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ADX Volatility Waves [BOSWaves]ADX Volatility Waves - Trend-Weighted Volatility Mapping with State-Based Wave Transitions Overview ADX Volatility Waves is a regime-aware volatility framework designed to map statistically significant price extremes through adaptive wave structures driven by trend strength. Rather than treating volatility as a static dispersion metric, this indicator conditions all volatility expansion, contraction, and zone placement on ADX-derived trend intensity. Price behavior is interpreted through wave-like transitions between balance, expansion, and exhaustion states rather than isolated band interactions. The result is a dynamic, gradient-based wave system that visually encodes volatility cycles and regime shifts in real time, allowing traders to contextualize price movement within trend-weighted volatility waves. Price is evaluated not by static thresholds, but by its position and progression within adaptive volatility waves shaped by directional strength. Conceptual Framework ADX Volatility Waves is built on the premise that volatility unfolds in waves, not straight lines. Traditional volatility tools identify dispersion but fail to account for how volatility behaves differently across trend regimes. By embedding ADX directly into volatility construction, this indicator ensures that volatility waves expand during strong directional phases and compress during weak or transitioning regimes. Three guiding principles define the framework: Volatility must be conditioned on trend strength Extremes occur within zones, not at lines Signals should emerge from completed wave transitions, not instantaneous touches This reframes analysis from reactive mean-reversion toward regime-aware wave interpretation. Theoretical Foundation The indicator fuses directional movement theory with statistical volatility modeling. Bollinger-derived dispersion provides the structural base, while ADX normalization controls the amplitude of volatility waves. As ADX increases, volatility waves widen and deepen; as ADX weakens, waves compress and tighten around equilibrium. From this foundation, extended upper and lower wave zones are constructed and smoothed to represent statistically significant expansion and contraction phases. At its core are three interacting systems: ADX-Controlled Volatility Engine : Standard deviation is dynamically scaled using normalized ADX values, producing trend-weighted volatility waves. Wave Zone Construction : Smoothed volatility boundaries are offset and expanded to form upper and lower wave zones, defining overextension and compression regions. State-Based Wave Transition Logic : Signals occur only after price completes a full wave cycle: expansion into an extreme wave zone followed by a confirmed return to equilibrium. This structure ensures that signals reflect completed volatility waves, not transient noise. How It Works ADX Volatility Waves processes price action through layered wave mechanics: Trend-Weighted Volatility Calculation : Volatility boundaries are dynamically adjusted using ADX influence, allowing wave amplitude to scale with trend strength. Structural Smoothing : Volatility boundaries are smoothed to stabilize wave geometry and reduce short-term distortions. Wave Offset & Expansion : Upper and lower wave zones are positioned beyond equilibrium and expanded proportionally to volatility range, forming clearly defined expansion waves. Gradient Wave Depth Mapping : Each wave zone is subdivided into multiple gradient layers, visually encoding increasing extremity as price moves deeper into a wave. Wave State Tracking & Cooldown Control : The system tracks prior wave occupancy, enforces neutral stabilization periods, and applies cooldowns to prevent overlapping wave signals. Compression Detection : Volatility width monitoring identifies compression phases, highlighting conditions where new volatility waves are likely to form. Together, these processes create a continuous, adaptive wave map of volatility behavior. Interpretation ADX Volatility Waves reframes market reading around volatility cycles: Upper Volatility Waves (Red Gradient) : Represent upside expansion phases. Deeper wave penetration indicates increased overextension relative to trend-adjusted volatility. Lower Volatility Waves (Green Gradient) : Represent downside expansion phases. Sustained presence signals pressure, while exits toward balance suggest wave completion. Equilibrium Zone : The neutral region between volatility waves. Confirmed re-entry into this zone marks the completion of a wave cycle and forms the basis for BUY and SELL signals. Regime Context via ADX : Strong ADX regimes widen waves, reducing premature reversal signals. Weak ADX regimes compress waves, increasing sensitivity to reversion. Wave progression and completion matter more than single-bar interactions. Signal Logic & Visual Cues ADX Volatility Waves produces single-entry BUY and SELL labels as its visual cues, plotted only when price first enters a volatility wave zone after the defined cooldown period. Buy Signal (Bottom Zone Entry) : A BUY label appears when price enters the lower volatility wave (oversold zone). This highlights potential