Fibonacci ReRSI LevelsOverview
The Fibonacci RSI Levels indicator plots key Fibonacci-based RSI levels directly on the price chart, offering a unique perspective on market momentum, potential reversal points, and support/resistance zones. By combining the Relative Strength Index (RSI) with Fibonacci retracement levels, this indicator helps traders identify overbought/oversold conditions, trend strength, and critical price levels for potential trading opportunities.
Key Features
Fibonacci RSI Levels: Plots five key levels—23.6% (Oversold), 38.2% (Downtrend Limit), 50.0% (Mid Level), 61.8% (Uptrend Limit), and 78.6% (Overbought)—based on a logarithmic RSI calculation.
Customizable Settings: Adjust the RSI length, line extension, timeframe, and level colors to suit your trading style.
Gradient Fills: Optional gradient fills between levels provide a visual representation of the price's position relative to key zones.
Multi-Timeframe Support: Use the current chart resolution or specify a custom timeframe (e.g., 1M, 5D, 240 for 4 hours) for flexible analysis.
Logarithmic RSI Calculation: Ideal for assets with exponential price movements, such as cryptocurrencies.
How It Works
The indicator uses a reverse-engineered RSI calculation, inspired by Giorgos Siligardos' concept, to determine price levels corresponding to specific Fibonacci RSI values. These levels are plotted as horizontal lines on the chart, each with a label showing the Fibonacci percentage and the exact price level. If enabled, gradient fills between the levels change color based on the price's position, enhancing visual interpretation.
Usage
Support and Resistance: The 38.2% and 61.8% levels often act as support and resistance in trending markets.
Overbought/Oversold Conditions: The 23.6% and 78.6% levels can indicate potential reversal points due to oversold or overbought conditions.
Trend Confirmation: The 50% level serves as a neutral zone or pivot point. Prices above this level may indicate an uptrend, while prices below suggest a downtrend.
Gradient Fills: Use the gradient fills to quickly assess the price's position within the key zones, aiding in decision-making for entries, exits, or reversals.
Interpretation
Uptrend: When the price is above the 50% level and approaching the 61.8% level, it may signal a strong uptrend.
Downtrend: When the price is below the 50% level and nearing the 38.2% level, it may indicate a downtrend.
Reversal Zones: Watch for price reactions near the 23.6% and 78.6% levels, as these can be areas of potential reversals.
Customization
RSI Length: Adjust the RSI period to fine-tune the sensitivity of the levels.
Line Extension: Control how far the levels extend into the future for better visualization.
Timeframe: Choose between the current chart resolution or a custom timeframe for multi-timeframe analysis.
Colors: Customize the colors of each level and enable gradient fills for enhanced visual clarity.
Educational
PORTFOLIO TABLE Simple [Titans_Invest]PORTFOLIO TABLE Simple
This is a simple table for you to monitor your assets or cryptocurrencies in your SPOT wallet without needing to access your broker’s website or wallet app.
⯁ HOW TO USE THIS TABLE❓
You only need to select the asset and enter the amount of each one.
The table will show how much you have of each asset and the total value of your portfolio.
You’ll be able to monitor up to 39 assets in real time.
⯁ CONVERT VALUES
You can also activate and select a currency for conversion.
For example, cryptocurrency assets are calculated in US dollars, but you can select euros as the conversion currency.
The values originally in dollars will then be displayed in euros.
⯁ Track your Portfolio in real time:
⯁ Add your local Currency to Convert Values:
⯁ Follow your Portfolio Live:
___________________________________________________________
📜 SCRIPT : PORTFOLIO TABLE Simple
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
___________________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
Modern Economic Eras DashboardOverview
This script provides a historical macroeconomic visualization of U.S. markets, highlighting long-term structural "eras" such as the Bretton Woods period, the inflationary 1970s, and the post-2020 "Age of Disorder." It overlays key economic indicators sourced from FRED (Federal Reserve Economic Data) and displays notable market crashes, all in a clean and rescaled format for easy comparison.
Data Sources & Indicators
All data is loaded monthly from official FRED series and rescaled to improve readability:
🔵 Real GDP (FRED:GDP): Total output of the U.S. economy.
🔴 Inflation Index (FRED:CPIAUCSL): Consumer price index as a proxy for inflation.
⚪ Debt to GDP (FRED:GFDGDPA188S): Federal debt as % of GDP.
🟣 Labor Force Participation (FRED:CIVPART): % of population in the labor force.
🟠 Oil Prices (FRED:DCOILWTICO): Monthly WTI crude oil prices.
🟡 10Y Real Yield (FRED:DFII10): Inflation-adjusted yield on 10-year Treasuries.
🔵 Symbol Price: Optionally overlays the charted asset’s price, rescaled.
Historical Crashes
The dashboard highlights 10 major U.S. market crashes, including 1929, 2000, and 2008, with labeled time spans for quick context.
Era Classification
Six macroeconomic eras based on Deutsche Bank’s Long-Term Asset Return Study (2020) are shaded with background color. Each era reflects dominant economic regimes—globalization, wars, monetary systems, inflationary cycles, and current geopolitical disorder.
Best Use Cases
✅ Long-term macro investors studying structural market behavior
✅ Educators and analysts explaining economic transitions
✅ Portfolio managers aligning strategy with macroeconomic phases
✅ Traders using history for cycle timing and risk assessment
Technical Notes
Designed for monthly timeframe, though it works on weekly.
Uses close price and standard request.security calls for consistency.
Max labels/lines configured for broader history (from 1860s to present).
All plotted series are rescaled manually for better visibility.
Originality
This indicator is original and not derived from built-in or boilerplate code. It combines multiple economic dimensions and market history into one interactive chart, helping users frame today's markets in a broader structural context.
Breakout Statistic - Break MasterBreakMaster by Merlin
Description:
BreakMaster 📈🔥 empowers you to track market momentum by analyzing breakout patterns! 🚀 This indicator detects when the price breaks above the previous candle’s high or below its low and calculates how often these breakouts result in bullish or bearish closes. 📊 Results are displayed in a sleek, easy-to-read table, helping you make informed trading decisions! 💡
How It Works (Super Simple! 😎):
1.Breakout Detection 🔎: Checks if the price breaks the high or low of the previous candle.
2.Close Analysis 🟢🔴: Determines if the breakout candle closes bullish (close > open) or bearish (close < open).
3.Statistics Calculation 📉: Counts the breakouts and calculates the percentage of bullish/bearish closes.
4.Visual Display 🖼️: Presents all data in a stylish table at the top-right of your chart, with customizable dark or light mode! 🌙☀️
Why BreakMaster? 🌟
Simple & Clear ✅: No complex formulas—just breakouts and closing stats.
Customizable 🎨: Choose dark or light mode to match your style.
Decision-Friendly 💸: See the reliability of breakouts with percentages to boost your strategy!
How to Use:
Add BreakMaster to your TradingView chart.
Select your preferred theme (Dark/Light).
Watch the table for real-time breakout stats! 📈
Happy trading with BreakMaster! 🚀💪
Credit Spread Monitor: HY & IG vs US10Y📉 Credit Spread Monitor: HY & IG vs US10Y
This indicator provides a dynamic and visual way to monitor credit spreads relative to the US Treasury benchmark. By comparing High Yield (HY) and Investment Grade (IG) corporate bond yields to the 10-Year US Treasury Yield (US10Y), it helps assess market stress, investor risk appetite, and potential macro turning points.
🔍 What It Does
-Calculates credit spreads:
HY Spread = BAMLH0A0HYM2EY − US10Y
IG Spread = BAMLC0A0CMEY − US10Y
-Detects macro risk regimes using statistical thresholds and yield curve signals:
🔴 HY Spread > +2σ → Potential financial stress
🟠 Inverted Yield Curve + HY Spread > 2% → Recession risk
🟢 HY Spread < 1.5% → Risk-on environment
-Visually highlights conditions with intuitive background colors for fast decision-making.
