QS H1 Close Directional Day Strategy⚡ QuantSignals | H1 Close Directional — Day Strategy (SPY/QQQ)
Trade the day with the first hour’s truth.
This strategy reads the first 60-minute candle to set a directional bias for the rest of the session, then executes limited, time-gated entries with EOD flat discipline. Built for SPY/QQQ and adaptable to other liquid ETFs.
Bias source: First hour (H1) open → close
Discipline: Max 2 trades/day, session-only entries, cooldown enforced
Risk control: Auto EOD exit + event date exclusions (FOMC, CPI, etc.)
🧠 Why it works
The first hour often sets the tone for intraday structure. By committing to H1 momentum (green = long bias, red = short bias) and restricting overtrading, this system avoids chop and focuses on clean trend continuation days. Add your preferred risk overlay (e.g., portfolio sizing or options hedging) for a complete plan.
🔑 Core Features
H1 Bias Engine — Long if the first hour closes green, short if it closes red.
Time Gating — Trades allowed only 9:00–15:00 (exchange time).
Cooldown — Configurable minimum bars between entries (anti-churn).
Daily Limits — Max 2 trades/day (reset each session).
Global Guardrail — Max total trades across the entire backtest.
Event Filter — Exclude dates (e.g., FOMC) to sidestep landmines.
Visuals — First hour highlighted; green/red markers show bias signals.
Flat by Close — Auto close all positions at session end.
⚙️ Inputs (What you can customize)
Tradeable Symbols (SPY,QQQ) — comma-separated list (informational).
Exclude Dates (YYYY-MM-DD) — e.g., 2024-03-20,2024-06-12 for FOMC.
Maximum Total Trades — cap backtest trade count (1–1000).
Max Daily Trades — internally set to 2 (edit in code if desired).
Entry Window — 09:00–15:00; modify in code to match your venue.
Cooldown — default 60 bars between entries (edit in code).
Tip: To expand beyond SPY/QQQ, duplicate the chart on IWM, QQQ, XLK, or FANG+ indices and compare.
📈 How it trades (under the hood)
Detect first hour → store H1 open/close.
Set bias → green = long, red = short.
Gate entries → only during market hours, obey cooldown, max 2/day.
Risk discipline → flat at end of day, regardless of P&L.
Avoid event risk → skips trading on your excluded dates.
🧪 Backtest Setup (recommended)
Timeframe: 1–5 min charts (bias still sourced from H1).
Session: Regular trading hours only (disable extended where applicable).
Commission/Slippage: Add realistic values in Strategy Properties.
Symbols: SPY, QQQ (high liquidity).
Walk-forward: Test multiple years, include bull/bear regimes.
🔍 Reading the chart
Yellow background: First hour highlighted.
Green triangle up: H1 closed green & conditions allow a long.
Red triangle down: H1 closed red & conditions allow a short.
Top-right dashboard: Win rate, total trades, profit factor, net P&L%.
🧩 Suggested Enhancements (optional)
Stop/Target module: Add a fixed stop or ATR-based stop.
Volatility filter: Skip days with extreme overnight gaps.
Trend filter: Only follow H1 bias if above/below 200EMA or VWAP.
Portfolio mode: Run multiple tickers and allocate by volatility.
⚠️ Important
This script is for education and research. Markets change; past performance ≠ future results. Always validate with your own risk rules and execution constraints.
❓ FAQ
Q: Does it trade more than two times a day?
A: No. It’s capped at 2 trades/day by design (you can edit this).
Q: Can I use this on futures or crypto?
A: Yes—adapt the session hours and excluded dates to your venue.
Q: Where are stops?
A: The baseline uses time-based exits (EOD) plus cooldown/limits. Add price-based stops if needed.
🔎 SEO Tags
0DTE, SPY, QQQ, first hour, H1, intraday, day trading, trend following, momentum, EOD exit, FOMC filter, cooldown, max trades per day, discipline, backtest
📝 Changelog
v1.0 — Initial release: H1 bias engine, day-only entries, cooldown, excluded dates, EOD flat, dashboard.
Quant
⚡ QuantSignals | 0DTE Lazy Pro🚀 Trade Smarter. Trade Faster. Trade with QS.
The 0DTE Lazy Pro strategy is an AI-inspired intraday framework that combines Bollinger Band mean reversion with Opening Range Breakout (ORB) and VWAP trend tracking — engineered for SPX/SPY 0DTE options and adaptable to stocks, futures, crypto.
Built on real QS trade logic used by our premium members, this strategy is optimized for high-probability setups, precise timing, and disciplined exits — no more guessing, no more chasing.
🧠 Core Features
✅ Triple-Mode Engine — Switch between:
• BB Mode: Fade overextended moves, capture mean reversion.
• ORB Mode: Ride powerful intraday breakouts.
• VWAP Mode: Align with institutional flow & trend bias.
✅ Adaptive Parameters — Automatically optimizes for asset type & timeframe.
✅ One-Trade-Per-Day Guard — Keeps discipline, avoids overtrading.
✅ Smart TP System — Asset-aware profit targets, including auto-scaling for non-SPX/SPY tickers.
✅ QS Scoreboard Overlay — Live stats on win rate, P&L, and strategy score right on your chart.
✅ Visual Clarity — Color-coded backgrounds, entry/exit markers, EMA, VWAP, and ORB levels for instant context.
💡 Why It Works
The 0DTE Lazy Pro isn’t just a “buy/sell” signal — it’s a complete trading framework:
Identifies precise entry zones based on volatility extremes and market structure.
Times trades with institutional reference points like VWAP and ORB.
Keeps you out of bad trades by enforcing time filters and daily limits.
Focuses on setups that historically offer the best risk-reward for intraday traders.
Our Premium QS community runs this exact framework on SPX 0DTE options, high-beta stocks, and volatile futures — and uses the AI dashboard to find the most promising daily setups.
🎯 Who Is This For?
SPX 0DTE traders wanting a repeatable intraday edge.
Stock & futures day traders looking for clean, structured setups.
Crypto scalpers seeking volatility-aware entries.
Busy traders who want a rules-based plan with visual clarity.
Whether you trade full-time or just a few hours a week, this script adapts to your style.
📊 Settings & Customization
Signal Modes: Toggle BB, ORB, VWAP — or mix for hybrid setups.
Trading Hours: Define exact market window or run 24/7.
TP Target: Adjustable, auto-scales per symbol.
ORB Duration: Set range capture in minutes.
Visual Options: Show/hide QS watermark, customize opacity, tweak chart visuals.
📌 Important Notes
Designed for 1m–10m intraday charts, optimized for SPX/SPY 0DTE but flexible for other markets.
Backtest results vary by symbol, timeframe, and data source.
Educational use only — not financial advice. Test before live trading.
🔥 Want More?
This is the public promo of our full QS Premium 0DTE Suite:
AI-Generated Daily Playbook for SPX/SPY.
Options Flow Heatmaps for market sentiment.
Theme Hunter™ & Earnings Detective™ for swing trades.
Private Discord with 24/7 signals, setups, and strategy refinements.
Join us: quantsignals.xyz
💬 Install now, run it on your favorite tickers, and see why traders call QS “the future of intraday trading.”
