above 0 as bullish bias and below 0 as bearish bias. • Mean-reversion context : look for exhaustion when the valuation enters the OB or OS region, then watch for exits from those regions or a return toward 0. • Signal confirmation : use the final score to confirm setups from structure or price action. • Adaptive banding : with dynamic thresholds, OB and OS adjust to prevailing variability rather than relying on fixed lines. • Component tuning : change weights to emphasize trend (raise DM, reduce RSI/CCI) or range behavior (raise RSI/CCI, reduce DM). PZO can help in swing environments. Why z-score blending helps Indicators often live on different scales. Z-scoring places them on a common, unitless axis, so a one-sigma move in RSI has comparable influence to a one-sigma move in CCI. This reduces scale bias and allows transparent weighting. It also facilitates regime-aware thresholds because the dynamic bands scale with recent dispersion. Inputs to know • Component lookbacks : rsilb, ccilb, dmlb, pzolb control each raw signal. • Standardization window : lookback sets the z-score memory. Longer smooths, shorter reacts. • Weights : w_rsi, w_cci, w_dm, w_pzo determine each component’s influence. • Smoothing : maType, smoothP, sig govern optional post-blend smoothing. • Dynamic bands : dyn_thres, dynLen, thres_k, centerZero configure the adaptive OB/OS logic. • UI : toggle the plot, table, candle coloring, and threshold lines. Reading the plot • Above 0 : composite pressure is positive. • Below 0 : composite pressure is negative. • OB region : valuation above the chosen OB line. Risk of mean reversion rises and momentum continuation needs evidence. • OS region : mirror logic on the downside. • Band exits : leaving OB or OS can serve as a normalization cue. Strengths • Normalizes heterogeneous signals into one interpretable series. • Adjustable component weights to match instrument behavior. • Dynamic thresholds adapt to changing volatility and drift. • Transparent diagnostics from the on-chart table. • Flexible smoothing choices, including ALMA and T3. Limitations and cautions • Z-scores assume a reasonably stationary window. Sharp regime shifts can make recent bands unrepresentative. • Highly correlated components can overweight the same effect. Consider adjusting weights to avoid double counting. • More smoothing adds lag. Less smoothing adds noise. • Dynamic bands recalibrate with dynLen ; if set too short, bands may swing excessively. If too long, bands can be slow to adapt. Practical tuning tips • Trending symbols: increase w_dm , use a modest smoother like EMA or T3, and use centerZero dynamic bands. • Choppy symbols: increase w_rsi and w_cci , consider ALMA with a higher sigma , and widen bands with a larger thres_k . • Multiday swing charts: lengthen lookback and dynLen to stabilize the scale. • Lower timeframes: shorten component lookbacks slightly and reduce smoothing to keep signals timely. Alerts • Enter and exit of Overbought and Oversold, based on the active band choice. • Bullish and bearish zero crosses. Use alerts as prompts to review context rather than as stand-alone trade commands. Final Remarks We created this to show people a different way of making indicators & trading. You can process normal indicators in multiple ways to enhance or change the signal, especially with this you can utilise machine learning to optimise the weights, then trade accordingly. All of the different components were selected to give some sort of signal, its made out of simple components yet is effective. As long as the user calibrates it to their Trading/ investing style you can find good results. Do not use anything standalone, ensure you are backtesting and creating a proper system.