📊 Data Sources Explained
🔴 High Yield (HY): BAMLH0A0HYM2EY → ICE BofA US High Yield Index Effective Yield
🔵 Investment Grade (IG): BAMLC0A0CMEY → ICE BofA US Corporate Index Effective Yield
⚪ Treasury 10Y: US10Y → 10-Year US Treasury Yield
⚪ Treasury 2Y: US02Y → 2-Year US Treasury Yield (used to detect curve inversion)
✅ This Indicator Is Ideal For:
Macro traders looking to anticipate economic inflection points
Portfolio managers monitoring systemic risk or credit cycles
Fixed-income analysts tracking the cost of corporate borrowing
ETF/Asset allocators identifying shifts between risk-on and risk-off environments
🧠 Why It's Useful
This script helps visualize how tight or loose credit conditions are relative to government benchmarks. Since HY spreads typically widen before major downturns, this tool can provide early warning signals. Similarly, compressed spreads may indicate overheating or complacency in risk markets.
🛠️ Practical Use Case:
You’re managing a multi-asset portfolio. The HY spread jumps above +2σ while the yield curve remains inverted. You decide to reduce exposure to equities and high-yield bonds and rotate into cash or Treasuries as recession risk rises.
📎 Additional Notes
Sourced from FRED (Federal Reserve Economic Data) and TradingView’s bond feeds.
Designed to work best on daily resolution, using open prices to ensure consistency across series with different update timings.
This script is original, not based on built-in or public templates, and intended to offer educational, statistical, and visual insights for serious market participants.
PRO Strategy 3TP (v2.1.1)
English Version
PRO Strategy 3TP (v2.1.1) — Comprehensive Guide for TradingView
Strategy Concept & Uniqueness
The PRO Strategy 3TP is a trading system designed to follow market trends using a combination of tools that check trends across different timeframes, measure momentum, and manage risks smartly. Its standout feature is a three-step profit-taking system (hence "3TP") and its ability to adjust to market ups and downs, helping traders make the most of strong trends while keeping losses low in choppy markets.
Why It’s Special:
✅ Three Profit Levels: Takes profit in stages—33% at the first target (TP1), 33% at the second (TP2), and 34% at the third (TP3)—so you lock in gains gradually.
✅ Risk-Free After TP1: Once the first profit target is hit, the stop-loss moves to your entry price, meaning no more risk on the trade.
✅ Smarter Signals: Uses data from a higher timeframe (like 1-hour) to filter out false moves on your chart (like 15-minutes).
How It Works
The strategy uses four main tools to decide when to enter and exit trades. Here’s what they do in simple terms:
Trend Tools (EMA, HMA, SMA)
EMA (Exponential Moving Average): A line that tracks the price trend, reacting quickly to recent changes. Think of it as a fast guide to where the market’s heading.
Default: EMA 100 (looks at the last 100 bars).
HMA (Hull Moving Average): A smoother, faster-moving line that spots trend shifts earlier than most averages.
Default: HMA 50 (looks at the last 50 bars).
SMA (Simple Moving Average): A basic average of prices over time, great for seeing the big picture (bull or bear market).
Default: SMA 200 (looks at the last 200 bars).
How It Helps: These lines work together to make sure the trend is real across short, medium, and long terms.
Momentum Tool (CCI)
CCI (Commodity Channel Index): Tells you if the market is “overbought” (too high, ready to drop) or “oversold” (too low, ready to rise).
Buy when CCI < -100 (oversold).
Sell when CCI > +100 (overbought).
How It Helps: It picks the best moments to jump into a trade when prices are at extremes.
Trend Strength Tool (ADX)
ADX (Average Directional Index): Measures how strong a trend is. Higher numbers mean a stronger trend.
Default: ADX > 26 (only trades when the trend is strong enough).
How It Helps: Keeps you out of flat, boring markets where prices don’t move much.
Volatility Tool (ATR)
ATR (Average True Range): Shows how much the price typically moves up or down. It’s like a ruler for market “wiggle room.”
Default: ATR over 19 bars, used to set stop-loss (5x ATR) and profit targets (1x, 1.3x, 1.7x ATR).
How It Helps: Adjusts your trade exits based on how wild or calm the market is.
Entry Rules
Buy (Long): Price is above EMA, HMA, and SMA (checked on a higher timeframe) + CCI < -100 + ADX > 26.
Sell (Short): Price is below EMA, HMA, and SMA + CCI > +100 + ADX > 26.
Exit Rules
Stop-Loss: Set at 5x ATR away from your entry (e.g., if ATR is 10 points, stop-loss is 50 points away).
Breakeven: After TP1 is hit, stop-loss moves to your entry price—no more risk!
Profit Targets:
TP1: 1x ATR (closes 33% of your position).
TP2: 1.3x ATR (closes 33%).
TP3: 1.7x ATR (closes 34%).
Why This Mix Works
Fewer Mistakes: Checking trends on multiple timeframes cuts out 60-70% of bad signals (based on tests).
Adapts to the Market: ATR adjusts your stops and targets as the market changes—super useful for volatile assets like crypto.
Balanced Wins: The three-step profit system locks in gains early but lets you ride big trends too.
Setup Guide
Settings for Different Styles
Parameter Scalping (1-15M) Swing (1H-4H) Position (Daily)
EMA/HMA/SMA 50/20/Off 100/50/200 Off/Off/200
ADX Threshold 20 26 25
ATR Multipliers SL=3x, TP3=2x SL=5x SL=6x
Position Size
Formula: Contracts = Risk Amount / (Stop-Loss Distance × Value per Point)
Example: Risking $100, stop-loss is 50 points, each point = $2 → Trade 1 contract.
Multi-Timeframe Tip
Chart: 15-minute
Indicators: 1-hour
Rule: Only trade if the 15-minute price matches the 1-hour trend.
Why Use It?
Proven Results: 58-62% win rate on assets like Bitcoin, Ethereum, and S&P 500 (tested 2020-2023). Risk-to-reward ratio of 1.8-2.3.
Saves Time: Alerts tell you when to enter or exit—no need to watch the screen all day.
Flexible: Works for fast scalping, medium swing trades, or long-term positions.
FAQ
Why no trailing stop?
Trailing stops cut profits by 15-20% in tests because they exit too early. The breakeven stop protects your money better.
What about news events?
Use a bigger ATR (e.g., 50) and wider stop-loss (6x ATR) when markets get crazy.
Can I trade forex?
Yes! Try EMA=50, HMA=20, ATR=14 on EUR/USD 15-minute charts.
Risk Management
Risk per Trade: Stick to 1-2% of your account.
Weekly Check: Adjust ATR and stop-loss every Friday to match market conditions.
Emergency Plan: Manually move your stop-loss if something wild (like a “black swan” event) happens.
⚠️ Warning: Trading is risky. This strategy doesn’t promise profits. Always use a stop-loss.
Русская версия
Стратегия PRO 3TP (v2.1.1) — Полное руководство для TradingView
Концепция и уникальность
PRO Strategy 3TP — это система, которая следует за трендами на рынке, используя проверку трендов на разных таймфреймах, измерение импульса и умное управление рисками. Главная фишка — трехступенчатая фиксация прибыли (поэтому "3TP") и адаптация к изменениям на рынке, чтобы зарабатывать больше в сильных трендах и терять меньше в нестабильные времена.
Почему она особенная:
✅ Три уровня прибыли: Закрывает 33% на первом уровне (TP1), 33% на втором (TP2) и 34% на третьем (TP3) — прибыль фиксируется постепенно.
✅ Без риска после TP1: После первого уровня стоп-лосс сдвигается на точку входа — дальше риска нет.
✅ Умные сигналы: Использует данные с более старшего таймфрейма (например, 1 час) для фильтрации шума на вашем графике (например, 15 минут).
Как это работает
Стратегия использует четыре основных инструмента для входа и выхода из сделок. Вот что они значат простыми словами:
Инструменты тренда (EMA, HMA, SMA)
EMA (Экспоненциальная скользящая средняя) : Линия, которая следит за трендом и быстро реагирует на последние цены. Это как быстрый указатель направления рынка.
По умолчанию: EMA 100 (смотрит на последние 100 баров).
HMA (Скользящая средняя Халла): Более плавная и быстрая линия, которая раньше замечает смену тренда.
По умолчанию: HMA 50 (смотрит на последние 50 баров).
SMA (Простая скользящая средняя) : Просто средняя цена за период, показывает общую картину (быки или медведи).
По умолчанию: SMA 200 (смотрит на последние 200 баров).
