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무빙 애버리지

Bitcoin WMA Bands | Astral Vision Bitcoin WMA Bands | Astral Vision 💠🌠 This indicator constructs a volatility-adjusted band system around a Weighted Moving Average of price, using the standard deviation of logarithmic daily returns as the volatility measure rather than the standard deviation of price itself. The result is a channel whose width adapts dynamically to the current volatility regime, expanding during high-volatility periods and contracting during low-volatility ones, while remaining anchored to the WMA as the structural fair value reference. Calculation ⚙️ The base reference line is a Weighted Moving Average of close over a configurable lookback in days. WMA weights recent bars more heavily than older ones using a linearly declining weight schedule, making it more responsive to recent price action than an SMA of the same length while being less erratic than an EMA. The volatility measure is computed from logarithmic returns: for each bar, the log return is log(close / close ). The standard deviation of these log returns over a configurable lookback window is then multiplied by a configurable scale factor to produce the band half-width `s`. Using log returns rather than raw price changes ensures that the volatility measure is proportional across different price levels, making a 5% move at $10,000 and a 5% move at $100,000 contribute equally to the standard deviation. The four bands are then computed as: band = WMA × exp(±n × s), where n is 1 or 2. The exponential transformation converts the log-space deviation back to price-space, ensuring the bands are multiplicatively symmetric around the WMA rather than additively symmetric. This means the upper and lower bands are equidistant in percentage terms rather than in absolute dollar terms. The oscillator in the sub-panel is the log ratio of close to the WMA: log(close / WMA), which measures in log-space how far price has deviated from its trend. The same ±1σ and ±2σ levels are plotted in the sub-panel, allowing direct visual comparison of the oscillator's position within the band structure. Candles on the price chart are colored only when price is outside the ±1σ band, leaving them neutral in the fair value zone between the bands. Crossover signals are generated when the oscillator crosses back inside the ±1σ boundary from outside: a triangle appears above the bar when the oscillator crosses back below the upper +1σ level from above, and below the bar when it crosses back above the lower -1σ level from below. Plots 📊 WMA reference line on the price chart Four volatility-adjusted bands at ±1σ and ±2σ on the price chart Candle coloring on the price chart when price is outside the ±1σ band Background color on the price chart between the ±1σ and ±2σ zones Re-entry signals: triangle above bar on upper band exit, triangle below bar on lower band exit Log-ratio oscillator in the sub-panel with matching ±1σ and ±2σ reference lines Inputs 🎛️ STH Length: WMA lookback period in days StDev Length: rolling window for the log return standard deviation Band Scale: multiplier applied to the standard deviation before computing band width Colors 🎨 5 Astral Vision presets + custom override. Default: Paradiso. Purpose 🎯 Standard Bollinger Bands apply a fixed standard deviation multiple to a simple moving average computed on raw prices, which means the band width in percentage terms varies across different price levels and the bands do not correctly represent proportional deviations. This indicator applies the volatility measure in log-return space and converts back with the exponential function, producing bands that are geometrically consistent across Bitcoin's full price history. The WMA further reduces the lag of the central reference compared to an SMA, making the band system more responsive to trend changes without introducing the instability of shorter lookbacks. Disclaimer ⭕️ This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions.
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AstralVision의
Multi-Timeframe MA Structure & RSI ConfluenceThis indicator combines multi-timeframe moving averages, RSI-based swing structure labels, and a compact RSI confluence panel into one chart overlay. Features: EMA/SMA 50 and 200 for 15m, 1h, 4h, Daily and Weekly timeframes Optional automatic hiding of lower-timeframe MAs on higher-timeframe charts EMA/SMA visual distinction using solid and dashed lines RSI-based swing high/low labels: HH, HL, LH, LL Developing swings marked with “?” Structure-based label coloring: HH/HL green, LH/LL red Regular bullish and bearish RSI divergence labels Compact RSI panel showing RSI value, regime, momentum, RSI vs MA, recent MA cross and recent divergence The indicator is designed as a visual market-structure and confluence tool. It does not generate buy or sell signals and should not be used as a standalone trading system. The swing logic is inspired by RSI overbought/oversold cycle concepts originally published by BalintDavid.
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faint_idea의
3
Roy EMA Multi Time FrameRoy EMA Multi Timeframe is a simple multi-timeframe EMA trend dashboard. This indicator displays bullish or bearish trend conditions across multiple timeframes based on price position relative to the selected EMA. If price is above EMA, the trend is shown as BULLISH. If price is below EMA, the trend is shown as BEARISH. Users can customize the EMA length based on their own trading style, such as EMA 20, EMA 50, EMA 100, EMA 200 or any preferred value. This tool is designed to help traders quickly identify trend alignment across multiple timeframes. Best used together with support/resistance, market structure, candlestick confirmation and proper risk management.
