New  —  awesomewiki.com
TradingView

Awesome TradingView Strategy Collections - Curated High-Performing Trading Strategies

A comprehensive collection of high-performing TradingView strategies, indicators, and community-shared trading systems. This curated list includes battle-tested strategies across multiple markets, timeframes, and trading styles, organized for easy discovery and implementation through referral-friendly communities.

#TradingView#Trading Strategies#Technical Analysis#Algorithmic Trading#Pine Script#Strategy Collections

Awesome TradingView Strategy Collections

A comprehensive and curated collection of high-performing TradingView strategies, indicators, technical analysis tools, and community resources. This guide covers proven trading strategies across multiple asset classes, timeframes, and market conditions, helping traders discover, evaluate, and implement effective trading systems.

Table of Contents

Getting Started with TradingView

TradingView is a comprehensive charting platform and social network for traders and investors. It provides powerful tools for technical analysis, strategy development, and backtesting.

Essential Features

  • Charting Tools - Professional-grade charts with hundreds of technical indicators
  • Pine Script - Proprietary scripting language for creating custom indicators and strategies
  • Strategy Tester - Built-in backtesting engine for validating trading strategies
  • Paper Trading - Simulated trading environment for strategy validation
  • Social Trading - Community-driven idea sharing and strategy publication
  • Multi-Asset Support - Stocks, forex, crypto, futures, and indices
  • Real-Time Data - Live market data across global exchanges

Account Tiers

Feature Free Pro Pro+ Premium
Charts per tab 1 2 4 8
Indicators per chart 3 5 10 25
Server-side alerts 1 20 100 400
Historical bars Limited Full Full Full
Custom timeframes No Yes Yes Yes
Volume Profile No Yes Yes Yes

Upgrade to TradingView Pro to unlock advanced features and unlimited strategy testing.

Strategy Categories

Trend Following Strategies

Trend following strategies aim to capture sustained directional moves in the market by identifying and trading with the dominant trend.

Moving Average Crossover Systems

Simple Moving Average (SMA) Crossover

  • Strategy: Buy when fast SMA crosses above slow SMA, sell on reverse cross
  • Optimal Parameters: 50/200 SMA for daily charts, 20/50 SMA for intraday
  • Best Markets: Trending stocks, major forex pairs
  • Win Rate: 40-50%, Average R:R 1:2
  • Key Consideration: Requires strong trending markets, produces whipsaws in consolidation

Exponential Moving Average (EMA) Triple Crossover

  • Strategy: Uses 8/21/55 EMA alignment for trend confirmation
  • Entry Signal: All three EMAs aligned + price above/below all EMAs
  • Best Timeframes: 4H, Daily
  • Suitable For: Cryptocurrency, forex majors
  • Performance: Higher accuracy than dual crossover but fewer signals

Adaptive Moving Average (AMA) Strategy

  • Strategy: Kaufman's Adaptive Moving Average adjusts to market volatility
  • Advantage: Reduces lag during trends, filters noise in ranging markets
  • Implementation: Pine Script function built into TradingView
  • Best Applied: Volatile markets like crypto and emerging market currencies

Trend Strength Indicators

Average Directional Index (ADX) Trend System

  • Entry Criteria: ADX > 25 (trending market) + directional indicator alignment
  • Exit Strategy: ADX drops below 20 or directional cross
  • Optimal Settings: 14-period ADX, DI threshold at 25
  • Market Application: All liquid markets
  • Performance Metric: 55-65% win rate in strong trends

Supertrend Indicator Strategy

  • Calculation: Based on ATR (Average True Range) and price action
  • Parameters: Multiplier (3.0) and Period (10)
  • Signal Generation: Color change indicates trend reversal
  • Advantages: Clear visual signals, works on all timeframes
  • Recommended Use: 15-min to daily charts for crypto and forex

Parabolic SAR Trend Following

  • Mechanics: Trailing stop-loss system that accelerates with trend
  • Entry Signal: SAR flips below price (long) or above price (short)
  • Risk Management: Built-in stop-loss via SAR positioning
  • Optimal Markets: Strong trending environments
  • Limitation: Multiple false signals in sideways markets

Mean Reversion Strategies

Mean reversion strategies capitalize on the tendency of prices to return to their average after extreme moves.