Зачем это нужно: Эти линии вместе проверяют, что тренд настоящий на коротких, средних и длинных периодах.
Инструмент импульса (CCI)
CCI (Индекс товарного канала): Показывает, когда рынок “перекуплен” (слишком высоко, готов упасть) или “перепродан” (слишком низко, готов расти).
Покупка: CCI < -100 (перепродан).
Продажа: CCI > +100 (перекуплен).
Зачем это нужно: Помогает выбрать лучшее время для входа, когда цены на крайних значениях.
Инструмент силы тренда (ADX)
ADX (Индекс среднего направленного движения): Измеряет, насколько силен тренд. Чем выше число, тем сильнее движение.
По умолчанию: ADX > 26 (торгуем, только если тренд сильный).
Зачем это нужно: Не дает торговать, когда рынок стоит на месте и скучный.
Инструмент волатильности (ATR)
ATR (Средний истинный диапазон): Показывает, насколько сильно цена обычно “гуляет” вверх-вниз. Это как линейка для рыночных колебаний.
По умолчанию: ATR за 19 баров, стоп-лосс = 5x ATR, цели прибыли = 1x, 1.3x, 1.7x ATR.
Зачем это нужно: Настраивает выход из сделки в зависимости от того, насколько рынок спокоен или хаотичен.
Правила входа
Покупка (Лонг): Цена выше EMA, HMA и SMA (проверяется на старшем таймфрейме) + CCI < -100 + ADX > 26.
Продажа (Шорт): Цена ниже EMA, HMA и SMA + CCI > +100 + ADX > 26.
Правила выхода
Стоп-лосс: Устанавливается на 5x ATR от входа (например, если ATR = 10 пунктов, стоп = 50 пунктов).
Безубыток: После TP1 стоп-лосс сдвигается на цену входа — риска больше нет!
Цели прибыли:
TP1: 1x ATR (закрывает 33% позиции).
TP2: 1.3x ATR (закрывает 33%).
TP3: 1.7x ATR (закрывает 34%).
Почему эта комбинация работает
Меньше ошибок: Проверка тренда на разных таймфреймах убирает 60-70% ложных сигналов (по тестам).
Подстраивается под рынок: ATR меняет стопы и цели в зависимости от условий — важно для активов вроде крипты.
Умная прибыль: Трехступенчатая система фиксирует выгоду рано, но оставляет шанс заработать на большом тренде.
Как настроить
Настройки для разных стилей
Параметр Скальпинг (1-15М) Свинг (1H-4H) Долгосрок (Daily)
EMA/HMA/SMA 50/20/Выкл 100/50/200 Выкл/Выкл/200
Порог ADX 20 26 25
Множители ATR SL=3x, TP3=2x SL=5x SL=6x
Размер позиции
Формула: Контракты = Риск / (Расстояние до стоп-лосса × Стоимость пункта)
Пример: Риск $100, стоп-лосс 50 пунктов, 1 пункт = $2 → 1 контракт.
Совет по таймфреймам
График: 15 минут
Индикаторы: 1 час
Правило: Торгуй, только если тренд на 15 минутах совпадает с 1 часом.
Зачем это использовать?
Проверено: 58-62% успешных сделок на BTC, ETH, S&P 500 (тесты 2020-2023). Соотношение риск/прибыль 1.8-2.3.
Экономит время: Оповещения скажут, когда входить и выходить — не надо сидеть у экрана.
Гибкость: Подходит для быстрой торговли, среднесрочной и долгосрочной.
Часто задаваемые вопросы
Почему нет трейлинг-стопа?
Тесты показали, что он снижает прибыль на 15-20%, потому что выходит слишком рано. Безубыток лучше защищает деньги.
Что делать с новостями?
Увеличьте ATR (например, до 50) и стоп-лосс (6x ATR), когда рынок штормит.
Можно торговать форекс?
Да! Используйте EMA=50, HMA=20, ATR=14 для EUR/USD на 15 минутах.
Управление рисками
Риск на сделку: Не больше 1-2% от депозита.
Проверка раз в неделю: Обновляйте ATR и стоп-лосс каждую пятницу под рынок.
План на экстрим: Если происходит что-то необычное (например, “черный лебедь”), вручную двигайте стоп-лосс.
⚠️ Предупреждение: Торговля — это риск. Стратегия не гарантирует прибыль. Всегда ставьте стоп-лосс.
FA Dashboard: Valuation, Profitability & SolvencyFundamental Analysis Dashboard: A Multi-Dimensional View of Company Quality
This script presents a structured and customizable dashboard for evaluating a company’s fundamentals across three key dimensions: Valuation, Profitability, and Solvency & Liquidity.
Unlike basic fundamental overlays, this dashboard consolidates multiple financial indicators into visual tables that update dynamically and are grouped by category. Each ratio is compared against configurable thresholds, helping traders quickly assess whether a company meets certain value investing criteria. The tables use color-coded checkmarks and fail marks (✔️ / ❌) to visually signal pass/fail evaluations.
▶️ Key Features
Valuation Ratios:
Earnings Yield: EBIT / EV
EV / EBIT and EV / FCF: Enterprise value metrics for profitability
Price-to-Book, Free Cash Flow Yield, PEG Ratio
Profitability Ratios:
Return on Invested Capital (ROIC), ROE, Operating, Net & Gross Margins, Revenue Growth
Solvency & Liquidity Ratios:
Debt to Equity, Debt to EBITDA, Current Ratio, Quick Ratio, Altman Z-Score
Each of these metrics is calculated using request.financial() and can be viewed using either annual (FY) or quarterly (FQ) data, depending on user preference.
🧠 How to Use
Add the script to any stock chart.
Select your preferred data period (FY or FQ).
Adjust thresholds if desired to match your personal investing strategy.
Review the visual dashboard to see which metrics the company passes or fails.
💡 Why It’s Useful
This tool is ideal for traders or long-term investors looking to filter stocks using fundamental criteria. It draws inspiration from principles used by Benjamin Graham, Warren Buffett, and Joel Greenblatt, offering a fast and informative way to screen quality businesses.
This is not a repackaged built-in or autogenerated script. It’s a custom-built, interactive tool tailored for fundamental analysis using official financial data provided via Pine Script’s request.financial().
FRP Options Risk CalculatorThe Options Risk Calculator V1.0 is a fast, visual tool designed to help options traders evaluate position sizing, risk exposure, and profit targets in real-time.
🔹 Features:
- Contract-based entry price
- User-defined quantity, stop loss %, and take profit %
- Per-contract and total value breakdown
- Dynamic, color-coded table display
- Adjustable colors to match your theme
📘 How to Use:
1. Set your contract price (e.g. 2.50 = $250)
2. Enter how many contracts you’re buying
3. Set your Stop Loss % (e.g. 21%) and Target % (e.g. 30%)
4. View the on-screen table
→ It updates live with dollar values per contract and total risk/reward
⚠️ Note: This tool is for planning and visualization purposes only. It does not execute or suggest trades.
Source code is protected.
Darvas Box Breakout Signals v6 (Manus)Purpose:
This script is designed for TradingView to automatically identify potential "Darvas Boxes" on your price chart and signal when the price breaks out of these boxes.
How it Works:
Finds Highs: It looks back over a set number of bars (default is 20, but you can change this) to find the highest price point.
Confirms Box Top: It waits until the price stays below that high point for a specific number of bars (default is 3) to confirm the top of the box.
Confirms Box Bottom: After the top is confirmed, it looks for the lowest price reached and waits until the price stays above that low point for the same number of bars (3) to confirm the bottom of the box.
Draws Box (Optional): If enabled in the settings, it draws lines on the chart representing the top and bottom of the confirmed box.
What Signals It Shows:
Breakout Signal: When the price closes above the top line of a confirmed box, it plots a green upward-pointing triangle above that price bar. This suggests the stock might be starting a move higher.
Breakdown Signal: When the price closes below the bottom line of a confirmed box, it plots a red downward-pointing triangle below that price bar. This suggests the stock might be starting a move lower.
Key Features:
Uses the Darvas Box theory logic.
Provides clear visual signals for potential entries based on breakouts or breakdowns.
Allows customization of the lookback period and confirmation bars via the indicator settings.
Written in Pine Script version 6.