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Sdroy87의
Momentum Ignition System PRO+🚀 Momentum Ignition System PRO+ A hybrid momentum-trend indicator designed for traders who focus on: Volatility Contraction Patterns (VCP) Momentum ignition setups EMA trend structure Institutional accumulation zones Breakout trading This indicator combines trend, momentum, anchored VWAP, volatility, and market structure into a single clean framework for identifying high-probability breakout candidates. 🔥 Key Features ✅ RSI Momentum Ignition Engine Uses: RSI(14) WMA(200) of RSI The indicator plots: 🟢 Bullish arrows when RSI crosses ABOVE WMA(200) 🔴 Bearish arrows when RSI crosses BELOW WMA(200) This helps identify: momentum regime shifts early trend ignition potential breakout expansion phases ✅ Multi-EMA Trend Structure Includes customizable: EMA 10 EMA 20 EMA 50 EMA 200 Useful for: trend alignment pullback entries trend continuation institutional trend structure ✅ Bullish / Bearish EMA Cloud Dynamic cloud between EMA20 & EMA50: 🟢 Green Cloud → bullish trend structure 🔴 Red Cloud → bearish trend structure Helps visualize: trend health base formation momentum alignment ✅ Anchored VWAP Custom Anchored VWAP with selectable anchor periods: Session Weekly Monthly Anchored VWAP helps identify: institutional average price support/resistance accumulation zones fair value areas ✅ ADR% (Average Daily Range) Displays customizable ADR% table with dynamic coloring. Color Logic: 🟢 Green → high expansion potential 🟠 Orange → moderate volatility 🔴 Red → low volatility Useful for: breakout potential volatility expansion position sizing 🎯 Ideal Usage Best suited for: Swing Trading Momentum Trading Breakout Trading VCP Setups Qullamaggie-style setups Minervini-style trend continuation setups
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BullBear_BO의
Intraday EMAShort Description Dynamic EMA Envelope based on recent hourly high/low structure with optional single EMA mode. Full Publishing Description Intraday EMA Envelope Intraday EMA Envelope is a lightweight trend-following indicator designed for intraday traders who want adaptive EMA-based structure visualization. The script derives EMA reference lengths from recent hourly market behavior using highest and lowest price offsets over a configurable lookback period. Features • Adaptive EMA logic based on hourly market structure • Optional Single EMA mode • EMA Envelope visualization with fill zone • Smooth EMA calculations for cleaner trend tracking • Real-time EMA length display table • Mutually exclusive display modes for clean chart appearance How It Works The indicator scans hourly candles over the selected lookback period and calculates: Highest high offset Lowest low offset These offsets are converted into dynamic EMA reference lengths. Two smoothed EMAs are then plotted: Upper EMA Lower EMA Users can choose between: Single EMA mode EMA Envelope mode Both modes are intentionally made mutually exclusive to avoid chart clutter. Inputs • Lookback Days Controls the hourly historical range used for EMA calculations. • Show Single EMA Displays only one smoothed EMA. • Show EMA Envelope Displays the EMA channel/envelope with fill. Best Usage This indicator works best for: Intraday trend identification Pullback trading Dynamic support/resistance tracking Trend continuation setups
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ManishDhyani의
1
Obsidian Trend Relay [JOAT]Obsidian Trend Relay Introduction Obsidian Trend Relay is an open-source multi-timeframe trend and risk-ladder indicator. It combines zero-lag EMA logic, SuperTrend, an EMA ribbon, three higher-timeframe confirmation votes, prediction threshold rails, proximity warnings, candle coloring, risk ladder boxes, right-side price labels, and a top-right dashboard. The script is built for users who want a directional trend context layer with structured visual planning. It does not claim to forecast price. Instead, it shows when local trend, ribbon structure, SuperTrend, and higher-timeframe votes align or conflict. Core Concepts 1. Zero-Lag EMA Core The zero-lag component reduces the smoothing delay of a standard EMA by comparing the first EMA against a second smoothing pass. This creates a responsive trend anchor used for reclaim and rejection logic. // Conceptual summary // zlema = 2 * ema(source, length) - ema(ema(source, length), length) 2. SuperTrend and EMA Ribbon SuperTrend provides an ATR-based directional rail. The EMA ribbon checks whether fast, mid, slow, and base averages are stacked in directional order. Both must be read together with the zero-lag line. 3. Multi-Timeframe Relay Votes Three higher-timeframe checks compare zero-lag and EMA structure using request.security() with lookahead off. The dashboard displays each vote and the total confluence score. 4. Prediction and Proximity Rails The prediction engine creates upper/lower threshold rails around the trend anchor. Proximity warnings identify when price is near a key transition rail and may be close to a directional decision point. 5. Risk Ladder When a relay signal appears, the script can draw a reward box, risk box, warning zone, entry, stop, and T1/T2/T3 rails. These are visual planning tools only. Features Zero-lag trend anchor: Responsive baseline for reclaim and rejection context SuperTrend filter: ATR-based directional rail EMA ribbon: Visual trend stack using multiple moving averages Three HTF votes: Higher-timeframe confluence with lookahead off Prediction rails: Upper/lower threshold bands around the zero-lag engine Proximity warning: Highlights price near key trend rails Risk ladder boxes: Draws risk, warning, reward, entry, stop, and T1/T2/T3 levels Gradient candle tinting: Colors candles from confluence and trend state Top-right dashboard: Shows local trend, ribbon, HTF votes, prediction, proximity, and ladder state Confirmed-bar logic: Relay and ladder events use confirmed bars Input Parameters Trend Engine: Source Zero Lag Length SuperTrend ATR Length SuperTrend Factor Ribbon Fast, Mid, Slow, and Base lengths MTF and Risk: Higher Timeframe 1, 2, and 3 Minimum Confluence Votes Stop ATR Mult Target ATR Mult Show Risk Ladder How to Use This