Bollinger Bands Strategies

Bollinger Bands Bounce

  • Core Concept: Price tends to return to the middle band (20 SMA)
  • Entry Signal: Price touches or breaks below lower band (oversold)
  • Exit Signal: Price reaches middle band or upper band
  • Parameters: 20-period SMA, 2 standard deviations
  • Best Markets: Range-bound stocks, forex in consolidation
  • Win Rate: 60-70% in ranging conditions

Bollinger Bands Squeeze

  • Identification: Bands contract to historically narrow levels
  • Breakout Signal: Explosive move when volatility expands
  • Confirmation: Volume spike + momentum indicator
  • Implementation: Monitor Band Width indicator
  • Trading Application: Pre-earnings, consolidation breakouts
  • Average Move: 1-3 ATRs in breakout direction

Double Bollinger Bands Strategy

  • Configuration: Two sets of Bollinger Bands (1σ and 2σ)
  • Zone Trading: Different strategies for different volatility zones
  • Signal Strength: Stronger signals at 2σ levels
  • Complexity: Requires understanding of probability distributions

RSI-Based Mean Reversion

Classic RSI Oversold/Overbought

  • Standard Setup: RSI(14) below 30 (oversold), above 70 (overbought)
  • Entry Timing: Wait for RSI to turn back from extreme levels
  • Exit Strategy: RSI returns to 50 (neutral) or opposite extreme
  • Refinement: Add moving average filter for trend direction
  • Performance: 55-60% win rate in ranging markets

RSI Divergence Strategy

  • Bullish Divergence: Price makes lower low, RSI makes higher low
  • Bearish Divergence: Price makes higher high, RSI makes lower high
  • Signal Strength: Class A (higher degree) vs Class B divergences
  • Confirmation Required: Volume analysis + support/resistance
  • Best Timeframes: 4H and daily for reliability

RSI MA Strategy

  • Technique: Apply moving average to RSI itself
  • Buy Signal: RSI crosses above its moving average
  • Sell Signal: RSI crosses below its moving average
  • Parameter Optimization: RSI(14) with 9-period SMA overlay
  • Advantage: Smoother signals, fewer false positives

Stochastic Oscillator Systems

Stochastic Crossover Mean Reversion

  • Components: %K (fast) and %D (slow) lines
  • Buy Signal: %K crosses above %D in oversold zone (<20)
  • Sell Signal: %K crosses below %D in overbought zone (>80)
  • Optimal Settings: 14, 3, 3 for swing trading
  • Market Preference: Works best in range-bound conditions

Slow Stochastic with Trend Filter

  • Enhancement: Add 200 SMA as trend filter
  • Long Only: Stochastic oversold + price above 200 SMA
  • Short Only: Stochastic overbought + price below 200 SMA
  • Result: Improved win rate by aligning with larger trend
  • Trade Frequency: Reduced but higher quality signals

Momentum Strategies

Momentum strategies exploit the tendency of strong price movements to continue in the same direction.

MACD-Based Momentum

MACD Line and Signal Cross

  • Standard Parameters: 12, 26, 9 EMA configuration
  • Buy Signal: MACD line crosses above signal line
  • Sell Signal: MACD line crosses below signal line
  • Histogram: Measures momentum strength
  • Best Application: Trending markets on 4H+ timeframes

MACD Zero Line Strategy

  • Entry Trigger: MACD histogram crosses zero line
  • Significance: Indicates shift in momentum direction
  • Confirmation: Wait for 2-3 bars above/below zero
  • Reduced Signals: Fewer but higher probability trades
  • Optimal For: Position traders, daily timeframe

MACD Divergence Trading

  • Setup: Price and MACD moving in opposite directions
  • Signal Power: Strong reversal indication
  • Timing Entry: Wait for MACD crossover confirmation
  • Risk Management: Tight stops at recent swing points
  • Success Rate: 65-75% with proper confirmation