Mutanabby_AI | Ultimate Algo | Remastered+Overview
The Mutanabby_AI Ultimate Algo Remastered+ represents a sophisticated trend-following system that combines Supertrend analysis with multiple moving average confirmations. This comprehensive indicator is designed specifically for identifying high-probability trend continuation and reversal opportunities across various market conditions.
Core Algorithm Components
**Supertrend Foundation**: The primary signal generation relies on a customizable Supertrend indicator with adjustable sensitivity (1-20 range). This adaptive trend-following tool uses Average True Range calculations to establish dynamic support and resistance levels that respond to market volatility.
**SMA Confirmation Matrix**: Multiple Simple Moving Averages (SMA 4, 5, 9, 13) provide layered confirmation for signal strength. The algorithm distinguishes between regular signals and "Strong" signals based on SMA 4 vs SMA 5 relationship, offering traders different conviction levels for position sizing.
**Trend Ribbon Visualization**: SMA 21 and SMA 34 create a visual trend ribbon that changes color based on their relationship. Green ribbon indicates bullish momentum while red signals bearish conditions, providing immediate visual trend context.
**RSI-Based Candle Coloring**: Advanced 61-tier RSI system colors candles with gradient precision from deep red (RSI ≤20) through purple transitions to bright green (RSI ≥79). This visual enhancement helps traders instantly assess momentum strength and overbought/oversold conditions.
Signal Generation Logic
**Buy Signal Criteria**:
- Price crosses above Supertrend line
- Close price must be above SMA 9 (trend confirmation)
- Signal strength determined by SMA 4 vs SMA 5 relationship
- "Strong Buy" when SMA 4 ≥ SMA 5
- Regular "Buy" when SMA 4 < SMA 5
**Sell Signal Criteria**:
- Price crosses below Supertrend line
- Close price must be below SMA 9 (trend confirmation)
- Signal strength based on SMA relationship
- "Strong Sell" when SMA 4 ≤ SMA 5
- Regular "Sell" when SMA 4 > SMA 5
Advanced Risk Management System
**Automated TP/SL Calculation**: The indicator automatically calculates stop loss and take profit levels using ATR-based measurements. Risk percentage and ATR length are fully customizable, allowing traders to adapt to different market conditions and personal risk tolerance.
**Multiple Take Profit Targets**:
- 1:1 Risk-Reward ratio for conservative profit taking
- 2:1 Risk-Reward for balanced trade management
- 3:1 Risk-Reward for maximum profit potential
**Visual Risk Display**: All risk management levels appear as both labels and optional trend lines on the chart. Customizable line styles (solid, dashed, dotted) and positioning ensure clear visualization without chart clutter.
**Dynamic Level Updates**: Risk levels automatically recalculate with each new signal, maintaining current market relevance throughout position lifecycles.
Visual Enhancement Features
**Customizable Display Options**: Toggle trend ribbon, TP/SL levels, and risk lines independently. Decimal precision adjustments (1-8 decimal places) accommodate different instrument price formats and personal preferences.
**Professional Label System**: Clean, informative labels show entry points, stop losses, and take profit targets with precise price levels. Labels automatically position themselves for optimal chart readability.
**Color-Coded Momentum**: The gradient RSI candle coloring system provides instant visual feedback on momentum strength, helping traders assess market energy and potential reversal zones.
Implementation Strategy
**Timeframe Optimization**: The algorithm performs effectively across multiple timeframes, with higher timeframes (4H, Daily) providing more reliable signals for swing trading. Lower timeframes work well for day trading with appropriate risk adjustments.
**Sensitivity Adjustment**: Lower sensitivity values (1-5) generate fewer but higher-quality signals, ideal for conservative approaches. Higher sensitivity (15-20) increases signal frequency for active trading styles.
**Risk Management Integration**: Use the automated risk calculations as baseline parameters, adjusting risk percentage based on account size and market conditions. The 1:1, 2:1, 3:1 targets enable systematic profit-taking strategies.
Market Application
**Trend Following Excellence**: Primary strength lies in capturing significant trend movements through the Supertrend foundation with SMA confirmation. The dual-layer approach reduces false signals common in single-indicator systems.
**Momentum Assessment**: RSI-based candle coloring provides immediate momentum context, helping traders assess signal strength and potential continuation probability.
**Range Detection**: The trend ribbon helps identify ranging conditions when SMA 21 and SMA 34 converge, alerting traders to potential breakout opportunities.
Performance Optimization
**Signal Quality**: The requirement for both Supertrend crossover AND SMA 9 confirmation significantly improves signal reliability compared to basic trend-following approaches.
**Visual Clarity**: The comprehensive visual system enables rapid market assessment without complex calculations, ideal for traders managing multiple instruments.
**Adaptability**: Extensive customization options allow fine-tuning for specific markets, trading styles, and risk preferences while maintaining the core algorithm integrity.
## Non-Repainting Design
**Educational Note**: This indicator uses standard TradingView functions (Supertrend, SMA, RSI) with normal behavior patterns. Real-time updates on current candles are expected and standard across all technical indicators. Historical signals on closed candles remain fixed and unchanged, ensuring reliable backtesting and analysis.
**Signal Confirmation**: Final signals are confirmed only when candles close, following standard technical analysis principles. The algorithm provides clear distinction between developing signals and confirmed entries.
Technical Specifications
**Supertrend Parameters**: Default sensitivity of 4 with ATR length of 11 provides balanced signal generation. Sensitivity range from 1-20 allows adaptation to different market volatilities and trading preferences.
**Moving Average Configuration**: SMA periods of 8, 9, and 13 create multi-layered trend confirmation, while SMA 21 and 34 form the visual trend ribbon for broader market context.
**Risk Management**: ATR-based calculations with customizable risk percentage ensure dynamic adaptation to market volatility while maintaining consistent risk exposure principles.
Recommended Settings
**Conservative Approach**: Sensitivity 4-5, RSI length 14, higher timeframes (4H, Daily) for swing trading with maximum signal reliability.
**Active Trading**: Sensitivity 6-8, RSI length 8-10, intermediate timeframes (1H) for balanced signal frequency and quality.
**Scalping Setup**: Sensitivity 10-15, RSI length 5-8, lower timeframes (15-30min) with enhanced risk management protocols.
## Conclusion
The Mutanabby_AI Ultimate Algo Remastered+ combines proven trend-following principles with modern visual enhancements and comprehensive risk management. The algorithm's strength lies in its multi-layered confirmation approach and automated risk calculations, providing both novice and experienced traders with clear signals and systematic trade management.
Success with this system requires understanding the relationship between signal strength indicators and adapting sensitivity settings to match current market conditions. The comprehensive visual feedback system enables rapid decision-making while the automated risk management ensures consistent trade parameters.
Practice with different sensitivity settings and timeframes to optimize performance for your specific trading style and risk tolerance. The algorithm's systematic approach provides an excellent framework for disciplined trend-following strategies across various market environments.
