NIFTY Option Buy Strategy MASTER v1This script is a complete option buying strategy framework for NIFTY, designed for both intraday and positional swing trades.
🔹 Built using multi-timeframe analysis (EMAs, MACD, RSI)
🔹 Combines key macro filters: India VIX, PCR, FII/DII net cash flows
🔹 Supports both Call (CE) and Put (PE) entries
🔹 Includes manual input dashboard for real-time market context
🔹 Trade logic includes:
Bollinger Band breakouts
Volume confirmation
VWAP filtering
EMA crossover + MACD alignment
Resistance/support proximity from option chain (manual)
📈 Smart Trade Management:
Multi-target system (e.g., exit 50% at RR=1, 50% at RR=2)
Trailing stop-loss after target 1 hits
Automatic exit on SL/TP or reverse signals
Visual markers for all entries, exits, and stops
📊 Built-in Dashboard:
Displays India VIX, PCR, FII/DII flows, and S/R levels
Strike price selection (ATM + offset logic)
🧪 Ideal for backtesting, alerts, and real-time execution.
Can be used with alerts + webhook for automated trading or signal generation.
⚠️ Note: This script is for educational purposes only. Always test on paper trading before going live.
Temel Analiz
GStrategy XRP 4hRSI + Smart Money Trading Strategy
This strategy combines RSI (Relative Strength Index) with Smart Money detection to identify high-probability reversal trades in trending markets. It uses strict entry/exit rules with a 10% hard stop-loss to manage risk.
Strategy Logic
1. Entry Conditions
Long Entry (Buy):
RSI < 30 (Oversold condition)
Smart Money Confirmation:
Bullish candle (close > open)
Volume > 35-period SMA (unusual buying pressure)
Price hits a 5-bar low (potential reversal level)
Short Entry (Sell):
RSI > 70 (Overbought condition)
Smart Money Confirmation:
Bearish candle (close < open)
Volume > 20-period SMA (unusual selling pressure)
Price hits a 5-bar high (potential rejection level)
2. Exit Conditions
Long Exit: RSI ≥ 70 (Take profit at overbought)
Short Exit: RSI ≤ 40 (Take profit at mid-level)
Stop-Loss: Hard 10% stop on all trades
3. Position Management
No overlapping trades (only 1 position at a time).
Stop-loss visualized on the chart (red line).
Key Features
✅ RSI Filter: Avoids false reversals by requiring extreme RSI levels.
✅ Smart Money Detection: Confirms institutional activity via volume + price action.
✅ Asymmetric Exits:
Longs exit at RSI 70 (full overbought).
Shorts exit earlier at RSI 40 (conservative profit-taking).
✅ Strict Risk Control: 10% stop-loss prevents large drawdowns.
Indicators Used
RSI (14-period)
Volume SMA (20 for shorts, 35 for longs)
5-bar High/Low for price extremes.
S&P500 Long nach X roten Tagen)The strategy buys the S&P future after 4 consecutive red days and an elevated VIX index, and exits either time-based, with a trailing stop, or after a predefined holding period.
Session HighlightsCrypto relevant global equity market open/close indicator, high opacity background highlights follow the following color scheme & daily time ranges (times in EST):
Orange: 8:00 PM to 9:30 PM (Sunday - Thursday): Japan/South Korea
Yellow: 9:30 PM to +1D 4:00 AM (Sunday - Thursday): Hong Kong
Aqua: 8:00 AM to 9:30 AM (Monday - Friday): US Premarket / Macro Data Release
Blue: 9:30 AM to 4:00 PM (Monday - Friday): US
White: 4:00 PM to +2D 6:00 PM (Friday - Sunday): Weekend
*Market Holidays not accounted for
High Volume Color ChangeHigh Volume Color Change Strategy
This indicator combines volume analysis with MACD to identify potential trading opportunities. It tracks trading performance and provides real-time P&L calculations.