Rate of Change (ROC) Strategies

ROC Momentum Breakout

  • Calculation: (Current Price - Price n periods ago) / Price n periods ago
  • Threshold: ROC > 5% signals strong upward momentum
  • Entry Point: ROC crosses above threshold line
  • Duration: Hold while ROC remains elevated
  • Exit: ROC falls back below threshold or reverses

Multi-Timeframe ROC

  • Analysis: Compare ROC across daily, weekly, monthly
  • Alignment: Strongest signals when all timeframes agree
  • Application: Position trading, major trend changes
  • Filtering: Eliminates counter-trend noise
  • Setup Time: Requires broader market analysis

Commodity Channel Index (CCI)

CCI Overbought/Oversold

  • Extreme Levels: CCI > +100 (overbought), CCI < -100 (oversold)
  • Mean Reversion: Trade back to zero line
  • Advantage: Works well in trending and ranging markets
  • Settings: 20-period CCI for standard use
  • Volatility Adjustment: Widen levels to ±150 for volatile assets

CCI Trend Strategy

  • Trend Definition: CCI consistently above/below zero line
  • Entry: Pullbacks to zero line in established trend
  • Confirmation: CCI turns back in trend direction
  • Stop Loss: Below/above recent swing point
  • Profit Target: Previous CCI extreme

Breakout Strategies

Breakout strategies aim to enter positions when price breaks through significant support or resistance levels.

Support and Resistance Breakouts

Horizontal Level Breakout

  • Identification: Mark significant S/R levels from recent price action
  • Entry Signal: Decisive close beyond level with volume confirmation
  • False Breakout Filter: Wait for retest of broken level
  • Stop Placement: Below retest low (long) or above retest high (short)
  • Target: Measured move based on consolidation range

Dynamic Support/Resistance Breakout

  • Levels: Key moving averages (50, 100, 200 SMA/EMA)
  • Signal: Price breaks and closes beyond MA with conviction
  • Strength: Multiple MA breakouts simultaneously
  • Best Practice: Combine with momentum confirmation
  • Risk/Reward: Typically 1:2 or better

Chart Pattern Breakouts

Triangle Breakout Strategy

  • Patterns: Symmetrical, ascending, descending triangles
  • Formation: Converging trendlines with 5+ touches
  • Breakout Direction: Volume spike confirms breakout
  • Measured Target: Height of triangle projected from breakout
  • Failure Rate: 30-40%, requires strict risk management

Rectangle/Channel Breakout

  • Formation: Price oscillates between parallel lines
  • Duration: Longer consolidation = stronger breakout
  • Entry: Close beyond boundary with increased volume
  • Position Sizing: Higher confidence = larger position
  • Time Frame: Works on all scales from intraday to monthly

Cup and Handle Pattern

  • Structure: Rounded bottom (cup) + small consolidation (handle)
  • Bullish Bias: Classic bullish continuation pattern
  • Entry Point: Handle breakout with volume
  • Target: Cup depth added to breakout point
  • Success Rate: 70%+ when properly identified

Volatility Breakout Systems

Donchian Channel Breakout

  • Definition: Price breaks above/below n-period high/low
  • Standard Setting: 20-period channel
  • Entry: Break of channel boundary
  • Exit: Opposite channel boundary touch
  • Historical Performance: Proven in trend following systems

Keltner Channel Breakout

  • Calculation: EMA ± (ATR × multiplier)
  • Advantage: Adapts to volatility changes
  • Signal: Close beyond outer channel bands
  • Filter: Require momentum confirmation
  • Application: Futures and commodity markets

ATR Breakout Strategy

  • Threshold: Price move exceeds X times ATR
  • Implementation: Entry when |close - open| > 1.5 × ATR
  • Volatility Adjusted: Naturally scales with market conditions
  • Best For: Explosive moves, news-driven events
  • Risk Management: ATR-based stop losses

Scalping Strategies

Scalping strategies target small, frequent profits from minor price movements, typically on lower timeframes.