Mutanabby_AI __ OSC+ST+SQZMOMMutanabby_AI OSC+ST+SQZMOM: Multi-Component Trading Analysis Tool
Overview
The Mutanabby_AI OSC+ST+SQZMOM indicator combines three proven technical analysis components into a unified trading system, providing comprehensive market analysis through integrated oscillator signals, trend identification, and volatility assessment.
Core Components
Wave Trend Oscillator (OSC): Identifies overbought and oversold market conditions using exponential moving average calculations. Key threshold levels include overbought zones at 60 and 53, with oversold areas marked at -60 and -53. Crossover signals between the two oscillator lines generate entry opportunities, displayed as colored circles on the chart for easy identification.
Supertrend Indicator (ST): Determines overall market direction using Average True Range calculations with a 2.5 factor and 10-period ATR configuration. Green lines indicate confirmed uptrends while red lines signal downtrend conditions. The indicator automatically adapts to market volatility changes, providing reliable trend identification across different market environments.
Squeeze Momentum (SQZMOM): Compares Bollinger Bands with Keltner Channels to identify consolidation periods and potential breakout scenarios. Black squares indicate squeeze conditions representing low volatility periods, green triangles signal confirmed upward breakouts, and red triangles mark downward breakout confirmations.
Signal Generation Logic
Long Entry Conditions:
Green triangles from Squeeze Momentum component
Supertrend line transitioning to green
Bullish crossovers in Wave Trend Oscillator from oversold territory
Short Entry Conditions:
Red triangles from Squeeze Momentum component
Supertrend line transitioning to red
Bearish crossovers in Wave Trend Oscillator from overbought territory
Automated Risk Management
The indicator incorporates comprehensive risk management through ATR-based calculations. Stop losses are automatically positioned at 3x ATR distance from entry points, while three progressive take profit targets are established at 1x, 2x, and 3x ATR multiples respectively. All risk management levels are clearly displayed on the chart using colored lines and informative labels.
When trend direction changes, the system automatically clears previous risk levels and generates new calculations, ensuring all risk parameters remain current and relevant to existing market conditions.
Alert and Notification System
Comprehensive alert framework includes trend change notifications with complete trade setup details, squeeze release alerts for breakout opportunity identification, and trend weakness warnings for active position management. Alert messages contain specific trading pair information, timeframe specifications, and all relevant entry and exit level data.
Implementation Guidelines
Timeframe Selection: Higher timeframes including 4-hour and daily charts provide the most reliable signals for position trading strategies. One-hour charts demonstrate good performance for day trading applications, while 15-30 minute timeframes enable scalping approaches with enhanced risk management requirements.
Risk Management Integration: Limit individual trade risk to 1-2% of total capital using the automatically calculated stop loss levels for precise position sizing. Implement systematic profit-taking at each target level while adjusting stop loss positions to protect accumulated gains.
Market Volatility Adaptation: The indicator's ATR-based calculations automatically adjust to changing market volatility conditions. During high volatility periods, risk management levels appropriately widen, while low volatility conditions result in tighter risk parameters.
Optimization Techniques
Combine indicator signals with fundamental support and resistance level analysis for enhanced signal validation. Monitor volume patterns to confirm breakout strength, particularly when Squeeze Momentum signals develop. Maintain awareness of scheduled economic events that may influence market behavior independent of technical indicator signals.
The multi-component design provides internal signal confirmation through multiple alignment requirements, significantly reducing false signal occurrence while maintaining reasonable trade frequency for active trading strategies.
Technical Specifications
The Wave Trend Oscillator utilizes customizable channel length (default 10) and average length (default 21) parameters for optimal market sensitivity. Supertrend calculations employ ATR period of 10 with factor multiplier of 2.5 for balanced signal quality. Squeeze Momentum analysis uses Bollinger Band length of 20 periods with 2.0 multiplication factor, combined with Keltner Channel length of 20 periods and 1.5 multiplication factor.
Conclusion
The Mutanabby_AI OSC+ST+SQZMOM indicator provides a systematic approach to technical market analysis through the integration of proven oscillator, trend, and momentum components. Success requires thorough understanding of each element's functionality and disciplined implementation of proper risk management principles.
Practice with demo trading accounts before live implementation to develop familiarity with signal interpretation and trade management procedures. The indicator's systematic approach effectively reduces emotional decision-making while providing clear, objective guidelines for trade entry, management, and exit strategies across various market conditions.
Ethereum OnChain Data Indicator - The Quant ScienceEthereum On Chain Data Indicator - The Quant Science™ is a quantitative indicator created for mid-long term analysis.
The indicator uses quantitative statistics to recreate a model that represents the most important data from the on-chain analysis for the Ethereum blockchain.
The on-chain data used to create this model are:
1. Total weekly transactions
2. Total monthly transactions
3. Frequency of transactions per second on a daily scale
4. Frequency of transactions per second on a weekly scale
5. Amount of Ethereum burned on a daily scale
6. Amount of Ethereum burned on a weekly scale
7. Volume of short positions on a daily scale
8. Volume of short positions on a weekly scale
9. Volume of short positions more/less than average on a daily scale
10. Volume of short positions more/less than average on a weekly scale
All these data were extrapolated and manipulated using the mean and standard deviation.
The end result is a powerful tool that enables mid-long term investors and traders to analyze on-chain data through quantitative analysis.
FEATURES
The blue color area refers to the average change in data on a weekly scale. The light blue colored area indicates the monthly changes in the data. It is interesting to observe the correlation relationship between price and times when short-run data increases compared to long-run data and vice versa.
The more intense purple histograms refer to the standard deviation of the mean change in data on an annual scale. Histograms of less intense purple color refer to the standard deviation of the mean variation of data on a monthly scale. It is interesting to observe the ratio of the standard deviation between two different time periods.
This indicator can be used to perform statistical comparative analysis for manual and mid-long term investments. It can also be used to create auto trading strategies when used and integrated within an algorithm.
On-chain data are updated every 24 hours, so the timeframes to be used for analysis with this indicator are: D, 4H, 1H.
Momentum Regression [BackQuant]Momentum Regression
The Momentum Regression is an advanced statistical indicator built to empower quants, strategists, and technically inclined traders with a robust visual and quantitative framework for analyzing momentum effects in financial markets. Unlike traditional momentum indicators that rely on raw price movements or moving averages, this tool leverages a volatility-adjusted linear regression model (y ~ x) to uncover and validate momentum behavior over a user-defined lookback window.
Purpose & Design Philosophy
Momentum is a core anomaly in quantitative finance — an effect where assets that have performed well (or poorly) continue to do so over short to medium-term horizons. However, this effect can be noisy, regime-dependent, and sometimes spurious.
The Momentum Regression is designed as a pre-strategy analytical tool to help you filter and verify whether statistically meaningful and tradable momentum exists in a given asset. Its architecture includes:
Volatility normalization to account for differences in scale and distribution.
Regression analysis to model the relationship between past and present standardized returns.
Deviation bands to highlight overbought/oversold zones around the predicted trendline.
Statistical summary tables to assess the reliability of the detected momentum.
Core Concepts and Calculations
The model uses the following:
Independent variable (x): The volatility-adjusted return over the chosen momentum period.
Dependent variable (y): The 1-bar lagged log return, also adjusted for volatility.