Key Features:
1. Volume Analysis:
- Detects high volume candles (1.5x above average volume)
- Uses a 10-bar lookback period for volume comparison
- Marks high volume candles on the chart (optional)
2. Trading Signals:
- Generates buy signals when price changes direction after a high volume candle
- Generates sell signals when price changes direction after a high volume candle
- Uses MACD convergence as an additional filter
- Shows signal markers on the chart
3. Performance Tracking:
- Tracks total trades and profitable trades
- Calculates cumulative P&L
- Shows current position and unrealized P&L
- Displays win rate percentage
4. Money Management:
- Uses initial balance to determine position size
- Compounds profits/losses for subsequent trades
- Calculates P&L based on percentage changes
- Tracks current balance and total P&L
5. Customization:
- Adjustable volume threshold
- Configurable lookback period
- Optional display of volume and signal labels
- Date range selection for analysis
6. Alerts:
- Separate alerts for buy and sell signals
- Clear messages indicating signal type
The strategy is designed for traders who want to:
- Identify high-volume price reversals
- Track their trading performance
- Manage position sizing based on account balance
- Compound their profits/losses
- Get clear buy/sell signals with alerts
Sesiones, FVG + Alertas [terrylag]Indicate the highs and lows of the most important sessions and alert when there is manipulation in the new session by marking the FVG imbalances to make an optimal entry.
Quarterly Earnings with NPMThis indicator is designed in a way so that it can indicate the quarterly earnings and also it can show us the change in sales and net profit margin as shown by Mark Minervini in his classes.
True SeasonalityCONCEPTS
True Seasonality Indicator designed to forecast price based on historical data, best use on daily chart.
DETAILS & EXAMPLE OF HOW TO USE
On Gold chart, the blue graph indicate the few projected days in the future. On 8 April 2025, the indicator showing potential uptrend movement until mid of April, and after that sideways for sometimes.
FEATURES
Adjustable forecast bars & lookback
LIMITATIONS
The Indicator is best applied on daily chart.
Not intended as a stand-alone signal, but should be as part of long-term strategy analysis.
Should be combined with other lower-timeframe technical tools like supply and demand to find entry and confirmation.
Valuation ToolOVERVIEW
Valuation Indicator is a trading tool which designed to help you identify the relative value of an asset, compared to the other asset.
CONCEPTS
The Indicator help you calculate the relative value between chosen assets by measuring their price deviation, for example comparing NASDAQ with Dollar Index or Treasury Bond. It is used primarily to identify overbought and oversold conditions.
To understand its relative value, Equities and Indices are usually compared to the Treasury Bond and Dollar Index, meanwhile other asset like Major FX Pairs, Precious Metals, and Energies are compared to Dollar Index.
The Indicator comes with adjustable parameters, like threshold, timeframe, and smooth value to flexibly reduce noice and improve accuracy.
DETAILS & EXAMPLE OF HOW TO USE
An example of Nasdaq chart to demonstrate the indicator in real market scenario.
Blue graph indicate the Dollar Index (DYX) Index, showing undervalued under -0.75 level.
On the same time, Orange graph indicate the Treasury Bond Index, showing also an undervalued level under -0.75.
Base on those information, combine with other technical strategy on the same timeframe or even lower timeframe. For example using Supply & Demand to find the entry.
The result is a massive push to the upside hitting more than 1:3.
FEATURES
3 Flexible symbols to pairing in 1 indicator.
Show and hide each symbol independently.
Adjustable timeframe, smoothing value, lower & upper threshold.
LIMITATIONS
The Indicator is best applied on weekly or daily chart.
Not intended as a stand-alone signal, but should be as part of long-term strategy analysis.
Should be combined with other lower-timeframe technical tools like supply and demand.
COT Commitment of Traders IndexOVERVIEW
Commitment of Traders (COT) Indicator is a trading tool which designed to visualise net positions/commitment of traders that is reported weekly basis to the commissions.
CONCEPTS
The Indicator help you understand the position of long or short trades by market participants relative to their historical positioning. The change in position will help you in analysing the medium-to-long term market trend.
The commercial traders represents producers or consumers of the commodity that usually positions as hedgers in the market, protecting their asset over market fluctuation risk. The non-commercial traders represents fund or money managers that the goal is speculate and take profit from the market fluctuations. Non-reportable represents small or retail traders.
Understand the relative of those all traders will give better insight of how to positions ourselves in the market.
DETAILS & EXAMPLE OF HOW TO USE
An example of Gold Future chart (GC1!) to demonstrate the indicator in real market scenario.
Blue graph indicate the Commercial Index, showing on the extreme low under 20 level. Commercial traders as a hedgers indicate the turning point over an asset in extreme value. This showing the potential change in market direction the upside.
On the same time, Orange graph indicate the Non-Commercial Index, showing an extreme high level above 80. Non-Commercial traders will most of the time trade with the trend. This showing the potential continuation of market direction to the upside.