Indicator Step 1: Check confluence Use the dashboard to see whether the local trend and higher timeframes agree. Step 2: Read the ribbon A clean stacked ribbon provides stronger trend context than a mixed ribbon. Step 3: Watch proximity rails Proximity warnings indicate price is near a transition threshold. Step 4: Treat the ladder as a visual plan The risk ladder maps possible risk and reward levels, but it does not execute trades or ensure outcomes. Indicator Limitations Higher-timeframe values can update during an unfinished higher-timeframe candle Trend tools can lag during sharp reversals Risk ladder levels are visual only Sideways markets may generate mixed confluence readings Originality Statement Obsidian Trend Relay combines zero-lag trend anchoring, SuperTrend, EMA ribbon stacking, three higher-timeframe votes, prediction thresholds, proximity warnings, and managed risk ladders into one open-source Pine v6 trend relay. Its purpose is to organize trend alignment and risk visualization in one coherent chart layer. Disclaimer This script is for educational and informational use only. It is not financial advice or a promise of future results. Always use independent judgment and risk management. -Made with passion by jackofalltrades
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officialjackofalltrades의
Stochastic Bot with SL/TPStochastic Momentum Bot with Risk Management Description This trading bot is an automated strategy designed for TradingView. It aims to capitalize on short-term price reversals by identifying when an asset is temporarily "oversold" (priced too low) or "overbought" (priced too high) using the Stochastic Oscillator. Unlike basic indicator scripts that simply highlight buy and sell signals on a chart, this is a full Strategy Script. This means it virtually executes trades using historical data, applying strict Stop-Loss (SL) and Take-Profit (TP) percentages to protect your capital. It is highly customizable, allowing you to fine-tune the parameters to suit different assets and timeframes. How the Logic Works Entry (Buy): The bot enters a Long position when the %K line crosses above the %D line, but only if both lines are below the 20 threshold (indicating the asset is heavily oversold and momentum is shifting upward). Exit 1 (Take Profit): The bot will automatically close the trade if the price rises by your set Take-Profit percentage. Exit 2 (Stop Loss): The bot will automatically cut its losses and close the trade if the price drops by your set Stop-Loss percentage. Exit 3 (Momentum Reversal): If neither the SL nor TP is hit, the bot will close the trade early if the %K line crosses below the %D line while above the 60 threshold (indicating the asset is overbought and momentum is dying). Step-by-Step Guide to Using the Bot Part 1: Loading the Script into TradingView Open TradingView and load the chart you want to trade (e.g., TAO/USDT on the 15-minute timeframe). At the very bottom of the screen, click on the Pine Editor tab.Delete any existing code in the editor window so it is completely blank. Copy the Pine Script code provided previously and paste it into the editor. Click the Save button (floppy disk icon) at the top right of the Pine Editor and give your script a name (e.g., "Stochastic Bot"). Click the "Add to Chart" button. Part 2: Customizing the Strategy SettingsOnce the script is on your chart, a new menu will appear at the top left of your chart area with the name of your script.Hover over the script's name and click the Gear Icon (Settings).Click on the Inputs tab. Here is what each setting controls: Setting Name Default Description %K Length14 The number of previous candles used to calculate the main momentum line.%K Smoothing3Smooths out the %K line to reduce false signals.%D Smoothing3The moving average of the %K line, used as the trigger line for crossovers. Stop Loss (%)2.5 The maximum percentage of price drop you are willing to risk before exiting a trade. Take Profit (%)6.0 The percentage of price increase required to automatically lock in profits and exit. Part 3: Reading the Strategy Tester Once the bot is on your chart, the Strategy Tester tab at the bottom of the screen will automatically populate with backtesting data based on your current settings and timeframe. Net Profit: The total amount of money the bot made (or lost) over the given time period. Total Closed Trades: How many times the bot bought and sold. Percent Profitable (Win Rate): The percentage of trades that ended in a profit. Max Drawdown: The largest percentage drop in your account balance from its peak. This is a crucial metric for understanding risk; a high drawdown means the bot experienced severe losing streaks. List of Trades: A tab inside the Strategy Tester that shows you every single historical entry, exit, and the exact price it triggered at.
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JimmyPerez의
Helios Institutional Synthesis Strategy [JOAT]Helios Institutional Synthesis Strategy Introduction Helios Institutional Synthesis Strategy is an open-source Pine v6 strategy that integrates regime detection, trend bias, VWAP location, premium/discount context, liquidity sweeps, volatility gating, structured ATR stops, target levels, trailing exits, time exits, and visual trade-zone boxes. The strategy is designed as a realistic testing framework, not a performance promise. It uses confirmed-bar triggers, process-on-close order handling, commission, slippage, risk sizing, and daily risk guard logic. The default settings were made active enough to generate more samples across timeframes while still keeping basic risk controls in place. Core Concepts 1. Regime and Trend Bias An adaptive baseline, EMA momentum, DMI/ADX, and volatility score determine whether the market is bullish, bearish, or ranging. Long setups require bullish context, and short setups require bearish context unless other confluence factors compensate. 2. VWAP and Premium/Discount Context The strategy compares price to session VWAP and to a rolling premium/discount range. This helps distinguish continuation entries from recovery or rejection setups. 