A simple linear regression is performed over a large lookback window (default: 1000 bars), which reveals the slope and intercept of the momentum line. These values are then used to construct:
A predicted momentum trendline across time.
Upper and lower deviation bands , representing ±n standard deviations of the regression residuals (errors).
These visual elements help traders judge how far current returns deviate from the modeled momentum trend, similar to Bollinger Bands but derived from a regression model rather than a moving average.
Key Metrics Provided
On each update, the indicator dynamically displays:
Momentum Slope (β₁): Indicates trend direction and strength. A higher absolute value implies a stronger effect.
Intercept (β₀): The predicted return when x = 0.
Pearson’s R: Correlation coefficient between x and y.
R² (Coefficient of Determination): Indicates how well the regression line explains the variance in y.
Standard Error of Residuals: Measures dispersion around the trendline.
t-Statistic of β₁: Used to evaluate statistical significance of the momentum slope.
These statistics are presented in a top-right summary table for immediate interpretation. A bottom-right signal table also summarizes key takeaways with visual indicators.
Features and Inputs
✅ Volatility-Adjusted Momentum : Reduces distortions from noisy price spikes.
✅ Custom Lookback Control : Set the number of bars to analyze regression.
✅ Extendable Trendlines : For continuous visualization into the future.
✅ Deviation Bands : Optional ±σ multipliers to detect abnormal price action.
✅ Contextual Tables : Help determine strength, direction, and significance of momentum.
✅ Separate Pane Design : Cleanly isolates statistical momentum from price chart.
How It Helps Traders
📉 Quantitative Strategy Validation:
Use the regression results to confirm whether a momentum-based strategy is worth pursuing on a specific asset or timeframe.
🔍 Regime Detection:
Track when momentum breaks down or reverses. Slope changes, drops in R², or weak t-stats can signal regime shifts.
📊 Trade Filtering:
Avoid false positives by entering trades only when momentum is both statistically significant and directionally favorable.
📈 Backtest Preparation:
Before running costly simulations, use this tool to pre-screen assets for exploitable return structures.
When to Use It
Before building or deploying a momentum strategy : Test if momentum exists and is statistically reliable.
During market transitions : Detect early signs of fading strength or reversal.
As part of an edge-stacking framework : Combine with other filters such as volatility compression, volume surges, or macro filters.
Conclusion
The Momentum Regression indicator offers a powerful fusion of statistical analysis and visual interpretation. By combining volatility-adjusted returns with real-time linear regression modeling, it helps quantify and qualify one of the most studied and traded anomalies in finance: momentum.
Rolling Log Returns [BackQuant]Rolling Log Returns
The Rolling Log Returns indicator is a versatile tool designed to help traders, quants, and data-driven analysts evaluate the dynamics of price changes using logarithmic return analysis. Widely adopted in quantitative finance, log returns offer several mathematical and statistical advantages over simple returns, making them ideal for backtesting, portfolio optimization, volatility modeling, and risk management.
What Are Log Returns?
In quantitative finance, logarithmic returns are defined as:
ln(Pₜ / Pₜ₋₁)
or for rolling periods:
ln(Pₜ / Pₜ₋ₙ)
where P represents price and n is the rolling lookback window.
Log returns are preferred because:
They are time additive : returns over multiple periods can be summed.
They allow for easier statistical modeling , especially when assuming normally distributed returns.
They behave symmetrically for gains and losses, unlike arithmetic returns.
They normalize percentage changes, making cross-asset or cross-timeframe comparisons more consistent.
Indicator Overview
The Rolling Log Returns indicator computes log returns either on a standard (1-period) basis or using a rolling lookback period , allowing users to adapt it to short-term trading or long-term trend analysis.
It also supports a comparison series , enabling traders to compare the return structure of the main charted asset to another instrument (e.g., SPY, BTC, etc.).
Core Features
✅ Return Modes :
Normal Log Returns : Measures ln(price / price ), ideal for day-to-day return analysis.
Rolling Log Returns : Measures ln(price / price ), highlighting price drift over longer horizons.
✅ Comparison Support :
Compare log returns of the primary instrument to another symbol (like an index or ETF).
Useful for relative performance and market regime analysis .
✅ Moving Averages of Returns :
Smooth noisy return series with customizable MA types: SMA, EMA, WMA, RMA, and Linear Regression.
Applicable to both primary and comparison series.
✅ Conditional Coloring :
Returns > 0 are colored green ; returns < 0 are red .
Comparison series gets its own unique color scheme.
✅ Extreme Return Detection :
Highlight unusually large price moves using upper/lower thresholds.
Visually flags abnormal volatility events such as earnings surprises or macroeconomic shocks.
Quantitative Use Cases
🔍 Return Distribution Analysis :
Gain insight into the statistical properties of asset returns (e.g., skewness, kurtosis, tail behavior).
📉 Risk Management :
Use historical return outliers to define drawdown expectations, stress tests, or VaR simulations.
🔁 Strategy Backtesting :
Apply rolling log returns to momentum or mean-reversion models where compounding and consistent scaling matter.
📊 Market Regime Detection :
Identify periods of consistent overperformance/underperformance relative to a benchmark asset.
📈 Signal Engineering :
Incorporate return deltas, moving average crossover of returns, or threshold-based triggers into machine learning pipelines or rule-based systems.
Recommended Settings
Use Normal mode for high-frequency trading signals.
Use Rolling mode for swing or trend-following strategies.
Compare vs. a broad market index (e.g., SPY or QQQ ) to extract relative strength insights.
Set upper and lower thresholds around ±5% for spotting major volatility days.
Conclusion
The Rolling Log Returns indicator transforms raw price action into a statistically sound return series—equipping traders with a professional-grade lens into market behavior. Whether you're conducting exploratory data analysis, building factor models, or visually scanning for outliers, this indicator integrates seamlessly into a modern quant's toolbox.
Cumulative Intraday Volume with Long/Short LabelsThis indicator calculates a running total of volume for each trading day, then shows on the price chart when that total crosses levels you choose. Every day at 6:00 PM Eastern Time, the total goes back to zero so it always reflects only the current day’s activity. From that moment on, each time a new candle appears the indicator looks at whether the candle closed higher than it opened or lower. If it closed higher, the candle’s volume is added to the running total; if it closed lower, the same volume amount is subtracted. As a result, the total becomes positive when buyers have dominated so far today and negative when sellers have dominated.
Because futures markets close at 6 PM ET, the running total resets exactly then, mirroring the way most intraday traders think in terms of a single session. Throughout the day, you will see this running total move up or down according to whether more volume is happening on green or red candles. Once the total goes above a number you specify (for example, one hundred thousand contracts), the indicator will place a small “Long” label at that candle on the main price chart to let you know buying pressure has reached that level. Similarly, once the total goes below a negative number you choose (for example, minus one hundred thousand), a “Short” label will appear at that candle to signal that selling pressure has reached your chosen threshold. You can set these threshold numbers to whatever makes sense for your trading style or the market you follow.
Because raw volume alone never turns negative, this design uses candle direction as a sign. Green candles (where the close is higher than the open) add volume, and red candles (where the close is lower than the open) subtract volume. Summing those signed volume values tells you in a single number whether buying or selling has been stronger so far today. That number resets every evening, so it does not carry over any buying or selling from previous sessions.
