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Moving Average Adaptive RSI [BackQuant]Moving Average Adaptive RSI What this is A momentum oscillator that reshapes classic RSI into a zero-centered column plot and makes it adaptive. It builds RSI from two parts: • A sensitivity window that scans several recent bars to capture the strongest up and down impulses. • A selectable moving average that smooths those impulses before computing RSI. The output ranges roughly from −100 to +100 with 0 as the midline, with optional extra smoothing and built-in divergence detection. How it works Impulse extraction • For each bar the script inspects the last rsi_sen bars and collects upward and downward price changes versus the current price. • It keeps the maximum upward change and maximum downward change from that window, emphasizing true bursts over single-bar noise. MA-based averaging • The up and down impulse series are averaged with your chosen MA over rsi_len bars. • Supported MA types: SMA, EMA, DEMA, WMA, HMA, SMMA (RMA), TEMA. Zero-centered RSI transform • RS = UpMA ÷ DownMA, then mapped to a symmetric scale: 100 − 200 ÷ (1 + RS) . • Above 0 implies positive momentum bias. Below 0 implies negative momentum bias. Optional extra smoothing • A second smoothing pass can be applied to the final oscillator using smoothing_len and smooth_type . Toggle with “Use Extra Smoothing”. Visual encoding • The oscillator is drawn as columns around the zero line with a gradient that intensifies toward extremes. • Static bands mark 80 to 100 and −80 to −100 for extreme conditions. Key inputs and what they change • Price Source : input series for momentum. • Calculation Period (rsi_len) : primary averaging window on up and down components. Higher = smoother, slower. • Sensitivity (rsi_sen) : how many recent bars are scanned to find max impulses. Higher = more responsive to bursts. • Calculation Type (ma_type) : MA family that shapes the core behavior. HMA or DEMA is faster, SMA or SMMA is slower. • Smoothing Type and Length : optional second pass to calm noise on the final output. • UI toggles : show or hide the oscillator, candle painting, and extreme bands. Reading the oscillator • Midline cross up (0) : momentum bias turning positive. • Midline cross down (0) : momentum bias turning negative. • Positive territory : – 0 to 40: constructive but not stretched. – 40 to 80: strong momentum, continuation more likely. – Above 80: extreme risk of mean reversion grows. • Negative territory : mirror the same levels for the downside. Divergence detection The script plots four divergence types using pivot highs and lows on both price and the oscillator. Lookbacks are set by lbL and lbR . • Regular bullish : price lower low, oscillator higher low. Possible downside exhaustion. • Hidden bullish : price higher low, oscillator lower low. Bias to trend continuation up. • Regular bearish : price higher high, oscillator lower high. Possible upside exhaustion. • Hidden bearish : price lower high, oscillator higher high. Bias to trend continuation down. Labels: ℝ for regular, ℍ for hidden. Green for bullish, red for bearish. Candle coloring • Optional bar painting: green when the oscillator is above 0, red when below 0. This is for visual scanning only. Strengths • Adaptive sensitivity via a rolling impulse window that responds to genuine bursts. • Configurable MA core so you can match responsiveness to the instrument. • Zero-centered scale for simple regime reads with 0 as a clear bias line. • Built-in regular and hidden divergence mapping. • Flexible across symbols and timeframes once tuned. Limitations and cautions • Trends can remain extended. Treat extremes as context rather than automatic reversal signals. • Divergence quality depends on pivot lookbacks. Short lookbacks give more signals with more noise. Long lookbacks reduce noise but add lag. • Double smoothing can delay zero-line transitions. Balance smoothness and timeliness. Practical usage ideas • Regime filter : only take long setups from your separate method when the oscillator is above 0, shorts when below 0. • Pullback confirmation : in uptrends, look for dips that hold above 0 or turn up from 0 to 40. Reverse for downtrends. • Divergence as a heads-up : wait for a zero-line cross or a price trigger before acting on divergence. • Sensitivity tuning : start with rsi_sen 2 to 5 on faster timeframes, increase slightly on slower charts. Alerts • MA-A RSI Long : oscillator crosses above 0. • MA-A RSI Short : oscillator crosses below 0. Use these as bias or timing aids, not standalone trade commands. Settings quick reference • Calculation : Price Source, Calculation Type, Calculation Period, Sensitivity. • Smoothing : Smoothing Type, Smoothing Length, Use Extra Smoothing. • UI : Show Oscillator, Paint Candles, Show Static High and Low Levels. • Divergences : Pivot Lookback Left and Right, Div Signal Length, Show Detected Divergences. Final thoughts This tool reframes RSI by extracting strong short-term impulses and averaging them with a moving-average model of your choice, then presenting a zero-centered output for clear regime reads. Pair it with your structure, risk and execution process, and tune sensitivity and smoothing to the market you trade.
مؤشر Pine Script®
من ‎BackQuant‎
Xmoon – 3 Push Divergence – PremiumWhat the Xmoon Indicator Does and Why It’s Special The Xmoon Indicator is an advanced and unique analytical tool, built on years of trading experience, research, and development. It is not merely a combination of a few simple indicators; it is a comprehensive, intelligent system that brings together the three main pillars of trading success—strategy, risk management, and trading psychology—into a single integrated tool. Strategy • Xmoon’s core algorithm is based on the 3 Push Divergence pattern in the RSI —a pattern not offered in other indicators. Most existing tools only detect divergence between two highs or two lows, whereas Xmoon can identify three consecutive highs or three consecutive lows with a momentum mismatch, which considerably increases the statistical likelihood of a trend reversal. Risk Management • Automatically calculates the size of each step entry based on per-step capital allocation, leverage, and entry/exit prices, using precise, weighted calculations. • These multi-step calculations run in real time and are shown clearly in the Information Box for quick reading. • A Liquidity Line (risk threshold) is computed for each setup and plotted on the chart so you can see at a glance where the position would be liquidated (futures) or where the analysis is invalidated (spot). Psychology & Decision-Making • From the moment a signal is generated, Xmoon plots all key levels— step entries, risk-free levels, targets, and the liquidity line —so the trader knows from the outset: o where the profitable exit is if the market follows the analysis; o where the break-even (risk-free) exit is if the market moves against the analysis. • This approach significantly reduces stress and emotional decision-making, because both favorable and unfavorable scenarios are predefined. Logic & Workflow of the Xmoon Indicator 1️⃣ Pivot Detection and Classification Xmoon first detects price pivots on the chart and classifies them— based on the bar distance between consecutive pivot highs/lows—into four tiers: Super Minor, Minor, Mid-Major, and Major . The greater the distance between pivots, the larger and more reliable the pivot becomes—though signals are generated less frequently. 2️⃣ Detecting the 3 Push Divergence Pattern At this stage, Xmoon identifies 3 Push Divergence patterns. The pattern forms when price prints three consecutive pivots in the same direction, i.e.: • Bullish: three successive higher highs • Bearish: three successive lower lows Meanwhile, at the corresponding points on the RSI , momentum moves the other way: • Bullish case: RSI peaks step down each time — weakening buying pressure • Bearish case: RSI troughs step up each time — weakening selling pressure This repeated price–momentum disagreement three times in a row can significantly increase the likelihood of a trend reversal. 