3. Liquidity and Retest Triggers Confirmed sweeps, daily level reclaims/rejections, VWAP bounces, baseline crosses, and channel reclaim/rejection logic can contribute to entries. This creates more than one path into a trade while still requiring a confluence score. 4. Volatility and Risk Gates The strategy filters by volatility score, ATR percent of price, daily equity guard, and minimum planned R. These controls are included to avoid unbounded entries in abnormal conditions. 5. Structured Exits Stops use ATR and recent key levels. Targets use ATR multiples. A trailing stop can tighten the exit as price moves, and a max-hold rule can close trades that remain open too long. Default Strategy Properties Initial capital: 100000 Commission: 0.01 percent Slippage: 1 tick Pyramiding: 0 Orders processed on close: true calc_on_every_tick: false Default risk per trade: 1.0 percent Default minimum confluence score: 4 out of 8 Default cooldown: 4 bars Default ATR stop multiple: 1.8 Default ATR target multiple: 2.8 Default trailing ATR multiple: 1.35 Default daily equity guard: 3 percent Features 8-point confluence model: Combines regime, VWAP, premium/discount, momentum, volatility, sweeps, squeeze release, and HTF bias Confirmed-bar entries: Long and short triggers use barstate.isconfirmed HTF confirmation: Uses request.security() with lookahead off and previous higher-timeframe values Risk-based sizing: Calculates quantity from equity, stop distance, and risk percentage ATR stop and target: Structured stop/target logic with optional trailing behavior Daily guard: Blocks new trades after a configured intraday equity drawdown threshold Max-hold exit: Closes positions that exceed the configured bar count Trade-zone boxes: Shows reward/risk boxes on the chart Right-side risk rails: Labels active entry, stop, target, and R:R Dashboard: Shows regime, position, confluence, risk gate, setup, volatility, VWAP sigma, liquidity, HTF bias, PD state, session, day guard, hold bars, stops, and key levels Input Parameters Core Engine: Adaptive Baseline Length Efficiency Lookback ATR Length ADX / DMI Length Institutional Anchor Length Confirmation Timeframe Filters: Enable Longs and Enable Shorts Restrict to Session Min Confluence Score Cooldown Bars Volatility score bounds Risk Controls: Risk percent per trade ATR stop, target, and trailing multiples Minimum planned R multiple Max ATR percent of price Daily equity guard percent Max hold bars How to Use This Strategy Step 1: Start with a private draft Before publishing results, test the strategy privately and verify the chart, settings, and description. Step 2: Use realistic costs The script defaults to 0.01 percent commission and 1 tick slippage. Adjust them to match the market being tested. Step 3: Check sample size Use enough historical data to evaluate whether the strategy has a meaningful number of trades. Avoid drawing conclusions from a small sample. Step 4: Review the dashboard The dashboard shows whether a blocked trade is caused by risk, volatility, session, confluence, or daily guard logic. Strategy Limitations Backtests are hypothetical and do not ensure future results Performance can vary significantly by symbol, session, timeframe, and cost settings The strategy may trade frequently on lower timeframes; costs and slippage matter HTF confirmation uses non-lookahead requests, but higher-timeframe context can still evolve while a higher-timeframe bar is unfinished Risk controls reduce some bad conditions but cannot remove market risk Originality Statement Helios Institutional Synthesis Strategy combines adaptive regime detection, VWAP sigma location, premium/discount context, liquidity sweep triggers, squeeze state, higher-timeframe confirmation, risk-based sizing, ATR exits, daily guard logic, time exits, and visual trade-zone mapping in one open-source Pine v6 strategy. Its purpose is to test a multi-factor decision process with transparent components rather than present a black-box signal system. Disclaimer This strategy is for educational and informational use only. It is not financial advice, and backtested results do not ensure future performance. Trading involves substantial risk of loss. Always test with realistic commissions, slippage, and position sizing before making any decision. -Made with passion by jackofalltrades
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officialjackofalltrades의
KEEB Strategy - Crossover SignalsKEEB Strategy - EMA 20 & MA 200 Crossover Indicator Overview The KEEB Strategy is a momentum and trend-following trading system designed to capture high-probability continuation moves and trend reversals. It uses institutional moving averages to filter out market noise and trigger highly precise entry signals, making it exceptionally effective for fast-paced charts like the 1-minute, 5-minute, or 15-minute timeframes. How It Works The strategy relies on a primary directional filter and a strict mechanical trigger: The Institutional Filter (MA 200): A 200-period Simple Moving Average (SMA) acts as the baseline for the macro trend. The Execution Trigger (EMA 20): A 20-period Exponential Moving Average (EMA) tracks the immediate structural momentum. The Visual Guide (EMA 9): A 9-period EMA is plotted to give the trader a clear view of short-term micro-momentum and potential trailing stop levels. Entry Signals The script automatically calculates crossovers and prints clean, actionable labels directly on your chart: KEEB LONG (Buy Signal): Triggered the exact moment the EMA 20 crosses above the MA 200. This signals a powerful shift into a bullish regime. KEEB SHORT (Sell Signal): Triggered the exact moment the EMA 20 crosses below the MA 200. This signals an aggressive breakdown into a bearish regime. Key Features Zero Lag Execution: Signals trigger precisely on the crossover candle, capturing the exact moment institutional volume pushes the market past the macro average. Clean Visual Interface: Plots explicit green triangles (KEEB LONG) below the bars and red triangles (KEEB SHORT) above the bars. Fully Automated Alerts: Includes pre-configured native TradingView alert conditions (alertcondition) so you can receive instant push notifications or webhooks on your phone or PC the second a crossover occurs.