expansion into undervalued extremes, providing visual context for trend assessment rather than a guaranteed execution trigger. Sell Signal (Top Zone Entry) : A SELL label appears when price enters the upper volatility wave (overbought zone). This marks potential overextension into upper volatility extremes, serving as a contextual indicator of trend stress. All labels respect cooldown tracking to prevent clustering. Alerts are tied directly to these zone-entry signals, and a separate alert monitors volatility squeezes for awareness of compression periods. Strategy Integration ADX Volatility Waves integrates cleanly into volatility-aware trading frameworks: Wave Context Mapping : Use wave depth to assess expansion and exhaustion risk rather than forcing immediate entries. Transition-Based Execution : Prioritize BUY and SELL signals formed after confirmed wave completion. Trend-Regime Filtering : In strong ADX regimes, treat waves as continuation pressure. In weak regimes, favor completed wave reversions. Volatility Cycle Awareness : Monitor compression phases to anticipate the emergence of new volatility waves. Multi-Timeframe Alignment : Apply higher-timeframe ADX regimes to contextualize lower-timeframe wave behavior. Technical Implementation Details Core Engine : ADX-normalized volatility expansion Wave System : Smoothed, offset, expanded volatility waves Visualization : Multi-layer gradient wave zones Signal Logic : State-based wave transitions with cooldown enforcement Alerts : Wave entry, wave completion, volatility compression Performance Profile : Lightweight, real-time optimized overlay Optimal Application Parameters Timeframe Guidance: 1 - 5 min : Short-term volatility waves and intraday transitions 15 - 60 min : Structured intraday wave cycles 4H - Daily : Macro volatility regimes and expansion phases Suggested Baseline Configuration: BB Length : 20 BB StdDev : 1.5 ADX Length : 14 ADX Influence : 0.8 Wave Offset : 1.0 Wave Width : 1.0 Neutral Confirmation : 5 bars These suggested parameters should be used as a baseline; their effectiveness depends on the asset volatility, liquidity, and preferred entry frequency, so fine-tuning is expected for optimal performance. Performance Characteristics High Effectiveness: Markets exhibiting rhythmic volatility expansion and contraction Assets with responsive ADX regime behavior Reduced Effectiveness: Erratic, news-driven price action Illiquid markets with distorted volatility metrics Integration Guidelines Confluence : Combine with BOSWaves structure or trend tools Discipline : Respect wave completion and cooldown logic Risk Framing : Interpret wave depth probabilistically, not predictively Regime Awareness : Always contextualize waves within ADX strength Disclaimer ADX Volatility Waves is a professional-grade volatility and regime-mapping tool. It does not predict price and does not guarantee profitability. Performance depends on market conditions, parameter calibration, and disciplined execution. BOSWaves recommends using this indicator as part of a comprehensive analytical framework incorporating trend, volatility, and structural context.
Pine Script® 인디케이터
BOSWaves의
10
Scalping Signals with MTF Fibo BandsThis indicator is a scalping / intraday signal system built on Multi-Timeframe (MTF) Fibonacci Bands, combined with an RSI midline filter and an optional direction-lock mechanism to reduce consecutive losing entries. 🔹 What does this indicator do? It plots two independent Fibonacci Band sets (A & B), each calculated from a higher timeframe SMA + ATR. Entry zones are defined between Band 2 and Band 3, representing statistically extreme price areas. You can choose to generate signals from: Band A only Band B only BOTH (A + B confirmation) 📈 Entry Logic LONG Price closes inside the Lower Zone (between Fib2 Lower & Fib3 Lower) RSI is above the midline (default 50) SHORT Price closes inside the Upper Zone (between Fib2 Upper & Fib3 Upper) RSI is below the midline (default 50) 🟧 Direction Lock System If enabled, the indicator locks the trade direction when a position hits Stop Loss before reaching TP1. This prevents repeated entries in the same direction during unfavorable conditions. 🔓 Unlock Logic The lock can be removed when: RSI crosses back over the midline (RSI > 50 for LONG, RSI < 50 for SHORT) AND price closes again inside the valid Band 2–3 zone With the optional setting enabled, a new entry can occur on the same candle 🛑 Stop Loss Logic (Important) This indicator uses price-action-based stop logic, not fixed pip stops. 1️⃣ Before TP1 LONG: Two consecutive candle closes below Fib3 Lower SHORT: Two consecutive candle closes above Fib3 Upper ⚠️ Because SL depends on candle closes, you must monitor lower timeframes (1m or below) to react quickly and avoid delayed exits. 2️⃣ After TP1 (Break-Even Protection) Once TP1 is touched: SL automatically shifts to Break-Even (entry price) Any return to entry will close the position ⚠️ Usage Warning This indicator is NOT designed for sharp, explosive, or news-driven moves Avoid using it during: High-impact news Extremely fast impulsive candles Sudden volatility spikes Best performance is achieved in structured price action environments, not chaotic market conditions.