3️⃣ Plotting the Pattern and Key Levels After the pattern is detected, Xmoon draws the divergence lines and plots the following levels on the chart: • Step entry lines based on the user-defined number of steps and allocated capital. • Risk-free (break-even) lines for exits without profit or loss. • Target lines indicating minimum profit objectives. • Liquidity level (risk threshold) marking where equity would be wiped out in futures. These visuals let the trader see, at a glance, the full picture of the pattern, planned entries/exits, and the risk range. 4️⃣ Information Box After the pattern is detected, Xmoon can display an on-chart Information Box alongside each detected pattern (when enabled in the settings). It includes: • Pivot type: Super Minor, Minor, Mid-Major, or Major. • Confirmation filters: 1. Higher-timeframe trend based on the 200-period moving average (MA200). 2. Higher-timeframe overbought/oversold status based on RSI. • Suggested entry size: based on actual capital and leverage. This box helps the trader quickly see the pattern quality, overall market context, and the suggested position size. ℹ️ Explanation of Confirmation Filters Using these filters can increase signal accuracy. This information is built into the Xmoon indicator, so you don’t need to add any extra indicators or tools to the chart. Xmoon performs the comparisons in real time and displays the filter results in the Information Box . • Higher-timeframe trend filter: If the higher-timeframe trend based on the 200-period moving average (MA200) is bullish, buy/long signals are stronger; if it’s bearish, sell/short signals are stronger. • Higher-timeframe overbought/oversold filter: If RSI is in the overbought zone, the probability of success for sell/short signals is higher; in the oversold zone, the probability of success for buy/long signals is higher. 🧩 What are the components of the Xmoon indicator, and why are they combined? • Core strategy: trend-reversal signals via a proprietary 3 Push Divergence algorithm. • Multi-stage confirmation: higher-timeframe trend based on MA200 , plus higher-timeframe RSI overbought/oversold confirmation. • Advanced position sizing: step-based sizing and weighted averaging . • Structured exit management: risk-free levels, targets , and liquidity level. • Supports fast decision-making: all vital information at a glance. This combination turns Xmoon into a complete, practical system that has not been implemented in this integrated way in any similar tool on TradingView, and it is precisely the sum of these features in a single indicator that sets Xmoon apart from comparable tools. How to Use the Xmoon Indicator 1️⃣ Add to chart: Add the indicator to the chart of your chosen symbol. 2️⃣ Configure parameters: In Settings , adjust the following to match your strategy: • Number of Entry steps: 2 to 10 steps • Pivot type: Super Minor / Minor / Mid-Major / Major • Pattern direction: Bullish / Bearish • Display options: show lines and the Information Box • Capital per trade • Higher-timeframe filters: timeframes for Trend and RSI 3️⃣ Enable alerts: Turn on alerts to receive immediate notifications when a 3 Push Divergence pattern is detected. 4️⃣ Review the Information Box: To assess pattern strength and alignment with the market after a signal appears, check: • Pivot size: Super Minor / Minor / Mid-Major / Major (for gauging pattern strength) • Confirmation filters: 1. Whether the detected pattern aligns with the higher-timeframe trend 2. Whether the detected pattern aligns with the higher-timeframe RSI overbought/oversold condition These details help you decide whether to enter the trade. 5️⃣ Step Entries After reviewing the conditions, open your first position at Step 1 . If price moves against you and reaches the Step 2 level, open a new position there, and continue opening additional positions at each subsequent step level. Whenever price reverses from any of these levels and moves in the direction of your analysis, all open positions will move into profit . In Xmoon, the number of entry steps is fully configurable ( 2 to 10 ). Set it according to your strategy—the system automatically calculates the size of each step based on the capital you allocate. 6️⃣ Exit Management Depending on market conditions, you can choose one of the following: • ⚖️ Exit at the risk-free level: when the market is uncertain and you prefer to close at break-even. • 🎯 Exit at the target level: when price has followed your analysis and you want to realize profit. ⚠️ Liquidity Level • Spot: analysis invalidation point. • Futures: the price at which a leveraged position’s equity would be wiped out. Why the Invite-Only Version of Xmoon Is Worth Getting • Proprietary 3 Push Divergence detection and confirmation that isn’t available in the free version or generic indicators. • Automatic, precise capital and step sizing, with visual plotting of key levels from the moment a signal is issued. • Real-time market context and pattern quality shown in the Information Box—no need to switch timeframes or add extra indicators. • Risk control and psychological support by outlining predefined scenarios from start to finish of the trade. • Limited access to help prevent misuse and reduce users’ financial risk, with dedicated training before activation. • Developed through extensive backtesting and live evaluation; outcomes depend on correct use and market conditions. We sincerely hope you have successful and profitable trades. 📣 If you have any questions or need further guidance, we’ll be happy to hear from you. It’s our pleasure to assist you anytime. 🔻🔻🔻 Persian Section – بخش فارسی 🔻🔻🔻 اندیکاتور ایکسمون چه کاری انجام می‌دهد و چرا خاص است اندیکاتور ایکسمون یک ابزار تحلیلی پیشرفته و منحصربه‌فرد است که حاصل سال‌ها تجربه ترید، تحقیق و توسعه است. این اندیکاتور صرفاً ترکیب چند اندیکاتور ساده نیست، بلکه یک سیستم جامع و هوشمند است که سه رکن اصلی موفقیت در معاملات یعنی استراتژی، مدیریت سرمایه و روانشناسی معامله‌گری را در یک ابزار یکپارچه گردآورده است در بخش استراتژی * الگوریتم اصلی ایکسمون بر اساس الگوی سه‌پوش واگرایی (تری پوش دایورجنس) در آر-اِس-آی طراحی شده است؛ الگویی که در سایر اندیکاتور ها ارائه نشده است، بیشتر ابزارهای موجود تنها واگرایی بین دو قله یا دو کف را تشخیص می‌دهند، در حالی که ایکسمون توانایی شناسایی سه قله یا سه کف متوالی با تضاد مومنتوم را دارد که این موضوع از نظر آماری احتمال بازگشت روند را به‌مراتب افزایش می‌دهد در بخش مدیریت سرمایه * محاسبه خودکار حجم هر پله، بر اساس سرمایه پله ای، لوریج و قیمت‌های ورود/خروج به‌صورت دقیق و وزنی انجام می‌شود * این محاسبات پیچیده برای چندین پله به شکل لحظه‌ای انجام شده و در باکس اطلاعات به ساده‌ترین شکل نمایش داده می‌شود * خط لیکوییدیتی (حد ریسک) برای هر الگو محاسبه و روی نمودار بصورت بصری رسم می‌شود تا کاربر در یک نگاه بداند سرمایه‌اش کجا صفر می‌شود (در فیوچرز) یا تحلیلش کجا باطل می‌شود (در اسپات) در بخش روانشناسی و تصمیم‌گیری * ایکسمون از همان لحظه صدور سیگنال، تمام خطوط کلیدی (ورودی پله‌ای، ریسک‌فری، تارگت، لیکوییدیتی) را رسم می‌کند تا معامله‌گر از ابتدا بداند * اگر بازار طبق تحلیل پیش برود، خروج سودآور کجاست * اگر بازار بر خلاف تحلیل پیش برود، نقطه خروج بی‌ضرر (ریسک‌فری) کجاست * این رویکرد باعث کاهش شدید استرس و تصمیم‌گیری احساسی می‌شود، چون سناریوهای خوش‌بینانه و بدبینانه از پیش مشخص هستند ⚙️ منطق و روش کار اندیکاتور ایکسمون 1️⃣ شناسایی و طبقه‌بندی پیوت‌ها اندیکاتور ایکسمون ابتدا پیوت‌های قیمتی را روی نمودار شناسایی کرده و بر اساس فاصله‌ی کندلی بین سقف یا کف ها، آن‌ها را در چهار دسته طبقه‌بندی می‌کند : سوپر مینور، مینور، میدماژور و ماژور هرچه فاصله بین پیوت ها بیشتر باشد، پیوت بزرگ‌تر و معتبرتر است، اما سیگنال‌ها کمتر تولید می‌شوند 2️⃣ تشخیص الگوی سه‌پوش واگرایی اندیکاتور ایکسمون در این مرحله الگوهای سه‌پوش واگرایی را شناسایی می‌کند، این الگو زمانی شکل می‌گیرد که قیمت سه پیوت متوالی هم‌جهت تشکیل دهد، یعنی * حالت صعودی : سه سقف پیاپی بالاتر از قبلی * حالت نزولی : سه کف پیاپی پایین‌تر از قبلی و همزمان، در نقاط متناظر در آر-اِس-آی حرکت معکوس دیده شود، به این معنا که * حالت صعودی، قله‌های آر-اِس-آی هر بار پایین‌تر از قبلی قرار گیرند - کاهش قدرت خرید * حالت نزولی، دره‌های آر-اِس-آی هر بار بالاتر از قبلی شکل گیرند - کاهش فشار فروش این تضاد قیمت و مومنتوم، وقتی سه بار