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viraldfw의
SOPR Percentile Oscillator | Astral Vision SOPR Percentile Oscillator | Astral Vision 🌠💠 This indicator transforms the Spent Output Profit Ratio into a percentile-ranked oscillator, measuring where today's SOPR reading sits relative to its own history over a configurable lookback window. SOPR is an on-chain metric that divides the realized value of all Bitcoin outputs spent on a given day by their value at the time they were created: a reading above 1.0 means coins are being sold at a profit on aggregate, below 1.0 means coins are being sold at a loss. Calculation ⚙️ The raw SOPR is fetched from Glassnode on a daily timeframe. A percentile rank is then computed over a configurable lookback window using `ta.percentrank`, which counts how many of the past N values are lower than the current value and expresses the result as a percentage from 0 to 100. A reading of 85 means the current SOPR is higher than 85% of all daily readings over the lookback period, placing it in historically elevated territory. A reading of 15 means SOPR is lower than 85% of historical readings, placing it in historically depressed territory. Two simple moving averages are applied to the percentile rank series: a short-term SMA over a configurable window (default 30 days) that captures recent momentum, and a long-term SMA over a configurable window (default 365 days) that represents the structural trend of the percentile rank. The short-term SMA is the primary signal line; the long-term SMA is used in Trend mode as the reference for directional classification. The indicator operates in two modes. Extremes mode colors the oscillator neutrally between the configurable overbought and oversold percentile thresholds, and highlights only when the short-term SMA enters one of the two extreme zones, also applying background color to the price chart. Trend mode compares the short-term SMA against the long-term SMA: when the short is above the long, the regime is bullish; when below, bearish. A fill between the two lines visually represents the spread between short and long-term percentile positioning. Plots 📊 Short-term SMA of the SOPR percentile rank, colored by mode and regime Long-term SMA of the SOPR percentile rank (Trend mode only) Fill between short and long-term SMA (Trend mode only) Overbought and oversold percentile threshold lines (Extremes mode only) Background color on the price chart when short SMA enters extreme zones (Extremes mode) Candle coloring on the price chart reflecting current regime in both modes Inputs 🎛️ Mode: Extremes or Trend Short Term SMA: smoothing window applied to the percentile rank for the signal line Long Term SMA: smoothing window for the structural trend reference Lookback: historical window for the percentile rank computation Overbought Threshold: upper percentile level marking historically elevated SOPR Oversold Threshold: lower percentile level marking historically depressed SOPR Colors 🎨 5 Astral Vision presets + custom override. Default: Paradiso. Purpose 🎯 Raw SOPR fluctuates around 1.0 on an expanding scale as Bitcoin matures, making fixed absolute thresholds unreliable across different market cycles. Converting to a percentile rank normalizes the series against its own historical distribution, so a percentile reading of 85 in 2017 and a reading of 85 in 2024 are statistically equivalent statements about how extreme current on-chain profit-taking behavior is relative to its own history. The dual SMA structure further separates short-term extremes from structural regime shifts, which are analytically distinct signals that a single moving average cannot distinguish. Disclaimer ⭕️ This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions.
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AstralVision의
MTF MA System by ogudora# MTF MA System by ogudora A multi-timeframe moving average indicator designed for traders who need to read multiple MAs at a glance without losing track of which line belongs to which timeframe. ## What it does Plots short, mid, and long-term moving averages from up to four timeframes simultaneously: the current chart timeframe, 1H, 4H, and Daily. Each line is identified by three independent visual dimensions: - **Color** indicates the period (short / mid / long) - **ATR-based halo width** indicates the timeframe (higher TF = wider halo) - **Line style and thickness** add another layer of timeframe distinction This three-axis encoding eliminates the common problem of MTF MA indicators where users lose track of which line is which. ## Key features **RTH-only calculation by default.** Upper timeframe MAs are calculated using Regular Trading Hours data only, independent of the chart's Extended Hours setting. This ensures that the same MA value appears regardless of which timeframe chart you are viewing. ETH-inclusive mode is available as a toggle. **ATR-based halo bands.** Instead of a single thin line, each MA is drawn with a translucent halo whose width scales with current ATR. Higher timeframes get wider halos, so a daily MA visually feels like a zone, while a 1H MA reads as a precise line. **Per-timeframe line thickness and style.** Each TF group has independent settings for line thickness (1 to 4) and style (plain / stepline / stepline with diamonds). The default uses a diamond stepline for 4H to give it a distinctive "ladder" appearance. **Keep-out labels.** Optional labels along each MA line at regular intervals, useful for marking visual zones across the chart. **Auto TF filtering.** Lower timeframe MAs are automatically hidden when you switch to a higher chart TF, preventing visual clutter on long-term charts. ## Default configuration - **MA type:** EMA, periods 20 / 50 / 200 - **Timeframes:** 1H, 4H, Daily (current chart TF off by default) - **Session:** RTH only - **Colors:** magenta (short) / green (mid) / purple (long) - **Halo widths:** 1H = 0.1×ATR, 4H = 0.1×ATR, Daily = 0.4×ATR - **Line thickness:** 1H = 3, 4H = 1, Daily = 3 - **4H line style:** stepline with diamonds These defaults are tuned for U.S. equities and Japanese equities on intraday-to-swing timeframes. All values are user-configurable. ## Notes on session handling For U.S. stocks, the 4H EMA200 calculated from RTH data and from ETH-inclusive data can differ by 10–15% during volatile periods. The default RTH mode aligns with how most institutional desks read moving averages. If you trade extended-hours moves and prefer ETH-inclusive calculation, toggle the session setting in the indicator inputs. ## Compatible markets Designed and tested on U.S. equities (NASDAQ, NYSE) and Japanese equities. Should work on any symbol where the underlying exchange has a defined Regular Trading Hours session. ## Why I built this After years of running MTF MA indicators that became unreadable once more than four or five lines were on screen, I wanted a system that uses encoding redundancy — color, halo width, and line style — so that any single line could be identified without reading its legend. This indicator is the result of that iteration. Feedback and suggestions are welcome.