Pine Script® 인디케이터
RCOTradingHelpline의
Volume MAs Oscillator | Lyro RS// This Pine Script® code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org // © LyroRS //@version=6 indicator("Volume MAs Oscillator | Lyro RS") import LyroRS/LMAs/1 as DynamicMAs //───────────────────────────────────────────────────────────────────────────────────────────────────────────── //─██████─────────████████──████████─████████████████───██████████████───────████████████████───██████████████─ //─██░░██─────────██░░░░██──██░░░░██─██░░░░░░░░░░░░██───██░░░░░░░░░░██───────██░░░░░░░░░░░░██───██░░░░░░░░░░██─ //─██░░██─────────████░░██──██░░████─██░░████████░░██───██░░██████░░██───────██░░████████░░██───██░░██████████─ //─██░░██───────────██░░░░██░░░░██───██░░██────██░░██───██░░██──██░░██───────██░░██────██░░██───██░░██───────── //─██░░██───────────████░░░░░░████───██░░████████░░██───██░░██──██░░██───────██░░████████░░██───██░░██████████─ //─██░░██─────────────████░░████─────██░░░░░░░░░░░░██───██░░██──██░░██───────██░░░░░░░░░░░░██───██░░░░░░░░░░██─ //─██░░██───────────────██░░██───────██░░██████░░████───██░░██──██░░██───────██░░██████░░████───██████████░░██─ //─██░░██───────────────██░░██───────██░░██──██░░██─────██░░██──██░░██───────██░░██──██░░██─────────────██░░██─ //─██░░██████████───────██░░██───────██░░██──██░░██████─██░░██████░░██───────██░░██──██░░██████─██████████░░██─ //─██░░░░░░░░░░██───────██░░██───────██░░██──██░░░░░░██─██░░░░░░░░░░██───────██░░██──██░░░░░░██─██░░░░░░░░░░██─ //─██████████████───────██████───────██████──██████████─██████████████───────██████──██████████─██████████████─ //───────────────────────────────────────────────────────────────────────────────────────────────────────────── // LyroRS v1.0 // Groups ma_g = "𝗠𝗢𝗩𝗜𝗡𝗚 𝗔𝗩𝗘𝗥𝗔𝗚𝗘" bands_g = "𝗕𝗔𝗡𝗗" display_g = '𝗗𝗜𝗦𝗣𝗟𝗔𝗬' // Inputs // -- Moving Average source = input.source(close, "Source", group= ma_g, tooltip= "Select where the data originates (open, high, low, close, etc..).") ma_type = input.string("EMA", "Select Moving Average", options= , group=ma_g, tooltip="Choose a moving average type to apply to the price multiplied by volume. VWMA already incorporates volume directly.") ma_length = input.int(30, "Moving Average Length", group= ma_g, tooltip= "Defines the length or period of the selected moving average.") // -- Bands band_length = input.int(27, "Band Length", group=bands_g, tooltip="Number of bars used to calculate standard deviation.") band_smoothing = input.float(0.8, "Band Smoothing", group=bands_g, minval=0, tooltip="Smooths the band edges to reduce noise.") pbm = input.float(1.8, "Positive Band Multiplier", group=bands_g, minval=0, tooltip="Multiplier for the upper band distance.") nbm = input.float(-0.85, "Negative Band Multiplier", group=bands_g, maxval=0, tooltip="Multiplier for the lower band distance.") // Color Inputs signal_type = input.string("Trend", "Select Signal Type", options= , group=display_g, tooltip="Select which way to use the indicator.") ColMode = input.string("Mystic", "Custom Color Palette", inline="drop", options= , display=display.none, group= display_g, tooltip="Select a predefined color scheme for the indicator display. (Major Themes color mode automatically switches colors based on the major asset you picked for valuation analysis.)") cpyn = input.bool (true, "Use Custom Palette", group= display_g, display=display.none, tooltip="Enables custom color selection for signals.") cp_UpC = input.color (#00ff00, "Custom Up", inline = "Custom Palette", group= display_g, display=display.none, tooltip="") cp_DnC = input.color (#ff0000, "Custom Down", inline = "Custom Palette", group= display_g, display=display.none, tooltip="User specifed bullish and bearish colors.") d_obos_sigs = input.bool (true, "Display Oversold/Overbought Signs", group= display_g, display=display.none, tooltip="Enables triangle signs to be displayed.") d_signs = input.bool (true, "Display Signs", group= display_g, display=display.none, tooltip="Enables signs for Trend mode.") d_bgcol = input.bool (true, "Display Background Color", group= display_g, display=display.none, tooltip="Enables background color for Reversion & Valuation mode.") // Colors color UpC = na color DnC = na // -- Predefined Colors switch ColMode "Classic" => UpC := #00E676 DnC := #880E4F "Mystic" => UpC := #30FDCF DnC := #E117B7 "Accented" => UpC := #9618F7 DnC := #FF0078 "Royal" => UpC := #FFC107 DnC := #673AB7 // -- Custom Colors if cpyn UpC := cp_UpC DnC := cp_DnC // Coloring Function for Valuation coloring(src) => color.from_gradient(src, ta.lowest(src, band_length), ta.highest(src, band_length), UpC, DnC) // Moving Average Switch float ma = na switch ma_type "SMA" => ma := DynamicMAs.SMA(source * volume, ma_length) / DynamicMAs.SMA(volume, ma_length) "EMA" => ma := DynamicMAs.EMA(source * volume, ma_length) / DynamicMAs.EMA(volume, ma_length) "WMA" => ma := DynamicMAs.WMA(source * volume, ma_length) / DynamicMAs.WMA(volume, ma_length) "VWMA" => ma := DynamicMAs.VWMA(source, volume, ma_length) // Already Volume Based MA "DEMA" => ma := DynamicMAs.DEMA(source * volume, ma_length) / DynamicMAs.DEMA(volume, ma_length) "TEMA" => ma := DynamicMAs.TEMA(source * volume, ma_length) / DynamicMAs.TEMA(volume, ma_length) "RMA" => ma := DynamicMAs.RMA(source * volume, ma_length) / DynamicMAs.RMA(volume, ma_length) "HMA" => ma := DynamicMAs.HMA(source * volume, ma_length) / DynamicMAs.HMA(volume, ma_length) "LSMA" => ma := DynamicMAs.LSMA(source * volume, ma_length, 0) / DynamicMAs.LSMA(volume, ma_length, 0) "SMMA" => ma := DynamicMAs.SMMA(source * volume, ma_length) / DynamicMAs.SMMA(volume, ma_length) "ALMA" => ma := DynamicMAs.ALMA(source * volume, ma_length, 0, 20) / DynamicMAs.ALMA(volume, ma_length, 0, 20) "ZLSMA" => ma := DynamicMAs.ZLSMA(source * volume, ma_length) / DynamicMAs.ZLSMA(volume, ma_length) "FRAMA" => ma := DynamicMAs.FRAMA(source * volume, ma_length) / DynamicMAs.FRAMA(volume, ma_length) "KAMA" => ma := DynamicMAs.KAMA(source * volume, ma_length) / DynamicMAs.KAMA(volume, ma_length) "JMA" => ma := DynamicMAs.JMA(source * volume, ma_length, 0) / DynamicMAs.JMA(volume, ma_length, 0) "T3" => ma := DynamicMAs.T3(source * volume, ma_length, 0.5) / DynamicMAs.T3(volume, ma_length, 0.5) price_diff = ((source - ma) / ma) * 100 // Percentage Difference between Source and the Moving Average of the source // Calculations for the Bands std = ta.stdev(price_diff, band_length) upperBandRaw = std * pbm lowerBandRaw = std * nbm var float upperBand = na var float lowerBand = na // Smooth upperBand := upperBandRaw * band_smoothing + nz(upperBand ) * (1 - band_smoothing) lowerBand := lowerBandRaw * band_smoothing + nz(lowerBand ) * (1 - band_smoothing) // Plot Color var color pc = na var color uB_color = na var color lB_color = na var int signal = 0 if signal_type == "Trend" uB_color := UpC lB_color := DnC if price_diff > upperBand pc := UpC signal := 1 if price_diff < lowerBand pc := DnC signal := -1 if signal_type == "Reversion" uB_color := DnC lB_color := UpC if price_diff > upperBand pc := DnC signal := -1 else if price_diff < lowerBand pc := UpC signal := 1 else pc := color.gray signal := 0 if signal_type == "Valuation" uB_color := UpC lB_color := DnC pc := coloring(price_diff) // Plot plot(price_diff, color= pc, linewidth = 2, title= "Volume MAs Oscillator") plot(upperBand, color= color.new(uB_color, 50), title= "Upper Band") plot(lowerBand, color= color.new(lB_color, 50), title= "Lower Band") plot(0, color= color.new(pc, 60), linewidth = 2, display= display.pane, title= "Mid Line") plot(0, color= color.new(pc, 75), linewidth = 5, display= display.pane, title= "Mid Line Glow 1") plot(0, color= color.new(pc, 85), linewidth = 10, display= display.pane, title= "Mid Line Glow 2") plotchar(upperBand + 0.5, char='▼', color= ta.crossunder(price_diff, upperBand) ? DnC : na, location=location.absolute, title= "Overbought Signal", display= d_obos_sigs ? display.pane : display.none, size= size.tiny) plotchar(lowerBand - 0.5, char='▲', color= ta.crossover(price_diff, lowerBand) ? UpC : na, location=location.absolute, title= "Oversold Signal", display= d_obos_sigs ? display.pane : display.none, size= size.tiny) reversion_enable = signal_type == "Reversion" valuation_enable = signal_type == "Valuation" bgcolor(d_bgcol and ((valuation_enable and price_diff > upperBand) or (reversion_enable and ta.crossunder(price_diff, upperBand))) ? color.new(DnC, 85) : na, title= "BG Color OB") bgcolor(d_bgcol and ((valuation_enable and price_diff > upperBand) or (reversion_enable and ta.crossunder(price_diff, upperBand))) ? color.new(DnC, 85) : na, title= "BG Color OB Overlay", force_overlay = true) bgcolor(d_bgcol and ((valuation_enable and price_diff < lowerBand) or (reversion_enable and ta.crossover(price_diff, lowerBand))) ? color.new(UpC, 85) : na, title= "BG Color OS") bgcolor(d_bgcol and ((valuation_enable and price_diff < lowerBand) or (reversion_enable and ta.crossover(price_diff, lowerBand))) ? color.new(UpC, 85) : na, title= "BG Color OS Overlay", force_overlay = true) plotshape(ta.crossover(signal, 0), title="Buy Signal", location=location.belowbar, style=shape.labelup, text="𝓛𝓸𝓷𝓰", textcolor=#000000, size=size.small, color=UpC, force_overlay=true, display= signal_type == "Trend" and d_signs == true ? display.pane : display.none) plotshape(ta.crossunder(signal, 0), title="Sell Signal", location=location.abovebar, style=shape.labeldown, text="𝓢𝓱𝓸𝓻𝓽", textcolor=#000000, size=size.small, color=DnC, force_overlay=true, display= signal_type == "Trend" and d_signs == true ? display.pane : display.none) plotcandle(open, high, low, close, color= pc, wickcolor = pc, bordercolor = pc, force_overlay = true, display= display.pane, title= "Plot Candle") barcolor(pc, title= "Barcolor") // ========================================================================================== // === Dashboard with Telegram Link === var table myTable = table.new(position.top_center, 1, 1, border_width=1, frame_color=color.black, bgcolor=color.white) // Add Telegram Message to Dashboard table.cell(myTable, 0, 0, "Join Telegram @mrexpert_ai", bgcolor=color.blue, text_color=color.white, text_size=size.normal)
Pine Script® 인디케이터
almokalja10의
FX Session High/Low Bands - Last 5 EST Days FX Session High/Low Bands - Last 5 Days Description: This indicator plots horizontal bands representing the high and low price levels from the major forex trading sessions over the last 5 days. It helps traders identify key support and resistance zones based on recent session activity. Features: Multiple Session Tracking: Displays high/low levels for major FX sessions: Asian Session (Tokyo) European Session (London) US Session (New York) 5-Day Lookback: Captures the highest high and lowest low from each session over the previous 5 trading days Visual Bands: Clear horizontal lines or filled zones showing session boundaries Dynamic Updates: Automatically recalculates as new session data becomes available How to Use: Support/Resistance: Previous session highs/lows often act as key price levels Breakout Trading: Watch for price breaking above/below session bands Range Trading: Trade within the bands during consolidation periods Session Overlap: Pay attention to multiple session bands converging Ideal For: Forex day traders Session-based trading strategies Support/resistance identification Multi-timeframe analysis
Pine Script® 인디케이터
drlicht1의
Probability-Based Adaptive Detection🙏🏻 PBAD (Probability-Based Adaptive Detection) : adaptive control tool for outliers || novelty detection, made for worst case data & processes, for the highest time complexity O(n^2) compared with the alternatives (would be explained in a sec). Thresholds are completely data driven and axiomatic, no need in provided hyperparameters, are not learned or optimized. The method accepts multiple weights, e.g. both temporal and volatility weights. Method briefly explained (I can go deeper if any1 asks explicitly): Performs weighted KDE on initial input data, finds KDE global maximum (mode), creates new “residuals” dataset by centering initial data around this value; Performs weighted KDE on residuals, uses sigmoid based probability mass targets with increasing probability coverage to construct a set of non-disjoint High Density Intervals (also called HDR, HPD in Bayesian terms); Uses these intervals to calculate analogs of centralized & standardized moments; Uses these ^^ moments to construct a set of control thresholds. The scheme used in PBAD is not only based on a central threshold, or on neighboring ones, it utilizes all previous thresholds, gaining more information. ... The most important part is to understand whether you really need PBAD. Because even tho it seems to be the best one given highest algocomplexity, irl it would work worse in cases when it’s not required by your data. Here’s the menu (aka taxonomy omg) of methods you can use that would let you make the right choice: Moment-Based Adaptive Detection (MBAD) : Norm: L2 Time complexity: original O(n), successfully reduced to O(1) in online version Use case: default, general purpose Based on: method of moments (powers of residuals from mean) Thresholds architecture: centralized Quantile-Based Adaptive Detection (QBAD): Norm: L1 Time complexity: O(nlogn) Use case: either bad data Or process instability Based