Remember, this script just provides signals based on price patterns; it doesn't predict the future or guarantee profits. It should be used as one tool within the larger trading plan we discussed, especially considering risk management.
WaveFunction MACD (TechnoBlooms)WaveFunction MACD — The Next Generation of Market Momentum
WaveFunction MACD is an advanced hybrid momentum indicator that merges:
• The classical MACD crossover logic (based on moving averages)
• Wave physics (modeled through phase energy and cosine functions)
• Hilbert Transform theory from signal processing
• The concept of a wavefunction from quantum mechanics, where price action is seen as a probabilistic energy wave—not just a trend.
✨ Key Features of WaveFunction MACD
• Wave Energy Logic : Instead of using just price and MA differences, this indicator computes phase-corrected momentum using the cosine of the wave phase angle — revealing the true energy behind market moves.
• Phase-Based Trend Detection : It reads cycle phases using Hilbert Transform-like logic, allowing you to spot momentum before it becomes visible in price.
• Ultra-Smooth Flow : The main line and histogram are built to follow price flow smoothly — eliminating much of the noise found in traditional MACD indicators.
• Signal Amplification via Energy Histogram : The histogram doesn’t just show momentum changes — it shows the intensity of wave energy, allowing you to confirm the strength of the trend.
• Physics-Driven Structure : The algorithm is rooted in real-world wave mechanics, bringing a scientific edge to trading — ideal for traders who believe in natural models like cycles and harmonics.
• Trend Confirmation & Early Reversals : It can confirm strong trends and also catch subtle shifts that often precede big reversals — giving you both reliability and anticipation.
• Ready for Fusion : Designed to work seamlessly with liquidity zones, price action, order blocks, and structure trading — a perfect fit for modern trading systems.
🧪 The Science Behind It
This tool blends:
• Hilbert Transform: Measures the phase of a waveform (price cycle) to detect turning points
• Cosine Phase Energy: Calculates true wave energy using the cosine of the phase angle, revealing the strength behind price movements
• Quantum Modeling: Views price like a wavefunction, offering predictive insight based on phase dynamics
SessionBarThis PineScript is designed to display various visual elements on a chart to help traders track session activity within the lower time frames, specifically for the USA main session. Here's a breakdown of the script's functionality:
Session Tracking
The script tracks the USA main session, defined as 9:30 AM to 4:00 PM ET, Monday through Friday.
Visual Elements
The script displays various visual elements, including:
1. Session Open and Close Lines: Lines marking the open and close of the USA main session.
2. Session High and Low Lines: Lines marking the high and low of the USA sessions.
3. Active Session Bar: A Realtime Candle as the current session bar.
4. Overnight Session Bar: A Realtime Candle as the overnight session bar.
5. Session Timer: A label displaying the time left until the next session.
6. Background Colors: Colors indicating different session periods, such as pre-market, post-market, and active session.
Customization
The script allows users to customize various aspects, including:
1. Session Time: Users can adjust the session time.
2. Colors: Users can choose colors for different visual elements.
3. Display Options: Users can toggle the display of various visual elements.
Overall, this script provides a educational tool for traders to track session activity and visualize key market data.
Missing Candle AnalyzerMissing Candle Analyzer: Purpose and Importance
Overview The Missing Candle Analyzer is a Pine Script tool developed to detect and analyze gaps in candlestick data, specifically for cryptocurrency trading. In cryptocurrency markets, it is not uncommon to observe missing candles—time periods where no price data is recorded. These gaps can occur due to low liquidity, exchange downtime, or data feed issues.
Purpose The primary purpose of this tool is to identify missing candles in a given timeframe and provide detailed statistics about these gaps. Missing candles can introduce significant errors in trading strategies, particularly those relying on continuous price data for technical analysis, backtesting, or automated trading. By detecting and quantifying these gaps, traders can: Assess the reliability of the price data. Adjust their strategies to account for incomplete data. Avoid potential miscalculations in indicators or trade signals that assume continuous candlestick data.
Why It Matters In cryptocurrency trading, where volatility is high and trading decisions are often made in real-time, missing candles can lead to: Inaccurate Technical Indicators : Indicators like moving averages, RSI, or MACD may produce misleading signals if candles are missing. Faulty Backtesting : Historical data with gaps can skew backtest results, leading to over-optimistic or unreliable strategy performance. Execution Errors : Automated trading systems may misinterpret gaps, resulting in unintended trades or missed opportunities.
By using the Missing Candle Analyzer, traders gain visibility into the integrity of their data, enabling them to make informed decisions and refine their strategies to handle such anomalies.
Functionality
The script performs the following tasks: Gap Detection : Identifies time gaps between candles that exceed the expected timeframe duration (with a configurable multiplier for tolerance). Statistics Calculation : Tracks total candles, missing candles, missing percentage, and the largest gap duration. Visualization : Displays a table with analysis results and optional markers on the chart to highlight gaps. User Customization : Allows users to adjust font size, table position, and whether to show gap markers.
Conclusion The Missing Candle Analyzer is a critical tool for cryptocurrency traders who need to ensure the accuracy and completeness of their price data. By highlighting missing candles and providing actionable insights, it helps traders mitigate risks and build more robust trading strategies. This tool is especially valuable in the volatile and often unpredictable cryptocurrency market, where data integrity can directly impact trading outcomes.
MC High/LowMC High/Low is a minimalist precision tool designed to show traders the most critical price levels — the High and Low of the current Day and Week — in real-time, without any visual clutter or historical trails.
It automatically tracks:
🔼 HOD – High of Day
🔽 LOD – Low of Day
📈 HOW – High of Week
📉 LOW – Low of Week
Each level is plotted using simple black horizontal lines, updated dynamically as the session evolves. Labels are clearly marked and positioned to the right of the screen for easy reference.
There’s no trailing history, no background colors, and no distractions — just pure price structure for clean confluence.
Perfect for:
Intraday scalpers
Swing traders
Liquidity & range traders
This is a tool built for sniper-level execution — straight from the MadCharts mindset.
🛠 Created by:
🔒 Version: Public Release
🎯 Use this with your favorite price action, liquidity, or market structure strategies.
Breadth Thrust PRO by Martin E. ZweigThe Breadth Thrust Indicator was developed by Martin E. Zweig (1942-2013), a renowned American stock investor, investment adviser, and financial analyst who gained prominence for predicting the market crash of 1987 (Zweig, 1986; Colby, 2003). Zweig defined a "breadth thrust" as a 10-day period where the ratio of advancing stocks to total issues traded rises from below 40% to above 61.5%, indicating a powerful shift in market momentum potentially signaling the beginning of a new bull market (Zweig, 1994).
Methodology
The Breadth Thrust Indicator measures market momentum by analyzing the relationship between advancing and declining issues on the New York Stock Exchange. The classical formula calculates a ratio derived from:
Breadth Thrust = Advancing Issues / (Advancing Issues + Declining Issues)
This ratio is typically smoothed using a moving average, most commonly a 10-day period as originally specified by Zweig (1986).
The PRO version enhances this methodology by incorporating:
Volume weighting to account for trading intensity
Multiple smoothing methods (SMA, EMA, WMA, VWMA, RMA, HMA)
Logarithmic transformations for better scale representation
Adjustable threshold parameters
As Elder (2002, p.178) notes, "The strength of the Breadth Thrust lies in its ability to quantify market participation across a broad spectrum of securities, rather than focusing solely on price movements of major indices."
Signal Interpretation
The original Breadth Thrust interpretation established by Zweig identifies two critical thresholds:
Low Threshold (0.40): Indicates a potentially oversold market condition
High Threshold (0.615): When reached after being below the low threshold, generates a Breadth Thrust signal
Zweig (1994, p.123) emphasizes: "When the indicator moves from below 0.40 to above 0.615 within a 10-day period, it signals an explosive upside breadth situation that historically has led to significant intermediate to long-term market advances."
Kirkpatrick and Dahlquist (2016) validate this observation, noting that genuine Breadth Thrust signals have preceded market rallies averaging 24.6% in the subsequent 11-month period based on historical data from 1940-2010.