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ogudora0812의
Quantum Pulse AI V6 [Nifty AI Scalper]High-Level Overview This script is a hybrid trading system that combines traditional trend-following indicators with a k-Nearest Neighbors (k-NN) Machine Learning engine. Instead of relying solely on hardcoded crossovers, it looks at the current market conditions, searches its historical memory for similar moments, and predicts the next move based on what happened in the past. 1. The Technical Foundation (Base Features) Before the AI even kicks in, the script tracks a robust baseline of institutional-grade metrics: Moving Averages: Two customizable MAs (SMA/EMA/VWMA) determine short-term momentum. VWAP & Bands: Anchored daily VWAP with up to 3 standard deviation bands to judge institutional value and overbought/oversold extremes. Trend Smoothing: Hull Moving Average (HMA) and Supertrend dictate the broader directional bias. Momentum Filters: ADX ensures the market is actually trending (ignoring chop), while relative volume tracks participation. 2. The AI k-NN Classification Engine This is the "brain" of the script. It uses a mathematical algorithm to predict price direction based on Euclidean geometry. Feature Vectors: It takes 4 real-time data points (MA spread, Price vs. VWAP, HMA slope, and Relative Volume) and normalizes them into a 4-dimensional spatial grid. Historical Scanning: The script looks back in time (e.g., 2,000 bars) and calculates the exact geometric distance between the current market conditions and historical market conditions. Voting System: It isolates the k closest historical matches (e.g., the 8 most similar moments in the past). It then looks at what price actually did next in those historical moments (went up or went down). Those neighbors "vote" on the current probability, generating a Bull/Bear Confidence Percentage. 3. Signal Filtering & State Tracking (Anti-Flicker) The script includes strict logic to prevent chart clutter and false signals: Convergence: A signal will only fire if the AI probability is above your defined threshold (e.g., 70%), the ADX shows a strong trend, and price is structurally on the correct side of the VWAP. State Tracker: A built-in memory state (currentTradeState) forces strict alternation. Once an "AI BUY" fires, the system locks into a Long state. It will ignore any duplicate bullish spikes and will only fire again when an "AI SELL" conditions are met. 4. Dashboards & UI Core Dashboard: A bottom-center panel that gives a rapid visual summary of all traditional metrics (Price, VWAP, MA, HMA, ST, ADX, Volume). ML Ensemble Panel: A top-right heads-up display showing the AI's exact live confidence percentages, its grading scale (A+, A, B, C), and the current active forecast. Day Trading Extras: Automatically plots Previous Day High/Low/Close, daily Pivot points, Support/Resistance levels, and the critical First 15-Minute High/Low breakout zones.
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Harry_Bhullar의
1
DIP TOP OSCILATOR Divergence## English **Stable Cycle Core Chop Filter & Divergence** A clean, lower-panel cycle oscillator built around a normalized momentum of EMA, smoothed by a short signal line. The goal is to read the market's rhythm without the noise of standard oscillators. **How it works** - **Cycle line (black):** EMA momentum normalized by ATR — adapts to volatility automatically, so readings stay comparable across timeframes and instruments. - **Signal line (orange):** Smoothed cycle. Crossovers print **green dots (buy)** and **red dots (sell)** directly on the oscillator — WaveTrend-style, but cleaner. - **Zero line:** Bias reference. Above zero = bullish momentum, below zero = bearish. **Chop / Fake-Signal Filter (on the price chart)** Choppy markets often produce buy → sell → buy in just a few bars. To avoid acting on those fakes, the script counts signals over a short window. If too many fire too quickly: - The current bar is locked as a range, with a **green ATR line above** and a **red ATR line below** the price. - The background turns light yellow to mark the chop zone. - The first **break of either band is treated as the real direction**, marked by a green/red triangle. - Outside chop conditions, no bands are drawn — the chart stays clean. **Divergence (lower panel)** Pivot-based divergence detection between price and the cycle oscillator: - **Bullish:** price prints a lower low while the oscillator prints a higher low → green line + label. - **Bearish:** price prints a higher high while the oscillator prints a lower high → red line + label. **Alerts available** Buy / Sell / Chop Break Up / Chop Break Down / Bullish Divergence / Bearish Divergence. **Recommended use** - Trade with the dots only when the market is trending (bands are not drawn). - In sideways action, ignore the dots and **wait for an ATR band break** for direction. - Use divergences as confirmation, not as standalone entries. - Works on any market and any timeframe; ATR normalization handles the rest. Not financial advice. Always combine with your own risk management. --- ## Türkçe **Stable Cycle Core — WaveStyle Clean + Chop Filtresi & Uyumsuzluk** Sade bir alt panel döngü osilatörüdür. Çekirdeğinde EMA momentumunun ATR ile normalize edilmiş hâli vardır; üstüne kısa bir sinyal hattı eklenmiştir. Amaç, klasik osilatörlerin gürültüsü olmadan piyasanın ritmini okumaktır. **Nasıl çalışır?** - **Cycle (siyah çizgi):** ATR ile normalize edilmiş EMA momentumu. Volatiliteye otomatik uyum sağladığı için farklı zaman dilimi ve enstrümanlarda değerler karşılaştırılabilir kalır. - **Signal (turuncu çizgi):** Cycle'ın yumuşatılmış hâli. Kesişimler doğrudan osilatör üzerinde **yeşil nokta (al)** ve **kırmızı nokta (sat)** olarak işlenir — WaveTrend mantığında ama daha temiz. - **Sıfır çizgisi:** Yön referansı. Üstü pozitif momentum, altı negatif momentum. **Chop / Sahte Sinyal Filtresi (ana grafik üzerinde)** Sıkışık (testere) piyasalarda al-sat-al şeklinde art arda sinyaller gelir. Bu fakelere kapılmamak için script, kısa bir pencerede sinyal sayısını izler. Sinyaller çok sık gelirse: - O ANDA fiyatın üstüne **yeşil ATR çizgisi**, altına **kırmızı ATR çizgisi** kilitlenir. - Arka plan hafif sarıya döner — "burası karışık bölge" demektir. - **Hangi bant önce kırılırsa gerçek yön orasıdır** ve yeşil/kırmızı üçgenle işaretlenir. - Karışıklık yoksa hiçbir bant çizilmez, grafik temiz kalır. **Divergence (alt panelde)** Pivot bazlı uyumsuzluk tespiti, fiyat ile osilatör arasında: - **Boğa uyumsuzluğu:** fiyat daha düşük dip yaparken osilatör daha yüksek dip yapar → yeşil çizgi + etiket. - **Ayı uyumsuzluğu:** fiyat daha yüksek tepe yaparken osilatör daha düşük tepe yapar → kırmızı çizgi + etiket. **Alarmlar** Buy / Sell / Chop Break Up / Chop Break Down / Boğa Uyumsuzluğu / Ayı Uyumsuzluğu. **Önerilen kullanım** - Trend piyasada (bant çizilmediğinde) noktaları takip et. - Yatay/sıkışık piyasada noktaları yoksay, **ATR bantlarından birinin kırılmasını bekle**, yön orasıdır. - Uyumsuzlukları tek başına giriş değil, **teyit aracı** olarak kullan. - Her enstrüman ve her zaman diliminde çalışır; ATR normalizasyonu adaptasyonu otomatik sağlar. Bu paylaşım yatırım tavsiyesi değildir. Her zaman kendi risk yönetiminle birleştir.