on: quantile moments (dyadic percentiles of residuals from median) Thresholds architecture: chained/recursive/sequential Probability-Based Adaptive Detection (PBAD): Norm: L0 Time complexity: O(n^2) Use case: both bad data And process instability Based on: probability moments (target probability masses of residuals from KDE mode) Thresholds architecture: decentralized (for lack of a better name xd, the idea is that these thresholds gain information from the all other threshold and are Not exclusively based on the central or neighboring thresholds) ... Examples of true use cases: ^^ an appropriate financial instrument to use PBAD ^^ and another one ... Additional details about how to use it: Keep the student5 kernel, it’s the best you can do. I added others mostly for comparisons and if you want to use the tool Not for its primary purpose (on a fine data) “Calculate for N bars” and “Starting at bar N” options allow to reduce calculation period only on the N number of last bars or next bars from a chosen one. It's vital, because calculations here are heavy Keep plotting offset at 1 (allows to visually compare current bar with the previous threshold values). This is the way it should be done on price data. HLC3 is the optimal source input, unless you want to use your own better one point estimate of each datapoint (in the best case done by using PBAD itself on OHLC+ values). In essence it should be used just like MBAD or QBAD, fade/push extensions and limit, fade/push/skip deviations & basis, or other strategies of your. Again, the only reason for 3 methods to exist is to be chosen for according data characteristics. Btw: This is the initial version, I don’t consider it perfected tbh, even tho it works as expected, however this method is very situational anyways. In this script KDE function is modified to ensure the outcoming probabilities Do sum up to 1. I didn’t do this normalization in Weighted KDE Mode script , but there it’s not required since we just need a KDE global max. see ya ∞
Pine Script® 인디케이터
gorx1의
1
TTM Squeeze Candles (Custom Colors) with Dynamic Strength BarHere is my tribute, tip of the cap to one of the greatest traders of our generation John F. Carter It was my goal to try and simply visualize the squeeze with candle sticks, dynamic momentum, and signals all on one chart in one indicator. Please study and master the squeeze setup before trying to apply this indicator . You must have a deep understanding of how to trade the squeeze. Read "Mastering The Trade " watch JC's videos etc, and practice with a simulated or paper account before ever trying out new strategies with real money. Not financial advice, I am not a financial advisor! DYOR- with that said - I hope you like it :) TTM squeeze candles **custom TradingView Pine Script (v6)** indicator that visualizes the **TTM Squeeze** strategy — a popular volatility-based momentum system originally developed by John Carter of TradeTheMarkets (TTM). This version enhances the classic TTM Squeeze with **custom candle coloring**, **dynamic momentum strength**, **visual alerts**, and a **real-time strength meter**. --- ## OVERVIEW: What is the TTM Squeeze? The **TTM Squeeze** identifies periods when **volatility is contracting** (price is consolidating), followed by a **potential explosive breakout** when volatility expands. It combines: 1. **Bollinger Bands (BB)** – measure statistical volatility 2. **Keltner Channels (KC)** – measure average true range (ATR) volatility 3. **Momentum Oscillator** – determines direction and strength of potential breakout > **Squeeze ON** = BB inside KC → Low volatility (consolidation) > **Squeeze OFF** = BB outside KC → Volatility expanding (breakout possible) ## BEST USED ON - **Timeframes**: 15m, 1H, 4H, Daily - **Markets**: Stocks, Forex, Crypto, Futures - **Pairs well with**: Volume, VWAP, Support/Resistance --- ## SUMMARY > **This is a highly visual, trader-friendly squeeze candle indicator that: > - **Colors candles** based on squeeze state and momentum strength > - **Shows real-time momentum intensity** via histogram + strength bar > - **Alerts on squeeze start/release** > - **Normalizes momentum** for fair strength comparison > - **Provides clean, actionable signals** for breakout trading --- **Ideal for swing traders and day traders** looking to catch **high-momentum breakouts from low-volatility consolidations** with **clear entry signals and conviction levels**.
