Mulai

Bands

Prof-Eth Log Regression BandsProf-Eth Log Regression Bands 🇬🇧 English Description Prof-Eth Log Regression Bands is a long-term Ethereum (ETH) market structure indicator based on logarithmic regression analysis. This indicator models Ethereum’s historical price behavior using time-based logarithmic growth, helping users identify: Macro trend direction Relative overvaluation and undervaluation zones Long-term risk areas during market cycles The script combines two complementary approaches: Adjustable Logarithmic Regression Bands for trend and valuation analysis Fixed Upper Logarithmic Regression Band designed to highlight historical cycle-top risk zones Key Features Time-based logarithmic regression (not price-based) Dynamic main, upper, and lower regression bands Long-term cycle awareness and macro context Designed for Ethereum (ETH) market structure analysis How to Use Lower Band: Potential long-term accumulation zones Main Band: Macro trend equilibrium level Upper Band: Increasing risk and overvaluation awareness Upper Log Regression Zone: Historical market cycle top proximity (risk management reference) Recommended Timeframes Daily (1D) Weekly (1W) ⚠️ This indicator does not generate buy or sell signals. It is intended for educational and analytical purposes only and should be used together with proper risk management and additional confirmation tools.
Indikator Pine Script®
oleh Hakan-Kocabey
8
WStdvB - weighted bands [cc]WStdvB is a volatility-driven trading strategy designed to identify high-probability breakouts and trend continuations using weighted standard deviation bands combined with multiple confirmation filters. At its core, the strategy adapts dynamically to market conditions by measuring volatility expansion and filtering trades only when structure, momentum, and trend alignment are present. ⸻ Core Concepts • Weighted Standard Deviation Bands Dynamic bands built around a configurable moving average to detect volatility breakouts. • Directional Bias Filters Trend filters ensure longs and shorts are only taken in the dominant market direction. • Volatility Confirmation Trades are allowed only when volatility is expanding relative to its own average, helping avoid low-energy market phases. • Supertrend Confirmation & Exit Logic Optional Supertrend filter for trend validation and adaptive exits during reversals. ⸻ Risk & Exit Management • ATR-Based Stop Loss Adaptive volatility stops that adjust to current market conditions. • Multiple Exit Conditions Positions can close based on: • Opposite band interaction • ATR stop • Moving average cross • Supertrend flip This layered exit logic is designed to protect capital while allowing profitable trends to develop. ⸻ Customization Every component can be enabled, disabled, or tuned: • Separate logic for long and short trades • Independent parameters for filters, bands, and exits • Optimized for both trending and volatile markets ⸻ Notes • Designed for experienced traders who understand volatility-based systems • Works best on liquid instruments and higher-quality price feeds • The indicator isn't repainting Please note that this strategy is for educational purposes only and should not be used for trading without further testing and analysis.
Strategi Pine Script®
oleh zendrer
1
UCTRPB RSI Price Bands [CoinTadpole]UCTRPB RSI Price Bands UCTRPB is a predictive price band indicator that reverse-engineers the RSI formula to project exact price levels where RSI would reach specific thresholds. This allows traders to plan systematic entries and exits BEFORE price arrives at key levels. 🔶 WHAT MAKES THIS DIFFERENT FROM EXISTING INDICATORS This is NOT a simple RSI overlay, threshold alert, or basic reverse-calculation script. Most open-source RSI tools provide: - Current RSI value only (reactive, not predictive) - Single threshold lines displayed on a separate RSI panel - Alerts triggered AFTER RSI crosses a level (too late for preparation) UCTRPB provides capabilities that standard RSI indicators cannot offer: 1. Reverse-Engineering Price Projection While normal RSI calculates momentum FROM price, this indicator works backwards. It solves the RSI equation in reverse using Wilder's smoothing method to determine what price movement would produce a specific RSI value, then projects those levels directly on your price chart as dynamic bands. 2. Multi-Tier Zone System Instead of single lines, displays gradient zones with upper and lower boundaries. The oversold zone shows two levels (default: RSI 20 and RSI 25), and the overbought zone shows two levels (default: RSI 73 and RSI 80). This enables systematic position building across multiple price levels. 3. Real-Time Percentage Distance Labels Displays exact percentage distance from current price to each zone boundary. You instantly see how far price needs to drop to reach oversold (-X%) or rise to reach overbought (+X%). 4. Adaptive EMA Smoothing User-adjustable smoothing parameter (1-20) adapts band responsiveness to different market conditions. Lower values for volatile low-cap altcoins, higher values for stable large-cap assets like Bitcoin. 5. Integrated Info Dashboard All critical values displayed in one compact table: Current RSI, Current Price, Oversold Zone range, Overbought Zone range. Monitor everything at a glance without cluttering your chart. 6. Pre-Calculated DCA Entry Targets Calculates exact prices for multiple RSI thresholds simultaneously, enabling planned Dollar-Cost Averaging entries before price arrives at those levels. 🔶 THE PROBLEM THIS SOLVES Many traders want to accumulate at RSI oversold levels. However, they face a critical challenge: The Challenge: - "I want to buy when RSI hits 20-25" - But what PRICE will that be? - You cannot know in advance - By the time RSI shows oversold, the opportunity requires instant reaction Manual reverse-calculation of RSI is mathematically complex and practically impossible in real-time. The formula involves Wilder's exponential smoothing with rolling averages that change every bar. The Solution: UCTRPB pre-calculates these price levels dynamically, updating with each new bar. You see target prices BEFORE the move happens, allowing systematic order placement rather than reactive decisions. As shown above, price touched the oversold zone and bounced. The indicator projected this support level BEFORE price arrived there. 🔶 MULTI-LEVEL DCA PLANNING SYSTEM Unlike single-threshold indicators, UCTRPB displays a dual-boundary zone system for systematic position building: 🟢 Oversold Zone (Green Band) - For Accumulation Planning The green gradient band shows where RSI would become oversold. Default settings: RSI 20-25 - Upper boundary (RSI 25): First accumulation target - conservative entry - Lower boundary (RSI 20): Second accumulation target - aggressive entry Example: Current price $1.00 - RSI 25 level = $0.88 (-12%) → Place 1st limit buy - RSI 20 level = $0.82 (-18%) → Place 2nd limit buy 🔴 Overbought Zone (Red Band) - For Take-Profit Planning The red gradient band represents where RSI would enter overbought territory. Default settings: RSI 73-80 - Lower boundary (RSI 73): First take-profit target - secure partial gains - Upper boundary (RSI 80): Second take-profit target - extended target Example: Current price $1.00 - RSI 73 level = $1.15 (+15%) → Place 1st take-profit - RSI 80 level = $1.28 (+28%) → Place 2nd take-profit This systematic approach enables: - Planned DCA entries at multiple levels instead of single-point entries - Graduated take-profit strategy to secure gains progressively - Execution based on predetermined plan rather than emotional reactions - Clear visibility of risk/reward before entering any position Labels display exact price range and percentage distance to each zone, allowing precise limit order placement. 🔶 HOW THE ALGORITHM WORKS The indicator applies reverse RSI calculation using Wilder's smoothing method: Step 1: Retrieve Current RSI Components Extracts current Average Gain and Average Loss values calculated using Wilder's exponential smoothing over the specified period (default: 14 bars). Step 2: Calculate Target RS Ratio For a target RSI value, calculates the required Relative Strength ratio. Formula: Target RS = Target RSI / (100 - Target RSI) Example: For RSI 25 → Target RS = 25/75 = 0.333 Example: For RSI 20 → Target RS = 20/80 = 0.250 Step 3: Determine Required Price Change Based on current averages and Wilder smoothing formula, calculates what price change in the next bar would produce the target RS ratio. This accounts for how the new bar's gain/loss affects the smoothed averages. Step 4: Project Price Levels Converts required price change to actual price levels displayed as bands on the chart. Step 5: Apply Adaptive Smoothing EMA smoothing reduces noise while maintaining responsiveness. Adjustable from 1 (raw, responsive) to 20 (smooth, stable). Mathematical Foundation: RSI = 100 - (100 / (1 + RS)) where RS = Average Gain / Average Loss UCTRPB solves this equation BACKWARDS to find the price that would produce a target RSI. 🔶 INFO TABLE DASHBOARD The information table provides quick reference without cluttering the chart: - Current RSI: Real-time RSI value - Current Price: Latest closing price - Oversold Zone: Price range for oversold territory - RSI Range: Your configured RSI levels - Overbought Zone: Price range for overbought territory All critical values visible at a glance. Table position is adjustable (Top/Bottom, Left/Right). Dashboard displays Current RSI, Price, and Zone levels in one place for quick reference. 🔶 BAND SMOOTHING SETTINGS The Line Smoothing parameter (default: 15) controls band appearance: Lower Values (1-10): - More responsive, sharper bands - Reacts quickly to price changes - Better for volatile, low-cap altcoins with rapid price movements - May show more noise Higher Values (15-20): - Smoother, more stable bands - Filters out short-term fluctuations - Better for high market cap assets (BTC, ETH) with substantial liquidity - Cleaner visual appearance Adjust based on the asset's typical volatility characteristics. 🔶 NON-REPAINTING CONFIRMATION This indicator does NOT repaint: - All calculations use closed bar data only - Historical bands remain fixed after each bar closes - What you see on historical charts is exactly what was displayed in real-time - Intrabar fluctuations may show potential levels, but final levels are confirmed only at bar close 🔶 RECOMMENDED SETTINGS Timeframes: - 15-minute and 1-hour charts recommended for active trading - 4-hour and Daily for swing trading setups - Lower timeframes may produce more noise Conservative Settings (Fewer but stronger signals): - Bitcoin: Oversold 20-25, Overbought 75-80 - Large-cap Altcoins: Oversold 20-25, Overbought 73-80 Aggressive Settings (More opportunities): - Small-cap Altcoins: Oversold 23-28, Overbought 70-75 - Higher RSI thresholds = more frequent zone touches Price approaching the overbought zone tends to face resistance, as shown above. 🔶 IMPORTANT LIMITATIONS - This indicator shows where RSI "would be" IF price moved there in the next bar - Bands recalculate dynamically with each new bar as market conditions change - This is a planning and analysis tool, not a guarantee of reversal at those levels - Strong trends can push through oversold/overbought zones without immediate reversal - Always use in conjunction with other analysis methods (support/resistance, volume, trend) - Market conditions can change rapidly and invalidate projected levels 🔶 RISK DISCLAIMER Trading involves substantial risk of loss. This indicator is provided for educational and informational purposes only. It does not constitute financial advice. Past indicator performance does not guarantee future results. All investment decisions are entirely your own responsibility. 🔶 HOW TO GET ACCESS This script is provided as Invite-Only. To request access, please check the links in my TradingView profile.
Indikator Pine Script®
oleh cointadpole
23
Multi-Sigma Bands [fmb]Multi-Sigma Bands plots standard deviation (sigma) bands around a selectable basis (SMA, EMA, RMA, or Linear Regression). It’s designed to help you spot when price is behaving “normally” versus when it’s stretching into statistically extended territory. What it shows - Basis: the central reference line (your chosen basis type) - ±1σ zone: the common range where price spends much of its time - ±2σ zone: extended range where moves often become more emotional or trend-driven - ±3σ zone: extreme range where price is statistically stretched (risk increases) How to read it - Inside ±1σ - Often normal behaviour and mean-reverting price action around the basis. - Between ±1σ and ±2σ - A meaningful extension. In trends, price can “walk” these areas for longer than expected. - Between ±2σ and ±3σ - Rare extension. Can signal exhaustion, blow-off behaviour, or capitulation depending on direction and context. How traders typically use it - Trend context - In strong uptrends, price may ride the upper bands (+1σ to +2σ) repeatedly. - In strong downtrends, the lower bands (-1σ to -2σ) can act the same way. - Bands show statistical stretch, not automatic reversal signals. - Extension and risk framing - The farther price is from the basis, the more “stretched” it is. - That usually means chasing becomes riskier and entries require tighter confirmation. - Range behaviour - Ranges often oscillate around the basis, with frequent returns toward the middle zone. Settings - Source: what price series to use (Close by default) - Length: lookback used for both basis and standard deviation - Basis: SMA, EMA, RMA, or LinReg - Stdev smoothing: optional smoothing on standard deviation for cleaner bands - σ multipliers: customise σ1, σ2, σ3 (defaults: 1, 2, 3) - Force Monthly Data (optional): calculate bands using a higher-timeframe source to reduce noise and focus on macro structure Disclaimer This indicator is for informational and educational purposes only and is not financial advice. Always use risk management and confirm with market structure and trend context.