Base on those information, combine with other technical strategy on the same timeframe or even lower timeframe. For example using Supply & Demand to find the entry.
The result is a massive push to the upside in the long term direction.
FEATURES
3 Index in 1 indicator
Customisable historical period and threshold
LIMITATIONS
The Indicator is best applied on weekly, due to the weekly release of COT data.
Not intended as a stand-alone signal, but should be as part of long-term strategy analysis.
Should be combined with other lower-timeframe technical tools like supply and demand.
Enhanced Seasonality Trade BacktestEnhanced Seasonality Trade Backtest
Overview
A comprehensive Pine Script indicator that backtests seasonal trading strategies by analyzing historical price performance during specific date ranges. The tool provides detailed statistics, visual markers, and election cycle filtering to identify profitable seasonal patterns.
Key Features
📊 Backtesting Engine
Tests up to 50 years of historical data
Configurable entry/exit dates (day/month)
Automatic holiday/weekend date adjustment
Separate analysis for long and short positions
🗳️ Election Cycle Filter
All Years: Test every year in the lookback period
Election Years: US presidential election years only (2024, 2020, 2016...)
Pre-Election Years: Years before elections (2023, 2019, 2015...)
Post-Election Years: Years after elections (2021, 2017, 2013...)
📈 Comprehensive Statistics
Win rate percentage
Total and average returns
Best/worst performing years
Detailed trade-by-trade breakdown
Years tested vs. years filtered
🎯 Visual Indicators
Entry/exit lines for all historical trades
Future trade date projections
Background highlighting during trade periods
Color-coded performance labels
⚙️ Customization Options
Toggle between long/short analysis
Show/hide price and date details
Adjustable table position
Future trade date visualization
Use Cases
Seasonal Trading: Identify recurring profitable periods (e.g., "Sell in May")
Election Cycle Analysis: Test how political cycles affect market performance
Strategy Validation: Backtest specific date-range strategies
Risk Assessment: Analyze worst-case scenarios and drawdowns
Perfect For
Swing traders looking for seasonal edges
Portfolio managers timing market entries/exits
Researchers studying market cyclicality
Anyone wanting to quantify seasonal market behavior
ONLY WORKS IN 1D TIME FRAME
ATR (14) Watermark📈 ATR (14) Watermark – Volatility Snapshot on Your Chart
This lightweight overlay displays the ATR (14) value and its percentage of the current price directly on your chart — along with a visual cue (🔴🟡🟢) to indicate volatility levels.
🔧 Features:
ATR (14) value and percentage of current price
🔴 High, 🟡 Medium, 🟢 Low volatility indicator
Adjustable vertical & horizontal positioning
Fully configurable text size and color
Clean, unobtrusive table watermark overlay
This tool is perfect for traders who want to quickly assess volatility without crowding the chart with lines or indicators.
DXY - JaviZzThe DXY indicator is a technical analysis tool used to compare the US Dollar Index (DXY) with other financial assets, such as the EUR/USD, in order to identify divergence signals. These divergences occur when the price movement of the DXY does not match the price movement of the other asset, which can be an indication of a possible trend change.
Features of the DXY Divergence Indicator:
- Allows you to select TVC or Capitol sources.
- Direct and in-line comparison: You can directly compare the movements of the DXY with the EUR/USD in a convenient, practical, and visual way on a single chart.
- It is an extremely accurate indicator, capable of clearly and effectively identifying local highs and lows.
- Since it is inverted and follows the same direction as the EUR/USD, it is very easy to detect divergences.
Ideal for traders who use smartphones or tablets and are looking to take advantage of the differences in the behavior of these two assets and make informed trading decisions anytime, anywhere.
Enhanced Zones with Volume StrengthEnhanced Zones with Volume Strength
Your reliable visual guide to market zones — now with Multi-Timeframe (MTF) power!
What you get:
Clear visual zones on your chart — color-coded boxes that highlight important price areas.
Blue Boxes for neutral zones — easy to spot areas of indecision or balance.
Gray Boxes to show normal volume conditions, giving you context without clutter.
Green Boxes highlighting bullish zones where strength is showing.
Red Boxes marking bearish zones where weakness might be in play.
Multi-Timeframe Support:
Seamlessly visualize these zones from higher timeframes directly on your current chart for a bigger-picture view, helping you make smarter trading decisions.