پیاپی رخ دهد، احتمال بازگشت روند را به‌شدت افزایش می‌دهد 3️⃣ ترسیم الگو و نمایش سطوح کلیدی پس از شناسایی الگو، ایکسمون خطوط واگرایی و همچنین خطوط و سطوح زیر را روی نمودار ترسیم می‌کند، این موارد شامل * 📍 خطوط ورود پله‌ای بر اساس تعداد پله و سرمایه تنظیم‌شده توسط کاربر * ⚖️ خطوط ریسک‌فری برای خروج بدون سود و زیان * 🎯 خطوط تارگت به ‌عنوان سطوح حداقل سود * 🛡 سطح لیکوییدیتی (حد ریسک) برای مشخص‌کردن نقطه صفر شدن سرمایه در معاملات فیوچرز این ترسیمات باعث می‌شود معامله‌گر در یک نگاه تصویر کامل از الگو، سطوح ورود و خروج و محدوده ریسک داشته باشد 4️⃣ باکس اطلاعات پس از شناسایی الگو، اندیکاتور ایکسمون یک باکس اطلاعات تکمیلی در کنار هر الگو نمایش می‌دهد، البته با فعال‌سازی گزینه مربوطه در تنظیمات، باکس اطلاعات در کنار الگو نمایش داده می‌شود و شامل موارد زیر می‌باشد * 🏷 نوع پیوت : سوپر مینور، مینور، میدماژور یا ماژور * 📋 فیلترهای تأییدی یک - جهت روند در تایم‌فریم بالاتر بر اساس میانگین متحرک دویست دو - وضعیت اشباع خرید/فروش در تایم‌فریم بالاتر بر اساس اندیکاتور آر-اِس-آی * 📊 حجم پیشنهادی ورود : بر اساس سرمایه واقعی و لوریج این باکس به معامله‌گر کمک می‌کند در یک نگاه کیفیت الگو، شرایط کلی بازار و حجم پیشنهادی ورود را بداند توضیح درباره فیلترهای تأییدی : استفاده از این فیلترها می‌تواند دقت سیگنال‌ها را افزایش دهد. این اطلاعات در اندیکاتور ایکسمون موجود است و نیازی نیست اندیکاتور یا ابزار اضافه دیگری به چارت اضافه کنید. ایکسمون مقایسه ها را در لحظه انجام میدهد و نتیجه فیلترها را در باکس اطلاعات به شما نشان میدهد * فیلتر جهت روند در تایم‌فریم بالاتر : اگر روند بالاتر بر اساس اِم-اِی-دویست صعودی باشد، سیگنال‌های خرید/لانگ قوی‌تر هستند و بالعکس * فیلتر تشخیص نواحی اشباع خرید/فروش در تایم‌فریم بالاتر : اگر آر-اِس-آی در محدوده اُورباوت باشد، احتمال موفقیت فروش بیشتر است و در محدوده اُورسولد احتمال موفقیت خرید بالاتر می‌رود 🧩 اجزای اندیکاتور ایکسمون چه هستند و چرا این اجزا با هم ترکیب شده‌اند * استراتژی اصلی : سیگنال بازگشت روند با الگوریتم اختصاصی سه‌پوش واگرایی * تأیید چندمرحله‌ای جهت روند در تایم فریم بالاتر بر اساس اِم-اِی-دویست و تایید وضعیت بیشینه خرید/فروش در تایم فریم بالاتر در اندیکاتور آر-اِس-آی * مدیریت سرمایه پیشرفته : محاسبه حجم پله‌ای و میانگین وزنی * مدیریت خروج ساختاریافته : سطوح ریسک‌فری، تارگت، لیکوییدیتی * پشتیبانی از تصمیم‌گیری سریع : همه اطلاعات حیاتی در یک نگاه این ترکیب، ایکسمون را به یک سیستم کامل و کاربردی تبدیل کرده که در هیچ ابزار مشابهی در تریدینگ‌ویو به این شکل یکپارچه پیاده‌سازی نشده است و دقیقاً مجموع این ویژگی‌ها در یک اندیکاتور است که ایکسمون را از ابزارهای مشابه متمایز می‌کند 📖 نحوه استفاده از اندیکاتور ایکسمون 1️⃣ افزودن اندیکاتور به چارت : اندیکاتور را به نمودار نماد دلخواه اضافه کنید 2️⃣ تنظیم پارامترها : از بخش تنظیمات، موارد زیر را بر اساس استراتژی شخصی خودتان مشخص کنید * تعداد پله‌های ورود: از دو تا ده پله * نوع پیوت ها: سوپر مینور/مینور/مید-ماژور/ماژور * نوع الگوها: نزولی/صعودی * نمایش خطوط و باکس اطلاعات * تعیین سرمایه در هر معامله * تایم‌فریم‌های فیلتر اِم-اِی-دویست و آر-اِس-آی 3️⃣ فعال‌سازی هشدارها : برای اطلاع فوری از شناسایی الگوهای سه‌پوش واگرایی ، آلارم‌ها را فعال کنید 4️⃣ بررسی باکس اطلاعات : برای سنجش قدرت الگو و هم‌جهتی با بازار، پس از صدور سیگنال، اطلاعات زیر را در باکس مشکی اطلاعات بررسی کنید * 🏷 نوع پیوت : بررسی میزان قدرت الگو - سوپر مینور، مینور، میدماژور یا ماژور * 📋 فیلترهای تأییدی یک - بررسی هم جهتی الگوی شناسایی شده با جهت روند در تایم‌فریم بالاتر دو - بررسی هم جهتی الگوی شناسایی شده با وضعیت اشباع خرید یا فروش در اندیکاتور آر-اِس-آی در تایم‌فریم بالاتر این اطلاعات به شما کمک می‌کند تصمیم بگیرید که آیا وارد معامله شوید یا خیر 5️⃣ ورود پله‌ای اگر پس از بررسی شرایط تصمیم به ورود گرفتید، اولین پوزیشن را در پله اول باز کنید و در صورتی که بازار در خلاف جهت موردنظر شما حرکت کرد و به سطح پله دوم رسید، یک پوزیشن جدید در همان سطح باز کنید و با رسیدن به سطوح بعدی، پوزیشن های بعدی را باز می کنید هر زمان که بازار از هر یک از این سطوح برگشت و در جهت تحلیل شما حرکت کرد، تمامی پوزیشن‌های باز شده وارد سود می‌شوند در اندیکاتور ایکسمون، تعداد پله‌های ورودی کاملاً قابل‌تنظیم است (بین دو تا ده پله ) و شما می‌توانید بر اساس استراتژی شخصی خود آن را تعیین کنید، سیستم به‌طور خودکار حجم هر پله را بر اساس سرمایه واردشده محاسبه می‌کند 6️⃣ مدیریت خروج بسته به شرایط بازار، می‌توانید یکی از دو روش زیر را انتخاب کنید * ⚖️ خروج در سطح ریسک‌فری : زمانی که بازار نامطمئن است و می‌خواهید بدون سود یا زیان از معامله خارج شوید * 🎯 خروج در سطح تارگت : زمانی که قیمت طبق تحلیل شما حرکت کرده است و بدنبال کسب سود هستید ⚠️سطح لیکوییدیتی * اسپات: نقطه ابطال تحلیل * فیوچرز: نقطه صفر شدن سرمایه پوزیشن با لوریج 💎 چرا نسخه اینوایت اونلی ایکسمون ارزش تهیه دارد * الگوریتم اختصاصی شناسایی و تأیید سه‌پوش واگرایی که در نسخه رایگان یا اندیکاتورهای عمومی وجود ندارد * محاسبات سرمایه و حجم پله‌ای به‌صورت خودکار و دقیق، همراه با رسم بصری سطوح کلیدی از لحظه صدور سیگنال * نمایش آنی شرایط بازار و کیفیت الگو در باکس اطلاعات بدون نیاز به تغییر تایم‌فریم یا افزودن اندیکاتورهای اضافی * کنترل ریسک و پشتیبانی روانی معامله‌گر با ارائه سناریوهای مشخص از ابتدا تا انتهای معامله * دسترسی محدود برای جلوگیری از استفاده نادرست و کاهش ریسک مالی کاربران، همراه با آموزش اختصاصی پیش از فعال‌سازی * اثبات‌شده در تست‌ها و معاملات واقعی با نتایج قابل اتکا، به شرط استفاده صحیح بر اساس آموزش صمیمانه امیدواریم معاملات موفق و پرسودی داشته باشید 📣 اگر سوالی دارید یا نیاز به راهنمایی بیشتری دارید، خوشحال می‌شویم از ما بپرسید با کمال میل در خدمت‌تان هستیم
مؤشر Pine Script®
من ‎XmoonTradeClub‎
Machine Learning BBPct [BackQuant]Machine Learning BBPct What this is (in one line) A Bollinger Band %B oscillator enhanced with a simplified K-Nearest Neighbors (KNN) pattern matcher. The model compares today’s context (volatility, momentum, volume, and position inside the bands) to similar situations in recent history and blends that historical consensus back into the raw %B to reduce noise and improve context awareness. It is informational and diagnostic—designed to describe market state, not to sell a trading system. Background: %B in plain terms Bollinger %B measures where price sits inside its dynamic envelope: 0 at the lower band, 1 at the upper band, ~ 0.5 near the basis (the moving average). Readings toward 1 indicate pressure near the envelope’s upper edge (often strength or stretch), while readings toward 0 indicate pressure near the lower edge (often weakness or stretch). Because bands adapt to volatility, %B is naturally comparable across regimes. Why add (simplified) KNN? Classic %B is reactive and can be whippy in fast regimes. The simplified KNN layer builds a “nearest-neighbor memory” of recent market states and asks: “When the market looked like this before, where did %B tend to be next bar?” It then blends that estimate with the current %B. Key ideas: • Feature vector . Each bar is summarized by up to five normalized features:   – %B itself (normalized)   – Band width (volatility proxy)   – Price momentum (ROC)   – Volume momentum (ROC of volume)   – Price position within the bands • Distance metric . Euclidean distance ranks the most similar recent bars. • Prediction . Average the neighbors’ prior %B (lagged to avoid lookahead), inverse-weighted by distance. • Blend . Linearly combine raw %B and KNN-predicted %B with a configurable weight; optional filtering then adapts to confidence. This remains “simplified” KNN: no training/validation split, no KD-trees, no scaling beyond windowed min-max, and no probabilistic calibration. How the script is organized (by input groups) 1) BBPct Settings • Price Source – Which price to evaluate (%B is computed from this). • Calculation Period – Lookback for SMA basis and standard deviation. • Multiplier – Standard deviation width (e.g., 2.0). • Apply Smoothing / Type / Length – Optional smoothing of the %B stream before ML (EMA, RMA, DEMA, TEMA, LINREG, HMA, etc.). Turning this off gives you the raw %B. 2) Thresholds • Overbought/Oversold – Default 0.8 / 0.2 (inside ). • Extreme OB/OS – Stricter zones (e.g., 0.95 / 0.05) to flag stretch conditions. 3) KNN Machine Learning • Enable KNN – Switch between pure %B and hybrid. • K (neighbors) – How many historical analogs to blend (default 8). • Historical Period – Size of the search window for neighbors. • ML Weight – Blend between raw %B and KNN estimate. • Number of Features – Use 2–5 features; higher counts add context but raise the risk of overfitting in short windows. 