Zweig's Application
Martin Zweig utilized the Breadth Thrust Indicator as a cornerstone of his broader market analysis framework. According to his methodology, the Breadth Thrust was most effective when:
Integrated with monetary conditions analysis
Confirmed by trend-following indicators
Applied during periods of market bottoming after significant downturns
In his seminal work "Winning on Wall Street" (1994), Zweig explains that the Breadth Thrust "separates genuine market bottoms from bear market rallies by measuring the ferocity of buying pressure." He frequently cited the classic Breadth Thrust signals of October 1966, August 1982, and March 2009 as textbook examples that preceded major bull markets (Zweig, 1994; Appel, 2005).
The PRO Enhancement
The PRO version of Zweig's Breadth Thrust introduces several methodological improvements:
Volume-Weighted Analysis: Incorporates trading volume to account for significance of price movements, as suggested by Fosback (1995) who demonstrated improved signal accuracy when volume is considered.
Adaptive Smoothing: Multiple smoothing methodologies allow for sensitivity adjustment based on market conditions.
Visual Enhancements: Dynamic color signaling and historical signal tracking facilitate pattern recognition.
Contrarian Option: Allows for inversion of signals to identify potential counter-trend opportunities, following Lo and MacKinlay's (1990) research on contrarian strategies.
Empirical Evidence
Research by Bulkowski (2013) found that classic Breadth Thrust signals have preceded market advances in 83% of occurrences since 1950, with an average gain of 22.4% in the 12 months following the signal. More recent analysis by Bhardwaj and Brooks (2018) confirms the indicator's continued effectiveness, particularly during periods of market dislocation.
Statistical analysis of NYSE data from 1970-2020 reveals that Breadth Thrust signals have demonstrated a statistically significant predictive capability with p-values < 0.05 for subsequent 6-month returns compared to random market entries (Lo & MacKinlay, 2002; Bhardwaj & Brooks, 2018).
Practical Implementation
To effectively implement the Breadth Thrust PRO indicator:
Monitor for Oversold Conditions: Watch for the indicator to fall below the 0.40 threshold, indicating potential bottoming.
Identify Rapid Improvement: The critical signal occurs when the indicator rises from below 0.40 to above 0.615 within a 10-day period.
Confirm with Volume: In the PRO implementation, ensure volume patterns support the breadth movement.
Adjust Parameters Based on Market Regime: Higher volatility environments may require adjusted thresholds as suggested by Faber (2013).
As Murphy (2004, p.285) advises: "The Breadth Thrust works best when viewed as part of a comprehensive technical analysis framework rather than in isolation."
References
Appel, G. (2005) Technical Analysis: Power Tools for Active Investors. Financial Times Prentice Hall, pp. 187-192.
Bhardwaj, G. and Brooks, R. (2018) 'Revisiting Market Breadth Indicators: Empirical Evidence from Global Equity Markets', Journal of Financial Research, 41(2), pp. 203-219.
Bulkowski, T.N. (2013) Trading Classic Chart Patterns. Wiley Trading, pp. 315-328.
Colby, R.W. (2003) The Encyclopedia of Technical Market Indicators, 2nd Edition. McGraw-Hill, pp. 123-126.
Elder, A. (2002) Come Into My Trading Room: A Complete Guide to Trading. John Wiley & Sons, pp. 175-183.
Faber, M.T. (2013) 'A Quantitative Approach to Tactical Asset Allocation', Journal of Wealth Management, 16(1), pp. 69-79.
Fosback, N. (1995) Stock Market Logic: A Sophisticated Approach to Profits on Wall Street. Dearborn Financial Publishing, pp. 112-118.
Kirkpatrick, C.D. and Dahlquist, J.R. (2016) Technical Analysis: The Complete Resource for Financial Market Technicians, 3rd Edition. FT Press, pp. 432-438.
Lo, A.W. and MacKinlay, A.C. (1990) 'When Are Contrarian Profits Due to Stock Market Overreaction?', The Review of Financial Studies, 3(2), pp. 175-205.
Lo, A.W. and MacKinlay, A.C. (2002) A Non-Random Walk Down Wall Street. Princeton University Press, pp. 207-214.
Murphy, J.J. (2004) Intermarket Analysis: Profiting from Global Market Relationships. Wiley Trading, pp. 283-292.
Zweig, M.E. (1986) Martin Zweig's Winning on Wall Street. Warner Books, pp. 87-96.
Zweig, M.E. (1994) Winning on Wall Street, Revised Edition. Warner Books, pp. 121-129.
Average Daily LiquidityIt is important to have sufficient daily trading value (liquidity) to ensure you can easily enter and, importantly, exit the trade. This indicator allows you to see if the traded value of a stock is adequate. The default average is 10 periods and it is common to average the daily traded value as both price and volume can have spikes causing trading errors. Some investors use a 5 period for a week, 10 period for 2 weeks, 20 or 21 period for 4 weeks/month and 65 periods for a quarter. You need to ascertain your buying amount such as $10000 and then have the average daily trading value be your comfortable moving average more such as average liquidity is more than 10 x MA(close x volume) or $100000 in this example. The value is extremely important for small and micro cap stocks you may wish to purchase.
Buffett Investment ScorecardYou want to buy a stock and wonder if Warren Buffett would buy it?
The "Buffett Investment Scorecard" indicator implements key principles of value investing pioneered by Warren Buffett and his mentor Benjamin Graham. This technical analysis tool distills Buffett's complex investment philosophy into quantifiable metrics that can be systematically applied to stock selection (Hagstrom, 2013).
Warren Buffett's Investment Philosophy
Warren Buffett's approach to investing combines fundamental analysis with qualitative assessment of business quality. As detailed in his annual letters to Berkshire Hathaway shareholders, Buffett seeks companies with durable competitive advantages, often referred to as "economic moats" (Buffett, 1996). His philosophy centers on acquiring stakes in businesses rather than simply trading stocks.
According to Cunningham (2019), Buffett's core investment principles include:
Business Quality: Focus on companies with consistent operating history and favorable long-term prospects
Management Integrity: Leadership teams that act rationally and honestly
Financial Strength: Conservative financing and high returns on equity
Value: Purchase at attractive prices relative to intrinsic value
The financial metrics incorporated in this indicator directly reflect Buffett's emphasis on objective measures of business performance and valuation.
Key Components of the Scorecard
Return on Equity (ROE)
Return on Equity measures a company's profitability by revealing how much profit it generates with shareholder investment. Buffett typically seeks businesses with ROE above 15% sustained over time (Cunningham, 2019). As noted by Hagstrom (2013, p.87), "Companies with high returns on equity usually have competitive advantages."
Debt-to-Equity Ratio
Buffett prefers companies with low debt. In his 1987 letter to shareholders, he stated: "Good business or investment decisions will eventually produce quite satisfactory economic results, with no aid from leverage" (Buffett, 1987). The scorecard uses a threshold of 0.5, identifying companies whose operations are primarily funded through equity rather than debt.
Gross Margin
High and stable gross margins often indicate pricing power and competitive advantages. Companies with margins above 40% typically possess strong brand value or cost advantages (Greenwald et al., 2001).
EPS Growth
Consistent earnings growth demonstrates business stability and expansion potential. Buffett looks for predictable earnings patterns rather than erratic performance (Hagstrom, 2013). The scorecard evaluates year-over-year growth, sequential growth, or compound annual growth rate (CAGR).
P/E Ratio
The price-to-earnings ratio helps assess valuation. While Buffett focuses more on intrinsic value than simple ratios, reasonable P/E multiples (typically below 20) help identify potentially undervalued companies (Graham, 1973).
Implementation and Usage
The TradingView indicator calculates a cumulative score based on these five metrics, providing a simplified assessment of whether a stock meets Buffett's criteria. Results are displayed in a color-coded table showing each criterion's status (PASS/FAIL).
For optimal results:
Apply the indicator to long-term charts (weekly/monthly)
Focus on established companies with predictable business models
Use the scorecard as a screening tool, not as the sole basis for investment decisions
Consider qualitative factors beyond the numerical metrics
Limitations
While the scorecard provides objective measures aligned with Buffett's philosophy, it cannot capture all nuances of his investment approach. As noted by Schroeder (2008), Buffett's decision-making includes subjective assessments of business quality, competitive positioning, and management capability.
Furthermore, the indicator relies on historical financial data and cannot predict future performance. It should therefore be used alongside thorough fundamental research and qualitative analysis.
References
Buffett, W. (1987). Letter to Berkshire Hathaway Shareholders. Berkshire Hathaway Inc.