Pine Script® 인디케이터
Morpheus835의
SUPER SPX T.SHere is the professional English description for your indicator. You can use this if you want to save the script in your TradingView library or share it with others. ### **Indicator Name:** `SPX Pro: EMA Crossover with RSI Filter` ### **Description:** This indicator is specifically optimized for **SPX (S&P 500)** trading, particularly for options traders (CALL/PUT). It combines trend-following moving averages with a momentum filter to identify high-probability entry points. --- ### **Key Features:** * **Dual EMA Engine:** Uses a **9-period Exponential Moving Average (Fast)** and a **21-period Exponential Moving Average (Slow)**. These are the standard benchmarks for identifying short-term momentum on the SPX. * **RSI Momentum Filter:** Unlike standard crossover indicators, this script includes a built-in **Relative Strength Index (RSI)** filter. * **CALL signals** are only generated if the RSI is below 65 (preventing buying at the absolute peak). * **PUT signals** are only generated if the RSI is above 35 (preventing selling at the absolute bottom). * **Visual Signals:** * **Green Triangle + "CALL":** Triggered when the 9 EMA crosses above the 21 EMA while the RSI allows for more upside. * **Red Triangle + "PUT":** Triggered when the 9 EMA crosses below the 21 EMA while the RSI allows for more downside. * **Clean Interface:** Displays the EMAs clearly on the chart to help identify dynamic support and resistance levels. --- ### **How to Use:** 1. **Timeframe:** Recommended for **5-minute** and **15-minute** charts for day trading. 2. **Confirmation:** Look for the signal to appear after the candle closes to ensure the crossover is confirmed. 3. **Strategy:** This indicator works best when the SPX is trending. During a "sideways" or "choppy" market, the RSI filter will help eliminate many false signals that standard crossovers usually fail to catch. --- **Next Step:** Would you like me to add a **"Table"** on the corner of the screen that shows the current RSI value and the trend status (Bullish/Bearish) so you don't have to keep looking at the bottom of the chart?
Pine Script® 인디케이터
Tarekzoom의
5 EMA vs 50 EMA Crossover with PCO/NCO//@version=5 indicator("5 EMA vs 50 EMA Crossover with PCO/NCO", overlay=true) // EMA Calculations emaFast = ta.ema(close, 5) emaSlow = ta.ema(close, 50) // Crossover Conditions buySignal = ta.crossover(emaFast, emaSlow) sellSignal = ta.crossunder(emaFast, emaSlow) // Plot EMAs plot(emaFast, color=color.blue, title="5 EMA") plot(emaSlow, color=color.orange, title="50 EMA") // Plot Buy/Sell Signals plotshape(buySignal, title="Buy (PCO)", location=location.belowbar, color=color.green, style=shape.labelup, text="PCO") plotshape(sellSignal, title="Sell (NCO)", location=location.abovebar, color=color.red, style=shape.labeldown, text="NCO") // Optional Alerts alertcondition(buySignal, title="Buy Alert (PCO)", message="PCO: 5 EMA crossed above 50 EMA") alertcondition(sellSignal, title="Sell Alert (NCO)", message="NCO: 5 EMA crossed below 50 EMA")
Pine Script® 인디케이터
biranchi_barik07의
Selected Days Indicator V3-TrDoes the stock drop every Wednesday? Do March months always move similarly? Does the 1st week of the month behave differently? Do you ever say "it always makes this move in these months"? Don't you want to see more clearly whether it actually makes this move or not? Don't you want to see and test periodically repeating price patterns? Hisse her Çarşamba düşüyor mu? Mart ayları hep benzer mi hareket ediyor? Ayın 1. haftası farklı mı davranıyor? Bazen "bu aylarda hep bu hareketi yapıyor" dediğiniz oluyor mu? Gerçekten de bu hareketi yapıp yapmadığını daha net görmek istemez misiniz? Periyodik tekrarlayan fiyat kalıplarını görmek ve test etmek istemiyor musunuz? 1. Problem Some stocks or crypto assets exhibit systematic behaviors on certain days, weeks, or months. But it's hard to see - everything is mixed together on the chart. This indicator isolates the days/weeks/months you want and shows only them. Hides everything else. 2. How It Works Three-layer filter: Day (Monday, Tuesday...), Week (1st, 2nd, 3rd week of the month), Month (January, February...). Select what you want, let the rest disappear. Example: Show only Thursdays of March-June-September. Or compare every 1st week of the month. View as candlestick, line, or column chart. 3. What's It Good For? Test "end-of-month effect". Find "day-of-the-week anomaly". Analyze crypto volatility by days. See seasonality in commodities. Discover patterns specific to your own strategy. Past data doesn't guarantee the future but provides statistical advantage.