Indikator Pine Script®
oleh Fullymobile
VWAP Tension Bands + Osc Sigma Gap [MAXmks]Hello Traders, This indicator started as an accident. I was building a different tool — a multi-metric dashboard — and added VWAP deviation as one of the components. I expected it to help catch falling knives. It didn't. But I noticed something else. During cooling-off periods — when volatility fades and price just sits there, not really going anywhere — VWAP deviation on lower timeframes would start climbing quietly. And more often than not, a pullback followed. Sometimes a liquidity sweep first, then a pullback. I watched this pattern for months before deciding to build a dedicated tool around it, adding oscillator confirmation to filter the noise. This is that tool. The core idea Markets act like a rubber band around VWAP — the further price stretches, the higher the tension. But raw deviation isn't enough. The real question: is momentum confirming the stretch, or lagging behind? The σ-Gap captures when these two disagree — price pushed hard, but internals haven't caught up. That's where mean-reversion setups tend to appear. The indicator tracks VWAP deviation across 2m / 5m / 15m simultaneously and compares it against a composite of momentum oscillators (Williams %R, CVD-based metrics). Signals require multi-timeframe consensus — no single timeframe can trigger alone. Adaptive thresholds What counts as "extreme" isn't fixed. Distance is measured in standard deviations (σ) , not pips or percentages — so the indicator adapts to volatility automatically. Thresholds scale with regime and historical distribution, adjusting to current market conditions in real time. Two modes Standard — adaptive thresholds, more signals. Good for active sessions and exploration. High Precision — adds divergence confirmation from multiple oscillators (MFI, Delta RSI, CVD Z-Score). Fewer signals, higher selectivity. Extreme Tension When σ-Gap exceeds 1.6× the threshold, the indicator can fire without full confirmation. Rare, but these are the "overstretched" moments worth watching. Filters (so you don't trade ghosts) RVOL filter blocks signals during low activity. Session close filter avoids entries near VWAP reset. 24h volume filter skips illiquid instruments. Cooldown prevents signal clustering in the same direction. Best use case Built for short-term mean-reversion — quick snapback plays on 5m–15m charts where price overextends and reverts within a few candles. The engine is optimized for this rhythm, not for trend-following or swings. On-chart Tension Bands show dynamic threshold zones around VWAP. Signals are non-repainting and confirmed on bar close. Compact HUD displays all metrics, filter states, and signal status in real time. Alerts Pre-signal alerts when conditions start forming. Confirmed signal alerts with full breakdown: VWAP deviation values, σ-Gap readings, divergences detected, current mode. Volume matters This is a VWAP-based indicator. No volume data = no signal. If your instrument shows "No Volume" in the dashboard, switch to a data feed that provides it (crypto spot, futures, stocks with real volume). A note on expectations I use this logic in my own research and it has shown useful results for me in my backtesting scenarios. But this is an indicator for analysis , not a magic button. Your execution, fees, slippage, and market regime all matter. Treat signals as context, not commands. DYOR. Feedback welcome. For educational and analysis purposes only. Not financial advice.
Indikator Pine Script®
oleh MAXmks
PK Scalper Pro Neon Cloud Killzone Dashboard 📌 Overview PK Scalper Pro — Neon Cloud + Killzone Dashboard (JST) combines a Wilders ATR trail, Fibonacci entry zones, session/killzone context, and a 7-factor environment score to form a dynamic trend-following scalping strategy. It adapts in real time to volatility, aiming for higher entry precision and optimized risk. ⚠️ For educational and research purposes only. Past performance does not guarantee future results. 🎯 Strategy Objectives React quickly to sharp moves and reversals while using hysteresis (bar confirmation) to suppress noise and deliver stable scalping signals. ✨ Key Features Neon Cloud visualization (Full / Entry / Premium-Discount / Fib Bands / Upper / Middle / Lower modes) 7-factor scalping score (ATR compression / ADX / Volume / Candle range / Range compression / RSI / BB width) — quantified 0–10 to measure environment suitability Stable state machine combining Sensitivity × Stability (confirmation bars) to determine start/end states reliably 📊 Trading Rules Long Entry: Trend = +1 and price <= f2 (78.6%), with is_scalping_time = true Optimal zone: between f3 (88.6%) and l100 (trail); automatic “Fib Entry (Long)” label Short Entry: Trend = −1 and price >= f2 (78.6%), with is_scalping_time = true Optimal zone: between f3 and l100; automatic “Fib Entry (Short)” label Exit / Reversal: Reverse or close on Trend crossover/crossunder When is_scalping_time = false is confirmed, prioritize taking profit 💰 Risk Management Parameters Recommended timeframes: 1–15m (FX / Indices / Crypto) Example: Account $10,000 / Commission 0.02% / Slippage 1.0 pips / Risk 1% per trade SL = ATR(14) × 1.5, TP = SL × Target R:R (default 2.0) ⚙️ Trading Parameters & Considerations ATRPeriod = 200 / ATRFactor = 8 / trailType = "modified" Sensitivity = "Medium" (entry ≈6, exit ≈4) / Stability = "Normal" (confirmation bars = 3) Fibonacci: ex↔trail range → f1=61.8, f2=78.6, f3=88.6, eq=50, l100=trail Killzone shown in JST; priority order NY > LDN > TKY, with remaining time countdown 🖼 Visual Support Highlights optimal zone (f3→100%) and Premium/Discount areas; PRIME conditions shown with purple background Dashboard displays direction 📈/📉, score, confirmation progress, Killzone (JST), TP/SL guidance, and Session info 🔧 Strategy Improvements & Uniqueness Introduces a 7-factor score + hysteresis to quantify and stabilize “enter/stop” conditions Defines precise deep pullback zone (88.6–100%) as optimal entry area Neon multi-layer cloud + fixed-row dashboard for high visibility and live stability ✅ Summary PK Scalper Pro integrates momentum (Trend), volatility adjustment (ATR), and multi-factor scoring into a responsive scalping framework. Its clear visuals and practical design improve reproducibility and decision confidence. ⚠️ No guarantee of future profits — always apply disciplined position sizing and risk management.
Indikator Pine Script®
oleh PakunFX
Universal Adaptive Tracking🙏🏻 Behold, this is UAT (Universal Adaptive Tracker) , with less words imma proceed how it compares with alternatives: ^^ comparison with non-adaptive quadratic regression (purple line), that has higher overshoots, less precision ^^ comparison with JMA and its adaptive gain. JMA’s gain is heavily limited, while UAT’s negative and positive gains are soft-saturated with p-order Möbius transform This drop is inspired by, dedicated to, and made will all love towards Jurik Research , who retired in October 2k21. When some1 steps out, some1 has to step in, and that time it’s me (again xd). But there’s some history u gotta know: Some history u gotta know: In ~2008 dudes from forexfactory reverse engineered Jurik Moving Average In late 1990s dudes from Jurik Research approximated the best possible adaptive tracking filter for evolution of prices via engineering miracles Today in 2k26, me I'm gonna present to you the real mathematical objects/entities behind JMA top-edge engineered approximates. You will prolly be even more happy now then all the dem together back then. Why all this? When we talk about object tracking stuff, e.g. air defense, drones, missiles, projectiles, prices, etc, it all comes down to adaptive control and (Position & Velocity & Acceleration) aka PVA state space models (the real stuff many of you count as DSP ). Why? Cuz while position (P) : (mean), or position & velocity (PV) : (linear regression) are stable enough in dem own ways, Position & Velocity & Acceleration (PVA) : (quadratic regression+) require adaptivity do be stable. And real world stuff needs PVA, due to non-linearity for starters. So that’s why. If your goal is Really smoothing and no lag, u gotta go there. I see a lot of folks are crazy with it and want it, so here is it, for y’all. And good news, this is perfect for your favorite Moving Windows. How to use it The upper study: The final filter (main state): just as you use other fast smoothers, MAs, etc, you know better than me here You can also turn in volatility bands in script’s style settings, these do not require any adjustments Finally, you can turn on, in the same place, separate trackers each based on negative and positive volatility exclusively. When both are almost equal, that indicates stability & persistence in markets. May sound like it’s nothing important, but I've never seen anything like it before. Also, if you'd allow your our inner mental gym hero gloriously arise, you can argue that these 2 separate trackers represent 2 fair prices (one for sellers, one for buyers). All better then 1 imaginary fair price for both (forget about it) The lower study: The lower study: you can analyze streams of upward of downward volatilities separately. This is incredibly powerful You can also turn these off and turn on neg & pos intensities, and use them as trend detector, when each or both cross 1.5 (naturally neutral) threshold. ^^ Upper study with expected typical and maximum volatility bands turned On ... The method explained What you got in the end is non-linear, adaptive, lighting fast when needed and slow when required price tracking. All built upon real math entities/objects, not a brilliantly engineered approximation of them. No parameters to optimize, data tells it all. ... It all starts from a process model, in our cause this is... MFPM (Mechanical Feedback Price Model) Doesn’t make gaussian assumptions like most quant mainstream tech, accepts that innovations are Laplace “at best”, relies in L inf and L0 spaces. I created this model neither trynna fit non-fitting ARMA / variants, nor trynna be silly assuming that price state evolution and markets are random. Theory behind it: if no new volume comes, then price evolution would be simply guided by the feedback based on previous trading activity, pushing prices towards the midrange between 2 latest datapoints, being the main force behind so called “pullbacks” and reason why most pullbacks end just a bit past 50% of a move. This is the Real mechanical feedback based mean reversion, that is always there in the markets no matter what, think of it as a background process that is always there, and fresh new volume deviates prices away from it. Btw, this can also be expressed as AR2 with both phis = 0.5 . Then I separate positive and negative innovations from this model and process them separately, reflecting the asymmetry between buy and sell forces, smth that most forget. Both of these follow exponential distribution . Each stream has its own memory so here we use recursive operators . We track maximum innovations (differences between real and expected datapoints) with exponentially decaying damping factor, and keep tracking typical innovation, with the same factor. Then we calculate what’s called in lovely audio engineering as “ crest factor ”, the difference is we don’t do RMS and stuff. But hey again we work with laplace innovations, so we keep things in L0 and L inf spirit. Then we go a couple of steps further, making this crest factor truly relative (resolution agnostic), and then, most importantly, we apply a natural saturation on it based on p-order Möbius transform, but not with arbitrary p and L, but guided by informational limits of the data. These final "intensity" parameters are what we need next to make our object tracking adaptive. Extended Beta(2, 2) Window This is imo the main part of this. Looking at tapering windows in DSP and how wavelets are made from derivatives of PDF functions of probability distributions, I figured that why use just one derivative? That made me come up with Universal Moving Average , that combines PDF and CDF of Beta(2, 2) distribution . And that is fine for P (position) tracking model. Here we need PVA (position & velocity & acceleration). We can realize that everything starts from PDF, and by adding derivatives and anti-derivatives of it as factors of final window weights, we can create smth truly unique, a weightset that is non-arbitrary and naturally provides response alike quadratic regression does, But, naturally smoothed. Why do I consider this a discovery, a primordial math object? Because x^2 itself and Beta(2, 2) based on it are the only primitives, esp out of all these dozens of DSP tapering windows, that provide you a finite amount of derivatives. You can keep differentiating Hann window until the kingdom f come, while Welch window aka Beta(2, 2) has a natural stopping point, because the 3rd derivative is 0, so we can’t use it. Symmetrically, we do 2 steps up from PDF, getting 1st and second anti-derivatives. What’s lovely, symmetrically, 3rd antiderivative even tho exist, it stops making any sense. 2nd one still makes sense, it’s smth like “potential” of probability distribution, not really discussed in mainstream open access sources. Finally, the last part is to introduce adaptivity using these intensity exponents we’ve calculated with MFPM. We do 2 separate trackers, one using the negative intensity exponent, another one uses positive intensity exponent. And at the end, even tho using both together is cool, the final state estimate is calculated simply as the state which intensity has higher. ^^ impulse response of our final kernel with fixed (non adaptive) intensity exponents: 1 (blue) and 2 (red). You see it's all about phase … And that’s all folks. … Actually no … Last, not least, is the ability to add additional innovation weight to the kernel: ^^ Weighting by innovations “On”. Provides incredible tracking precision, paid with smoothness. I think this screenshot, showing what happened after the gap, and how the tracker managed to react, explains it all. ... Live Long and Prosper, all good TradingView ∞