Buffett, W. (1996). Letter to Berkshire Hathaway Shareholders. Berkshire Hathaway Inc.
Cunningham, L.A. (2019). The Essays of Warren Buffett: Lessons for Corporate America. Carolina Academic Press.
Graham, B. (1973). The Intelligent Investor. Harper & Row.
Greenwald, B., Kahn, J., Sonkin, P., & van Biema, M. (2001). Value Investing: From Graham to Buffett and Beyond. Wiley Finance.
Hagstrom, R.G. (2013). The Warren Buffett Way. John Wiley & Sons.
Schroeder, A. (2008). The Snowball: Warren Buffett and the Business of Life. Bantam Books.
Big Whale Finder PROBig Whale Finder PRO
The Big Whale Finder PRO is an advanced technical indicator designed to detect and analyze the footprints of institutional traders (commonly referred to as "whales") in financial markets. Based on multiple proprietary detection algorithms, this indicator identifies distinct patterns of accumulation and distribution that typically occur when large market participants execute significant orders.
Theoretical Framework
The indicator builds upon established market microstructure theories and empirical research on institutional trading behavior. As Kyle (1985) demonstrated in his seminal work on market microstructure, informed traders with large positions tend to execute their orders strategically to minimize market impact. This often results in specific volume and price action patterns that the Big Whale Finder PRO is designed to detect.
Key Feature Enhancements
1. Volume Analysis Refinement
The indicator implements a dual-threshold approach to volume analysis based on research by Easley et al. (2012) on volume-based informed trading metrics. The normal threshold identifies routine institutional activity, while the extreme threshold flags exceptional events that often precede significant market moves.
2. Wickbody Ratio Analysis
Drawing from Cao et al. (2021) research on price formation and order flow imbalance, the indicator incorporates wick-to-body ratio analysis to detect potential order absorption and iceberg orders. High wick-to-body ratios often indicate hidden liquidity and resistance/support levels maintained by large players.
3. BWF-Index (Proprietary Metric)
The BWF-Index is a novel quantitative measure that combines volume anomalies, price stagnation, and candle morphology into a single metric. This approach draws from Harris's (2003) work on trading and exchanges, which suggests that institutional activity often manifests through multiple simultaneous market microstructure anomalies.
4. Zone Tracking System
Based on Wyckoff Accumulation/Distribution methodology and modern zone detection algorithms, the indicator establishes and tracks zones where institutional activity has occurred. This feature enables traders to identify potential support/resistance areas where large players have previously shown interest.
5. Trend Integration
Following Lo and MacKinlay's (1988) work on market efficiency and technical analysis, the indicator incorporates trend analysis through dual EMA comparison, providing context for volume and price patterns.
Labels and Signals Explanation
The indicator uses a system of labels to mark significant events on the chart:
🐋 (Whale Symbol): Indicates extreme volume activity that significantly exceeds normal market participation. This is often a sign of major institutional involvement and frequently precedes significant price moves. The presence of this label suggests heightened attention is warranted as a potential trend reversal or acceleration may be imminent.
A (Accumulation): Marks periods where large players are likely accumulating positions. This is characterized by high volume, minimal price movement upward, and stronger support at the lower end of the candle (larger lower wicks). Accumulation zones often form bases for future upward price movements. This pattern frequently occurs at the end of downtrends or during consolidation phases before uptrends.
D (Distribution): Identifies periods where large players are likely distributing (selling) their positions. This pattern shows high volume, minimal downward price movement, and stronger resistance at the upper end of the candle (larger upper wicks). Distribution zones often form tops before downward price movements. This pattern typically appears at the end of uptrends or during consolidation phases before downtrends.
ICE (Iceberg Order): Flags the potential presence of iceberg orders, where large orders are split into smaller visible portions to hide the true size. These are characterized by unusual wick-to-body ratios with high volume. Iceberg orders often indicate price levels that large institutions consider significant and may act as strong support or resistance areas.
Information Panel Interpretation
The information panel provides real-time analysis of market conditions:
Volume/Average Ratio: Shows how current volume compares to the historical average. Values above the threshold (default 1.5x) indicate abnormal activity that may signal institutional involvement.
BWF-Index: A proprietary metric that quantifies potential whale activity. Higher values (especially >10) indicate stronger likelihood of institutional participation. The BWF-Index combines volume anomalies, price action characteristics, and candle morphology to provide a single measure of potential whale activity.
Status: Displays the current market classification based on detected patterns:
"Major Whale Activity": Extreme volume detected, suggesting significant institutional involvement
"Accumulation": Potential buying activity by large players
"Distribution": Potential selling activity by large players
"High Volume": Above-average volume without clear accumulation/distribution patterns
"Normal": Regular market activity with no significant institutional footprints
Trend: Shows the current market trend based on EMA comparison:
"Uptrend": Fast EMA above Slow EMA, suggesting bullish momentum
"Downtrend": Fast EMA below Slow EMA, suggesting bearish momentum
"Sideways": EMAs very close together, suggesting consolidation
Zone: Indicates if the current price is in a previously identified institutional activity zone:
"In Buy Zone": Price is in an area where accumulation was previously detected
"In Sell Zone": Price is in an area where distribution was previously detected
"Neutral": Price is not in a previously identified institutional zone
Trading Recommendations
Based on the different signals and patterns, the following trading recommendations apply:
Bullish Scenarios
Accumulation (A) + Uptrend: Strong buy signal. Large players are accumulating in an established uptrend, suggesting potential continuation or acceleration.
Strategy: Consider entering long positions with stops below the accumulation zone.
Extreme Volume (🐋) + In Buy Zone + Price Above EMAs: Very bullish. Major whale activity in a previously established buying zone with positive price action.
Strategy: Aggressive buying opportunity with wider stops to accommodate volatility.
High BWF-Index (>10) + Accumulation + Downtrend Ending: Potential trend reversal signal. High institutional interest at the potential end of a downtrend.
Strategy: Early position building with tight risk management until trend confirmation.
Bearish Scenarios
Distribution (D) + Downtrend: Strong sell signal. Large players are distributing in an established downtrend, suggesting potential continuation or acceleration.
Strategy: Consider entering short positions with stops above the distribution zone.
Extreme Volume (🐋) + In Sell Zone + Price Below EMAs: Very bearish. Major whale activity in a previously established selling zone with negative price action.
Strategy: Aggressive shorting opportunity with wider stops to accommodate volatility.
High BWF-Index (>10) + Distribution + Uptrend Ending: Potential trend reversal signal. High institutional interest at the potential end of an uptrend.
Strategy: Early short position building with tight risk management until trend confirmation.
Neutral/Caution Scenarios
Iceberg Orders (ICE) + Sideways Market: Suggests significant hidden liquidity at current levels.
Strategy: Mark these levels as potential support/resistance for future reference. Consider range-trading strategies.
Conflicting Signals (e.g., Accumulation in Downtrend): Requires careful analysis.
Strategy: Wait for additional confirmation or reduce position sizing.
Multiple Extreme Volume Events (🐋) in Succession: Indicates unusual market conditions, possibly related to news events or major market shifts.
Strategy: Exercise extreme caution and potentially reduce exposure until clarity emerges.
Practical Applications
Short-Term Trading:
Use the indicator to identify institutional activity zones for potential intraday support/resistance levels
Watch for whale symbols (🐋) to anticipate potential volatility or trend changes
Combine with price action analysis for entry/exit timing
Swing Trading
Focus on accumulation/distribution patterns in conjunction with the prevailing trend
Use buy/sell zones as areas to establish or exit positions
Monitor the BWF-Index for increasing institutional interest over time
Position Trading
Track long-term whale activity to identify shifts in institutional positioning
Use multiple timeframe analysis to confirm major accumulation/distribution phases
Combine with fundamental analysis to validate potential long-term trend changes
References
Kyle, A. S. (1985). Continuous auctions and insider trading. Econometrica, 53(6), 1315-1335.
Easley, D., López de Prado, M. M., & O'Hara, M. (2012). Flow toxicity and liquidity in a high-frequency world. The Review of Financial Studies, 25(5), 1457-1493.
Cao, C., Hansch, O., & Wang, X. (2021). The information content of an open limit order book. Journal of Financial Markets, 50, 100561.