How to use it:
Adjust the box width (in bars) to fit your trading style and timeframe.
Customize colors and opacity to suit your chart theme.
Toggle neutral blue and gray volume boxes on/off to focus on what matters most to you.
Set the maximum number of boxes to keep your chart clean and performant.
Why you’ll love it:
This indicator cuts through the noise by visually marking zones where volume and price action matter the most — without overwhelming your chart. The MTF feature means you’re always aligned with higher timeframe trends without switching views.
Pro tip:
Use these boxes as dynamic support/resistance areas or to confirm trade setups alongside your favorite indicators.
No complicated formulas here, just crisp, actionable visuals designed for clarity and confidence.
COT-Index-NocTradingCOT Index Indicator
The COT Index Indicator is a powerful tool designed to visualize the Commitment of Traders (COT) data and offer insights into market sentiment. The COT Index is a measurement of the relative positioning of commercial traders versus non-commercial and retail traders in the futures market. It is widely used to identify potential market reversals by observing the extremes in trader positioning.
Customizable Timeframe: The indicator allows you to choose a custom time interval (in months) to visualize the COT data, making it flexible to fit different trading styles and strategies.
How to Use:
Visualize Market Sentiment: A COT Index near extremes (close to 0 or 100) can indicate potential turning points in the market, as it reflects extreme positioning of different market participant groups.
Adjust the Time Interval: The ability to adjust the time interval (in months) gives traders the flexibility to analyze the market over different periods, which can be useful in detecting longer-term trends or short-term shifts in sentiment.
Combine with Other Indicators: To enhance your analysis, combine the COT Index with your technical analysis.
This tool can serve as an invaluable addition to your trading strategy, providing a deeper understanding of the market dynamics and the positioning of major market participants.
Doganayy2 Buy/Sell & liquidityTrap🔧 User-Changeable Settings and Their Meanings
1. ✅ Is Wick Filter Active?
What does it do?: Controls the length of the candle wick.
Effect: If active, a long wick is considered a trap (a sign of manipulation).
2. 📊 Is Volume Filter Active?
What does it do?: Controls abnormally high volume according to the volume average.
Effect: If active, high volume candles are considered for a liquidity trap signal.
3. 📈 Is RSI Filter Active?
What does it do?: Controls overbought/oversold according to the RSI level.
Effect: If active;
If RSI > ?, a long trap is searched.
If RSI < ?, a short trap is searched.
4. 🔴🟢 Is Candle Color (Direction) Filter Active?
What does it do?: Controls whether the candle is green or red.
Effect: If active;
A red candle (selling pressure) is required for a long trap.
A green candle (buying pressure) is required for a short trap.
5. 🧮 Is Fibonacci Level Filter Active?
What does it do?: Checks whether the price has reached important Fibonacci levels.
Effect: If active;
For a long trap, the price must rise above the Fibo level.
For a short trap, the price must fall below the Fibo level.
6. 📏 Is ATR Filter Active?
What does it do?: Checks whether there is sufficient deviation in the price according to the ATR.
Effect: If active;
A trap signal is given according to whether the price has moved too far from the ATR.
📌 As a result:
As these filters are activated, the system's long/short trap detection becomes tighter and produces fewer but more reliable signals. If you close the filters, you will receive more signals, but reliability may decrease.
Purpose of the indicator: To present buy/sell opportunities by detecting liquidity traps.
PER Bands (Auto EPS)PER Bands Indicator - Technical Specification
Function
This PineScript v6 overlay indicator displays horizontal price bands based on Price-to-Earnings Ratio multiples. The indicator calculates price levels by multiplying earnings per share values by user-defined PER multiples, then plots these levels as horizontal lines on the chart.
Data Sources
The script attempts to automatically retrieve earnings per share data using TradingView's `request.financial()` function. The system first queries trailing twelve months EPS data, then annual EPS data if TTM is unavailable. When automatic retrieval fails or returns zero values, the indicator uses manually entered EPS values as a fallback.
Configuration Options
Users can configure five separate PER multiples (default values: 10x, 15x, 20x, 25x, 30x). Each band supports individual color customization and adjustable line width settings from 1 to 5 pixels. The indicator includes toggles for band visibility and optional fill areas between adjacent bands with 95% transparency.