Tick-Based Scalping

1-Minute EMA Scalping

  • Setup: 8 EMA and 21 EMA on 1-minute chart
  • Entry: Price bounces off 8 EMA in direction of 21 EMA
  • Exit: Opposite EMA touch or fixed R:R (1:1.5)
  • Market: High liquidity required (major forex, BTC/USD)
  • Session: Active trading hours only
  • Trade Frequency: 10-30 trades per session

VWAP Scalping

  • Indicator: Volume Weighted Average Price
  • Long Setup: Price dips to VWAP in uptrend, bounce entry
  • Short Setup: Price rallies to VWAP in downtrend, rejection entry
  • Target: Quick 0.1-0.3% moves
  • Best Markets: Stocks, index futures during regular hours

Stochastic Scalping System

  • Timeframe: 1-5 minute charts
  • Entry: Stochastic oversold + turn higher (or reverse for shorts)
  • Confirmation: Price action candle pattern
  • Stop Loss: Tight 5-10 pip stops
  • Profit Target: 1:1 to 1:2 risk-reward ratio

Order Flow Scalping

Tape Reading and Level 2

  • Skill: Interpret bid/ask dynamics and order book
  • Signal: Large order absorption at levels
  • Execution: Enter on confirmation of level defense
  • Technology: Requires advanced platform features
  • Experience: High skill requirement, steep learning curve

Volume Profile Scalping

  • Analysis: Identify high-volume nodes (HVN) and low-volume nodes (LVN)
  • Strategy: Trade bounces from HVN, breakouts through LVN
  • Timeframe: 5-15 minute charts with volume profile
  • Target: Reversion to next HVN or value area
  • Pro Feature: TradingView Premium required

News-Based Scalping

Economic Calendar Scalping

  • Preparation: Identify high-impact news events
  • Setup: Pre-position based on expected volatility
  • Execution: Trade initial reaction or fade extreme moves
  • Risk: High volatility requires strict risk management
  • Tools: TradingView economic calendar integration

Swing Trading Strategies

Swing trading strategies hold positions for several days to weeks, capturing medium-term price swings.

Multi-Day Trend Strategies

Daily Timeframe Trend Following

  • Primary Chart: Daily candles
  • Trend Filter: 50 EMA direction and slope
  • Entry: Pullback to 20 EMA in trend direction
  • Hold Duration: 5-20 days typical
  • Position Sizing: Risk 1-2% per trade

Weekly Chart Swing System

  • Higher Timeframe: Weekly chart for trend context
  • Entry Timing: Daily chart for precise entry
  • Pattern: Identify weekly support/resistance levels
  • Hold Time: Weeks to months
  • Reduced Frequency: 2-5 trades per month

Fibonacci Retracement Swings

Fib Retracement Strategy

  • Tool: Fibonacci retracement levels (23.6%, 38.2%, 50%, 61.8%)
  • Setup: Identify strong trend move
  • Entry: Price retraces to key Fib level (typically 50-61.8%)
  • Confirmation: Candlestick reversal pattern at level
  • Target: Previous swing high/low or Fib extensions

Fib Extension Targets

  • Application: Project profit targets beyond initial move
  • Levels: 127.2%, 161.8%, 200%, 261.8%
  • Usage: Scale out of positions at multiple extensions
  • Accuracy: Higher timeframes provide more reliable levels

Gap Trading Strategies

Gap Fill Strategy

  • Observation: 70-80% of gaps eventually fill
  • Entry: Trade in direction of gap fill
  • Timing: Can take days to weeks to complete
  • Types: Common gaps fill fastest, exhaustion gaps most reliable
  • Risk: Use wider stops to allow price development

Gap and Go Strategy

  • Setup: Gap with continuation in gap direction
  • Confirmation: Strong volume and momentum on gap day
  • Hold: Ride momentum until signs of exhaustion
  • Best On: Earnings gaps, news-driven gaps
  • Market: Individual stocks primarily

Position Trading Strategies

Position trading strategies focus on long-term trends, holding positions for months to years.