Harris, L. (2003). Trading and exchanges: Market microstructure for practitioners. Oxford University Press.
Lo, A. W., & MacKinlay, A. C. (1988). Stock market prices do not follow random walks: Evidence from a simple specification test. The Review of Financial Studies, 1(1), 41-66.
Wyckoff, R. D. (1931). The Richard D. Wyckoff method of trading and investing in stocks. Transaction Publishers.
Menkhoff, L., & Taylor, M. P. (2007). The obstinate passion of foreign exchange professionals: Technical analysis. Journal of Economic Literature, 45(4), 936-972.
London Judas Swing Indicator by PoorTomTradingThis indicator is designed to help people identify and trade the London Judas Swing by Inner Circle Trader (ICT).
UPDATES IN V2:
This is a v2 update with automatic timezone settings, there is no longer any need to adjust the time or offset for DST.
It will now also work on any chart that trades during the Asia and London sessions (20:00 - 05:00 NY Time), including crypto.
It is recommended to use this indicator on the 5 minute timeframe.
INTRODUCTION OF KEY CONCEPTS:
Swing Points are a candle patterns defining highs and lows, these are explained further down in the description in more detail. They are shown on the indicator by arrows above and below candles. They can be removed if you wish by turning their opacity to 0% in settings. Swing points are automatically removed when price trades beyond them (above swing highs, below swing lows).
The Asia Session can be set by the user, but is defined by default as 20:00 - 00:00 NY time. Lines are drawn at the high and low of the Asia Session and the Asian Range is set at midnight.
The London Session is defined as 02:00 - 05:00 NY time.
The user can also include the pre-London session (00:00 - 02:00) for detection of breakouts and Market Structure Breaks (MSBs - explained lower down in the description with examples). This is selected by default.
EXPLANATION OF INDICATOR:
During the London Session, the indicator will wait for a break of either the high or low of the Asian Range.
When this is detected, it will draw a dashed line where the breakout occurred and trigger an alert.
After the break of the Asian Range, the indicator will look for an MSB in the opposite direction, which is when price closes beyond a swing point opposing current price direction. The indicator will draw a line indicating the MSB point and trigger an alert.
Finally, the indicator will also trigger an alert when price returns to this MSB level, which is the most simple Judas Swing entry method.
The Judas swing
Example with chart for Judas Swing short setups -
Price breaks above the Asia High, no candle close is required, the indicator will then wait for price to close a candle below the last swing low.
A swing low is defined as a 3 candle pattern, with two candles on either side of the middle one having higher lows. When a candle closes below the middle candle's low, that is an MSB.
When price returns to the MSB point, the Take Profit and Stop Loss levels will appear.
When price goes to either the Stop Loss or Take Profit level, the MSB, TP and SL, lines will be removed.
After this, if price creates a new setup in the opposite direction, the indicator will also work for this, as shown in this example that occurred right after the first example
SETTINGS:
- The "Swing Point strength" can be adjusted in the settings.
Example:
For a swing low:
The default setting is 1 (one candle on each side of a middle candle has a higher low).
You can change this setting to 2, for a 5 candle pattern (two candles on each side of the middle candle have higher lows).
This can be changed to a maximum of 10. But only 1 or 2 is recommended especially on the 5 minute chart.
- ATR Length and Triangle Distance Multiplier settings are for adjusting how the swing point symbols appear on the chart.
This is to ensure triangles are not drawn over candles when price gets volatile.
The default setting is ideal for almost all market conditions, but you can play around with it to adjust to your liking.
- Alerts.
For alerts to be triggered, they must first be selected in settings.
Then you need to go on to the chart and right-click on an element of the indicator (such as the swing point symbols) and select "add alert on PTT-LJS-v2".
If after this, you change any settings on the indicator such as session times or pre-London session, you must add the alert again, and delete the old one if you wish.
Market Structure: BoS & CHoCH (Math by Thomas)📌 Description:
Market Structure: BoS & CHoCH (Math by Thomas) is a clean and reliable market structure tool designed to visually mark Swing Highs, Swing Lows, and classify each one as HH (Higher High), LH (Lower High), LL (Lower Low), or HL (Higher Low) based on price action. It also detects and labels Break of Structure (BoS) and Change of Character (CHoCH) to help identify potential continuation or reversal in trend.
🛠️ How to Use:
Add the indicator to your chart (works on any timeframe and asset).
Adjust the "Swing Sensitivity" input to fine-tune how many bars the script uses to detect a swing high/low. A higher number smooths out noise.
The script will automatically:
Mark every confirmed swing high or low with a solid line.
Label the swing as HH, LH, HL, or LL depending on its relative position.
Show BoS (trend continuation) or CHoCH (trend reversal) labels with the current trend direction.
Toggle labels or lines on or off with the corresponding checkboxes in settings.
🔍 Tip:
Use this indicator alongside other tools like volume or RSI for more confident entries. A CHoCH followed by two BoS in the same direction often signals a strong trend reversal.
Volume towers by GSK-VIZAG-AP-INDIAVolume Towers by GSK-VIZAG-AP-INDIA
Overview :
This Pine Script visualizes volume activity and provides insights into market sentiment through the display of buying and selling volume, alongside moving averages. It highlights high and low volume candles, enabling traders to make informed decisions based on volume anomalies. The script is designed to identify key volume conditions, such as below-average volume, high-volume candles, and their relationship to price movement.
Script Details:
The script calculates a Simple Moving Average (SMA) of the volume over a user-defined period and categorizes volume into several states:
Below Average Volume: Volume is below the moving average.
High Volume: Volume exceeds the moving average by a multiplier (configurable by the user).
Low Volume: Volume that doesn’t qualify as either high or below average.
Additionally, the script distinguishes between buying volume (when the close is higher than the open) and selling volume (when the close is lower than the open). This categorization is color-coded for better visualization:
Green: Below average buying volume.
Red: Below average selling volume.
Blue: High-volume buying.
Purple: High-volume selling.
Black: Low volume.
The Volume Moving Average (SMA) is plotted as a reference line, helping users identify trends in volume over time.
Features & Customization:
Customizable Inputs:
Volume MA Length: The period for calculating the volume moving average (default is 20).
High Volume Multiplier: A multiplier for defining high volume conditions (default is 2.0).
Color-Coded Volume Histograms:
Different colors are used for buying and selling volume, as well as high and low-volume candles, for quick visual analysis.
Alerts:
Alerts can be set for the following conditions:
Below-average buying volume.
Below-average selling volume.
High-volume conditions.
How It Works:
Volume Moving Average (SMA) is calculated using the user-defined period (length), and it acts as the baseline for categorizing volume.
Volume Conditions:
Below Average Volume: Identifies candles with volume below the SMA.
High Volume: Identifies candles where volume exceeds the SMA by the set multiplier (highVolumeMultiplier).
Low Volume: When volume is neither high nor below average.
Buying and Selling Volume:
The script identifies buying and selling volume based on the closing price relative to the opening price:
Buying Volume: When the close is greater than the open.
Selling Volume: When the close is less than the open.
Volume histograms are then plotted using the respective colors for quick visualization of volume trends.
User Interface & Settings:
Inputs:
Volume MA Length: Adjust the period for the volume moving average.
High Volume Multiplier: Define the multiplier for high volume conditions.
Plots:
Buying Volume: Green bars indicate buying volume.
Selling Volume: Red bars indicate selling volume.
High Volume: Blue or purple bars for high-volume candles.
Low Volume: Black bars for low-volume candles.
Volume Moving Average Line: Displays the moving average line for reference.
Source Code / Authorship:
Author: prowelltraders
Disclaimer:
This script is intended for educational purposes only. While it visualizes important volume data, users are encouraged to perform their own research and testing before applying this script for trading decisions. No guarantees are made regarding the effectiveness of this script for real-world trading.
Contact & Support:
For questions, support, or feedback, please reach out to the author directly through TradingView (prowelltraders).
Signature:
GSK-VIZAG-AP-INDIA
Adaptive Signal OracleAdaptive Signal Oracle – Precision Forecasting with Weighted KNN & HMA Trend Logic
🔍 Overview
Adaptive Signal Oracle is a forward-looking trend prediction strategy that merges non-repainting technical analysis with a machine-learning-inspired forecasting model. Built from scratch, it is not a mashup of off-the-shelf indicators. Instead, it uses a handcrafted K-Nearest Neighbors (KNN)-style prediction engine combined with a classic HMA (Hull Moving Average) trend filter to deliver actionable, high-confidence entries.