Visual Components
The indicator plots five horizontal lines representing different PER valuation levels. Optional fill areas create colored zones between consecutive bands. A data table in the top-right corner displays current EPS source, EPS value, current PER ratio, and calculated price levels for each configured multiple.
Calculation Method
The indicator performs the following calculations:
- Band Price = Current EPS × PER Multiple
- Current PER = Current Price ÷ Current EPS
These calculations update on each bar close using the most recent available EPS data.
Alert System
The script includes alert conditions for price crossovers above the lowest PER band and crossunders below the highest PER band. Additional alert conditions can be configured for any band level through the alert creation interface.
Debug Features
Debug mode displays character markers on the chart indicating when TTM or annual EPS data is available. This feature helps users verify which data source the indicator is using for calculations.
Data Requirements
The indicator requires positive, non-zero EPS values to function correctly. Stocks with negative earnings or zero EPS will display "N/A" for current PER calculations, though bands will still plot using the manual EPS input value.
Exchange Compatibility
Automatic EPS data availability varies by exchange. United States equity markets typically provide comprehensive fundamental data coverage. International markets may have limited automatic data availability, requiring manual EPS input for accurate calculations.
Technical Limitations
The indicator cannot fetch real-time EPS updates and relies on TradingView's fundamental data refresh schedule. Historical EPS changes are not reflected in past band positions, as the indicator uses current EPS values for all historical calculations.
Display Settings
The information table shows EPS source type (TTM Auto, Annual Auto, Manual, or Manual Fallback), allowing users to verify data accuracy. The table refreshes only on the last bar to optimize performance and reduce computational overhead.
Code Structure
Built using PineScript v6 syntax with proper scope management for plot and fill functions. The script uses global scope for all plot declarations and conditional logic within plot parameters to handle visibility settings.
Version Requirements
This indicator requires TradingView Pine Script version 6 or later due to the use of `request.financial()` functions and updated syntax requirements for plot titles and fill operations.
US10Y 63-Day Range Percentageto checking 10 years pressure . using this strategy where you should risk off and risk on
Ethereum Rainbow Chart (9 Levels with Legend)The Ethereum Rainbow Chart is a long-term, color-coded chart that displays Ethereum’s price on a logarithmic scale to show historical trends and growth patterns. It uses colored bands to highlight different price zones, helping to visualize how ETH’s price has moved over time without focusing on short-term fluctuations.
Advanced Petroleum Market Model (APMM)Advanced Petroleum Market Model (APMM): A Multi-Factor Fundamental Analysis Framework for Oil Market Assessment
## 1. Introduction
The petroleum market represents one of the most complex and globally significant commodity markets, characterized by intricate supply-demand dynamics, geopolitical influences, and substantial price volatility (Hamilton, 2009). Traditional fundamental analysis approaches often struggle to synthesize the multitude of relevant indicators into actionable insights due to data heterogeneity, temporal misalignment, and subjective weighting schemes (Baumeister & Kilian, 2016).
The Advanced Petroleum Market Model addresses these limitations through a systematic, quantitative approach that integrates 16 verified fundamental indicators across five critical market dimensions. The model builds upon established financial engineering principles while incorporating petroleum-specific market dynamics and adaptive learning mechanisms.
## 2. Theoretical Framework
### 2.1 Market Efficiency and Information Integration
The model operates under the assumption of semi-strong market efficiency, where fundamental information is gradually incorporated into prices with varying degrees of lag (Fama, 1970). The petroleum market's unique characteristics, including storage costs, transportation constraints, and geopolitical risk premiums, create opportunities for fundamental analysis to provide predictive value (Kilian, 2009).
### 2.2 Multi-Factor Asset Pricing Theory
Drawing from Ross's (1976) Arbitrage Pricing Theory, the model treats petroleum prices as driven by multiple systematic risk factors. The five-factor decomposition (Supply, Inventory, Demand, Trade, Sentiment) represents economically meaningful sources of systematic risk in petroleum markets (Chen et al., 1986).