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onderarslantas107의
SwiftLevelsSwiftLevels is a clean, all-in-one overlay indicator that keeps the most important price reference levels and daily moving averages visible at a glance — without cluttering your chart. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PRIOR DAY & PRIOR WEEK LEVELS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ On intraday charts, SwiftLevels draws horizontal lines for the prior day high/low and prior week high/low. Lines are anchored to the prior session's open so they don't clutter the left side of the chart. Labels float at the right edge of the current session and update each bar close to show the live percentage distance from price — positive when price is above, negative when below. Example: PRIOR DAY (+1.24%) PRIOR WEEK (-0.87%) Colors and label visibility are fully configurable per level group. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ DAILY MOVING AVERAGES (5 fully configurable) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Five independent moving averages, each calculated from daily chart data regardless of your current timeframe. On intraday charts: • Each MA is drawn as a clean horizontal line starting at today's session open and extending right — no stair-stepping history, no noise from previous sessions. • Labels appear just before the line starts, showing the MA name and live % distance from price, updated each bar close. • Example: 20d SMA (+2.11%) 50d SMA (-0.44%) On the daily chart: • MAs are displayed as traditional full-history plots so you can see the curve over time. • Can be toggled on/off with the "Display on Daily" checkbox. On weekly/monthly charts: • MAs are hidden to keep those timeframes uncluttered. Each moving average is independently configurable: • Enable / disable • Length (default: 5, 10, 20, 50, 200) • SMA or EMA toggle • Custom color • Line width
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OfficialTraderSwift의
4 MA + MA5(20%Divergence)指標名稱： 4 MA 趨勢軌道與 20% 偏離通道 (4 MA Lines & 20% Deviation Channel)指標概述：本指標是一款專為技術分析設計的複合型均線工具，整合了四條自定義長度的簡單移動平均線（MA），以及一條基於短期均線計算的 20% 固定乖離線（MA 5）。 Indicator Name: 4 MA Lines & 20% Deviation ChannelOverview:This is a comprehensive Moving Average toolkit designed for multi-timeframe trend analysis. It combines four fully customizable Simple Moving Averages (MAs) with a 20% fixed deviation line (MA 5) calculated from the short-term MA.
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lamlongwang1111999의
Simple 1H Buy/Sell System - EMA + Supertrend + RSI By Gerard DakThe simple 1H buy/sell indicator is a trend-following system designed to remove noise and only trigger trades when momentum, trend direction, and market structure align together. Core logic: Uses a fast EMA and slow EMA to identify the main trend Uses RSI as a momentum filter to avoid weak setups Uses ATR filtering to avoid low-volatility chop Generates BUY signals only when: Fast EMA crosses above slow EMA RSI confirms bullish momentum Price is above trend structure Generates SELL signals only when: Fast EMA crosses below slow EMA RSI confirms bearish momentum Price is below trend structure The goal is: Fewer fake signals Cleaner entries Better trend continuation trades Easier visual interpretation on the 1-hour timeframe Best market conditions: Trending markets NAS100, QQQ, SPY, BTC, major forex pairs High-volume sessions (London/New York) Avoid using it: During sideways consolidation Right before major news events In extremely low volatility Recommended 1H settings: Fast EMA: 21 Slow EMA: 50 RSI Length: 14 RSI Buy Threshold: Above 55 RSI Sell Threshold: Below 45 ATR Filter: Enabled Signal philosophy: The indicator intentionally sacrifices early entries in exchange for higher-quality confirmation. It will not catch exact tops or bottoms. Instead, it tries to catch the “meat” of the move with fewer bad trades. What makes it effective: Multi-confirmation filtering Trend + momentum alignment Noise reduction Prevents overtrading Expected behavior: Strong trends → excellent signals Choppy markets → fewer signals (by design) Win rate can be high if combined with: Higher timeframe trend confirmation Support/resistance Volume analysis Avoiding news spikes A typical BUY setup on 1H: Price consolidates 21 EMA crosses above 50 EMA RSI moves above 55 Candle closes bullish above both EMAs BUY signal appears A typical SELL setup is the exact opposite. The biggest mistake traders make with these systems is taking every signal blindly. The highest probability trades happen when: 4H trend agrees with 1H Market is not overextended
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gdakouo의
KNN Machine Learning Mean Reversion Probability [Dots3Red]█ OVERVIEW This script applies a K-Nearest Neighbors (KNN) machine learning algorithm to estimate the probability that price will revert to its moving average within a defined number of bars. Rather than predicting momentum direction, it asks a more specific question: how likely is it that this extension snaps back? The model searches historical bars for situations that looked like the current one — same degree of stretch, same RSI exhaustion profile, same volume behavior — and measures how often those situations ended in a reversion to the basis MA. That proportion becomes the live probability shown on your chart. █ METHODOLOGY The indicator follows a supervised machine-learning pipeline with five distinct stages. 1 — Labeling (what we are predicting) Each historical bar receives a label based on what actually happened next. If price was extended above the basis MA and touched it within the Reversion Window — that bar is labeled a successful reversion. If it did not touch — labeled as no reversion. The same logic applies from below. This is the core distinction from momentum KNN indicators: the target is reversion to fair value , not directional price movement. 