Indikator Pine Script®
oleh gorx1
5
Bear Market Resistance BandsBear Market Resistance Bands Indicator – How It Works This overlay indicator helps identify potential resistance zones during bearish market conditions, downtrends, or corrective rallies within larger bear phases. It plots dynamic overhead levels where price often struggles to break higher, and where selling pressure tends to increase — making it useful for short setups, fading rallies, or confirming bearish continuation. 1. The Three Resistance Levels The indicator draws three moving averages that act as layered resistance bands: Fast Resistance A 20-period Simple Moving Average (SMA) of the close price (length is adjustable). Shown as a red line (linewidth 2). This is the quickest, most sensitive level — rallies frequently stall or reverse here first. Medium Resistance A 50-period SMA of the close price (also adjustable). Shown as an orange line (linewidth 2). This acts as a stronger, deeper resistance zone. Rallies that reach this level are considered more significant tests of supply. Slow Resistance The 200-day Volume Weighted Average Price (VWAP) from the daily timeframe. Only displayed if the "Show 200-day VWAP" setting is turned on (enabled by default). Plotted in very dark red (#8B0000) with circle markers and thicker line (linewidth 3). This is the slowest-moving, longest-term resistance level — often a major institutional supply zone in prolonged bear markets. These lines form a descending resistance corridor. The areas between them are shaded with semi-transparent red fills to make the zones visually clear:Light red fill between Fast and Medium levels. Darker red fill between Medium and VWAP (when shown). 2. Background Coloring – Strong Bear Zone When the closing price is below all active resistance levels (below Fast SMA, below Medium SMA, and below VWAP if enabled), the chart background turns a very faint red. This highlights periods of strong bearish control, where upside momentum is weak and sellers dominate. 3. Rejection Signals – Bearish Rejection Triangles The indicator marks moments when price rallies up to a resistance level and then turns down — interpreted as sellers rejecting higher prices. These signals appear as small downward triangles above the bar: Reject Fast – red triangle: price crosses below the Fast SMA after touching or approaching it. Reject Med – orange triangle: price crosses below the Medium SMA. Reject VWAP – maroon triangle: price crosses below the 200-day VWAP (only if VWAP is enabled). These triangles are classic visual cues for failed rallies or bearish reversals at resistance — often good spots for short entries or to add to existing shorts in downtrends.You can set an alert on any of these rejection events (“Bearish Resistance Rejection”). 4. How to Read the Indicator in PracticePrice Action / Position Price Action / Position - What It Usually Means - Typical Market Context - Trading Implication (Bearish View) Price stays below all bands + red background - Sellers in full control - Strong downtrend / bear market - Bearish bias – hold/add shorts Price rallies into the red/orange fills - Counter-trend rally testing supply - Bear market bounce / dead-cat bounce - Watch for rejection – prepare to short Downward triangle appears at a band - Sellers defend the level – rally fails - Resistance confirmed - High-probability short signal Multiple rejections at the same level - Persistent overhead supply - Distribution phase - Stay short / avoid buying Price breaks and closes above all bands - Potential bullish shift / resistance broken - Caution – bear case weakening - Reduce shorts, monitor for reversal Best Use Cases - Timing short entries on rallies during downtrends — especially when a rejection triangle appears at the Medium or VWAP level. - Confirming bearish trend strength — frequent rejections + persistent red background = classic bear market behavior. - Avoiding false bottoms — rallies that fail at the Fast or Medium band often signal continuation lower. - Major assets — works particularly well on indices (SPX, NDX), large-cap stocks, and cryptocurrencies during bear phases, where the 200-day VWAP frequently acts as a key battleground. Customization Tips Adjust Fast Length and Medium Length to match your timeframe (shorter for intraday, longer for swing/position trading). Toggle the 200-day VWAP off if you prefer simpler visuals or trade non-stock assets where VWAP is less relevant. Combine with volume indicators, RSI, or lower-timeframe price action for higher-conviction setups. In essence, this indicator turns classic moving averages and VWAP into a clear visual system for spotting bearish resistance zones and failed rallies. When price repeatedly gets rejected at these red/orange bands with downward triangles, it reinforces the idea that sellers remain in control — a simple but powerful tool for bear-market or corrective-phase trading. If you have questions about applying it to a specific chart or want ideas for complementary indicators, feel free to join us in our discord server: discord.gg/y73tgmT9H6
Indikator Pine Script®
oleh WaywardScripts
1
MAD Supertrend [Alpha Extract]A sophisticated SuperTrend implementation that replaces traditional ATR calculations with Mean Absolute Deviation methodology for adaptive volatility measurement and band construction. Utilizing SMA baseline with MAD-based deviation bands and optional adaptive factor adjustments, this indicator delivers institutional-grade trend detection with strength-based filtering and dynamic visual feedback. The system's MAD approach provides superior noise reduction compared to ATR while maintaining responsiveness to genuine volatility changes, combined with momentum-based strength calculations for high-conviction signal generation. 🔶 Advanced MAD-Based Band Construction Implements Mean Absolute Deviation calculation as volatility proxy, measuring absolute price deviations from mean and smoothing for stable band generation without ATR dependency. The system calculates SMA baseline, computes MAD from configurable lookback period, applies factor multipliers to create upper and lower bands, then implements classic SuperTrend ratcheting logic where bands only adjust when price violates previous levels or calculations warrant updates. // Core MAD SuperTrend Framework SMA_Value = ta.sma(src, SMA_Length) Mean = ta.sma(src, MAD_Length) Abs_Deviation = abs(src - Mean) MAD_Value = ta.sma(Abs_Deviation, MAD_Length) // Band Construction with Ratcheting Upper_Band = SMA_Value + MAD_Factor * MAD_Value Lower_Band = SMA_Value - MAD_Factor * MAD_Value // Ratcheting logic prevents premature band adjustments 🔶 Adaptive Factor Adjustment Engine Features optional adaptive multiplier system that modulates MAD factor based on normalized MAD magnitude relative to recent extremes, creating bands that automatically expand during high-volatility regimes and contract during consolidation. The system applies min-max normalization to MAD values over configurable lookback, multiplies by adaptation parameter, and adds to base factor for dynamic volatility sensitivity without manual recalibration. 🔶 Momentum-Based Strength Filter Implements sophisticated strength calculation measuring price momentum relative to baseline divided by volatility-adjusted MAD bands, producing normalized 0-1 strength scores with exponential smoothing. The system calculates distance from SMA baseline, normalizes by MAD-derived band width, and applies configurable minimum threshold requiring sufficient momentum before trend signals activate, filtering weak or choppy market conditions. 🔶 SuperTrend Direction Logic Utilizes classic SuperTrend methodology adapted for MAD bands where trend direction flips on opposite band violations with state persistence until confirmation. The system tracks whether price closes above upper band (bearish flip to bullish) or below lower band (bullish flip to bearish), maintains directional state until opposing violation occurs, and generates binary +1/-1 trend signals suitable for systematic position management. 🔶 Intelligent Candle Sticking System Provides advanced line positioning option that anchors SuperTrend line to candle wicks or bodies rather than pure calculation values for enhanced visual clarity. The system supports two modes: Wick (positions at high/low extremes based on trend direction) and Body (constrains line between calculation and candle extremes), creating cleaner chart presentation while maintaining mathematical integrity of underlying signals. 🔶 Dynamic Gradient Visualization Framework Implements color intensity modulation based on smoothed strength calculations, transitioning from muted to vivid hues as momentum conviction increases. The system applies gradient interpolation using strength ratio, creating visual feedback where strong trending moves display intense colors while weak or consolidating conditions show faded tones across trend line, channel bands, and candle coloring for immediate regime assessment. 🔶 MAD Channel Architecture Features volatility-adjusted channel bands centered on baseline or candle-stuck line with configurable multiplier for support/resistance visualization. The system calculates upper and lower bounds using MAD values scaled by adaptive factors and channel multipliers, applies dynamic transparency based on trend strength, and creates filled regions that intensify during strong trends and fade during weak conditions. 🔶 Multi-Layer Glow Effect System Provides sophisticated line rendering with triple-layer plot system creating glow effect through progressively wider and more transparent outer layers. The system plots core trend line at specified width with full color intensity, adds inner glow layer at +2 width with moderate transparency, and outer glow at +4 width with higher transparency, creating visual depth and emphasis without cluttering chart space. 🔶 Strength-Based State Management Implements intelligent trend state logic requiring both directional signal and minimum strength threshold breach before confirming trend transitions. The system calculates raw SuperTrend direction, evaluates smoothed strength against configurable minimum, generates filtered trend state that can be bullish (+1), bearish (-1), or neutral (0), and maintains state persistence using hold logic that prevents oscillation during ambiguous conditions. 🔶 Comprehensive Alert Integration Generates trend flip alerts when filtered state transitions from bearish to bullish or bullish to bearish with full confirmation requirements satisfied. The system detects state changes through comparison with previous bar, triggers single alert per transition rather than continuous notifications, and provides customizable message templates for automated trading system integration or manual notification preferences. 🔶 Performance Optimization Architecture Utilizes efficient calculation methods with null value handling, nz() functions preventing errors during initialization bars, and optimized gradient calculations. The system includes intelligent state persistence minimizing recalculation overhead, streamlined MAD computation avoiding redundant mean calculations, and smooth visual updates maintaining consistent performance across extended historical periods. This indicator delivers sophisticated SuperTrend analysis through Mean Absolute Deviation methodology providing superior statistical properties compared to traditional ATR-based approaches. MAD calculations offer more robust volatility measurement resistant to extreme outliers while maintaining sensitivity to genuine market regime changes. The system's adaptive factor adjustment, momentum-based strength filtering, and dynamic visual feedback make it essential for traders seeking reliable trend-following signals with reduced false breakouts during choppy conditions. The combination of MAD bands, candle-sticking options, gradient strength visualization, and comprehensive filtering creates institutional-grade trend detection suitable for systematic approaches across cryptocurrency, forex, and equity markets with clear entry/exit signals and comprehensive alert capabilities.