Once you have this indicator on your chart, you simply watch the “summed volume” line as it moves throughout the day. If it climbs past your long threshold, you know buyers are firmly in control and a long entry might make sense. If it falls past your short threshold, you know sellers are firmly in control and a short entry might make sense. In quieter markets or times of low volume, you might use a smaller threshold so that even modest buying or selling pressure will trigger a label. During very active periods, a larger threshold will prevent too many signals when volume spikes frequently.
This approach is straightforward but can be surprisingly powerful. It does not rely on complex formulas or hidden statistical measures. Instead, it simply adds and subtracts daily volume based on candle color, then alerts you when that total reaches levels you care about. Over several years of historical testing, this formula has shown an ability to highlight moments when intraday sentiment shifts decisively from buyers to sellers or vice versa. Because the indicator resets every day at 6 PM, it always reflects only today’s sentiment and remains easy to interpret without carrying over past data. You can use it on any intraday timeframe, but it works especially well on five-minute or fifteen-minute charts for futures contracts.
If you want a clear gauge of whether buyers or sellers are dominating in real time, and you prefer a rule-based method rather than a complex model, this indicator gives you exactly that. It shows net buying or selling pressure at a glance, resets each session like most intraday traders do, and marks the moments when that pressure crosses the levels you decide are important. By combining a daily reset with signed volume, you get a single number that tells you precisely what the crowd is doing at any given moment, without any of the guesswork or hidden calculations that more complicated indicators often carry.
Symbol Seasonality Matrix (w/ BTC Base) Symbol Seasonality Matrix (w/ BTC Base)
Compare monthly performance between Bitcoin and any symbol across time
🧠 Overview
This indicator provides a side-by-side monthly return table of Bitcoin (BTCUSD from Bitfinex) and any selected symbol (e.g., ETH, stocks, etc.). It visualizes seasonality patterns, historical performance shifts, and relative trends in a clean matrix layout with dynamic line overlays.
⚙️ Mechanism
BTC Benchmarking:
BTC monthly returns are always shown as a benchmark against the selected chart symbol.
Monthly ROI Calculation:
For each month, the indicator tracks the open and close price and calculates the monthly return using:
(close_end - close_start) / close_start × 100%
It stores both price and return for BTC and the chart symbol.
Table Structure:
Each year is split into two halves:
2023 (Jan ~ Jun) and 2023 (Jul ~ Dec) for clarity.
Color Coding:
Green for positive months
Red for negative months
Monthly trend lines and labels drawn in consistent colors
Background shading per month helps track seasonality
Plot Modes:
regular: raw price
percent: relative % change from the start of selected period
normalized: base=1 scaling to compare trends
Time Range Selector:
You can define start time and end time for comparison — all logic, including table, plots, and highlights, will focus only on this window.
🧭 How to Use
Set the time range:
Choose a meaningful window such as the past 3 years or 2018–2021 to study behavior.
Compare Symbol vs BTC:
Load BTCUSD in a separate chart for baseline.
Switch to ETHUSD, SPY, or any altcoin/equity to view overlayed performance.
Analyze Seasonality:
Look for months with repeated strong/weak performance (e.g., BTC strong in October).
Compare how your asset aligns with BTC trends or diverges.
Choose View Mode:
Use percent to adjust Y-axis scaling and directly compare relative movements.
Use normalized to detect trend correlation without caring about price level.
🔍 Why It’s Useful
Spot seasonal alpha and align entries with favorable months
See if a symbol outperforms or underperforms BTC consistently
Get price-to-return context visually, not just via numbers
Quickly compare assets in real scale or normalized scale
📌 Tip
Try publishing this to a layout with multiple tickers (ETH, SOL, AAPL) to instantly switch comparisons.
Pair with volume-based or macro indicators to layer signals.
Rolling Beta against SPY📈 Pine Script Showcase: Rolling Beta Against SPY
Understanding how your favorite stock or ETF moves in relation to a benchmark like the S&P 500 can offer powerful insights into risk and exposure. This script calculates and visualizes the rolling beta of any asset versus the SPY ETF (which tracks the S&P 500).
🧠 What Is Beta?
Beta measures the sensitivity of an asset's returns to movements in the broader market. A beta of:
- 1.0 means the asset moves in lockstep with SPY,
- >1.0 indicates higher volatility than the market,
- <1.0 implies lower volatility or possible defensive behavior,
- <0 suggests inverse correlation (e.g., hedging instruments).
🧮 How It Works
This script computes rolling beta over a user-defined window (default = 60 periods) using classic linear regression math:
- Calculates daily returns for both the asset and SPY.
- Computes covariance between the two return streams.
- Divides by the variance of SPY returns to get beta.
⚙️ Customization
You can adjust the window size to control the smoothing:
- Shorter windows capture recent volatility changes,
- Longer windows give more stable, long-term estimates.
📊 Visual Output
The script plots the beta series dynamically, allowing you to observe how your asset’s correlation to SPY evolves over time. This is especially useful in regime-change environments or during major macroeconomic shifts.
💡 Use Cases
- Portfolio construction: Understand how your assets co-move with the market.
- Risk management: Detect when beta spikes—potentially signaling higher market sensitivity.
- Market timing: Use beta shifts to infer changing investor sentiment or market structure.
📌 Pro Tip: Combine this rolling beta with volatility, Sharpe ratio, or correlation tracking for a more robust factor-based analysis.
Ready to add a layer of quantitative insight to your chart? Add the script to your watchlist and start analyzing your favorite tickers against SPY today!
CAM | Comparison and Normalisation Indicator Description: "CAM | Comparison and Normalisation" 🌟
Overview 📊
The "CAM | Comparison and Normalisation" indicator is a must-have tool for forex traders! 🚀 It analyzes the strength of a currency pair’s base and quote currencies against the pair’s price movement, using automatic detection, composite calculations, and normalization—all wrapped in a colorful, easy-to-read package. 🎨
How It Works 🛠️
- 🔍 **Automatic Currency Detection**: Instantly spots the base (e.g., EUR in EURUSD) and quote (e.g., USD) currencies—no manual setup needed!
- 💪 **Composite Strength Calculation**: Measures each currency’s power by averaging its rate against 9 major currencies (GBP, EUR, CHF, USD, AUD, CAD, NZD, JPY, NOK). A true strength test! 🏋️♂️
- 📏 **Normalization**: Scales everything with a smart formula (price minus moving average, divided by standard deviation) so base, quote, and pair prices play on the same field. ⚖️
- 🎨 **Dynamic Visualization**:
- Plots 3 normalized lines with unique colors:
- **Base Composite** (e.g., purple for GBP, blue for EUR)
- **Quote Composite** (e.g., green for USD, yellow for JPY)
- **Actual Pair** (⚪ white)
- Adds labels on the last bar (e.g., "Base: GBP" in purple). 🏷️
- 📊 **Performance Histogram**: Shows the base vs. quote strength gap with a green (👍) or red (👎) area chart—adjusted by the pair’s price.