4) Filtering • Method – None, Adaptive, Kalman-style (first-order), or Hull smoothing. • Strength – How aggressively to smooth. “Adaptive” uses model confidence to modulate its alpha: higher confidence → stronger reliance on the ML estimate. 5) Performance Tracking • Win-rate Period – Simple running score of past signal outcomes based on target/stop/time-out logic (informational, not a robust backtest). • Early Entry Lookback – Horizon for forecasting a potential threshold cross. • Profit Target / Stop Loss – Used only by the internal win-rate heuristic. 6) Self-Optimization • Enable Self-Optimization – Lightweight, rolling comparison of a few canned settings (K = 8/14/21 via simple rules on %B extremes). • Optimization Window & Stability Threshold – Governs how quickly preferred K changes and how sensitive the overfitting alarm is. • Adaptive Thresholds – Adjust the OB/OS lines with volatility regime (ATR ratio), widening in calm markets and tightening in turbulent ones (bounded 0.7–0.9 and 0.1–0.3). 7) UI Settings • Show Table / Zones / ML Prediction / Early Signals – Toggle informational overlays. • Signal Line Width, Candle Painting, Colors – Visual preferences. Step-by-step logic A) Compute %B Basis = SMA(source, len); dev = stdev(source, len) × multiplier; Upper/Lower = Basis ± dev. %B = (price − Lower) / (Upper − Lower). Optional smoothing yields standardBB . B) Build the feature vector All features are min-max normalized over the KNN window so distances are in comparable units. Features include normalized %B, normalized band width, normalized price ROC, normalized volume ROC, and normalized position within bands. You can limit to the first N features (2–5). C) Find nearest neighbors For each bar inside the lookback window, compute the Euclidean distance between current features and that bar’s features. Sort by distance, keep the top K . D) Predict and blend Use inverse-distance weights (with a strong cap for near-zero distances) to average neighbors’ prior %B (lagged by one bar). This becomes the KNN estimate. Blend it with raw %B via the ML weight. A variance of neighbor %B around the prediction becomes an uncertainty proxy ; combined with a stability score (how long parameters remain unchanged), it forms mlConfidence ∈ . The Adaptive filter optionally transforms that confidence into a smoothing coefficient. E) Adaptive thresholds Volatility regime (ATR(14) divided by its 50-bar SMA) nudges OB/OS thresholds wider or narrower within fixed bounds. The aim: comparable extremeness across regimes. F) Early entry heuristic A tiny two-step slope/acceleration probe extrapolates finalBB forward a few bars. If it is on track to cross OB/OS soon (and slope/acceleration agree), it flags an EARLY_BUY/SELL candidate with an internal confidence score. This is explicitly a heuristic—use as an attention cue, not a signal by itself. G) Informational win-rate The script keeps a rolling array of trade outcomes derived from signal transitions + rudimentary exits (target/stop/time). The percentage shown is a rough diagnostic , not a validated backtest. Outputs and visual language • ML Bollinger %B (finalBB) – The main line after KNN blending and optional filtering. • Gradient fill – Greenish tones above 0.5, reddish below, with intensity following distance from the midline. • Adaptive zones – Overbought/oversold and extreme bands; shaded backgrounds appear at extremes. • ML Prediction (dots) – The KNN estimate plotted as faint circles; becomes bright white when confidence > 0.7. • Early arrows – Optional small triangles for approaching OB/OS. • Candle painting – Light green above the midline, light red below (optional). • Info panel – Current value, signal classification, ML confidence, optimized K, stability, volatility regime, adaptive thresholds, overfitting flag, early-entry status, and total signals processed. Signal classification (informational) The indicator does not fire trade commands; it labels state: • STRONG_BUY / STRONG_SELL – finalBB beyond extreme OS/OB thresholds. • BUY / SELL – finalBB beyond adaptive OS/OB. • EARLY_BUY / EARLY_SELL – forecast suggests a near-term cross with decent internal confidence. • NEUTRAL – between adaptive bands. Alerts (what you can automate) • Entering adaptive OB/OS and extreme OB/OS. • Midline cross (0.5). • Overfitting detected (frequent parameter flipping). • Early signals when early confidence > 0.7. These are purely descriptive triggers around the indicator’s state. Practical interpretation • Mean-reversion context – In range markets, adaptive OS/OB with ML smoothing can reduce whipsaws relative to raw %B. • Trend context – In persistent trends, the KNN blend can keep finalBB nearer the mid/upper region during healthy pullbacks if history supports similar contexts. • Regime awareness – Watch the volatility regime and adaptive thresholds. If thresholds compress (high vol), “OB/OS” comes sooner; if thresholds widen (calm), it takes more stretch to flag. • Confidence as a weight – High mlConfidence implies neighbors agree; you may rely more on the ML curve. Low confidence argues for de-emphasizing ML and leaning on raw %B or other tools. • Stability score – Rising stability indicates consistent parameter selection and fewer flips; dropping stability hints at a shifting backdrop. Methodological notes • Normalization uses rolling min-max over the KNN window. This is simple and scale-agnostic but sensitive to outliers; the distance metric will reflect that. • Distance is unweighted Euclidean. If you raise featureCount, you increase dimensionality; consider keeping K larger and lookback ample to avoid sparse-neighbor artifacts. • Lag handling intentionally uses neighbors’ previous %B for prediction to avoid lookahead bias. • Self-optimization is deliberately modest: it only compares a few canned K/threshold choices using simple “did an extreme anticipate movement?” scoring, then enforces a stability regime and an overfitting guard. It is not a grid search or GA. • Kalman option is a first-order recursive filter (fixed gain), not a full state-space estimator. • Hull option derives a dynamic length from 1/strength; it is a convenience smoothing alternative. Limitations and cautions • Non-stationarity – Nearest neighbors from the recent window may not represent the future under structural breaks (policy shifts, liquidity shocks). • Curse of dimensionality – Adding features without sufficient lookback can make genuine neighbors rare. • Overfitting risk – The script includes a crude overfitting detector (frequent parameter flips) and will fall back to defaults when triggered, but this is only a guardrail. • Win-rate display – The internal score is illustrative; it does not constitute a tradable backtest. • Latency vs. smoothness – Smoothing and ML blending reduce noise but add lag; tune to your timeframe and objectives. Tuning guide • Short-term scalping – Lower len (10–14), slightly lower multiplier (1.8–2.0), small K (5–8), featureCount 3–4, Adaptive filter ON, moderate strength. • Swing trading – len (20–30), multiplier ~2.0, K (8–14), featureCount 4–5, Adaptive thresholds ON, filter modest. • Strong trends – Consider higher adaptive_upper/lower bounds (or let volatility regime do it), keep ML weight moderate so raw %B still reflects surges. • Chop – Higher ML weight and stronger Adaptive filtering; accept lag in exchange for fewer false extremes. How to use it responsibly Treat this as a state descriptor and context filter. Pair it with your execution signals (structure breaks, volume footprints, higher-timeframe bias) and risk management. If mlConfidence is low or stability is falling, lean less on the ML line and more on raw %B or external confirmation. Summary Machine Learning BBPct augments a familiar oscillator with a transparent, simplified KNN memory of recent conditions. By blending neighbors’ behavior into %B and adapting thresholds to volatility regime—while exposing confidence, stability, and a plain early-entry heuristic—it provides an informational, probability-minded view of stretch and reversion that you can interpret alongside your own process.