Indikator Pine Script®
oleh AlphaExtract
Blockcircle Waveform BandsThe Blockcircle Waveform Bands is a comprehensive trend-following indicator built around a layered moving average ribbon system. The core idea is simple: when shorter-term averages stack above longer-term ones in proper sequence, the trend is healthy. When they compress, cross, or invert, something is changing. This indicator was developed to solve a common problem. Traders often clutter their charts with multiple moving averages, each added separately, each requiring manual tweaking. Waveform Bands consolidates everything into a single, unified view. You get fast, medium, and slow bands that expand and contract with momentum, change color based on trend direction, and provide clear reference points for entries, exits, and trend assessment. Also included is a configurable higher-timeframe bias band, which allows you to track the macro trend without switching timeframes. Most useful is following the 21W EMA and 20W SMA crosses. What Makes This Indicator Different While moving average ribbons are a well-known concept, this indicator extends beyond simple MA plotting in several meaningful ways that justify its protected source status. First, the indicator calculates a proprietary confluence score ranging from negative 100 to positive 100. This score is not just counting crossovers. It uses weighted contributions from band alignment, price position across multiple timeframe zones, and momentum confirmation via rate of change integration. The specific weighting logic and calculation method represent original development work not available in standard MA ribbon indicators. Second, the summary scoring system evaluates trend quality on a 0 to 100 scale using a multi-factor algorithm. Trend state contributes up to 35 points, band alignment contributes up to 30 points, price position contributes up to 20 points, and momentum confirmation contributes up to 15 points. This weighted approach provides objective trend measurement rather than relying solely on visual interpretation. Third, the signal generation framework offers five distinct signal methods, each with three sensitivity levels, creating fifteen unique configurations. This is a complete signal system with filtering logic, not simply MA crossover alerts. The interaction between signal type, sensitivity, and the optional trend filter creates a flexible framework that traders can calibrate to their specific style. Fourth, the optional smoothing layer applies additional processing after the base MA calculations are complete. This reduces noise and whipsaws during choppy conditions while maintaining responsiveness during genuine trend moves. These proprietary elements, particularly the scoring algorithms and signal framework, represent the original work that distinguishes this from standard open-source MA ribbons available elsewhere. Key Features Multi-Band Ribbon System: Three distinct bands covering short, medium, and long-term trend structure. The fast band uses configurable MAs with default periods of 8, 13, and 16 for immediate price action. The mid band spans 21 to 42 periods, capturing the intermediate swing structure. The slow band covers 50 to 60 periods, representing the underlying trend foundation. Each band can be independently toggled, colored, and adjusted. Flexible Moving Average Types: Choose from eight MA calculation methods including EMA, SMA, WMA, VWMA, HMA, DEMA, TEMA, and ZLEMA. Set a default type for all bands or override individually per band. Useful for those who prefer Hull MA smoothness or the responsiveness of DEMA and TEMA. Major Moving Averages: Built-in 200-period MA for institutional-level support and resistance. Pi cycle MA using 314 periods for longer-term cycle analysis. Fully customizable additional MA with adjustable length, type, and color. Clear visual distinction with configurable line widths. Higher Timeframe Bias Band: Dual MA system pulled from any higher timeframe you choose. Default configuration mirrors the popular 21-week EMA versus 20-week SMA setup. Both MAs are fully adjustable in length, type, and timeframe. Automatic bullish or bearish fill coloring based on which MA leads. Keeps macro context visible without leaving your current chart. Dynamic Trend Coloring: All bands automatically shift color based on detected trend state. Bullish alignment shows green spectrum, bearish shows red, neutral shows yellow. Trend Detection and Scoring: Algorithmic trend state detection based on band alignment and price position. Confluence scoring system weighing multiple factors from negative 100 to positive 100. Band alignment tracking showing whether each band is internally bullish or bearish. Band expansion and contraction monitoring for momentum assessment. Strength percentage calculation for trend conviction measurement. Signal Generation: Multiple signal type options including band crosses, price crosses, and full alignment signals. Three sensitivity levels to match different trading styles and timeframes. Optional filtering to show only signals confirmed by the slow band. Dashboard Display: Comprehensive table with summary score, bias direction, and trend status. Compact mode available for reduced screen footprint. Alerts: Pre-configured alerts for buy and sell signals. Trend change notifications when bias shifts bullish or bearish. Major MA cross alerts for the 200 MA and Pi MA. Band alignment alerts when all bands synchronize. Confluence threshold alerts for strong directional readings. How To Use Identifying Trend Direction: Look at the overall band structure first. In a healthy uptrend, the fast band sits above the mid band, which sits above the slow band. Price should be trading above the fast band or at least within it. The dynamic coloring gives you an instant read. If everything is green, the trend structure is bullish. Red means bearish. Yellow or mixed colors indicate transition or consolidation. Check the dashboard summary row for a quick score. Above 60 suggests a solid trend, while below 40 indicates weakness or chop. Using the Bias Band for Macro Context: The higher timeframe bias band tells you whether the larger trend supports your trade idea. If you are looking to buy on a daily chart, check whether the weekly bias band is bullish, meaning the fast MA is above the slow MA. When the price is above both bias MAs and the band is bullish, conditions favor long positions. When the price is below both and the band is bearish, conditions favor shorts or staying out. The fill color between the bias MAs changes automatically. Green fill indicates bullish macro bias and red indicates bearish. This is visible at a glance without checking numbers. Finding Entry Points: Look for pullbacks into the mid band during established trends. When the fast band compresses toward the mid band and then expands again, this often marks a continuation entry. Band crossings can signal new trend initiations. When the fast band crosses above the mid band with confirming price action, it suggests a potential long entry. The opposite applies for shorts. Use the signal markers as alerts to potential opportunities, but confirm with price action. A signal appearing while the price is holding above a key band carries more weight than one appearing in isolation. Managing Risk and Exits: The slow band often acts as a trailing stop reference during trends. As long as price holds above the slow band on pullbacks, the trend remains intact. This is not always true, but it serves as a helpful general guideline. Losing the mid band on a closing basis often warns that the move is weakening. This might prompt partial profit-taking or tightening stops. The 200 MA serves as a major support or resistance level. Trends that break below the 200 after an extended move often accelerate to the downside. Reading Momentum Through Band Width: When all bands are tightly compressed, expect a directional move soon. Compression represents energy building up. Expanding bands confirm momentum is present in the current move. Watch for continued expansion on trend days. Contracting bands during a trend may warn that momentum is fading, even if the price has not reversed yet. Combining Multiple Timeframes: Enable multi-timeframe mode to see higher timeframe MAs plotted on your current chart. Be careful with this as it can crowd the display, but it is useful for seeing different timeframes stacked together. This helps identify where significant support or resistance exists above your normal view. The bias band already provides macro context, but you can set it to different timeframes for different purposes. Day traders might use daily bias bands while swing traders might prefer weekly. How To Read The Table The summary row gives you the overall picture. A high score with bullish bias and strong trend status represents ideal conditions for trend-following entries. Individual band status rows tell you if any divergence exists between timeframes. If the fast band is bearish but mid and slow are bullish, you might be seeing a pullback rather than a reversal. Price position percentages show how extended the price is from each band. Extreme readings in either direction suggest potential mean reversion or exhaustion. Limitations This indicator is designed for trending markets and performs best when clear directional movement exists. During extended consolidation or ranging conditions, the confluence score may oscillate near zero and signals may produce mixed results. Like all moving average based systems, signals are lagging by nature. The indicator confirms trends rather than predicting them. Early entries require additional confirmation from price action or other methods. The default settings are optimized for daily and higher timeframes on crypto and forex markets. Intraday traders and those analyzing other asset classes may need to adjust the band lengths to match their specific conditions. This indicator should be used as part of a complete trading approach that includes proper risk management and position sizing. It is not intended as a standalone system. Getting Started Start with the default settings and observe how the indicator behaves on your preferred instruments and timeframes before customizing. The indicator works on all markets and timeframes, but the default MA lengths are optimized for daily and higher charts. For intraday trading, consider reducing the band lengths proportionally. Use the compact table mode if the full dashboard feels cluttered. The essential information remains visible while using less screen space. Set up alerts for trend changes and major MA crosses so you do not need to watch charts constantly. Let the indicator notify you when conditions change.
Indikator Pine Script®
oleh blockcircle
Kinetic Flow [PyraTime]📊 INDICATOR OVERVIEW Kinetic Flow is a professional-grade momentum and trend-detection engine designed for traders who prioritize precision and clarity. By synthesizing Kinetic Flow Analysis with Fractal Efficiency Filtering, the V8 Flow edition provides a sophisticated, data-driven visualization of market regimes while systematically neutralizing noise through its proprietary "Chop Shield." 🎯 CORE TECHNOLOGIES 🔹 Kinetic Flow Engine Adaptive Equilibrium: A state-managed basis line that calculates the path of least resistance. Volatility-Scaled Ribbons: ATR-dynamic channels that expand and contract based on market energy. Iron-Clad Stability: Logic-locked to closed-bar calculations to eliminate intrabar flickering and "ghost" signals. 🔹 Chop Shield (Fractal Efficiency) Market Fragmentation Detection: Mathematically identifies when price action lacks directional efficiency. Regime Filtering: Automatically shifts the indicator into a "Neutral" state during low-efficiency phases to prevent whipsaws. Fibonacci Thresholding: Defaulted to 61.8% for optimal balance between speed and reliability. 🔹 Professional Signal System Transition Labels: High-contrast BUY and SELL markers at momentum pivot points. Overextension Logic: Strategic TP (Take-Profit) markers appear when the "Strain" on the kinetic ribbon reaches exhaustion levels. Visual Regime Mapping: Adaptive candle coloring provides an immediate heat-map of current market conditions (Bullish, Bearish, or Filtered). 🔹 PyraTime Dashboard (V8 HUD Standard) A specialized, monospace HUD positioned at the Bottom-Right for non-intrusive data monitoring: CONTEXT: Real-time regime status (BULLISH | BEARISH | FILTERED). EFFICIENCY: A percentage-based score of directional trend strength. VOL RATIO: Real-time volatility tracking via precision ATR. STATUS: Instant operational feedback (ACTIVE | FILTERED).
Indikator Pine Script®
oleh PyraTime
2
Mr. SnappyMr. Snappy is an advanced VWAP mean reversion indicator designed to identify high-probability price reversals when markets become overextended from the Volume Weighted Average Price (VWAP). Like a curveball that appears to be going one direction before snapping back, Mr. Snappy identifies when price has stretched too far from VWAP and is primed to snap back to equilibrium. Built for intraday traders seeking precision entries with clearly defined risk management. CORE FEATURES: Adaptive ATR-Based Bands - Dynamic threshold zones that adjust to market volatility Auto ATR Technology - Automatically calibrates band placement based on historical price behavior within a 20-40% ATR range, analyzing where price has historically reversed near VWAP to create "brick wall" resistance levels Predictive Band Algorithms - Five experimental modes for advanced traders: • Recent Reversal Points: Averages historical reversal distances • Volume-Weighted Reversal: Weights reversals by volume significance • Failed Breakout Detection: Tracks where momentum breaks failed • Multi-Timeframe Confluence: Analyzes higher timeframe VWAP distances • Linear Regression Channel: Statistical deviation bands Dual Signal System - Overextended mean reversion signals for stretched price action plus VWAP reaction signals for bounces and rejections in trending markets Automatic SL/TP Lines - Extends stop loss and take profit lines forward until price hits them, keeping your risk management visible throughout the trade Flexible Take Profit Targeting - Multiple TP calculation methods: • VWAP (classic mean reversion target) • VWAP Bands (opposite band target) • Fixed Risk-Reward Ratios (1:1 through 7:1) • 50% Pivot Retracement • Percentage to Daily High/Low Confirmation Logic - Optional two-candle confirmation system requiring directional movement before signal trigger, filtering whipsaw entries while adding slight delay Overextended Tolerance - Adjustable buffer zone from 0-50% requiring price to extend beyond the bands by a specified amount before triggering signals, preventing premature entries on minor extensions CUSTOMIZATION OPTIONS: Toggle between manual ATR threshold or Auto ATR for dynamic adjustment Show or hide bands and fills for clean chart presentation while keeping signals visible Adjustable pivot types - Local pivots for recent price action or Swing pivots for longer-term reference points Multi-timeframe analysis support for confluence trading Fully customizable ATR length, lookback periods, tolerance levels, and band calculation methods USE CASES: Scalping overextended moves that snap back to VWAP Day trading mean reversion setups on liquid instruments Fading extreme deviations when price stretches beyond statistical norms VWAP bounce and rejection plays in trending conditions Quick reaction trades when price touches VWAP in a defined trend RISK DISCLAIMER: VWAP resets daily at the start of each trading session. If holding trades across sessions, take profit targets may become invalid as VWAP recalculates. Always reference the NEW VWAP level as your exit target after reset. Consider closing positions before session end or manually adjusting targets. TP lines do NOT auto-update after VWAP reset. This indicator is a tool for technical analysis and does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management and position sizing. BEST PERFORMANCE: Mr. Snappy works optimally on liquid instruments including stocks, futures, forex majors, and cryptocurrency on intraday timeframes ranging from 1-minute to 15-minute charts. Higher timeframes may produce signals but mean reversion setups are strongest on shorter intervals where VWAP acts as a strong gravitational center. Experimental features including Auto ATR and Predictive Bands are clearly marked with visual warnings when active. These advanced algorithms may impact performance on lower-end devices when analyzing extensive historical data. TECHNICAL SPECIFICATIONS: Uses daily ATR for volatility-adjusted bands VWAP calculation includes volume weighting for institutional price levels Pivot-based stop loss placement using recent swing highs and lows Local pivot lookback default: 2 bars | Swing pivot lookback default: 5 bars Auto ATR analysis period: 50 bars (configurable 20-200) Maximum active SL/TP lines: 50 (automatic cleanup) Overextended tolerance default: 1% Manual ATR threshold default: 30% Premium indicator developed for serious intraday traders who demand precise entries, disciplined exits, and adaptive market analysis. Mr. Snappy identifies when price has thrown a curveball and is ready to snap back to the mean.