Pine Script®指標
由BackQuant提供
Volumetric Support and Resistance [BackQuant]Volumetric Support and Resistance What this is This Overlay locates price levels where both structure and participation have been meaningful. It combines classical swing points with a volume filter, then manages those levels on the chart as price evolves. Each level carries: • A reference price (support or resistance) • An estimate of the volume that traded around that price • A touch counter that updates when price retests it • A visual box whose thickness is scaled by volatility The result is a concise map of candidate support and resistance that is informed by both price location and how much trading occurred there. How levels are built Find structural pivots uses ta.pivothigh and ta.pivotlow with a user set sensitivity. Larger sensitivity looks for broader swings. Smaller sensitivity captures tighter turns. Require meaningful volume computes an average volume over a lookback period and forms a volume ratio for the current bar. A pivot only becomes a level when the ratio is at least the volume significance multiplier. Avoid clustering checks a minimum level distance (as a percent of price). If a candidate is too close to an existing level, it is skipped to keep the map readable. Attach a volume strength to the level estimates volume strength by averaging the volume of recent bars whose high to low range spans that price. Levels with unusually high strength are flagged as high volume. Store and draw levels are kept in an array with fields for price, type, volume, touches, creation bar, and a box handle. On the last bar, each level is drawn as a horizontal box centered at the price with a vertical thickness scaled by ATR. Borders are thicker when the level is marked high volume. Boxes can extend into the future. How levels evolve over time • Aging and pruning : levels are removed if they are too old relative to the lookback or if you exceed the maximum active levels. • Break detection : a level can be removed when price closes through it by more than a break threshold set as a fraction of ATR. Toggle with Remove Broken Levels. • Touches : when price approaches within the break threshold, the level’s touch counter increments. Visual encoding • Boxes : support boxes are green, resistance boxes are red. Box height uses an ATR based thickness so tolerance scales with volatility. Transparency is fixed in this version. Borders are thicker on high volume levels. • Volume annotation : show the estimated volume inside the box or as a label at the right. If a level has more than one touch, a suffix like “(2x)” is appended. • Extension : boxes can extend a fixed number of bars into the future and can be set to extend right. • High volume bar tint : bars with volume above average × multiplier are tinted green if up and red if down. Inputs at a glance Core Settings • Level Detection Sensitivity — pivot window for swing detection • Volume Significance Multiplier — minimum volume ratio to accept a pivot • Lookback Period — window for average volume and maintenance rules Level Management • Maximum Active Levels — cap on concurrently drawn levels • Minimum Level Distance (%) — required spacing between level prices Visual Settings • Remove Broken Levels — drop a level once price closes decisively through it • Show Volume Information on Levels — annotate volume and touches • Extend Levels to Right — carry boxes forward Enhanced Visual Settings • Show Volume Text Inside Box — text placement option • Volume Based Transparency and Volume Based Border Thickness — helper logic provided; current draw block fixes transparency and increases border width on high volume levels Colors • Separate colors for support, resistance, and their high volume variants How it can be used • Trade planning : use the most recent support and resistance as reference zones for entries, profit taking, or stop placement. ATR scaled thickness provides a practical buffer. • Context for patterns : combine with breakouts, pullbacks, or candle patterns. A breakout through a high volume resistance carries more informational weight than one through a thin level. • Prioritization : when multiple levels are nearby, prefer high volume or higher touch counts. • Regime adaptation : widen sensitivity and increase minimum distance in fast regimes to avoid clutter. Tighten them in calm regimes to capture more granularity. Why volume support and resistance is used in trading Support and resistance relate to willingness to transact at certain prices. Volume measures participation. When many contracts change hands near a price: • More market players hold inventory there, often creating responsive behavior on retests • Order flow can concentrate again to defend or to exit • Breaks can be cleaner as trapped inventory rebalances Conditioning level detection on above average activity focuses attention on prices that mattered to more participants. Alerts • New Support Level Created • New Resistance Level Created • Level Touch Alert • Level Break Alert Strengths • Dual filter of structure and participation, reducing trivial swing points • Self cleaning map that retires old or invalid levels • Volatility aware presentation using ATR based thickness • Touch counting for persistence assessment • Tunable inputs for instrument and timeframe Limitations and caveats • Volume strength is an approximation based on bars spanning the price, not true per price volume • Pivots confirm after the sensitivity window completes, so new levels appear with a delay • Narrow ranges can still cluster levels unless minimum distance is increased • Large gaps may jump past levels and immediately trigger break conditions Practical tuning guide • If the chart is crowded: increase sensitivity, increase minimum level distance, or reduce maximum active levels • If useful levels are missed: reduce volume multiplier or sensitivity • If you want stricter break removal: increase the ATR based break threshold in code • For instruments with session patterns: tailor the lookback period to a representative window Interpreting touches and breaks • First touch after creation is a validation test • Multiple shallow touches suggest absorption; a later break may then travel farther • Breaks on high current volume merit extra attention Multi timeframe usage Levels are computed on the active chart timeframe. A common workflow is to keep a higher timeframe instance for structure and a lower timeframe instance for execution. Align trades with higher timeframe levels where possible. Final Thoughts This indicator builds a lightweight, self updating map of support and resistance grounded in swings and participation. It is not a full market profile, but it captures much of the practical benefit with modest complexity. Treat levels as context and decision zones, not guarantees. Combine with your entry logic and risk controls.