مؤشر Pine Script®
من ‎BackQuant‎
2
Price Acceleration Matrix [QuantAlgo]🟢 Overview The Price Acceleration Matrix indicator is an advanced momentum analysis tool that measures the rate of change in price velocity across multiple timeframes simultaneously. It transforms raw price data into velocity measurements for each timeframe, then calculates the acceleration of these velocities to identify when momentum is building or deteriorating. By analyzing acceleration alignment across all three timeframes, the system can distinguish between strong directional moves (all timeframes accelerating in the same direction) and weak, choppy movements (mixed acceleration signals). This multi-timeframe acceleration matrix provides traders with early warning signals for momentum shifts, trend continuation and reversal opportunities across different timeframes and asset classes. 🟢 How It Works The indicator employs a three-stage calculation process that transforms price data into actionable acceleration signals. First, it calculates velocity (rate of price change) for each of the three user-defined timeframes by measuring the percentage change in price over the specified lookback periods. These velocity calculations are normalized by their respective timeframe lengths to ensure fair comparison across different periods. In the second stage, the system calculates acceleration by measuring the change in velocity from one bar to the next for each timeframe, effectively capturing the second derivative of price movement. This acceleration data reveals whether momentum is building (positive acceleration) or deteriorating (negative acceleration) at each timeframe level. The final stage creates the acceleration matrix score by evaluating alignment across all three timeframes. When all timeframes show positive acceleration, the system averages them for maximum bullish signal strength. When all show negative acceleration, it averages them for maximum bearish signal strength. However, when acceleration signals are mixed across timeframes, the system applies a penalty by dividing the average by two, indicating consolidation or conflicting momentum forces. The resulting signal is then smoothed using an Exponential Moving Average and scaled to the -3 to +3 range using a user-defined threshold parameter. 🟢 How to Use 1. Signal Interpretation and Momentum Analysis Positive Territory (Above Zero): Indicates accelerating upward momentum with bullish bias and favorable conditions for long positions Negative Territory (Below Zero): Signals accelerating downward momentum with bearish bias and favorable conditions for short positions Extreme Levels (±2 to ±3): Represent maximum acceleration alignment across all timeframes, indicating high-probability momentum continuation Moderate Levels (±1 to ±2): Suggest building momentum with good timeframe alignment but less conviction than extreme readings Near Zero (-0.5 to +0.5): Indicates mixed signals, consolidation, or momentum exhaustion requiring caution 2. Overbought/Oversold Zone Analysis Above +2 (Overbought Zone): Markets showing extreme bullish acceleration may be due for profit-taking or short-term pullbacks Below -2 (Oversold Zone): Markets showing extreme bearish acceleration may present reversal opportunities or bounce potential Zone Exits: When acceleration retreats from extreme zones, it often signals momentum exhaustion and potential trend changes 🟢 Pro Tips for Trading → Early Momentum Detection: Watch for acceleration crossing above zero after periods of negative readings, as this often precedes major price movements by several bars, providing early entry opportunities before traditional indicators signal. → Momentum Exhaustion Signals: Exit or take profits when acceleration reaches extreme levels (±2.5 or higher) and begins to decline, even if price continues in the same direction, as momentum deterioration typically precedes price reversals. → Acceleration Divergence Strategy: Look for divergences between price highs/lows and acceleration peaks/troughs, as these often signal weakening momentum and potential reversal opportunities before they become apparent on price charts. → Threshold Optimization: Adjust the acceleration threshold based on asset volatility - higher thresholds (0.7-1.0) for volatile assets to reduce false signals, lower thresholds (0.3-0.5) for stable assets to maintain sensitivity. → Alert-Based Trading: Utilize the built-in alert system for bullish/bearish reversals (±2 level crosses) and trend changes (zero line crosses) to capture momentum shifts without constant chart monitoring, especially effective for swing trading approaches. → Risk Management Integration: Reduce position sizes when acceleration readings are weak (below ±1.0) and increase allocation when strong acceleration alignment occurs (above ±2.0), as signal strength correlates directly with probability of successful trades.
مؤشر Pine Script®
من ‎QuantAlgo‎
6
TCP | Market Session | Session Analyzer📌 TCP | Market Session Indicator | Crypto Version A powerful, real-time market session visualization tool tailored for crypto traders. Track the heartbeat of Asia, Europe, and US trading hours directly on your chart with live session boxes, behavioral analysis, liquidity grab detection, and countdown timers. Know when the action starts, how the market behaves, and where the traps lie. 🔰 Introduction: Trade the Right Hours with the Right Tools Time matters in trading. Most significant moves happen during key sessions—and knowing when and how each session unfolds can give you a sharp edge. The TCP Market Session Indicator, developed by Trade City Pro (TCP), puts professional session tracking and behavioral insights at your fingertips. Whether you're a scalper or swing trader, this indicator gives you the timing context to enter and exit trades with greater confidence and clarity. 🕒 Core Features • Live Session Boxes : Highlight active ranges during Asia, Europe, and US sessions with dynamic high/low updates. • Session Start/End Labels : Know exactly when each session begins and ends plotted clearly on your chart with context. • Session Behavior Analysis : At the end of each session, the indicator classifies the price action as: - Trend Up - Trend Down - Consolidation - Manipulation • Liquidity Grab Detection: Automatically detects possible stop hunts (fake breakouts) and marks them on the chart with precision filters (volume, ATR, reversal). • Session Countdown Table: A live dashboard showing: - Current active session - Time left in session - Upcoming session and how many minutes until it starts - Utility time converter (e.g. 90 min = 01:30) • Vertical Session Lines: Visualize past and upcoming session boundaries with customizable history and future range. • Multi-Day Support: Draw session ranges for previous, current, and future days for better backtesting and forecasting. ⚙️ Settings Panel Customize everything to fit your trading style and schedule: • Session Time Settings: Set the opening and closing time for each session manually using UTC-based minute inputs. → For example, enter Asia Start: 0, Asia End: 480 for 00:00–08:00 UTC. This gives full flexibility to adjust session hours to match your preferred market behavior. • Enable or Disable Elements: Toggle the visibility of each session (Asia, Europe, US), as well as: - Session Boxes - Countdown Table - Session Lines - Liquidity Grab Labels • Timezone Selection: Choose between using UTC or your chart’s local timezone for session calculations. • Customization Options: Select number of past and future days to draw session data Adjust vertical line transparency Fine-tune label offset and spacing for clean layout 📊 Smart Session Boxes Each session box tracks high, low, open, and close in real time, providing visual clarity on market structure. Once a session ends, the box closes, and the behavior type is saved and labeled ideal for spotting patterns across sessions. • Asia: Green Box • Europe: Orange Box • US: Blue Box 💡 Why Use This Tool? • Perfect Timing: Don’t get chopped in low-liquidity hours. Focus on sessions where volume and volatility align. • Pattern Recognition: Study how price behaves session-to-session to build better strategies. • Trap Detection: Spot manipulation moves (liquidity grabs) early and avoid common retail pitfalls. • Macro Session Mapping: Use as a foundational layer to align trades with market structure and news cycles. 🔍 Example Use Case You're watching BTC at 12:45 UTC. The indicator tells you: The Asia session just ended (label shows “Asia Session End: Trend Up”) Europe session starts in 15 minutes A liquidity grab just triggered at the previous high—label confirmed Now you know who’s active, what the market just did, and what’s about to start—all in one glance. ✅ Why Traders Trust It • Visual & Intuitive: Fully chart-based, no clutter, no guessing • Crypto-Focused: Designed specifically for 24/7 crypto markets (not outdated forex models) • Non-Repainting: All labels and boxes stay as printed—no tricks • Reliable: Tested across multiple exchanges, pairs, and timeframes 🧩 Built by Trade City Pro (TCP) The TCP Market Session Indicator is part of a suite of professional tools used by over 150,000 traders. It’s coded in Pine Script v6 for full compatibility with TradingView’s latest capabilities. 🔗 Resources • Tutorial: Learn how to analyze sessions like a pro in our TradingView guide: "TradeCityPro Academy: Session Mapping & Liquidity Traps" • More Tools: Explore our full library of indicators on
مؤشر Pine Script®
من ‎tradecitypro‎
45