Indikator Pine Script®
oleh MessyJess
Rumiancev Reaction ZonesRumiancev Reaction Zones Rumiancev Reaction Zones (RRZ) is a clean, non-signal overlay that highlights potential reaction areas — places where price often slows down, bounces, or becomes stretched relative to the current market range. RRZ is NOT a trading bot. It does not provide guaranteed entries/exits. Use it as a context tool alongside your own confirmation (structure, trend bias, momentum/volume, etc.). ──────────────────────────────────────── WHAT IS DRAWN ON THE CHART ──────────────────────────────────────── 🔵 Blue Zone • Buy Area (Filled Band) A lower reaction band (“discount / downside stretch”). • Upper edge: Blue Zone • Buy Area (blue line) • Lower edge: Blue Zone • Lower Band (hidden band edge) When price enters this band, reactions become more likely (bounces, stabilization, reclaim moves). 🟠 Orange Zone • Sell Area (Filled Band) An upper reaction band (“stretch / upside extension”). • Lower edge: Orange Zone • Sell Area (orange line) • Upper edge: Orange Zone • Upper Band (hidden band edge) When price reaches this band, pauses, pullbacks, or distribution can appear. ⚪ Guide Line (Gray) A neutral reference line inside the structure. Helps to judge whether price is closer to “discount” (Blue side) or “stretch” (Orange side). 🟢 Deep Line (Green) — Aggressive Context (NOT a zone) A deeper downside reference line (green), not a filled band. If price reaches it, conditions are typically more volatile and risk is higher. Treat it as a high-risk context line, not an automatic entry. 🔴 Orange Extreme (Red) — High Extension (NOT a zone) A high-extension reference line above the Orange Zone. Often used as a strong risk-reduction context after extended upside moves. ──────────────────────────────────────── HOW TO USE RRZ (PRACTICAL FRAMEWORK) ──────────────────────────────────────── 1) Blue Zone approach (potential entries) • When price enters the Blue Zone , wait for confirmation first (rejection wick, reclaim back above the zone edge, local structure holding). • Consider scaling in gradually rather than entering full size at once. • If price continues deeper toward the green Deep Line , treat it as higher risk and act only if your plan and risk limits allow it. 2) Orange Zone approach (potential exits) • When price reaches the Orange Zone , many traders consider partial risk reduction (scale out, protect profit, tighten stops). • Near the red Orange Extreme line, many traders consider stronger risk reduction (up to closing most/all), especially after impulsive runs. IMPORTANT: RRZ marks areas , not entries. Always define invalidation (stop/idea failure point) and position size before acting. ──────────────────────────────────────── CONFIRMATION IDEAS (SIMPLE) ──────────────────────────────────────── • Rejection wicks / reclaim back above a zone edge • Break & retest of local structure • Momentum/volume shift you personally trust • Alignment with higher-timeframe direction ──────────────────────────────────────── SETTINGS ──────────────────────────────────────── • Depth → sensitivity (lower = more reactive, higher = steadier) • Smoothness → adaptation speed (lower = faster, higher = smoother) • Zone Width → thickness of the Blue/Orange fills (visual width) ──────────────────────────────────────── EXAMPLES (CHART IMAGES) ──────────────────────────────────────── Example 1 — Orange Zone reaction (Daily) Price pushes into the Orange Zone (stretch area), then cools off and rotates lower. RRZ helps visualize this as a place to watch for rejection or profit-taking context. Example 2 — Repeated cycles (Daily) Multiple cycles where touches into the Orange Zone often coincide with pauses/pullbacks, while dips into the Blue Zone tend to act as reaction areas during corrections. Example 3 — Blue Zone reaction after a sell-off (4H) A sharp move pushes price into the Blue Zone , followed by stabilization and reaction. The Orange Zone remains overhead as the next upside stretch region to monitor. ──────────────────────────────────────── NOTES ──────────────────────────────────────── • Zones are dynamic and update as new market data forms. • No future-looking data (“lookahead”) is used. ──────────────────────────────────────── DISCLAIMER ──────────────────────────────────────── This script is for educational and informational purposes only and is not financial advice. Trading involves risk. No indicator can guarantee results.
Indikator Pine Script®
oleh Rumiancev
Point of Control [BigBeluga]🔵 OVERVIEW Point of Control identifies the exact price level with the highest traded volume over a selected lookback period. This level—called the Point of Control (PoC) —marks where the greatest market participation occurred, representing a zone of highest volume. The indicator helps traders visualize dominant volume concentrations, fair-value levels, and structural balance within recent price action. 🔵 CONCEPTS Point of Control (PoC) — The single price level within the defined lookback range that has accumulated the most traded volume. Volume Distribution Bins — The price range is divided into 25 equal bins, and volume is aggregated per bin to locate the maximum concentration. Range Boundaries — The highest and lowest price within the lookback window are used to form the upper and lower reference limits. PoC Channel — Optional upper and lower bands plotted around the main PoC to visualize a fair-value corridor. Volume Intensity Mapping — Candle color dynamically shifts based on the candle’s position relative to the PoC channel, showing whether price is balanced or trending away from high-volume levels. 🔵 FEATURES Configurable Lookback Range — Adjust how many bars (10–400) are used for calculating the PoC. Precise PoC Calculation — Volume aggregation across 25 bins to identify the exact volume peak. Dynamic Channel Visualization — PoC bands above and below the central level to indicate equilibrium tolerance. Adaptive Candle Coloring — - Neutral → price inside PoC channel. Gray - Bullish → price above PoC channel. Blue 🔵 - Bearish → price below PoC channel. Orange 🟠 Automatic Volume Labeling — Displays total volume at the active PoC level for quick reference. Directional Indicators — 🔵 or 🟠 markers appear when price shifts above or below the PoC channel. Range Visualization — Plots the highest and lowest points of the active lookback window for contextual awareness. Live Updating Logic — PoC recalculates automatically every 15 bars for efficient chart performance and accuracy. 🔵 HOW TO USE Volume Anchoring — Use PoC as a reference for where the majority of volume occurred; price often reacts to or consolidates around this level. Trend Confirmation — Sustained price movement away from PoC channel may signal developing directional imbalance. Value Tracking — Watch the shifting of PoC across time to identify where fair value migrates during market evolution. Equilibrium Mapping — When price hovers around PoC, the market is balanced; when it departs, a new value zone may form. Combine With Volume Profiles — Use alongside profile tools for higher-resolution analysis of institutional activity. 🔵 CONCLUSION Point of Control provides a pure, volume-centric view of market balance by pinpointing where most transactions occurred within any chosen range. It delivers a clean and efficient visualization of fair value zones—helping traders track the heartbeat of market participation, recognize dominant liquidity areas, and stay aligned with where true market interest resides.
Indikator Pine Script®
oleh BigBeluga
14
EMA Distance BandsEMA Distance Bands Use EMA Distance Bands to visualize historical price extension directly on your chart by translating percentage-based distance statistics into multi-tier adaptive price envelopes around a reference EMA. These bands represent normal vs extreme price behavior relative to a higher-timeframe EMA, giving traders quantitative context about how far price is stretched from its structural mean. Timeframe-agnostic, the indicator works across all chart and EMA timeframe combinations, making it versatile for scalping, intraday, and swing trading. ✂️ What It Does - Plots a selectable EMA from any timeframe on your chart - Measures percentage distance between price and the EMA - Computes average and standard deviation of this distance over a configurable lookback - Converts these statistics into price-based bands: - 0.5σ band → minor deviations / “normal range” - 1σ band → typical daily/weekly variation - 2σ band → rare/extreme price extensions - Shades the “normal range” for visual clarity Bitcoin Daily Chart vs Weekly EMA 🔦Intention: EMA Distance Bands are designed to answer the question: “Where does price normally trade, and how extreme is the current deviation from the structural mean?” Unlike a simple moving average envelope, the bands quantify rarity, giving traders a clear sense of statistical stretch. ✨ Key Features: - Timeframe-agnostic EMA reference - Multi-tier bands (0.5σ, 1σ, 2σ) for granular context - Dynamic shading of normal range - Numeric insight: compare current distance vs historical standard deviation - Non-repainting, fully historical - Clean on-chart visualization - Works across all instruments and chart timeframes 📚 How to Read It Price inside 1σ band → normal, statistically expected range Price between 1σ and 2σ → stretched, may revert Price outside 2σ band → extreme, rare price extensions Compare with EMA Distance Index oscillator to see exact numeric distance relative to current bands Bitcoin 1h chart vs 4h EMA 📈 Best Practices - EMA timeframe should be equal to or higher than chart timeframe - Use for context, risk framing, and identifying stretched conditions - Combine with chart structure, VWAP, or volume for discretionary signals - Adjust lookback based on chart timeframe for meaningful bands 🎹 Common Use Cases - Identify mean-reversion opportunities - Detect intraday or swing overextensions - Evaluate trend pullbacks vs session/daily context - Risk framing and stop placement - Volatility regime awareness 🛠️ Settings Overview - EMA Length – period of the reference EMA - EMA Timeframe – timeframe of EMA calculation (scalable across charts) - Lookback Bars – number of chart bars used to compute average and standard deviation 🖥️ Why This Is Powerful This enhanced band system turns your EMA reference into a quantitative envelope, showing where price usually is, how extreme it is currently, and providing numeric and visual context in one tool. Paired with the EMA Distance Index oscillator, it forms a complete framework for assessing price location and statistical stretch across any timeframe. ⚠️ Disclaimer: EMA Distance Bands are intended for contextual and statistical analysis of price relative to a selected EMA. The bands illustrate typical ranges and extreme deviations, but do not constitute trade recommendations. Market conditions can change rapidly, and historical patterns or standard deviations do not predict future price movements. Users are responsible for their own decisions, including risk management, trade execution, and capital allocation. The developer is not liable for any losses or damages resulting from the use of this indicator. By using this tool, you accept full responsibility for your trading actions. If you'd like access or have any questions, feel free to reach out to me directly via DM.