## 3. Methodology
### 3.1 Data Sources and Quality Framework
The model integrates 16 fundamental indicators sourced from verified TradingView economic data feeds:
Supply Indicators:
- US Oil Production (ECONOMICS:USCOP)
- US Oil Rigs Count (ECONOMICS:USCOR)
- API Crude Runs (ECONOMICS:USACR)
Inventory Indicators:
- US Crude Stock Changes (ECONOMICS:USCOSC)
- Cushing Stocks (ECONOMICS:USCCOS)
- API Crude Stocks (ECONOMICS:USCSC)
- API Gasoline Stocks (ECONOMICS:USGS)
- API Distillate Stocks (ECONOMICS:USDS)
Demand Indicators:
- Refinery Crude Runs (ECONOMICS:USRCR)
- Gasoline Production (ECONOMICS:USGPRO)
- Distillate Production (ECONOMICS:USDFP)
- Industrial Production Index (FRED:INDPRO)
Trade Indicators:
- US Crude Imports (ECONOMICS:USCOI)
- US Oil Exports (ECONOMICS:USOE)
- API Crude Imports (ECONOMICS:USCI)
- Dollar Index (TVC:DXY)
Sentiment Indicators:
- Oil Volatility Index (CBOE:OVX)
### 3.2 Data Quality Monitoring System
Following best practices in quantitative finance (Lopez de Prado, 2018), the model implements comprehensive data quality monitoring:
Data Quality Score = Σ(Individual Indicator Validity) / Total Indicators
Where validity is determined by:
- Non-null data availability
- Positive value validation
- Temporal consistency checks
### 3.3 Statistical Normalization Framework
#### 3.3.1 Z-Score Normalization
The model employs robust Z-score normalization as established by Sharpe (1994) for cross-indicator comparability:
Z_i,t = (X_i,t - μ_i) / σ_i
Where:
- X_i,t = Raw value of indicator i at time t
- μ_i = Sample mean of indicator i
- σ_i = Sample standard deviation of indicator i
Z-scores are capped at ±3 to mitigate outlier influence (Tukey, 1977).
#### 3.3.2 Percentile Rank Transformation
For intuitive interpretation, Z-scores are converted to percentile ranks following the methodology of Conover (1999):
Percentile_Rank = (Number of values < current_value) / Total_observations × 100
### 3.4 Exponential Smoothing Framework
Signal smoothing employs exponential weighted moving averages (Brown, 1963) with adaptive alpha parameter:
S_t = α × X_t + (1-α) × S_{t-1}
Where α = 2/(N+1) and N represents the smoothing period.
### 3.5 Dynamic Threshold Optimization
The model implements adaptive thresholds using Bollinger Band methodology (Bollinger, 1992):
Dynamic_Threshold = μ ± (k × σ)
Where k is the threshold multiplier adjusted for market volatility regime.
### 3.6 Composite Score Calculation
The fundamental score integrates component scores through weighted averaging:
Fundamental_Score = Σ(w_i × Score_i × Quality_i)
Where:
- w_i = Normalized component weight
- Score_i = Component fundamental score
- Quality_i = Data quality adjustment factor
## 4. Implementation Architecture
### 4.1 Adaptive Parameter Framework
The model incorporates regime-specific adjustments based on market volatility:
Volatility_Regime = σ_price / μ_price × 100
High volatility regimes (>25%) trigger enhanced weighting for inventory and sentiment components, reflecting increased market sensitivity to supply disruptions and psychological factors.
### 4.2 Data Synchronization Protocol
Given varying publication frequencies (daily, weekly, monthly), the model employs forward-fill synchronization to maintain temporal alignment across all indicators.
### 4.3 Quality-Adjusted Scoring
Component scores are adjusted for data quality to prevent degraded inputs from contaminating the composite signal:
Adjusted_Score = Raw_Score × Quality_Factor + 50 × (1 - Quality_Factor)
This formulation ensures that poor-quality data reverts toward neutral (50) rather than contributing noise.
## 5. Usage Guidelines and Best Practices
### 5.1 Configuration Recommendations
For Short-term Analysis (1-4 weeks):
- Lookback Period: 26 weeks
- Smoothing Length: 3-5 periods
- Confidence Period: 13 weeks
- Increase inventory and sentiment weights
For Medium-term Analysis (1-3 months):
- Lookback Period: 52 weeks
- Smoothing Length: 5-8 periods
- Confidence Period: 26 weeks
- Balanced component weights
For Long-term Analysis (3+ months):
- Lookback Period: 104 weeks
- Smoothing Length: 8-12 periods
- Confidence Period: 52 weeks
- Increase supply and demand weights
### 5.2 Signal Interpretation Framework
Bullish Signals (Score > 70):
- Fundamental conditions favor price appreciation
- Consider long positions or reduced short exposure
- Monitor for trend confirmation across multiple timeframes
Bearish Signals (Score < 30):
- Fundamental conditions suggest price weakness
- Consider short positions or reduced long exposure
- Evaluate downside protection strategies
Neutral Range (30-70):
- Mixed fundamental environment
- Favor range-bound or volatility strategies
- Wait for clearer directional signals
### 5.3 Risk Management Considerations
1. Data Quality Monitoring: Continuously monitor the data quality dashboard. Scores below 75% warrant increased caution.
2. Regime Awareness: Adjust position sizing based on volatility regime indicators. High volatility periods require reduced exposure.