- ⚙️ **Customizable Settings**: Adjust Scaling Period (50), Histogram Scale (0.5), and Levels (1, -1) to fit your style! 🎚️
Benefits 🌈
- 🧠 **Simplified Analysis**: Normalized data cuts through the noise, making trends crystal clear.
- ✅ **Enhanced Decisions**: Colorful lines and histograms spotlight trading signals fast.
- ⏱️ **Time-Saver**: No setup—just drop it on a chart and go!
- 🌍 **Versatile**: Works on any supported pair, with colors adapting automatically (e.g., orange AUD on AUDCAD).
- 👀 **Eye-Catching**: Currency-specific colors (like purple GBP from pound notes) make it fun and easy to follow.
How It Helps Traders 💡
- 📈 **Spot Trends**: See if the base is flexing 💪 or the quote is fading 📉, and how it ties to the pair’s price.
- ⚠️ **Catch Divergences**: Histogram flags when currency strength and price don’t match—hello, opportunity! 🚨
- 🛡️ **Manage Risk**: Normalized values and levels help gauge overbought/oversold zones for smarter stops.
- **Big Picture**: Compare currency strength to pair price for strategic edge, whether scalping or swinging.
Example in Action 🎬
- **GBPUSD Chart**:
- purple GBP line climbs, greenUSD dips, histogram turns green 👍—GBP’s gaining! If the white pair line rises too, it’s a bullish hint.
Conclusion ✨
"CAM | Comparison and Normalisation" turns forex complexity into clear, actionable insights. With its auto-detection, vibrant visuals, and trader-friendly design, it’s your shortcut to smarter trades! 📈💰
CAM| Bar volatility and statsCAPRICORN ASSETS MANAGEMENT
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CAM | Bar Volatility and Stats Indicator
The CAM | Bar Volatility and Stats indicator is designed to track historical price movements, analyzing bar volatility and key statistical trends in financial instruments. By evaluating past bars, it provides insights into market dynamics, helping traders assess volatility, trend strength, and momentum patterns.
Key Features & Functionality:
✅ Volatility Analysis – Measures historical volatility by calculating the average price range per bar and displaying it in pips.
✅ Bull & Bear Bar Statistics – Tracks the number of bullish and bearish bars within a given lookback period, including their respective percentages.
✅ Consecutive Bar Sequences – Identifies and records the longest streaks of consecutive bullish or bearish bars, providing insights into market trends.
✅ Average Volatility by Trend – Computes separate volatility values for bullish and bearish bars, helping traders understand trend-based price behavior.
✅ Real-Time Labeling – Displays a live statistics summary directly on the chart, updating dynamically with each new bar.
Benefits for Traders:
📊 Enhanced Market Insight – Quickly assess market conditions, determining whether volatility is increasing or decreasing.
📈 Trend Strength Identification – Identify strong bullish or bearish sequences to improve trade timing and strategy development.
⏳ Better Risk Management – Use historical volatility metrics to fine-tune stop-loss and take-profit levels.
🛠 Customizable Analysis – Adjustable lookback period and display options allow traders to focus on the data that matters most.
This indicator is an essential tool for traders looking to refine their decision-making process by leveraging volatility-based statistics. Whether trading Forex, stocks, or commodities, it provides valuable insights into price action trends and market conditions.
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Normalized Price ComparisonNormalized Price Comparison Indicator Description
The "Normalized Price Comparison" indicator is designed to provide traders with a visual tool for comparing the price movements of up to three different financial instruments on a common scale, despite their potentially different price ranges. Here's how it works:
Features:
Normalization: This indicator normalizes the closing prices of each symbol to a scale between 0 and 1 over a user-defined period. This normalization process allows for the comparison of price trends regardless of the absolute price levels, making it easier to spot relative movements and trends.
Crossing Alert: It features an alert functionality that triggers when the normalized price lines of the first two symbols (Symbol 1 and Symbol 2) cross each other. This can be particularly useful for identifying potential trading opportunities when one asset's relative performance changes against another.
Customization: Users can input up to three symbols for analysis. The normalization period can be adjusted, allowing flexibility in how historical data is considered for the scaling process. This period determines how many past bars are used to calculate the minimum and maximum prices for normalization.
Visual Representation: The indicator plots these normalized prices in a separate pane below the main chart. Each symbol's normalized price is represented by a distinct colored line:
Symbol 1: Blue line
Symbol 2: Red line
Symbol 3: Green line
Use Cases:
Relative Performance Analysis: Ideal for investors or traders who want to compare how different assets are performing relative to each other over time, without the distraction of absolute price differences.
Divergence Detection: Useful for spotting divergences where one asset might be outperforming or underperforming compared to others, potentially signaling changes in market trends or investment opportunities.
Crossing Strategy: The alert for when Symbol 1 and Symbol 2's normalized lines cross can be used as a part of a trading strategy, signaling potential entry or exit points based on relative price movements.
Limitations:
Static Alert Messages: Due to Pine Script's constraints, the alert messages cannot dynamically include the names of the symbols being compared. The alert will always mention "Symbol 1" and "Symbol 2" crossing.
Performance: Depending on the timeframe and the number of symbols, performance might be affected, especially on lower timeframes with high data frequency.
This indicator is particularly beneficial for those interested in multi-asset analysis, offering a streamlined way to observe and react to relative price movements in a visually coherent manner. It's a powerful tool for enhancing your trading or investment analysis by focusing on trends and relationships rather than raw price data.
MeanReversion - LogReturn/Vola ZScoreShows the z-Score of log-return (blue line) and volatility (black line). In statistics, the z-score is the number of standard deviations by which a value of a raw score is above or below the mean value.
This indicator aggregates z-score based on two indicators:
MeanReversion by Logarithmic Returns
MeanReversion by Volatility
Change the time period in bars for longer or shorter time frames. At a daily chart 252 mean on trading year, 21 mean one trading month.
Guassian Distribution Forecast [prediction intervals]The Indicator
The Indicator combines volatility and frequency distributions to forecast an area of possible price expansion with an approximate confidence interval / level and level of significance (significance level).
The Script Formula
Additional comments
To alter the models forecasting precision to reflect a given confidence interval, e.g the 90% confidence level (C.L.), use the 1.64 multiplier (toggle value in "Standard normal distribution sd" setting), to use a specific C.L., e.g. the 85th percentile either search for this on google, or calculate it yourself using a Standard Normal Distribution Probability table. Additionaly volatility may be changed by toggling the lookback period setting, this can be thought of as widening the distribution tails.
The look forward parameter is currently fixed at 20, this is because it does not currently work correctly with higher integers, I will try resolve this problem and any other bugs as soon as possible
Rocket Grid Algorithm - The Quant ScienceThe Rocket Grid Algorithm is a trading strategy that enables traders to engage in both long and short selling strategies. The script allows traders to backtest their strategies with a date range of their choice, in addition to selecting the desired strategy - either SMA Based Crossunder or SMA Based Crossover.
The script is a combination of trend following and short-term mean reversing strategies. Trend following involves identifying the current market trend and riding it for as long as possible until it changes direction. This type of strategy can be used over a medium- to long-term time horizon, typically several months to a few years.