Indikator Pine Script®
oleh largepetrol
Adaptive Strength Overlay (MTF) [BackQuant]Adaptive Strength Overlay (MTF) A multi-timeframe RSI strength visualizer that projects oscillator “pressure” directly onto price using adaptive gradient fills between percent bands. Built to make strength, exhaustion, and regime context readable at a glance, without needing to stare at a separate oscillator panel. Mean-Reversion mode example What this indicator does This indicator converts RSI strength into a chart overlay that reacts to momentum and extremes, then visualizes it as colored “pressure zones” around price. Instead of plotting RSI in a sub-window, it: Builds 1 to 3 symmetric percent bands above and below price. Computes RSI strength on up to 3 different timeframes (MTF). Smooths RSI with your selected moving average type. Maps RSI values into discrete transparency “buckets”. Fills between the bands with a gradient whose opacity reflects strength or exhaustion. Displays a compact RSI table for all enabled timeframes. Provides alert conditions for extremes and midline shifts on each timeframe. The result is an overlay that looks like a dynamic envelope. When strength rises, the envelope “lights up” in the direction of the move. When strength becomes stretched, the outer zones become visually prominent. Core idea: “Strength as an overlay” RSI is normally interpreted in a separate oscillator panel. That makes context-switching slow: You check price action. You look down at RSI. You mentally translate RSI into risk or trend bias. This script removes that translation step by projecting strength directly onto the price area, using band fills as a visual language: More visible fill = stronger strength or more extreme condition (depending on mode). Less visible fill = weak strength or neutral state. Two operating modes 1) Trend mode Trend mode emphasizes strength aligned with direction: When RSI is strong on the upside, upper bands become more visible. When RSI is strong on the downside, lower bands become more visible. Neutral RSI fades, so the chart de-clutters during chop. Use Trend mode when: You want a clean trend-following overlay. You want to quickly see which timeframe(s) are powering the move. You want to filter entries to moments when strength confirms direction. 2) Mean-Reversion mode Mean-Reversion mode flips the emphasis to highlight exhaustion against the move : Upper extremes become a “potential exhaustion” cue. Lower extremes become a “potential exhaustion” cue. The overlay is tuned to make stretched conditions obvious. This is not an automatic “short overbought / long oversold” system. It is a visualization mode that makes “extended” conditions stand out faster, especially when multiple timeframes align. How the bands work (Percent Bands) The indicator constructs up to three symmetric envelopes around price: Band 1: percent1 scaled by scale Band 2: percent2 scaled by scale (optional) Band 3: percent3 scaled by scale (optional) The percent bands are simple deviations from the selected price source: Upper = price * (1 + (percent * scaling)/100) Lower = price * (1 - (percent * scaling)/100) Why this matters: It anchors “strength visualization” to meaningful price distance. It makes the overlay comparable across assets because it’s percent-based. It gives you a consistent spatial frame for reading momentum versus extension. Multi-timeframe engine (MTF) The script runs the same strength calculation on up to three timeframes: Timeframe 1 uses the chart timeframe by default (empty string input). Timeframe 2 is optional and defaults to Daily. Timeframe 3 is optional and defaults to Weekly. Each timeframe has: Its own RSI period (len, len2, len3). Its own smoothing length (slen, slen2, slen3). The same smoothing type selection (EMA, HMA, etc). This creates a layered view: TF1 often reflects tactical pressure (entries/exits). TF2 reflects structural pressure (swing context). TF3 reflects macro bias (regime context). When multiple timeframes agree, the fills stack and the overlay becomes visually louder. When they disagree, the overlay looks mixed or muted, which is exactly the point. Smoothing options (why so many) Raw RSI can be noisy. This script lets you smooth RSI with multiple MA types, which changes how “responsive” the overlay feels: EMA/RMA smooth without lagging as hard as SMA. HMA responds faster but can be twitchy. LINREG can feel more “structural”. ALMA and T3/TEMA provide heavier smoothing profiles with different lag characteristics. This isn’t cosmetic. Your smoothing choice affects: How early the overlay “lights up” in Trend mode. How long extremes remain highlighted in Mean-Reversion mode. How often fills flicker in chop. Strength mapping (the transparency buckets) Instead of mapping RSI to a continuous color scale, the script uses a discrete transparency ladder. That creates a clean, readable visual that avoids constant flickering. The logic assigns two transparency values per timeframe: Upper-side transparency responds to lower RSI zones (weak upside strength). Lower-side transparency responds to higher RSI zones (strong upside strength). Then the script uses those transparencies differently depending on mode: Trend mode shows “strength aligned with direction”. Mean-Reversion mode swaps the emphasis so “extremes” stand out as potential stretch. You can think of it as: Trend mode highlights continuation strength. Mean-Reversion mode highlights potential exhaustion. Fill stacking (how the overlay is built) The overlay uses layered fills: Fill from price to Band 1 Fill from Band 1 to Band 2 (if enabled) Fill from Band 2 to Band 3 (if enabled) Upper side uses the negative color (typically red) and lower side uses the positive color (typically green), because upper bands represent “above price” space and lower bands represent “below price” space. The intensity is controlled by the computed transparency per timeframe and selected mode. Important behavior: Disabling Band 2 or Band 3 can change how the stacked fills look, because you are removing fill segments. If you want a clean look, run only Band 1. If you want a “regime heat” look, run Bands 1–3 with higher scaling. Table (MTF RSI dashboard) A compact table prints RSI values for each configured timeframe: Row labels show TF. Values show the smoothed RSI output that drives the overlay. Use it for quick confirmation: If overlay looks strong but table RSI is neutral, your band settings might be too tight. If TF3 RSI is extreme while TF1 is neutral, you are likely in a macro stretched regime with local consolidation. Alerts (built-in) Alerts are provided for each timeframe separately, covering: Entering upper extreme (cross above 70) Exiting upper extreme (cross below 70) Entering lower extreme (cross below 30) Exiting lower extreme (cross above 30) Bullish midline cross (cross above 50) Bearish midline cross (cross below 50) This enables workflows like: Notify when TF2 enters extreme, then wait for TF1 mean-reversion confirmation. Notify when TF3 crosses midline, then only take TF1 trend setups in that direction. How to use it (practical reads) Trend mode reads Strong continuation: TF1 and TF2 fills become clearly visible on the same side. Healthy pullback: TF1 fades but TF2 stays visible, suggesting underlying structure remains strong. Chop warning: fills alternate or remain mostly invisible, indicating neutral strength. Mean-Reversion mode reads Exhaustion zones: outer fills become prominent near the extremes, signaling stretched conditions. Compression after extreme: fill fades while price stabilizes, suggesting “cooling off” rather than immediate reversal. Multi-TF stretch: TF2 and TF3 extremes together often mark higher significance zones. Recommended setup presets Preset A: Clean trend overlay Mode: Trend Bands: only Band 1 Scale: 1–2 Smoothing: EMA, moderate slen (6–10) TF2: Daily on intraday charts Preset B: Regime and exhaustion mapper Mode: Mean-Reversion Bands: Bands 1–3 Scale: 2–4 Smoothing: T3 or RMA, slightly higher slen TF2: Daily, TF3: Weekly Limitations This is a strength visualization tool, not a full entry/exit system. Percent bands are not volatility-adjusted, they are distance frames. In very high vol conditions, you may need higher band percentages or higher scaling. MTF values update on their own timeframe closes, so higher timeframes will step rather than update every bar.
Indikator Pine Script®
oleh BackQuant
ATR Bands (MA Distance)ATR Bands (MA Distance) plots volatility-based bands at a multiple of ATR away from a selected moving average. Unlike percentage envelopes or standard deviation bands, this indicator measures distance from the moving average using ATR, representing the market’s normal “breathing range” rather than statistical probability. Key Features The center line is a selectable moving average (EMA, SMA, RMA/Wilder, or WMA). Upper and lower bands are calculated as: Moving Average ± ATR × Multiplier Band width automatically adapts to changing market volatility. Designed for consistent use across different markets and timeframes without parameter re-optimization. Non-repainting: all values are calculated only from confirmed historical bars. Intended Use ATR Bands (MA Distance) is best used as a context and preparation tool , not as a direct entry or exit signal. Typical use cases include: Identifying areas where price is extended relative to its recent volatility. Visualizing normal vs. stretched price distance from the moving average. Supporting range-based analysis or trade preparation when combined with other indicators (e.g., oscillators). Important Notes / How NOT to Use This indicator does NOT generate buy or sell signals by itself . Touching or crossing a band does not imply an automatic reversal. In strong trending markets, price may stay outside the bands for extended periods. ATR Bands should not be interpreted as overbought/oversold levels on their own. This indicator does NOT repaint. Once a bar is closed, its values will not change. For best results: Use ATR Bands as a preparation zone, then wait for confirmation from your own entry logic. Disable or ignore band-based mean-reversion ideas during strong trend conditions. Concept Summary (Short) ATR Bands (MA Distance) visualize how far price has moved from its moving average in terms of volatility, without repainting and without relying on percentage deviation or statistical assumptions. Optional Short Description (Preview) Volatility-based, non-repainting ATR bands plotted at a distance from a moving average. Designed for market context and trade preparation — not standalone signals.