3. Correlation Analysis: Monitor correlation with crude oil prices to validate model effectiveness.
4. Fundamental-Technical Divergence: Pay attention when fundamental signals diverge from technical indicators, as this may signal regime changes.
### 5.4 Alert System Optimization
Configure alerts conservatively to avoid false signals:
- Set alert threshold at 75+ for high-confidence signals
- Enable data quality warnings to maintain system integrity
- Use trend reversal alerts for early regime change detection
## 6. Model Validation and Performance Metrics
### 6.1 Statistical Validation
The model's statistical robustness is ensured through:
- Out-of-sample testing protocols
- Rolling window validation
- Bootstrap confidence intervals
- Regime-specific performance analysis
### 6.2 Economic Validation
Fundamental accuracy is validated against:
- Energy Information Administration (EIA) official reports
- International Energy Agency (IEA) market assessments
- Commercial inventory data verification
## 7. Limitations and Considerations
### 7.1 Model Limitations
1. Data Dependency: Model performance is contingent on data availability and quality from external sources.
2. US Market Focus: Primary data sources are US-centric, potentially limiting global applicability.
3. Lag Effects: Some fundamental indicators exhibit publication lags that may delay signal generation.
4. Regime Shifts: Structural market changes may require model recalibration.
### 7.2 Market Environment Considerations
The model is optimized for normal market conditions. During extreme events (e.g., geopolitical crises, pandemics), additional qualitative factors should be considered alongside quantitative signals.
## References
Baumeister, C., & Kilian, L. (2016). Forty years of oil price fluctuations: Why the price of oil may still surprise us. *Journal of Economic Perspectives*, 30(1), 139-160.
Bollinger, J. (1992). *Bollinger on Bollinger Bands*. McGraw-Hill.
Brown, R. G. (1963). *Smoothing, Forecasting and Prediction of Discrete Time Series*. Prentice-Hall.
Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. *Journal of Business*, 59(3), 383-403.
Conover, W. J. (1999). *Practical Nonparametric Statistics* (3rd ed.). John Wiley & Sons.
Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. *Journal of Finance*, 25(2), 383-417.
Hamilton, J. D. (2009). Understanding crude oil prices. *Energy Journal*, 30(2), 179-206.
Kilian, L. (2009). Not all oil price shocks are alike: Disentangling demand and supply shocks in the crude oil market. *American Economic Review*, 99(3), 1053-1069.
Lopez de Prado, M. (2018). *Advances in Financial Machine Learning*. John Wiley & Sons.
Ross, S. A. (1976). The arbitrage theory of capital asset pricing. *Journal of Economic Theory*, 13(3), 341-360.
Sharpe, W. F. (1994). The Sharpe ratio. *Journal of Portfolio Management*, 21(1), 49-58.
Tukey, J. W. (1977). *Exploratory Data Analysis*. Addison-Wesley.
SF-NQ-3mSF Dual BB Momentum Strategy
// Description:
// This intraday trading strategy is designed to capture volatility breakouts and momentum shifts using advanced technical tools.
// It employs a multi-layer volatility framework through dual Bollinger Bands with configurable parameters to define dynamic entry and exit zones.
// Momentum filtering is achieved via a stochastic-based indicator to improve trade timing and reduce false signals.
//
// The strategy integrates adaptive risk management through ATR-based dynamic trailing stops combined with fixed stop loss and take profit levels.
// Additionally, it features a unique forced exit mechanism that triggers during specific volatility expansion patterns to protect capital.
//
// Multi-timeframe analysis is utilized, sampling price ranges from higher timeframes to improve signal robustness and reduce noise.
//
// Key Features:
// - Dual Bollinger Bands system for dynamic support/resistance and risk boundaries.
// - Stochastic momentum filter to help confirm trade entries and filter adverse market conditions.