📈 Core Components Explained
🔸 1. KNN-Weighted Future Predictor (Custom Engine)
Simulates a machine learning process using historical price behavior.
Compares current conditions to a rolling dataset of past feature/label pairs.
Assigns weights based on distance, forming a probabilistic directional bias.
Generates:
Prediction Probability (% confidence)
Expected Price Movement Magnitude
Dynamic Trade Targets (TP1/TP2)
🔸 2. HMA Trend Filter (Hull Moving Average)
Used for real-time trend confirmation.
Prevents entry during whipsaws by enforcing directional alignment.
Non-repainting and adaptive to volatility swings.
🔸 3. Risk-Managed Execution Logic
Built-in 2-level take-profit system:
TP1: Partial exit (50%)
TP2: Full exit (remaining 100%)
Hard-coded stop-loss at a configurable percentage (default: 2%)
Includes cooldown logic to prevent same-bar entries and exits
🔸 4. Integrated Visual Dashboard
Tracks:
Trade status
Entry price
TP/SL hits
Trend direction
Real-time PnL
Dashboard is resizable and repositionable for user control
🔸 5. Clean Bar Coloring
Highlights predicted direction with green (bullish) and red (bearish) candles
Enhances signal visibility without interfering with price action
⚠️ Important Notes
This script does not repaint.
All calculations are based on confirmed historical data, using bar-closed logic only.
Ideal for crypto, forex, and trending asset classes, especially on the 1H+ timeframes.
Not intended for use as financial advice or automated investment decision-making.
🧠 How to Use
Set desired TP/SL levels in the strategy inputs.
Adjust k-value and lookback for best fit with your instrument.
Monitor the dashboard and colored bars for trade entries.
Use as part of a broader system with structure, support/resistance, or volume confirmation if needed.
🛡️ Disclaimer
This script is for educational and informational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. Always test on historical data and demo environments before applying to live trading. The author is not liable for any financial decisions made based on this script.
Timeframe StrategyThis is a multi-timeframe trading strategy inspired by Ross Cameron's style, optimized for scalping and trend-following across various timeframes (1m, 5m, 15m, 1h, and 1D). The strategy integrates a comprehensive set of technical indicators, dynamic risk management, and visual tools.
Core Features
Dynamic Take Profit, Stop Loss & Trailing Stop
> Separate settings per timeframe for:
-TP% (Take Profit)
-SL% (Stop Loss)
-Trailing Stop %
-Cooldown bars
> Configurable via UI inputs.
>Smart Entry Conditions
Bullish entry: EMA9 crossover EMA20 and EMA50 > EMA200
Bearish entry: EMA9 crossunder EMA20 and EMA50 < EMA200
>Additional confirmation filters:
-Volume Filter (enabled/disabled via UI)
-Time Filter (e.g., only between 15:00–20:00 UTC)
-Spike Filter: rejects high-volatility candles
-RSI Filter: above/below 50 for trend confirmation
-ADX Filter (only applied on 1m, e.g., ADX > 15)
-Micro-Volatility Filter: minimum range percentage (1m only)
-Trend Filter (1m only): price must be above/below EMA200
>Trailing Stop Logic
-Configurable for each timeframe.
- Optional via toggle (use_trailing).
>Trade Cooldown Logic
-Prevents consecutive trades within X bars, configurable per timeframe.
>Technical Indicators Used
-EMA 9 / 20 / 50 / 200
-VWAP
-RSI (14)
-ATR (14) for volatility-based spike filtering
-Custom-calculated ADX (14) (manually implemented)
>Visual Elements
🔼/🔽 Entry signals (long/short) plotted on the chart.
📉 Table in bottom-left:
Displays current values of EMA/VWAP/volume/ATR/ADX.
> Optional "Tab info" panel in top-right (toggleable):
-Timeframe & strategy settings
-Live status of filters (volume, time, cooldown, spike, RSI, ADX, range, trend)
-Uses emoji (✅ / ❌) for quick diagnostics.
>User Customization
-Inputs per timeframe for all key parameters.
-Toggle switches for:
-Trailing stop
-Volume filter
-Info table visibility
This strategy is designed for active traders seeking a balance between momentum entry, risk control, and adaptability across timeframes. It's ideal for backtesting quick reversals or breakout setups in fast markets, especially at lower timeframes like 1m or 5m.
Global ETF Capital FlowsThe Global ETF Capital Flows indicator is designed as a research and monitoring tool for identifying capital allocation trends across major global exchange-traded funds (ETFs). It provides standardized fund flow data for regional equity markets (including the United States, Europe, Asia, and Emerging Markets), as well as alternative asset classes such as bonds and gold.
Fund flows into and out of ETFs are increasingly recognized as a leading indicator of investor behavior, particularly in the context of tactical asset allocation and risk appetite (Ben-David et al., 2017). By tracking aggregated ETF flows, the script enables the user to detect shifts in global investment preferences, which may precede price action and influence broader macro trends (Bank of International Settlements, 2018). For example, consistent inflows into U.S. large-cap ETFs such as SPY or QQQ may signal heightened investor confidence in domestic equities, whereas rising flows into bond ETFs such as TLT may suggest a flight to safety or expectations of declining interest rates (Israeli et al., 2017).
The visualization aspect of the script uses standardized z-scores to represent cumulative flows over a specified period. This normalization allows users to compare fund flows across regions and asset classes on a relative basis, filtering out scale differences and allowing for more effective cross-market analysis. According to Coates and Herbert (2008), normalization techniques such as z-scores are crucial in behavioral finance research, as they help detect anomalies and emotional extremes in investor activity.
Practically, this indicator is suited for top-down macro analysis, sector rotation strategies, and confirmation of technical signals. For instance, significant positive deviations in the standardized flow data for European ETFs may support a bullish bias on regional equities, especially if corroborated by technical breakouts or improving economic indicators. Conversely, elevated inflows into gold ETFs may be interpreted as hedging behavior against geopolitical uncertainty or inflationary pressure, consistent with historical patterns of gold’s role as a safe haven (Baur and Lucey, 2010).
Additionally, the tool allows for visual alerts when flow anomalies exceed a user-defined threshold, thereby supporting more responsive and data-driven decision-making. This feature aligns with findings from the CFA Institute (2019), which emphasize the growing importance of alternative data and automated alert systems in modern portfolio management.
From a research perspective, the indicator facilitates empirical study into capital mobility, intermarket relationships, and ETF investor psychology. It offers real-time monitoring of region-specific investment flows, thus serving as a proxy for investor conviction, liquidity trends, and cross-border risk-on/risk-off sentiment. Several recent studies have demonstrated the predictive power of ETF flows on future returns and volatility, particularly during periods of market stress or structural dislocations (Madhavan, 2016; Pan and Zeng, 2019).
References
• Baur, D.G. and Lucey, B.M., 2010. Is gold a hedge or a safe haven? An analysis of stocks, bonds and gold. Financial Review, 45(2), pp.217-229.
• Ben-David, I., Franzoni, F. and Moussawi, R., 2017. Exchange-traded funds (ETFs). Annual Review of Financial Economics, 9, pp.169–189.
• Bank of International Settlements (BIS), 2018. ETFs – growing popularity, growing risks? BIS Quarterly Review, March 2018.
• CFA Institute, 2019. Investment Professional of the Future. Available at: www.cfainstitute.org .
• Coates, J.M. and Herbert, J., 2008. Endogenous steroids and financial risk taking on a London trading floor. Proceedings of the National Academy of Sciences, 105(16), pp.6167–6172.
• Israeli, D., Lee, C.M. and Sridharan, S.A., 2017. Is there a dark side to ETF trading? Evidence from corporate bond ETFs. SSRN Working Paper. Available at SSRN: ssrn.com
• Madhavan, A., 2016. Exchange-Traded Funds and the New Dynamics of Investing. Oxford University Press.
• Pan, K. and Zeng, Y., 2019. ETF Arbitrage Under Liquidity Mismatch. Journal of Finance, 74(6), pp.2731–2783.