Smart Trend Signals [QuantAlgo]🟢 Overview The Smart Trend Signals indicator is created to address a fundamental challenge in technical analysis: generating timely trend signals while adapting to varying market volatility conditions. The indicator distinguishes itself by employing volatility-adjusted calculations that automatically modify signal sensitivity based on current market conditions, rather than using fixed parameters that perform inconsistently across different market environments. By processing Long and Short signals through separate dynamic calculation engines, each optimized for its respective directional bias, the indicator reduces the common issue of delayed or conflicting signals that plague many traditional trend-following tools. Additionally, the integration of linear regression-based trend confirmation adds another layer of signal validation, helping to filter market noise while maintaining responsiveness to genuine price movements. This adaptive approach makes the indicator practical for both traders and investors across different asset classes and timeframes, from short-term forex/crypto scalping to long-term equity position analysis. 🟢 How It Works The indicator uses a straightforward calculation process that combines volatility measurement with momentum detection to generate directional signals. The system first calculates Average True Range (ATR) over a user-defined period to measure current market volatility. This ATR value is then multiplied by the Smart Trend Multiplier setting to create dynamic reference levels that expand during volatile periods and contract during calmer market conditions. For signal generation, the indicator maintains separate calculation paths for Long/Buy and Short/Sell opportunities. Long signals are generated when price moves above a dynamically calculated level below the current price, confirmed by an exponential moving average crossover in the same direction. Short signals work in reverse, triggering when price moves below a calculated level above the current price, also requiring EMA confirmation. This dual-path approach allows each signal type to operate with parameters suited to its directional bias. 🟢 How to Use Long Signals (Green Labels): Appear as "Long" labels below price bars when the indicator detects upward price momentum above the calculated reference level, confirmed by EMA crossover. These signals identify moments when price action demonstrates bullish characteristics based on the volatility-adjusted calculations. Short Signals (Red Labels): Display as "Short" labels above price bars when downward price momentum below the reference level is detected and confirmed by EMA crossover. These signals highlight instances where price action exhibits bearish characteristics according to the indicator's mathematical framework. Customizable Bar Coloring: This feature colors individual price bars to match the current signal direction. When enabled, each bar reflects the indicator's current directional bias, creating a continuous visual representation of trend periods across the chart timeline. Built-in Alert System: Provides automatic notifications for new signals with detailed exchange and ticker information. The alert system monitors the indicator's calculations continuously and triggers notifications when new long or short signals are generated, allowing traders/investors to track multiple instruments simultaneously. 🟢 Pro Tips for Trading and Investing → Parameter Adjustment: Higher Smart Trend Multiplier settings generate fewer signals that may be more selective, while lower settings produce more frequent signals that may include more false positives. Test different settings to find what works for your trading style and market conditions. → Timeframe Analysis: Using higher timeframes for general trend direction and lower timeframes for entry timing is a common approach. → Risk Management: No indicator eliminates the need for proper risk management. Use appropriate position sizing and stop-loss strategies regardless of signal quality or frequency. → Market Conditions: The indicator may perform differently in trending versus ranging markets. Frequent signal changes might indicate choppy conditions. Backtest and paper trade before risking real capital.
مؤشر Pine Script®
من ‎QuantAlgo‎
2
Cumulative Volume Delta (SB-1) 2.0 📈 Cumulative Volume Delta (CVD) — Stair-Step + Threshold Alerts 🔍 Overview This Cumulative Volume Delta (CVD) tool visualizes aggressive buying and selling pressure in the market by plotting candlestick-style bars based on volume delta. It helps traders understand which side — buyers or sellers — is exerting more control on lower timeframes and highlights momentum shifts through stair-step patterns and delta threshold breaks. Resets to zero at EOD Ideal for futures traders, scalpers, and intraday strategists looking for orderflow-based confirmation. 🧠 What Is CVD? CVD (Cumulative Volume Delta) measures the difference between market buys and sells over a specific timeframe. When the delta is rising, it suggests buyers are being more aggressive. Falling delta suggests seller dominance. This script aggregates volume delta from a lower timeframe and plots it in a higher timeframe context, allowing you to track microstructure shifts within larger candles. 📊 Features ✅ CVD Candlesticks Each bar represents volume delta as an OHLC-style candle using: Open: Delta at the start of the bar High/Low: Peak delta range Close: Final delta value at bar close Teal candles = Net buying pressure Red candles = Net selling pressure ✅ Threshold Levels (Key Visual Zones) The script includes horizontal dashed lines at: +5,000 and +10,000 → Signify strong buying pressure -5,000 and -10,000 → Signify strong selling pressure 0 line → Neutrality line (no net pressure) These levels act as volume-based support/resistance zones and breakout confirmation tools. For example: A CVD cross above +5,000 shows buyers taking control A CVD cross above +10,000 implies strong bullish momentum A CVD cross below -5,000 or -10,000 signals intense selling pressure 📈 Stair-Step Pattern Detection Detects two specific volume-based continuation setups: Bullish Stair-Step: Both the high and low of the CVD candle are higher than the previous candle Bearish Stair-Step: Both the high and low of the CVD candle are lower than the previous candle These patterns often appear during trending moves and serve as confirmation of strength or continuation. Visual markers: 🟢 Green triangles below bars = Bullish stair-step 🔴 Red triangles above bars = Bearish stair-step 🔔 Alert Conditions Get real-time alerts when: Bullish Stair-Step is detected Bearish Stair-Step is detected CVD crosses above +5,000 CVD crosses below -5,000 📢 Alerts only trigger on crossover, not every time CVD remains above or below. This avoids repetitive notifications. ⚙️ Inputs & Customization Anchor Timeframe: The higher timeframe to which CVD data is applied (default: 1D) Lower Timeframe: The timeframe used to calculate the CVD delta (default: 5 minutes) Optional Override: Use custom timeframe toggle to force your own micro timeframe 📌 How to Use This CVD Indicator (Step-by-Step Guide) ✅ 1. Confirm Bias Using the Zero Line The zero line (0 CVD) represents neutral pressure — neither buyers nor sellers are dominating. Use it as your first filter: 🔼 If CVD is above 0 and rising → Buyer control 🔽 If CVD is below 0 and falling → Seller control 🧠 Tip: CVD rising while price is consolidating may signal hidden buyer interest. ✅ 2. Watch for Crosses of Key Levels: +5,000 and +10,000 These levels act as momentum thresholds: Level Signal Type What It Means +5,000 Buyer breakout Buyers are starting to dominate +10,000 Strong bull bias Strong institutional or algorithmic buying flow -5,000 Seller breakout Sellers are taking control -10,000 Strong bear bias Heavy selling pressure is entering the market Wait for CVD to cross above +5K or below -5K to confirm the active side. Use these crossovers as entry triggers, breakout confirmations, or trade filters. 🔔 Alerts fire only when the level is first crossed, not every bar above/below. ✅ 3. Use Stair-Step Patterns for Continuation Confirmation The indicator shows stair-step patterns using triangle signals: 🟢 Green triangle below bar = Bullish stair-step Suggests a higher high and higher low in delta → buyers stepping up 🔴 Red triangle above bar = Bearish stair-step Suggests lower highs and lower lows in delta → selling pressure building Use stair-step signals: To confirm a continuation of trend As an entry or add-on signal Especially after a threshold breakout 🧠 Example: If CVD breaks above +5K and forms bullish stairs → confirms strong trend, ideal for momentum entries. ✅ 4. Combine with Price Action or Structure CVD works best when used with price, not in isolation. For example: 📉 Price makes a new low but CVD doesn’t → potential bullish divergence 📈 CVD surges while price lags → buyers are absorbing, breakout likely Use it with: VWAP Orderblocks Liquidity sweeps Break of market structure/MSS/BOS ✅ 5. Set Anchor Timeframe = Daily Set Lower Timeframe = 5 minutes (default) This lets you: See intraday flow inside daily bars Confirm whether a daily candle is being built on net buying or selling 🧠 You’re essentially seeing intra-bar aggression within a bigger time structure. 🧭 Example Trading Setup Bullish Scenario: CVD is rising and above 0 CVD crosses above +5,000 → alert fires Green stair-step appears Price breaks local resistance or liquidity sweep completes ✅ Consider long entry with structure and CVD alignment 🎯 Place stops below last stair-step or structural low 📌 Final Notes This tool does not repaint and is designed to work in real-time across all futures, crypto, and equity instruments that support volume data. If your symbol does not provide volume, the script will notify you. Use it in confluence with VWAP, liquidity zones, or structure breaks for high-confidence trades.