// - ATR-based trailing stops with configurable trailing offset and minimum distance to lock in profits dynamically.
// - Forced exit on consecutive volatility expansion bars to mitigate risk during sudden market moves.
// - Configurable multi-timeframe sampling for more reliable entry signals.
// - JSON formatted alert messages for seamless integration with external automation platforms.
//
// Parameters Overview:
// Users can customize Bollinger Band periods, multipliers, and types (SMA or EMA) for both primary and secondary bands.
// Stop loss and take profit levels are adjustable to balance risk and reward preferences.
// Stochastic filter periods and threshold values are tunable to match user trading style.
// ATR period and trailing stop parameters provide flexible exit management.
// Forced exit features can be enabled or disabled according to user risk tolerance.
//
// Usage Recommendations:
// - Suitable for futures, forex, and other liquid markets with intraday timeframes.
// - Parameter optimization is recommended for each instrument and timeframe to enhance performance.
// - Comprehensive backtesting and paper trading should be conducted before deploying on live accounts.
// - Users should combine this strategy with prudent risk management and position sizing.
//
// Disclaimer:
// This strategy is provided as a tool for educational and analytical purposes only and comes without guarantees of profit.
// Market conditions vary, and past performance is not indicative of future results.
// Users assume full responsibility for any trading decisions made using this strategy.
//
// Licensing:
// This script is open-source under the TradingView Mozilla Public License 2.0.
Advanced MA + Volume + Market StructureHere's a comprehensive description for your Pine Script publication:
Advanced MA + Volume + Market Structure Indicator
A comprehensive trading indicator that combines multiple technical analysis tools into one efficient package, designed for traders who need precise market structure analysis with clean, actionable visuals.
📊 Key Features:
1. Dual Moving Average System
Displays both SMA and EMA options (20, 50, 100, 200 periods)
Toggle between SMA only, EMA only, or both simultaneously
Color-coded for quick visual identification
Perfect for multi-timeframe confluence analysis
2. Dynamic Volume Analysis
Advanced volume categorization using VWAP and ATR
Six-tier color coding system:
Dark Red: High volume bearish (strong selling below VWAP)
Red: Normal volume bearish
Orange: Low volume bearish
Dark Green: High volume bullish (strong buying above VWAP)
Lime: Normal volume bullish
Aqua: Low volume bullish
Volume strength calculated relative to 20-period average
3. Intelligent Market Structure Detection
Automatically identifies and labels:
HH (Higher Highs) - Bullish
HL (Higher Lows) - Bullish
LH (Lower Highs) - Bearish
LL (Lower Lows) - Bearish
ATR-filtered pivots to reduce false signals
Real-time structure analysis with trend strength (via ADX)
4. Volatility-Adjusted Bollinger Bands
Dynamic transparency based on market volatility
Clearer visualization during high volatility periods
Standard 20-period with 2.0 deviation (customizable)
5. Market Structure Dashboard
Clean information box displaying:
Current market structure (Uptrend/Downtrend/Expanding/Contracting)
Trend strength indicator (Strong/Moderate/Weak via ADX)
Last pivot high/low patterns
Current pivot values
ADX reading for trend strength confirmation
🎯 Ideal For:
Intrabar trading strategies
EMA touch/bounce strategies
Market structure traders
Volume profile analysis
Swing trading setups
Multi-timeframe analysis
⚙️ Customization Options:
MA type selection (SMA/EMA/Both)
Bollinger Bands toggle
Volume coloring on/off
Pivot lookback period adjustment
ATR multiplier for pivot validation
VWAP-based volume analysis toggle
Label and structure box visibility
🔔 Built-in Alerts:
Uptrend confirmation (HH + HL detected)
Downtrend confirmation (LH + LL detected)
High volume bullish moves above VWAP
High volume bearish moves below VWAP
⚡ Performance Optimized:
Efficient calculation methods
Table updates only on structure changes
Conditional processing based on user selections
Minimal resource usage
💡 Trading Tips:
Look for volume expansion at key MA levels for high-probability setups
Use structure labels to confirm trend direction before entry
Monitor ADX readings for trend strength (>25 = strong trend)
Watch for structure breaks with high volume for potential reversals
Combine with price action for confluence
This indicator combines the best of trend following, volume analysis, and market structure into one powerful tool. Whether you're scalping intrabar moves or swing trading, this indicator provides the visual clarity and data you need to make informed decisions.