Short-term mean reversing, on the other hand, involves taking advantage of short-term price movements that deviate from the average price. This type of strategy is usually applied over a much shorter time horizon, such as a few days to a few weeks. By rapidly entering and exiting positions, the strategy seeks to capture small, quick gains in volatile market conditions.
Overall, the script blends the best of both worlds by combining the long-term stability of trend following with the quick gains of short-term mean reversing, allowing traders to potentially benefit from both short-term and long-term market trends.
Traders can configure the start and end dates, months, and years, and choose the length of the data they want to work with. Additionally, they can set the percentage grid and the upper and lower destroyers to manage their trades effectively. The script also calculates the Simple Moving Average of the chosen data length and plots it on the chart.
The trigger for entering a trade is defined as a crossunder or crossover of the close price with the Simple Moving Average. Once the trigger is activated, the script calculates the total percentage of the side and creates a grid range. The grid range is then divided into ten equal parts, with each part representing a unique grid level. The script keeps track of each grid level, and once the close price reaches the grid level, it opens a trade in the specified direction.
The equity management strategy in the script involves a dynamic allocation of equity to each trade. The first order placed uses 10% of the available equity, while each subsequent order uses 1% less of the available equity. This results in the allocation of 9% for the second order, 8% for the third order, and so on, until a maximum of 10 open trades. This approach allows for risk management and can help to limit potential losses.
Overall, the Rocket Grid Algorithm is a flexible and powerful trading strategy that can be customized to meet the specific needs of individual traders. Its user-friendly interface and robust backtesting capabilities make it an excellent tool for traders looking to enhance their trading experience.
Grid Indicator - The Quant ScienceQuickly draw a 10-level grid on your chart with our open-source tool.
Our grid tool offers a unique solution to traders looking to maximize their profits in volatile market conditions. With its advanced features, you can create customized grids based on your preferred start price and line distance, allowing you to easily execute trades and capitalize on price movements. The tool works automatically, freeing up your time to focus on other important aspects of your trading strategy.
The benefits of using this tool are numerous. Firstly, it eliminates the need for manual calculation, making the analysis process much more efficient. Secondly, the automatic nature of the tool ensures that each grids are draw at precisely prices, giving you the best possible chance of maximizing your analysis. Finally, the ability to easily customize grids means that you can adapt your strategy quickly and effectively, even in rapidly changing market conditions.
So why wait? Take control of your trading and start using our innovative grid tool today! With its advanced features and ease of use, it's the perfect solution for traders of all levels looking to take their trading to the next level.
HOW TO USE
Using it is easy. Add the script to your chart and set the price and distance between the grids.
Probabilities Module - The Quant Science This module can be integrate in your code strategy or indicator and will help you to calculate the percentage probability on specific event inside your strategy. The main goal is improve and simplify the workflow if you are trying to build a quantitative strategy or indicator based on statistics or reinforcement model.
Logic
The script made a simulation inside your code based on a single event. For single event mean a trading logic composed by three different objects: entry, take profit, stop loss.
The script scrape in the past through a look back function and return the positive percentage probability about the positive event inside the data sample. In this way you are able to understand and calculate how many time (in percentage term) the conditions inside the single event are positive, helping to create your statistical edge.
You can adjust the look back period in you user interface.
How can set up the module for your use case
At the top of the script you can find:
1. entry_condition : replace the default condition with your specific entry condition.
2. TPcondition_exit : replace the default condition with your specific take profit condition.
3. SLcondition_exit : replace the default condition with your specific stop loss condition.
Extreme Volume Support Resistance LevelsExtreme Volume Support Resistance Levels are S/R levels(zones, basically), based on extreme volume .
Settings:
Lookback -- number of bars, which algorithm will be using;
Volume Threshold Period -- period of MA (Volume MA), which smoothers volume in order to find the extremes;
Volume Threshold Multiplier -- multiplier for Volume MA, which "lift" Volume MA and thus will provide the algorithm with more accurate extreme volume ;
Number of zones to show -- number of last S/R zones, which will be shown on the chart.
RU:
Extreme Volume Support Resistance Levels — это уровни S/R (зоны, в основном), основанные на избыточном объеме.
Параметры:
Lookback -- число баров, которое алгоритм будет использовать для расчётов;
Volume Threshold Period -- период MA (Volume MA), которая сглаживает объем для нахождения экстремумов объёма;
Volume Threshold Multiplier -- множитель для Volume MA, который "поднимает" Volume MA и тем самым обеспечивает алгоритм более точными значениями экстремального объёма;
Количество зон для отображения -- количество оставшихся зон S/R, которые отображаются на графике.
Real Cummulative Delta (New TV Function)Thanks to the new TradingView indicator Up/Down Volume, it is now possible to get accurate information on Agression (market buying vs market selling)
However, as they only provide the value of delta, I've made this indicator to show the cummulative value, in the form of candles.
It is great to detect divergences in the macro and in the micro scale (As in divergences in each candle and divergences in higher or lower tops or bottoms)
Hope you can make good use of it!
Q-TrendQ-Trend is an multipurpose indicatorm that can be used for swing- and trend-trading equally on any timeframe (non-volatile markets are better for this thing).
Settings:
Trend period - used to calculate trend line in the special moments(will explain below);
ATR Multiplier - changes sensitivity. The higher the multiplier = the more sensitive it is.
Also option to smooth source data (helps get cleaner signals, as always).
How to use?
Signals are given on the chart. Also ou can use trend line as S/R line.
The idea behind:
Terms:
SRС = Source
TL = trend line;
MP = ATR multiplier;
ATR = ATR :)
TL = (highest of source P-bars back + lowest of source P-bars back) / 2
Epsilon = MP * ATR
I was thinking for a week about combining volatility and relation between highest and lowest price point. That why I called indicator Q-Trend = Quantitative Trend , as I was trying to think about price in a mathematical way.
Okay, time to go philosophical:
1) TL is shows good price trend, but as it is slow enough and not enough informative, we need add additional conditions to produce signals.
2) Okay, so what can we add as conditions? We need to take volatility into account, as it is crucial in the moments of market uncertainty. So let's use ATR (Average True Range) somehow. My idea is that if SRC breaks TL + ATR , then it means that there will be upmove and we update our TL . Analogically for SRC breaking TL - ATR (breaks are crosses of TL +- ATR lines) .
Conclusion:
- if SRC breaks TL + ATR , it is a BUY signal and update of trend line;
- if SRC breaks TL - ATR , it is a SELL signal and update of trend line;
I think that such indicator already exisits on TradingView, as I've already saw something similar, but long ago, so please don't report, if such thing already exists.
But if not, then I hope, that you will gain some profits with Q-Trend :)
I will continue my work on this thing, so stay tuned.
Trade with your own risks and have your profits!
Wish you all the best!
- Tarasenko Fyodor
[EDU] Close Open Estimation Signals (COE Signals)EN:
Close Open Estimation ( aka COE ) is a very simple swing-trading indicator based on even simpler idea. This indicator is from my educational series, which means that I just want to share with another way to look at the market in order to broaden your knowledge .
Idea :
Let's take n previous bars and make a sum a of close - open -values of each bar. Knowledgeable of you may already see the similarity to RSI calculation idea . Now let's plot this sum and see what we have now.