Pine Script®指標
由BackQuant提供
5
EMA Oscillator [Alpha Extract]A precision mean reversion analysis tool that combines advanced Z-score methodology with dual threshold systems to identify extreme price deviations from trend equilibrium. Utilizing sophisticated statistical normalization and adaptive percentage-based thresholds, this indicator provides high-probability reversal signals based on standard deviation analysis and dynamic range calculations with institutional-grade accuracy for systematic counter-trend trading opportunities. 🔶 Advanced Statistical Normalization Calculates normalized distance between price and exponential moving average using rolling standard deviation methodology for consistent interpretation across timeframes. The system applies Z-score transformation to quantify price displacement significance, ensuring statistical validity regardless of market volatility conditions. // Core EMA and Oscillator Calculation ema_values = ta.ema(close, ema_period) oscillator_values = close - ema_values rolling_std = ta.stdev(oscillator_values, ema_period) z_score = oscillator_values / rolling_std 🔶 Dual Threshold System Implements both statistical significance thresholds (±1σ, ±2σ, ±3σ) and percentage-based dynamic thresholds calculated from recent oscillator range extremes. This hybrid approach ensures consistent probability-based signals while adapting to varying market volatility regimes and maintaining signal relevance during structural market changes. // Statistical Thresholds mild_threshold = 1.0 // ±1σ (68% confidence) moderate_threshold = 2.0 // ±2σ (95% confidence) extreme_threshold = 3.0 // ±3σ (99.7% confidence) // Percentage-Based Dynamic Thresholds osc_high = ta.highest(math.abs(z_score), lookback_period) mild_pct_thresh = osc_high * (mild_pct / 100.0) moderate_pct_thresh = osc_high * (moderate_pct / 100.0) extreme_pct_thresh = osc_high * (extreme_pct / 100.0) 🔶 Signal Generation Framework Triggers buy/sell alerts when Z-score crosses extreme threshold boundaries, indicating statistically significant price deviations with high mean reversion probability. The system generates continuation signals at moderate levels and reversal signals at extreme boundaries with comprehensive alert integration. // Extreme Signal Detection sell_signal = ta.crossover(z_score, selected_extreme) buy_signal = ta.crossunder(z_score, -selected_extreme) // Dynamic Color Coding signal_color = z_score >= selected_extreme ? #ff0303 : // Extremely Overbought z_score >= selected_moderate ? #ff6a6a : // Overbought z_score >= selected_mild ? #b86456 : // Mildly Overbought z_score > -selected_mild ? #a1a1a1 : // Neutral z_score > -selected_moderate ? #01b844 : // Mildly Oversold z_score > -selected_extreme ? #00ff66 : // Oversold #00ff66 // Extremely Oversold 🔶 Visual Structure Analysis Provides a six-tier color gradient system with dynamic background zones indicating mild, moderate, and extreme conditions. The histogram visualization displays Z-score intensity with threshold reference lines and zero-line equilibrium context for precise mean reversion timing. snapshot 4H 1D 🔶 Adaptive Threshold Selection Features intelligent threshold switching between statistical significance levels and percentage-based dynamic ranges. The percentage system automatically adjusts to current volatility conditions using configurable lookback periods, while statistical thresholds maintain consistent probability-based signal generation across market cycles. 🔶 Performance Optimization Utilizes efficient rolling calculations with configurable EMA periods and threshold parameters for optimal performance across all timeframes. The system includes comprehensive alert functionality with customizable notification preferences and visual signal overlay options. 🔶 Market Oscillator Interpretation Z-score > +3σ indicates statistically significant overbought conditions with high reversal probability, while Z-score < -3σ signals extreme oversold levels suitable for counter-trend entries. Moderate thresholds (±2σ) capture 95% of normal price distributions, making breaches statistically significant for systematic trading approaches. snapshot 🔶 Intelligent Signal Management Automatic signal filtering prevents false alerts through extreme threshold crossover requirements, while maintaining sensitivity to genuine statistical deviations. The dual threshold system provides both conservative statistical approaches and adaptive market condition responses for varying trading styles. Why Choose EMA Oscillator ? This indicator provides traders with statistically-grounded mean reversion analysis through sophisticated Z-score normalization methodology. By combining traditional statistical significance thresholds with adaptive percentage-based extremes, it maintains effectiveness across varying market conditions while delivering high-probability reversal signals based on quantifiable price displacement from trend equilibrium, enabling systematic counter-trend trading approaches with defined statistical confidence levels and comprehensive risk management parameters.
Pine Script®指標
由AlphaExtract提供
1