مؤشر Pine Script®
من ‎samb817‎
Ultimate Precision Buy/Sell with SL - Clean Labels FIXThis is a premium indicator designed for traders who demand accuracy, simplicity, and clean visual signals. ✅ Key Features: 📈 Precise Buy/Sell entries based on trend confirmation (EMA) and momentum (RSI) 🛡️ Automatic Stop Loss (SL) drawn for every trade, calculated from ATR 🔄 SL line dynamically moves with each new candle to reflect live action ❗ Only one active signal at a time – no clutter, no repaints ⏱ Optimized for 1H timeframe 💰 Best for Forex pairs, Gold (XAUUSD), Silver (XAGUSD), Platinum (XPTUSD) 🧠 How it works: Buy Signal: When fast EMA > slow EMA & RSI crosses above 30 Sell Signal: When fast EMA < slow EMA & RSI crosses below 70 A single SL line is drawn per trade and remains until either: Opposite signal appears, or SL is hit ⚠️ No repainting. No noise. Just precision. If you want to trade smart, clean and with confidence – this indicator is built for you.
مؤشر Pine Script®
من ‎Stisomark‎
SeikaAlgo–Long/Short Buy/Sell SignalSeikaAlgo–Long/Short Buy/Sell Signal — Simple, Visual, Reliable Signals SeikaAlgo makes high-probability trading simple and actionable for everyone—no complex rules, no guesswork. Just follow these 3 steps: How It Works 1. Watch for Buy/Sell Signals Buy and Sell signals are printed right on your chart, only after the candle closes—never repaints, never lags. Trade with confidence. 2. Enter at Candle Close Buy: Enter at the close of a candle when a green “B” label appears and price crosses above the green EMA 9. Sell: Enter at the close of a candle when a red “S” label appears and price crosses below the red EMA 9. 3. Take Profit Move your stop loss with each new candle (trailing stop), or use the EMA 9 line to trail stops. Take profit when price reaches a Daily Fibonacci Level. Example — 5min SPY Buy Signal: Green label prints above green EMA 9 after candle closes. Enter at close, stop just below the signal candle’s low. Sell Signal: Red label prints below red EMA 9 after candle closes. Enter at close, stop just above the signal candle’s high. Key Features No Lag, No Repainting: Signals only appear after a candle is complete—so you’re never chasing ghosts. Clear Visual Cues: Instantly know when to buy, sell, or step aside. Built-in Trailing Stop Logic: Protect your trades easily. Works On Any Market/Timeframe: Perfect for stocks, futures, crypto, or forex. SeikaAlgo is an invite-only indicator. Add it to your chart, follow the labels and EMA, and trade with confidence—no clutter, no confusion. Simple, visual, reliable.
مؤشر Pine Script®
من ‎Asa666‎
Time-Price Velocity [QuantAlgo]🟢 Overview The Time-Price Velocity indicator uses advanced velocity-based analysis to measure the rate of price change normalized against typical market movement, creating a dynamic momentum oscillator that identifies market acceleration patterns and momentum shifts. Unlike traditional momentum indicators that focus solely on price change magnitude, this indicator incorporates time-weighted displacement calculations and ATR normalization to create a sophisticated velocity measurement system that adapts to varying market volatility conditions. This indicator displays a velocity signal line that oscillates around zero, with positive values indicating upward price velocity and negative values indicating downward price velocity. The signal incorporates acceleration background columns and statistical normalization to help traders identify momentum shifts and potential reversal or continuation opportunities across different timeframes and asset classes. 🟢 How It Works The indicator's key insight lies in its time-price velocity calculation system, where velocity is measured using the fundamental physics formula: velocity = priceChange / timeWeight The system normalizes this raw velocity against typical price movement using Average True Range (ATR) to create market-adjusted readings: normalizedVelocity = typicalMove > 0 ? velocity / typicalMove : 0 where "typicalMove = ta.atr(lookback)" provides the baseline for normal price movement over the specified lookback period. The Time-Price Velocity indicator calculation combines multiple sophisticated components. First, it calculates acceleration as the change in velocity over time: acceleration = normalizedVelocity - normalizedVelocity Then, the signal generation applies EMA smoothing to reduce noise while preserving responsiveness: signal = ta.ema(normalizedVelocity, smooth) This creates a velocity-based momentum indicator that combines price displacement analysis with statistical normalization, providing traders with both directional signals and acceleration insights for enhanced market timing. 🟢 How to Use 1. Signal Interpretation and Threshold Zones Positive Values (Above Zero): Time-price velocity indicating bullish momentum with upward price displacement relative to normalized baseline Negative Values (Below Zero): Time-price velocity indicating bearish momentum with downward price displacement relative to normalized baseline Zero Line Crosses: Velocity transitions between bullish and bearish regimes, indicating potential trend changes or momentum shifts Upper Threshold Zone: Area above positive threshold (default 1.0) indicating strong bullish velocity and potential reversal point Lower Threshold Zone: Area below negative threshold (default -1.0) indicating strong bearish velocity and potential reversal point 2. Acceleration Analysis and Visual Features Acceleration Columns: Background histogram showing velocity acceleration (the rate of change of velocity), with green columns indicating accelerating velocity and red columns indicating decelerating velocity. The interpretation depends on trend context: red columns in downtrends indicate strengthening bearish momentum, while red columns in uptrends indicate weakening bullish momentum Acceleration Column Height: The height of each column represents the magnitude of acceleration, with taller columns indicating stronger acceleration or deceleration forces Bar Coloring: Optional price bar coloring matches velocity direction for immediate visual trend confirmation Info Table: Real-time display of current velocity and acceleration values with trend arrows and change indicators 3. Additional Features: Confirmed vs Live Data: Toggle between confirmed (closed) bar analysis for stable signals or current bar inclusion for real-time updates Multi-timeframe Adaptability: Velocity normalization ensures consistent readings across different chart timeframes and asset volatilities Alert System: Built-in alerts for threshold crossovers and direction changes 🟢 Examples with Preconfigured Settings Default : Balanced configuration suitable for most timeframes and general trading applications, providing optimal balance between sensitivity and noise filtering for medium-term analysis. Scalping : High sensitivity setup with shorter lookback period and reduced smoothing for ultra-short-term trades on 1-15 minute charts, optimized for capturing rapid momentum shifts and frequent trading opportunities. Swing Trading : Extended lookback period with enhanced smoothing and higher threshold for multi-day positions, designed to filter market noise while capturing significant momentum moves on 1-4 hour and daily timeframes.