Pine Script® 인디케이터
ExperiMentalist의
EMA 8 / 20 / 200Created to easily use the 8/20/200 strategy. This indicator is designed to give a clear, multi-timeframe view of trend, momentum, and structure using three exponential moving averages. 1. Trend direction (EMA 200 – pink) The 200 EMA acts as the long-term trend filter. Price above the 200 EMA suggests a bullish market bias. Price below the 200 EMA suggests a bearish market bias. Many traders avoid taking trades against this higher-timeframe direction. 2. Momentum and trade bias (EMA 20 – blue) The 20 EMA reflects short-term momentum. When price respects the 20 EMA in an uptrend, pullbacks often provide continuation entries. In downtrends, the 20 EMA frequently acts as dynamic resistance. 3. Entry timing (EMA 8 – yellow) The 8 EMA is a fast reaction line used for precise timing. Crosses of the 8 EMA over the 20 EMA can signal momentum shifts. Strong trends often show price holding above (or below) the 8 EMA during impulse moves. 4. Confluence and trade filtering The indicator works best when the EMAs are aligned: Bullish alignment: EMA 8 > EMA 20 > EMA 200 Bearish alignment: EMA 8 < EMA 20 < EMA 200 Misaligned EMAs usually indicate consolidation or low-probability conditions. 5. Risk management context EMAs can act as dynamic support and resistance: Stops are often placed beyond the 20 EMA or 200 EMA depending on trade horizon. Loss of EMA structure is a warning sign that the trend may be weakening. In short, the indicator is a trend-first, momentum-second framework that helps you decide when to trade, in which direction, and when to stay out.
Pine Script® 인디케이터
Knotty0807의
premium//@version=5 indicator("Custom Binance Premium Index + Alerts", overlay=false) // === 1. 数据源（可修改） === // 永续合约价格（默认 BTCUSDT 永续） futures = request.security("BINANCE:BTCUSDT_PERP", timeframe.period, close) // 现货价格（默认 BTCUSDT 现货） spot = request.security("BINANCE:BTCUSDT", timeframe.period, close) // === 2. 计算自定义溢价指数 === premium = ((futures / spot) - 1) * 100 // === 3. 用户设定阈值（你给的值） === upper = 1.5 // 溢价 ≥ 1.5 触发告警 lower = -2.0 // 溢价 ≤ -2.0 触发告警 // === 4. 绘图 === plot(premium, title="Premium Index (%)", color=color.new(color.blue, 0)) hline(upper, "Upper Threshold (1.5%)", color=color.new(color.red, 0)) hline(lower, "Lower Threshold (-2.0%)", color=color.new(color.green, 0)) // === 5. 告警条件 === alertcondition(premium >= upper, title="溢价 ≥ 1.5%", message="Premium Index ≥ 1.5%（永续合约偏高，多头较强）" ) alertcondition(premium <= lower, title="溢价 ≤ -2.0%", message="Premium Index ≤ -2.0%（永续合约偏低，空头压力大）" ) // === 6. 信息显示 === label.new(bar_index, premium, "Premium: " + str.tostring(premium, "#.##") + "%", style=label.style_label_left, color=color.new(color.blue, 85))
Pine Script® 인디케이터
hh7h68y5jx의