We can see, that whenever COE crosses over 0-level, uptrend begins, and if COE crosses under 0-level, downtrend begins. The speed of such signals can be adjusted by changing lookback period: the lower the lookback, the faster signals you get, but high-quality ones can be obtained only via not-so-fast lookback as when the market is consolidating or volatility is to high, there can be many garbage signals, like 95+% of other indicators have.
Let's explore more and calculate volatility of COE(v_coe in the code): current COE - previous CEO .
Now it appears that when v_coe crosses over 0-level, it's a signal, that this is a new low and soon the uptrend will follow. Analogically for crossing under 0-level .
I guess now you understood what these all are about: COE crossings show global trend signals , while Volatility COE ( v_coe or VCOE ) crossings show reversal points .
For signals I further calculated volatility of VCOE(VVCOE) and then volatility of VVCOE(VVVCOE). Why? Because for me they seem to be more accurate, but you are welcome to experiment and figure best setups for yourself and by yourself, I just share my opinion and experience .
COE can be helpful only in high liquidity markets with good trend or wide sideways .
If you want to experiment with COE, just copy the code and play with it. Curious of you will probably find it helpful eventhough the idea is way too simple.
By it's perfomance COE can probably beat QQE at open price settings.
(use open of the price at indicator to get zero repaint! )
Examples :
If you any questions, feel free to DM me or leave comments.
Good luck and take your profits!
- Fyodor Tarasenko
RU:
Close Open Estimation ( aka COE ) — это очень простой индикатор свинг-трейдинга, основанный на еще более простой идее. Этот индикатор из моей образовательной серии, а это значит, что я просто хочу поделиться с другим взглядом на рынок , чтобы расширить ваши знания .
Идея :
Возьмем n предыдущих баров и составим сумму a из close - open -значений каждого бара. Знающие люди могут уже заметить сходство с идеей расчета RSI . Теперь давайте построим эту сумму и посмотрим, что у нас сейчас есть.
Мы видим, что всякий раз, когда COE пересекает выше 0-уровня, начинается восходящий тренд , а если COE пересекает ниже 0-уровня, начинается нисходящий тренд. Скорость таких сигналов можно регулировать изменением ретроспективы: чем меньше ретроспектива, тем быстрее вы получаете сигналы, но качественные можно получить только через не- такой быстрый взгляд назад, как когда рынок консолидируется или волатильность слишком высока, может быть много мусорных сигналов, как у 95+% других индикаторов.
Давайте рассмотрим больше и рассчитаем волатильность COE(v_coe в коде): текущий COE - предыдущий CEO .
Теперь кажется, что когда v_coe пересекает уровень 0, это сигнал о том, что это новый минимум и вскоре последует восходящий тренд . Аналогично для пересечения под 0-уровнем .
Думаю, теперь вы поняли, о чем все это: COE пересечения показывают глобальные сигналы тренда , а пересечения Volatility COE ( v_coe или VCOE ) показывают точки разворота .
Для сигналов я дополнительно рассчитал волатильность VCOE(VVCOE), а затем волатильность VVCOE(VVVCOE). Почему? Потому что для меня они кажутся более точными, но вы можете поэкспериментировать и подобрать оптимальные настройки для себя и для себя, я просто делюсь своим мнением и опытом .
COE может быть полезен только на рынках с высокой ликвидностью и хорошим трендом или широким боковиком .
Если вы хотите поэкспериментировать с COE, просто скопируйте код и поэкспериментируйте с ним. Любознательные из вас, вероятно, сочтут это полезным, хотя идея слишком проста.
По своей результативности СОЕ может составить конкуренцию широко известному QQE, используя open цены.
(используйте open цены на индикаторе, чтобы получить нулевую перерисовку! )
Примеры :
Если у вас есть вопросы, пишите мне в личные сообщения или оставляйте комментарии.
Удачи и профита всем!
- Федор Тарасенко
Probabilistic Analysis Table - The Quant ScienceProbabilistic Analysis Table - The Quant Science ™ is the quantitative table measuring the probability of price changes and quantifies the ratio of sessions for three different assets.
This table measures the ratios of bull and bear events and measures the probability of each event through data generated automatically by the algorithm.
The data are calculated for three different assets:
1. Main asset: set on the chart.
2. Second asset: set by user interface.
3. Third asset: set by the user interface.
The timeframe is set by the chart and is the same for all three assets. You can change the timeframes directly from the chart.
The user can add tickers and adjust the analysis period directly from the user interface. The user can edit the percentage changes and the values to be analyzed for each asset, directly from the user interface.
TABLE DESCRIPTION
1. Total global trade session: are the total number of bars for each asset.
2. Total positive trade session: are the number of positive bars for each asset.
3. Probability positive trade session: is the ratio of total sessions to positive sessions.
4. Total negative trade session: are the number of negative bars for each asset.
5. Probability negative trade session: is the ratio of total sessions to negative sessions.
6. Positive trade session 0.50%: are the number of positive bars greater than 0.50% for each asset.
7. Probability positive trade session 0.50%: is the ratio of total sessions to positive sessions with increases greater than 0.50% (this value is set by default, you can change it from the user interface).
8. Negative trade session -0.50%: are the number of negative bars smaller than -0.50% for each asset.
9. Probability negative trade session -0.50%: is the ratio of total sessions to negative sessions with declines less than -0.50% (this value is set by default, you can change it from the user interface).
10. Positive trade session 1%: are the number of positive bars greater than 1% for each asset.
11. Probability positive trade session 1%: is the ratio of total sessions to positive sessions with increases greater than 1% (this value is set by default, you can change it from the user interface).
12. Negative trade session -1%: are the number of negative bars less than -1% for each asset.
13. Probability negative trade session -1%: is the ratio of total sessions to negative sessions with declines less than -1% (this value is set by default, you can change it from the user interface).
This table was created for traders and quantitative investors who need to quickly analyze session ratios and probabilities.
Yield Trend Indicator - The Quant ScienceYield Trend Indicator - The Quant Science™ is a quantitative indicator representing percentage yields and average percentage yields of three different assets.
Percentage yields are fundamental data for all quantitative analysts. This indicator was created to offer immediate calculations and represent them through an indicator consisting of lines and columns. The columns represent the percentage yield of the current timeframe, for each asset. The lines represent the average percentage yield, of the current timeframe, for each asset.
The user easily adds tickers from the user interface and the algorithm will automatically create the quantitative data of the chosen assets.
The blue refers to the main asset, the main set on the chart.
The yellow refers to the second asset, added by the user interface.
The red refers to the third asset, added by the user interface.
The timeframe is for all assets the one set to the chart, if you use a chart with timeframe D, all data is processed on this timeframe. You can use this indicator on all timeframes without any restrictions.
The user can change the type of formula for calculating the average yield easily via the user interface. This software includes the following formulas:
1. SMA (Simple Moving Average)
2. EMA (Exponential Moving Average)
3. WMA (Weighted Moving Average)
4. VWMA (Volume Weighted Moving Average)
The user can customize the indicator easily through the user interface, changing colours and many other parameters to represent the data on the chart.