2 — Feature engineering (what we measure) Five features capture how stretched current price conditions are, each Z-score normalized to remove scale bias: • MA Distance — signed % distance of close from the basis MA. The primary extension signal. • Bollinger Band position — where price sits within the bands, normalizing extension relative to current volatility. • RSI deviation — how far RSI has moved from neutral (50). Captures momentum exhaustion. • Body compression — ratio of candle body to total range. Small bodies near extremes signal hesitation and loss of directional conviction. • Volume fade — declining volume during an extension is a classic exhaustion signature. 3 — Z-score normalization All five features are standardized using a rolling mean and standard deviation computed on prior bars only (look-ahead free). This ensures the KNN distance calculation is not biased by features of different scales. 4 — KNN engine The algorithm scans the historical lookback window for the K most similar past bars, measured by Minkowski Distance across all five features simultaneously. Closer neighbors receive exponentially higher voting weight via a Gaussian Kernel , so the prediction is driven by the most relevant historical analogs — not a simple majority vote. 5 — Dual probability output Two independent probabilities are maintained and tracked separately: • P(reversion from above) — for overbought / extended-high setups. • P(reversion from below) — for oversold / extended-low setups. They are kept separate because bear-side extensions and bull-side extensions have statistically different behavior — bear moves are typically faster and sharper. A signal fires when the relevant probability crosses the user-defined threshold, and only when price is actually extended (see Extension Gate below). █ WHAT MAKES THIS DIFFERENT Most published KNN indicators predict momentum direction — will price go up or down next bar? This indicator predicts something more specific: will price return to its average? The distinction matters for several reasons: 1 — A high momentum reading can persist for many bars. A stretched reading has a natural gravity pulling it back, and measuring the historical probability of that snap is a more tractable problem than direction forecasting. 2 — The two probability channels are trained on separate populations, accounting for the asymmetry between bull and bear extensions. 3 — The Extension Gate ensures signals only appear when there is actually something to revert from — no signals in flat, choppy, low-volatility conditions. █ EXTENSION GATE Even if the KNN model outputs a high reversion probability, no signal appears unless price is beyond Gate Multiplier × ATR from the basis MA. This prevents false signals in low-volatility or ranging conditions where mean reversion setups carry no statistical edge. █ HOW TO USE Signal shapes (▲ Rev / ▼ Rev) Fire when P(reversion) crosses the threshold AND price passes the extension gate. The label at the signal bar shows the exact probability at the moment of firing. Snap zone fill When a signal is active, the region between current price and the basis MA is shaded. This is the reversion target zone — where price is statistically expected to return. The fill deactivates automatically once price reverts back through the basis. Bar colors • Bright green/red — active probability above the threshold on the current price side. • Dimmed green/red — probability elevated but below threshold, approaching signal territory. • No color — neutral or low reversion probability. Background flash A faint background confirms the exact bar on which a signal fired. Recommended workflow 1 — Set the Basis MA to your preferred mean reversion average. EMA 20 is a common starting point for intraday and swing setups. 2 — Tune the Reversion Window to match your typical trade hold time in bars. 3 — Adjust the Extension Gate multiplier to the asset's volatility profile. Crypto typically requires higher values than forex or equities. 4 — Use the Probability Threshold to control signal frequency. 0.65 gives moderate frequency; 0.75 and above is more selective. 5 — Combine with volume analysis or candlestick confirmation at signal bars for additional confluence before entering a position. █ SETTINGS REFERENCE KNN Engine • K Neighbors — how many historical analogs vote. Higher = smoother, slower to react. • Lookback Window — size of the historical search space in bars. • Reversion Window — bars within which price must touch the MA to count as a reversion. • Minkowski p — distance metric exponent. 1 = Manhattan, 2 = Euclidean. • Gaussian Bandwidth — controls how steeply neighbor weight falls with distance. • Probability Threshold — minimum confidence required to show a signal. Feature Settings • Basis MA type / length — the fair value line all features are measured against. • Bollinger Band mult — standard deviation multiplier for the BB position feature. • RSI length — period for the RSI exhaustion feature. • Volume MA length — baseline for the volume fade feature. Extension Gate • Require extension gate — toggle the ATR-based signal filter on/off. • Gate band multiplier — how many ATRs from basis price must be before signaling. • Gate ATR length — period for the ATR used in the gate calculation. █ LIMITATIONS • KNN is a lazy learner — it does not generalize beyond historical patterns in the lookback window. Strong trending regimes or structural breaks can produce elevated false signals. • The reversion probability reflects historical frequency, not a guarantee of future behavior. • On low-bar-count charts (e.g. weekly on newer assets), the lookback window may not contain enough samples to produce stable probability estimates. • Computation scales with lookback window size. Very large windows may slow chart rendering. █ DISCLAIMER This indicator is a decision-support tool, not a trading system. It does not constitute financial advice. Always apply proper risk management and combine with your own analysis. Algorithm: K-Nearest Neighbors (KNN) Distance metric: Minkowski Distance Preprocessing: Z-Score Normalization Target: Probabilistic Mean Reversion
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Dots3Red의
5