Indikator Pine Script®
oleh SunnySpots
CUSUM Volatility BreakoutCUSUM Volatility Breakout A statistical trend-detection and volatility-breakout indicator that identifies subtle momentum shifts earlier than traditional tools. OVERVIEW The CUSUM control chart is a statistical tool designed to detect small, gradual shifts from a target value. In trading, it helps identify the early stages of a trend, giving traders a heads-up before momentum becomes obvious on standard price charts. By spotting these subtle movements, the CUSUM Volatility Breakout indicator (CUSUM VB) can highlight potential breakout opportunities earlier than traditional indicators. In other words, a statistical trend detection & breakout indicator. Copyright © 2025 CoinOperator HOW IT WORKS CUSUM VB uses a combination of differenced price series, volume normalization, and dynamic control limits: CUSUM Principle: Tracks cumulative deviations of price from a zero reference. Signals occur when cumulative deviations exceed a control limit shown on the chart and clears any enabled filters. Adaptive Volatility: H adjusts automatically based on short- vs long-term ATR ratios, allowing faster detection during volatile periods and reduced false signals in calm markets. Volume Weighting (optional): Amplifies price CUSUM values during high-volume bars to prioritize market participation strength. ATR Confirmation (optional): Ensures breakouts are accompanied by expanded volatility. Bollinger Band Squeeze Integration (optional): Confirms trend breakouts by detecting volatility contraction and release shown on the chart as triangles. Signals: Arrows on the price chart mark the bars where trades are actually filled, based on conditions detected on the prior signal bar. Long Entry: Confirmed positive CUSUM breach (price & volume) with BB breakout (signal bar). Short Entry: Confirmed negative CUSUM breach (price & volume) with BB breakout (signal bar). Exit Signals: Triggered automatically by opposite-side signals. Alerts, when created, fire on the bars where fills occur. CHART COMPONENTS CUSUM Upper Price (CU Price) and CUSUM Lower Price (CL Price) are green/red circles for confirmed signals. ● Rapid upward accumulation of CU Price indicates a developing bullish trend. ● Rapid downward accumulation of CL Price indicates a developing bearish trend. Decision/Control limits (UCL/LCL, red) Zero line (reference for the differenced price series baseline) Optional BB triangles and volume CUSUM SETUP AND CONFIGURATION Differenced Price Series Differenced Price Length and Lag Increase differencing lag or window length → Increases variance of residuals → Wider control limits (UCL/LCL) → Slower to trigger. Decrease lag or window → Tighter limits, more responsive to short-term regime shifts. CUSUM Parameters Volume-Weighted CUSUM NOTE : Uses price length if 'Confirm Price with Volume' is disabled, otherwise will use volume length. Amplifies CUSUM price responses during high-volume bars and reduces them during low-volume bars. This links trend detection to market participation strength. Volume-Weighted CUSUM doesn’t replace price confirmation with volume; it modulates it by volume intensity, amplifying price signals when participation is strong and suppressing them when weak. Recommended when analyzing assets with consistent volume patterns (e.g., stocks, major futures). Disable for low-liquidity or irregular-volume instruments (e.g., crypto pairs, small-cap stocks). ATR Confirmation Enable this feature to confirm CUSUM signals only when price deviations are accompanied by higher-than-normal volatility. The indicator compares current ATR to a smoothed ATR to detect volatility expansion. This helps distinguish true breakouts from low-volatility noise and reduces false signals during quiet periods. Adjust the ATR lookback length, smoothing length, and expansion factor to control sensitivity. Rule of thumb: ATR Length ≈ 0.5 × differenced price length to 1.5 × differenced price length gives balanced sensitivity. ATR Smoothing 5–10 bars. ATR Expansion 5% to 50%. CUSUM Input Mode Select how CUSUM processes differenced price and log-normalized volume — either directly (Txfrm Data) or as deviations from a short-term EMA baseline (Residuals): Txfrm Data = transformed input: differenced price & log-normalized volume as input for CUSUM (larger swings, more frequent control limit breaches) Residuals = deviation from short-term EMA baseline (smaller swings, fewer control limit breaches, but higher signal quality). Residual EMA Length: Defines how quickly the residual baseline adapts to recent differenced price moves. Shorter = more reactive; longer = smoother baseline. Keep EMA length moderate; over-smoothing can distort timing. Control Sensitivity (K) Increase K → Less sensitive → CUSUM accumulates slower → Fewer signals, captures only major trends. Decrease K → More sensitive → CUSUM accumulates faster → More signals, captures minor swings too. Reset Mode : Method of resetting CUSUM values. Immediate Reset: Reset both immediately after any signal breach. Traditional SPC. Opposite-Side Reset: Reset only the opposite side when a valid signal fires. Best for ongoing trend tracking. Decay Reset: Gradually reduce CUSUM values toward zero with a decay factor each bar. Maintains trend memory but allows slow “forgetting.” Threshold Reset: Reset only if CUSUM returns below a small threshold (10 % of H). Filters noise without full wipe. No Reset / Continuous: Never reset; instead track running totals. Long-term cumulative bias measurement. Conflict Handling : Method of handling conflicting signals. Ignore Both: Discards both when overlap occurs. Prioritize Latest: Chooses the direction implied by the most recent close. Prioritize Stronger: Compares absolute magnitudes of CU Price vs CL Price. Average Resolve: Looks at the difference; small overlap → ignore, otherwise pick direction by sign. Sequential Confirm: Requires N consecutive same-direction signals before confirmation. Volume Parameters (Optional) Amplification Factor Adjusts volume sensitivity and effectively rescales the log series of volume to a comparable magnitude with price changes. Since price and volume are normalized in a compatible way, the amplification factor is used instead of independent K and H values for volume. Bollinger Bands (Optional) Lookback Synchronization BB Lookback (for CUSUM): Number of bars that define a window for the BB signal to look back for the CUSUM signal. CUSUM Lookback (for BB): Number of bars that define a window for the CUSUM signal to look back for the BB signal. Both can be enabled for stricter alignment. Relationship Between K, H, ARL₀ and ARL₁ H (max) is usually the only H you need to adjust. With everything else being constant, increasing either K or H (max) generally increases both ARL₀ and ARL₁ : higher thresholds reduce false alarms but slow detection, and lower thresholds do the opposite. Increase Min Target ARL ratio → ARL₀ increases (safer, fewer false alarms) ARL₁ decreases or stays small (faster detection) Control limits slightly expand to achieve separation Strategy becomes more selective and stable Decrease Min Target ARL ratio → ARL₀ decreases (more false alarms tolerated) ARL₁ increases (slower detection tolerated) Control limits tighten Strategy becomes more sensitive but lower quality The ARL Ratio of ARL₀ / ARL₁ is typically between 3 and 8. This implies you want your ARL₀ (false-alarm interval) ≈ 'Min Target ARL ratio' × differenced price length window. Example: "Min Target ARL ratio = 4.0" ⇒ implies you want your ARL₀ (false-alarm interval) ≈ 4 × differenced price length. Assume price length = 50 (typical differencing window). ARL ratio = 4.0 → target ARL = 4 × 50 = 200 bars. ● On a 6-hour chart (≈4 bars/day) → ~50 days between expected false alarms (on average). ● On a daily chart → ~200 trading days between false alarms (very conservative). ARL ratio = 8.0 → target ARL = 400 bars → twice as infrequent signals vs ratio=4. ARL ratio = 2.0 → target ARL = 100 bars → about half the inter-signal interval. Another way to think about it: probability of a false alarm on any bar ≈ 1 / target ARL. If you want ~1% of bars producing alarms, target ARL ≈ 100. QUICK START Start with the defaults. Set price series → length/order/lag Configure CUSUM thresholds → K, H min/max 1. Adjust the price differencing lag/window. 2. Verify that it captures real price inflection points without overreacting to bar noise. Enable optional filters → Volume, ATR, BB The optional Bollinger Bands squeeze usually works best if used with CUSUM Input Mode = Txfrm Data. Monitor CUSUM chart → CU Price, CL Price, thresholds, zero line Act on signals → data window / chart triangles Adjust sensitivity → H (max), K, lengths Monitor ARL ratio and CUSUM behavior for fine-tuning Note : When you’ve finalized the length, lag, and order of the Price Difference, as well as the Ln(Vol) Series of “Confirm Price with Volume” if enabled, then pass both through the Augmented Dickey–Fuller (ADF) mean reversion test to ensure they are stationary, i.e., mean reverting. You can find a ready-made indicator for such use at . Many thanks to tbtkg for this indicator. SUMMARY CUSUM VB combines CUSUM statistical control, volatility-adaptive thresholds, volume weighting, and optional BB breakout confirmation to provide robust, actionable signals across a wide variety of trading instruments. Why traders use it : Fast detection of shifts, reduced false alarms, versatile across markets. Ideal for : Futures (continuous contracts), forex, crypto, stocks, ETFs, and commodity/index CFDs, especially where: ● Price and volume data exist ● Breakouts and volatility shifts are tradable ● There’s enough liquidity for meaningful signals Visualization : Upper/lower CUSUM circles, UCL/LCL thresholds, optional highlight traded background, optional volume and BB overlays on the chart, optional entry/exit labels on the price chart, as well as entry/exit signals in the data window. Alerts : For entry/exit labels when trades are actually filled. CUSUM VB is designed for traders who want statistically grounded trend detection with configurable sensitivity, visual clarity, and multi-market versatility. DISCLAIMER This software and documentation are provided “as is” without any warranties of any kind, express or implied. CoinOperator assumes no responsibility or liability for any errors, omissions, or losses arising from the use or interpretation of this software or its outputs. Trading and investing carry inherent risks, and users are solely responsible for their own decisions and results.
Indikator Pine Script®
oleh CoinOperator
4
BBands + Overbought/Oversold MarkersAdvanced Bollinger Bands indicator with overbought/oversold signals, automatic squeeze detection, and multi-timeframe (MTF) capabilities. Retains all functions of the original Bollinger Bands indicator from TradingView with a few added features: Overbought/Oversold Markers: Visual signals when price opens and closes outside the bands 🔴 Red Highlight & Arrow → Price opens & closes above the upper BB (potential overbought/excess momentum). 🟢 Green Highlight & Arrow → Price opens & closes below the lower BB (potential oversold/reversal). Squeeze Detection: Automatically highlights when bandwidth reaches its lowest point (narrowest BB width) in the lookback period, signalling potential breakout zones Multi-Timeframe Bands: Display Bollinger Bands from any timeframe on your current chart (e.g., weekly bands on a daily chart), including markers and squeeze zones Dual Rendering MTF Modes: Choose between traditional plots (unlimited history) or smooth line drawing (~125-165 MTF bars of history) Built-in Alerts: Set alerts for overbought conditions, oversold conditions, squeeze detection, or any combination Fully Customizable: Adjust MA type (SMA/EMA/RMA/WMA/VWMA), standard deviation multiplier, colors, and marker styles Perfect for: Swing traders, MTF analysis, volatility-based entries, and identifying consolidation/expansion cycles.
Indikator Pine Script®
oleh CryptoPl3be
BB Squeeze - HighQToolsBBW Squeeze — HighQTools As always, if anyone has any tips or additional features they'd like to see, feel free to reach out! Overview The BBW Percentile Squeeze highlights periods of exceptionally compressed volatility by measuring Bollinger Band Width (BBW) and ranking it within a rolling historical percentile. When BBW falls into the lowest portion of its own distribution, price is statistically “tight” relative to recent history—a condition that often precedes volatility expansion. Instead of plotting an oscillator in a separate pane, this tool expresses information directly on the price chart by changing bar colors during squeeze conditions, keeping charts clean and execution-focused. How It Works Standard Bollinger Bands are calculated using a configurable length and standard deviation. Band width is normalized and evaluated against a rolling lookback window. The current width is converted into a percentile rank (0–100): Lower percentile = tighter volatility Higher percentile = expanded volatility When the percentile drops below the user-defined threshold, the market is considered to be in a squeeze. An optional RTH-only mode allows the percentile calculation to consider Regular Trading Hours bars only, which is especially useful for futures traders who want to ignore overnight volatility distortions. Visual Signals Squeeze Bars Bars are recolored when BBW percentile falls below the selected threshold, indicating extreme compression. Release Bar (optional) The first bar exiting the squeeze can be highlighted separately, marking the resolution of compression. No oscillator, no bands, no shapes—only context applied directly to price. How to Use It The squeeze itself is not a trade signal. Squeeze conditions indicate stored energy—expect range expansion, not direction. Focus on: Market structure Higher-timeframe context Volume, delta, or acceptance/rejection The release from squeeze often provides the best opportunity, especially when aligned with directional bias or structural breaks. For best results, use this tool as a context filter alongside execution setups rather than as a standalone entry signal. Recommended Settings BB Length: 10 Std Dev: 2.0 Percentile Lookback: 200–300 bars Squeeze Threshold: 5-10 percentile RTH-only: Enabled for index futures Disclaimer This indicator is designed to provide context, not predictions. Always combine volatility information with sound risk management and a complete trading plan.