مؤشر Pine Script®
من ‎QuantAlgo‎
5
MTPI TOTAL / BTC | JeffreyTimmermansMedium-Term Probability Indicator (MTPI) The "Medium-Term Probability Indicator (MTPI)" is a multi-factor model designed to evaluate the medium-term state of a market. By aggregating signals from 20 underlying inputs, it generates a composite score that classifies the market as Bullish, Bearish, or Neutral. This helps traders understand the prevailing market regime and adapt strategies accordingly. Key Features Multi-Input Scoring: Combines up to 20 individual inputs (indicators, conditions, or models) into a single probability-based score. Composite Market State: Translates raw input signals into three states: Bullish, Bearish, or Neutral. Dynamic Background Coloring: Uses color-coded background shading to visually separate bullish, bearish, and neutral phases. MTPI Score: Calculates a final numeric score (ranging from -1 to +1) to quantify the market’s directional bias. Dashboard Display: Shows all input signals, their individual states, and the aggregated MTPI score at a glance. Medium-Term Focus: Helps identify prevailing conditions that last from several weeks to several months. Inputs & Settings MTPI Settings: Input Signals (1 to 20): Default: Predefined conditions. Each input evaluates the market from a unique perspective (trend, momentum, volatility, etc.). Composite Score Calculation: Default weighting is equal across all inputs. Color Settings: Bullish: Bright green background Neutral: Gray/orange background Bearish: Bright red background These colors can be customized as desired. Calculation Process Signal Aggregation: Each input generates a state: 1 to 0.1 = Bullish 0.1 to -0.1 = Neutral -0.1 to -1 = Bearish Scoring: The MTPI aggregates these values and calculates an average score. Classification: Bullish: Score > 0 Bearish: Score < 0 Neutral: Score ≈ 0 Visualization: Background Coloring: Highlights the dominant phase on the chart. Dashboard: Displays individual input states, the total MTPI score, and the resulting classification. How to Use the MTPI Identifying Market Regimes: Bullish: Majority of inputs align positively. Favor long positions or trend-following strategies. Bearish: Majority of inputs align negatively. Favor short positions or defensive strategies. Neutral: Mixed signals. Caution or range-bound strategies may be preferable. Transition Detection: Changes in background color or the MTPI dashboard (score flipping from positive to negative, or vice versa) indicate potential regime shifts. Dynamic Dashboard: Score: Displays the net sum of all input signals (normalized). State: Provides the classification (Bullish, Bearish, Neutral). Trend: Visual cues for each input showing the current contribution to the MTPI. Conclusion The Medium-Term Probability Indicator (MTPI) consolidates multiple signals into a single, intuitive visualization that helps traders quickly assess the medium-term market environment. Its combination of a multi-input dashboard, composite scoring, and background coloring makes it a powerful decision-support tool. This script is developed by Jeffrey Timmermans and is designed to complement other analysis methods.
مؤشر Pine Script®
من ‎JeffreyTimmermans‎
Quality Buy/Sell Indicator with Scalping Mode + SL OnlyQuality Buy/Sell Indicator with Scalping Mode + SL Only is designed for traders who want clean and reliable signals for both swing and scalping strategies. ✅ Features: Buy & Sell signals based on EMA and MACD logic Scalping Mode (switch ON for faster, more frequent signals) SL (Stop Loss) line displayed for every trade for easy risk management Clean chart – no TP1, TP2, TP3 clutter Option to show only the latest signal or the entire signal history ✅ How it works: In normal mode you get fewer, more reliable signals – perfect for intraday or swing trading. In scalping mode the indicator generates more signals for short-term trades (1–15m charts). The Show All Signals switch allows you to keep the entire history visible, or only the latest trade setup for maximum clarity. ✅ Best suited for: Traders who want clean charts without TP lines Intraday and scalping traders looking for multiple setups per session Swing traders who prefer clear Buy/Sell with risk control
مؤشر Pine Script®
من ‎Stisomark‎
Signalgo MASignalgo MA is a TradingView indicator based on moving average (MA) trading by combining multi-timeframe logic, trend strength filtering, and adaptive trade management. Here’s a deep dive into how it works, its features, and why it stands apart from traditional MA indicators. How Signalgo MA Works 1. Multi-Timeframe Moving Average Analysis Simultaneous EMA & SMA Tracking: Signalgo MA calculates exponential (EMA) and simple (SMA) moving averages across a wide range of timeframes—from 1 minute to 3 months. Layered Cross Detection: It detects crossovers and crossunders on each timeframe, allowing for both micro and macro trend detection. Synchronized Signal Mapping: Instead of acting on a single crossover, the indicator requires agreement across multiple timeframes to trigger signals, filtering out noise and false positives. 2. Trend Strength & Quality Filtering ADX Trend Filter: Trades are only considered when the Average Directional Index (ADX) confirms a strong trend, ensuring signals are not triggered during choppy or directionless markets. Volume & Momentum Confirmation: For the strongest signals, the system requires: A significant volume spike Price above/below a longer-term EMA (for buys/sells) RSI momentum confirmation One-Time Event Detection: Each crossover event is flagged only once per occurrence, preventing repeated signals from the same move. Inputs Preset Parameters: EMA & SMA Lengths: Optimized for both short-term and long-term analysis. ADX Length & Minimum: Sets the threshold for what is considered a “strong” trend. Show Labels/Table: Visual toggles for displaying signal and trade management information. Trade Management: Show TP/SL Logic: Toggle to display or hide take-profit (TP) and stop-loss (SL) levels. ATR Length & Multipliers: Fine-tune how SL and TP levels adapt to market volatility. Enable Trailing Stop: Option to activate dynamic stop movement after TP1. Entry & Exit Strategy Entry Logic Long (Buy) Entry: Triggered when multiple timeframes confirm bullish EMA/SMA crossovers, ADX confirms trend strength, and all volume/momentum filters align. Short (Sell) Entry: Triggered when multiple timeframes confirm bearish crossunders, with the same strict filtering. Exit & Trade Management Stop Loss (SL): Automatically set based on recent volatility (ATR), adapting to current market conditions. Take Profits (TP1, TP2, TP3): Three profit targets at increasing reward multiples, allowing for flexible trade management. Trailing Stop: After TP1 is hit, the stop loss moves to breakeven and a trailing stop is activated to lock in further gains. Event Markers: Each time a TP or SL is hit, a visual label is placed on the chart for full transparency. Strict Signal Quality Filters: Signals are only generated when volume spikes, momentum, and trend strength all align, dramatically reducing false positives. Adaptive, Automated Trade Management: Built-in TP/SL and trailing logic mean you get not just signals, but a full trade management suite, rarely found in standard MA indicators. Event-Driven, Not Static: Each signal is triggered only once per event, eliminating repetitive or redundant entries. Visual & Alert Integration: Every signal and trade event is visually marked and can trigger TradingView alerts, keeping you informed in real time. Trading Strategy Application Versatility: Suitable for scalping, day trading, swing trading, and longer-term positions thanks to its multi-timeframe logic. Noise Reduction: The layered filtering logic means you only see the highest-probability setups, helping you avoid common MA “fakeouts” and overtrading. So basically what separates Signalgo MA from traditional MA indicators? 1. Multi-Timeframe Analysis Traditional MA indicators: Usually measure crossovers or signals within a single timeframe. Signalgo MA: simultaneously calculates fast/slow EMAs & SMAs for multiple periods. This enables it to create signals based on synchronized or stacked momentum across multiple periods, offering broader trend confirmation and reducing noise from single-timeframe signals. 2. Combinatorial Signal Logic Traditional: A basic crossover is typically “if fast MA crosses above/below slow MA, signal buy/sell.” Signalgo MA: Generates signals only when MA crossovers align across several timeframes, plus takes into consideration the presence or absence of conflicting signals in shorter or longer frames. This reduces false positives and increases selectivity. 3. Trend Strength Filtering (ADX Integration) Traditional: Many MA indicators are “blind” to trend intensity, potentially triggering signals in low volatility or ranging conditions. Signalgo MA: Employs ADX as a minimum trend filter. Signals will only fire if the trend is sufficiently strong, reducing whipsaws in choppy or sideways markets. 4. Volume & Strict Confirmation Layer Traditional: Few MA indicators directly consider volume or require confluence with other major indicators. Signalgo MA: Introduces a “strict signal” filter that requires not only MA crossovers and trend strength, but also (on designated frames): Significant volume spike, Price positioned above/below a higher timeframe EMA (trend anchor), RSI momentum confirmation. 5. Persistent, Multi-Level TP/SL Automated Trade Management Traditional: Separate scripts or manual management for stop-loss, take-profit, and trailing-stops, rarely fully integrated visually. Signalgo MA: Auto-plots up to three take-profit levels, initial stop, and a trailing stop (all ATR-based) on the chart. It also re-labels these as they are hit and resets for each new entry, supporting full trade lifecycle visualization directly on the chart. 6. Higher Timeframe SMA Crosses for Long-Term Context Traditional: Focuses only on the current chart’s timeframe. Signalgo MA: Incorporates SMA cross logic for weekly, monthly, and quarterly periods, which can contextualize lower timeframe trades within broader cycles, helping filter against counter-trend signals. 7. “Signal Once” Logic to Prevent Over-Trading Traditional: Will often re-fire the same signal repeatedly as long as the condition is true, possibly resulting in signal clusters and over-trading. Signalgo MA: Fires each signal only once per condition—prevents duplicate alerts for the same trade context.
مؤشر Pine Script®
من ‎signalgo‎
2