Indikator Pine Script®
oleh HighQTools
Market Acceptance Envelope [Interakktive]The Market Acceptance Envelope (MAE) is a diagnostic tool that shows where price statistically belongs — not where it might go. Unlike traditional bands that expand with volatility, MAE expands with acceptance: regions where price rotates comfortably, efficiency drops, and the market agrees on fair value. This is the anti-Bollinger thesis: bands should represent where price IS accepted, not where it MIGHT reach based on standard deviation. █ USAGE The filled corridor represents the current acceptance zone — where price has demonstrated rotational behavior with low directional efficiency. When price is inside the corridor, it's "home." When outside, it's exploring territory the market hasn't yet accepted. For discretionary traders, MAE provides instant context: "Is price where it belongs, or is it extended?" For systematic traders, the exported values (confidence, asymmetry, position) can inform position sizing and filter logic. █ ACCEPTANCE CENTROID Unlike traditional bands centered on a moving average, MAE uses an Acceptance Centroid — a time-weighted price level where acceptance behavior concentrates. The centroid is calculated by weighting price by: • Inverse efficiency (low efficiency = high acceptance) • Volatility stability (stable vol = higher weight) • Dwell factor (time spent near level) This means the centroid drifts toward where price actually rotates, not simply where it averages. █ ASYMMETRIC BOUNDARIES MAE calculates upper and lower boundaries independently. Markets rarely treat up and down equally — during uptrends, the upper boundary may be wider (more accepted upside exploration), while the lower boundary stays tight (quick rejection of dips). This asymmetry is visible on the chart and exported as a metric (-1 to +1). █ CONFIDENCE-BASED VISIBILITY The corridor's opacity reflects acceptance confidence: • High confidence → clearly visible corridor (price is in accepted rotation) • Low confidence → faded corridor (trending/directional market, acceptance not established) When the corridor fades, it's telling you: "Acceptance hasn't been earned here yet." █ WHAT THIS INDICATOR IS • A diagnostic acceptance envelope showing where price statistically belongs • Asymmetric by design — upper and lower calculated independently • Confidence-weighted visibility — fades when acceptance is not earned • Non-repainting — uses closed-bar data only █ WHAT THIS INDICATOR IS NOT • NOT Bollinger Bands (no standard deviation around a mean) • NOT Keltner Channels (no ATR-scaled envelope) • NOT a signal generator — no touches = signals philosophy • NO arrows, NO entries/exits, NO buy/sell recommendations █ HOW IT WORKS MAE uses an acceptance-weighted calculation approach: 1. ACCEPTANCE WEIGHT Each bar receives a weight based on: • Efficiency: (1 - efficiency) — low efficiency = rotational = high acceptance • Volatility Stability: stable vol environment = higher weight • Dwell Factor: price staying near central tendency = higher weight 2. ACCEPTANCE CENTROID Weighted average of price using acceptance weights: centroid = Σ(price × weight) / Σ(weight) Smoothed adaptively — faster during drift, slower when stable. 3. ASYMMETRIC BOUNDARIES Upper and lower distances calculated separately: • rngUp = acceptance-weighted average of (price - centroid) when price > centroid • rngDn = acceptance-weighted average of (centroid - price) when price < centroid 4. CONFIDENCE SCORE Composite of average acceptance weight, volatility stability, and centroid stability. Maps to corridor opacity: high confidence = visible, low confidence = faded. █ SETTINGS Market Acceptance Envelope — Core • Acceptance Lookback (20): Bars to evaluate for acceptance conditions. Higher = smoother, slower response. • Preset (Swing): Scalper = tight/fast, Swing = balanced, Position = wide/stable. • Envelope Sensitivity (1.0): Width multiplier. Higher = wider corridor. Market Acceptance Envelope — Visuals • Show Corridor (true): Display the acceptance corridor. • Show Centroid (false): Display the acceptance centroid line. Market Acceptance Envelope — Data Window • Show Data Window Values (false): Export MAE metrics for external use. █ EXPORTED VALUES When Data Window is enabled: • mae_upper: Upper boundary value • mae_lower: Lower boundary value • mae_centroid: Acceptance centroid value • mae_width: Corridor width (upper - lower) • mae_asymmetry: Asymmetry ratio (-1 to +1, negative = lower wider) • mae_confidence: Acceptance confidence (0-100) • mae_position: Price position (-1 = below, 0 = inside, +1 = above) █ SUITABLE MARKETS Works on all markets: Stocks, Futures, Forex, Crypto, Indices. Works on all timeframes. Higher timeframes show more stable acceptance zones. █ DISCLAIMER This indicator is for educational and informational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management. This is a diagnostic tool — it provides context, not signals.
Indikator Pine Script®
oleh Interakktive
2
Hurst-Optimized Adaptive Channel [Kodexius]Hurst-Optimized Adaptive Channel (HOAC) is a regime-aware channel indicator that continuously adapts its centerline and volatility bands based on the market’s current behavior. Instead of using a single fixed channel model, HOAC evaluates whether price action is behaving more like a trend-following environment or a mean-reverting environment, then automatically selects the most suitable channel structure. At the core of the engine is a robust Hurst Exponent estimation using R/S (Rescaled Range) analysis. The Hurst value is smoothed and compared against user-defined thresholds to classify the market regime. In trending regimes, the script emphasizes stability by favoring a slower, smoother channel when it proves more accurate over time. In mean-reversion regimes, it deliberately prioritizes a faster model to react sooner to reversion opportunities, similar in spirit to how traders use Bollinger-style behavior. The result is a clean, professional adaptive channel with inner and outer bands, dynamic gradient fills, and an optional mean-reversion signal layer. A minimalist dashboard summarizes the detected regime, the current Hurst reading, and which internal model is currently preferred. 🔹 Features 🔸 Robust Regime Detection via Hurst Exponent (R/S Analysis) HOAC uses a robust Hurst Exponent estimate derived from log returns and Rescaled Range analysis. The Hurst value acts as a behavioral filter: - H > Trend Start threshold suggests trend persistence and directional continuation. - H < Mean Reversion threshold suggests anti-persistence and a higher likelihood of reverting toward a central value. Values between thresholds are treated as Neutral, allowing the channel to remain adaptive without forcing a hard bias. This regime framework is designed to make the channel selection context-aware rather than purely reactive to recent volatility. 🔸 Dual Channel Engine (Fast vs Slow Models) Instead of relying on one fixed channel, HOAC computes two independent channel candidates: Fast model: shorter WMA basis and standard deviation window, intended to respond quickly and fit more reactive environments. Slow model: longer WMA basis and standard deviation window, intended to reduce noise and better represent sustained directional flow. Each model produces: - A midline (basis) - Outer bands (wider deviation) - Inner bands (tighter deviation) This structure gives you a clear core zone and an outer envelope that better represents volatility expansion. 🔸 Rolling Optimization Memory (Model Selection by Error) HOAC includes an internal optimization layer that continuously measures how well each model fits current price action. On every bar, each model’s absolute deviation from the basis is recorded into a rolling memory window. The script then compares total accumulated error between fast and slow models and prefers the one with lower recent error. This approach does not attempt curve fitting on multiple parameters. It focuses on a simple, interpretable metric: “Which model has tracked price more accurately over the last X bars?” Additionally: If the regime is Mean Reversion, the script explicitly prioritizes the fast model, ensuring responsiveness when reversals matter most. 🔸 Optional Output Smoothing (User-Selectable) The final selected channel can be smoothed using your choice of: - SMA - EMA - HMA - RMA This affects the plotted midline and all band outputs, allowing you to tune visual stability and responsiveness without changing the underlying decision engine. 🔸 Premium Visualization Layer (Inner Core + Outer Fade) HOAC uses a layered band design: - Inner bands define the core equilibrium zone around the midline. - Outer bands define an extended volatility envelope for extremes. Gradient fills and line styling help separate the core from the extremes while staying visually clean. The midline includes a subtle glow effect for clarity. 🔸 Adaptive Bar Tinting Strength (Regime Intensity) Bar coloring dynamically adjusts transparency based on how far the Hurst value is from 0.5. When market behavior is more decisively trending or mean-reverting, the tint becomes more pronounced. When behavior is closer to random, the tint becomes more subtle. 🔸 Mean-Reversion Signal Layer Mean-reversion signals are enabled when the environment is not classified as Trending: - Buy when price crosses back above the lower outer band - Sell when price crosses back below the upper outer band This is intentionally a “return to channel” logic rather than a breakout logic, aligning signals with mean-reversion behavior and avoiding signals in strongly trending regimes by default. 🔸 Minimalist Dashboard (HUD) A compact table displays: - Current regime classification - Smoothed Hurst value - Which model is currently preferred (Fast or Slow) - Trend flow direction (based on midline slope) 🔹 Calculations 1) Robust Hurst Exponent (R/S Analysis) The script estimates Hurst using a Rescaled Range approach on log returns. It builds a returns array, computes mean, cumulative deviation range (R), standard deviation (S), then converts RS into a Hurst exponent. calc_robust_hurst(int length) => float r = math.log(close / close ) float returns = array.new_float(length) for i = 0 to length - 1 array.set(returns, i, r ) float mean = array.avg(returns) float cumDev = 0.0 float maxCD = -1.0e10 float minCD = 1.0e10 float sumSqDiff = 0.0 for i = 0 to length - 1 float val = array.get(returns, i) sumSqDiff += math.pow(val - mean, 2) cumDev += (val - mean) if cumDev > maxCD maxCD := cumDev if cumDev < minCD minCD := cumDev float R = maxCD - minCD float S = math.sqrt(sumSqDiff / length) float RS = (S == 0) ? 0.0 : (R / S) float hurst = (RS > 0) ? (math.log10(RS) / math.log10(length)) : 0.5 hurst This design avoids simplistic proxies and attempts to reflect persistence (trend tendency) vs anti-persistence (mean reversion tendency) from the underlying return structure. 2) Hurst Smoothing Raw Hurst values can be noisy, so the script applies EMA smoothing before regime decisions. float rawHurst = calc_robust_hurst(i_hurstLen) float hVal = ta.ema(rawHurst, i_smoothHurst) This stabilized hVal is the value used across regime classification, dynamic visuals, and the HUD display. 3) Regime Classification The smoothed Hurst reading is compared to user thresholds to label the environment. string regime = "NEUTRAL" if hVal > i_trendZone regime := "TRENDING" else if hVal < i_chopZone regime := "MEAN REV" Higher Hurst implies more persistence, so the indicator treats it as a trend environment. Lower Hurst implies more mean-reverting behavior, so the indicator enables MR logic and emphasizes faster adaptation. 4) Dual Channel Models (Fast and Slow) HOAC computes two candidate channel structures in parallel. Each model is a WMA basis with volatility envelopes derived from standard deviation. Inner and outer bands are created using different multipliers. Fast model (more reactive): float fastBasis = ta.wma(close, 20) float fastDev = ta.stdev(close, 20) ChannelObj fastM = ChannelObj.new(fastBasis, fastBasis + fastDev * 2.0, fastBasis - fastDev * 2.0, fastBasis + fastDev * 1.0, fastBasis - fastDev * 1.0, math.abs(close - fastBasis)) Slow model (more stable): float slowBasis = ta.wma(close, 50) float slowDev = ta.stdev(close, 50) ChannelObj slowM = ChannelObj.new(slowBasis, slowBasis + slowDev * 2.5, slowBasis - slowDev * 2.5, slowBasis + slowDev * 1.25, slowBasis - slowDev * 1.25, math.abs(close - slowBasis)) Both models store their structure in a ChannelObj type, including the instantaneous tracking error (abs(close - basis)). 5) Rolling Error Memory and Model Preference To decide which model fits current conditions better, the script stores recent errors into rolling arrays and compares cumulative error totals. var float errFast = array.new_float() var float errSlow = array.new_float() update_error(float errArr, float error, int maxLen) => errArr.unshift(error) if errArr.size() > maxLen errArr.pop() Each bar updates both error histories and computes which model has lower recent accumulated error. update_error(errFast, fastM.error, i_optLookback) update_error(errSlow, slowM.error, i_optLookback) bool preferFast = errFast.sum() < errSlow.sum() This is an interpretable optimization approach: it does not attempt to brute-force parameters, it simply prefers the model that has tracked price more closely over the last i_optLookback bars. 6) Winner Selection Logic (Regime-Aware Hybrid) The final model selection uses both regime and rolling error performance. ChannelObj winner = regime == "MEAN REV" ? fastM : (preferFast ? fastM : slowM) rawMid := winner.mid rawUp := winner.upper rawDn := winner.lower rawUpInner := winner.upper_inner rawDnInner := winner.lower_inner In Mean Reversion, the script forces the fast model to ensure responsiveness. Otherwise, it selects the lowest-error model between fast and slow. 7) Optional Output Smoothing After the winner is selected, the script optionally smooths the final channel outputs using the chosen moving average type. smooth(float src, string type, int len) => switch type "SMA" => ta.sma(src, len) "EMA" => ta.ema(src, len) "HMA" => ta.hma(src, len) "RMA" => ta.rma(src, len) => src float finalMid = i_enableSmooth ? smooth(rawMid, i_smoothType, i_smoothLen) : rawMid float finalUp = i_enableSmooth ? smooth(rawUp, i_smoothType, i_smoothLen) : rawUp float finalDn = i_enableSmooth ? smooth(rawDn, i_smoothType, i_smoothLen) : rawDn float finalUpInner = i_enableSmooth ? smooth(rawUpInner, i_smoothType, i_smoothLen) : rawUpInner float finalDnInner = i_enableSmooth ? smooth(rawDnInner, i_smoothType, i_smoothLen) : rawDnInner This preserves decision integrity since smoothing happens after model selection, not before. 8) Dynamic Visual Intensity From Hurst Transparency is derived from the distance of hVal to 0.5, so stronger behavioral regimes appear with clearer tints. int dynTrans = int(math.max(20, math.min(80, 100 - (math.abs(hVal - 0.5) * 200))))
Indikator Pine Script®
oleh UnknownUnicorn113699460