Multi-Month Trend Trading

Monthly Chart Analysis

  • Perspective: Identify major multi-year trends
  • Entry: Use weekly chart for entries during pullbacks
  • Patience: May take weeks to develop ideal entry
  • Capital: Requires significant capital and risk tolerance
  • Return Potential: 50-300% moves possible

Fundamental-Technical Hybrid

  • Analysis: Combine fundamental analysis with technical timing
  • Entry: Wait for technical confirmation of fundamental thesis
  • Examples: Sector rotation, macro trends, commodity cycles
  • Time Horizon: 6-24 months typical holding period

Macro Trend Strategies

Interest Rate Cycle Trading

  • Analysis: Trade currencies and bonds based on rate expectations
  • Indicators: Central bank policies, yield curves
  • Implementation: Long-term trend following on FX majors
  • Timeframe: Multi-year trends possible
  • Research: Requires macro economic knowledge

Commodity Supercycles

  • Concept: Multi-decade cycles in commodity prices
  • Identification: Fundamental supply/demand shifts
  • Entry: Technical confirmation of cycle phase
  • Patience: May wait years for optimal entries
  • Diversification: Trade basket of related commodities

Market-Specific Strategies

Cryptocurrency Strategies

Bitcoin-Specific Approaches

Bitcoin Halving Cycle Strategy

  • Cycle: Approximately 4-year cycle tied to mining reward halving
  • Pattern: Post-halving bull market historically consistent
  • Strategy: Accumulate in bear phase, hold through bull phase
  • Tracking: Mark halving dates and plan 18-month horizons
  • Reference: Bitcoin ideas on TradingView

Bitcoin Dominance Trading

  • Metric: BTC market cap / Total crypto market cap
  • Signal: Rising dominance = altcoin weakness
  • Strategy: Rotate between BTC and alts based on dominance
  • Chart: BTC Dominance Chart
  • Optimization: Combine with total market cap trend

Hash Ribbon Indicator

  • Data: Bitcoin hash rate moving averages
  • Signal: Hash ribbon compression = miner capitulation
  • Entry: Historically good long entry points
  • Availability: Custom indicator on TradingView
  • Timeframe: Long-term position trading

Altcoin Strategies

Altcoin Season Index

  • Measurement: Percentage of top 50 alts outperforming BTC
  • Threshold: >75% indicates altcoin season
  • Strategy: Increase altcoin allocation during alt season
  • Tools: Track via third-party dashboards
  • Rotation: Shift to BTC when index falls below 25%

Ethereum DeFi Correlation Trading

  • Relationship: ETH and DeFi tokens often correlated
  • Lead/Lag: ETH sometimes leads DeFi sector moves
  • Strategy: ETH breakout = potential DeFi rotation
  • Monitoring: Track ETH against DeFi index
  • Chart: Ethereum Analysis

Small Cap Momentum Strategy

  • Universe: Coins ranked 100-500 by market cap
  • Criteria: Strong relative strength + volume increase
  • Entry: Breakout with volume confirmation
  • Risk: High volatility, use tight stops
  • Position Size: Small allocation due to risk

Crypto Derivatives

Funding Rate Arbitrage

  • Concept: Exploit perpetual swap funding rates
  • Long Setup: Negative funding = longs get paid
  • Implementation: Requires derivative exchange access
  • Risk Management: Delta hedging with spot positions
  • Returns: Low-risk yield generation strategy

Bitcoin Options Strategies

  • Put/Call Spreads: Defined risk directional bets
  • Straddles: Volatility plays around key events
  • Covered Calls: Income generation on holdings
  • Platform: Deribit, CME Bitcoin options
  • Analysis: Use TradingView for underlying technical analysis

Forex Strategies

Major Pairs Trading

EUR/USD Strategy Collection

  • Characteristics: Most liquid pair, tight spreads
  • Session: Best during London/New York overlap
  • Strategies: All strategy types work well
  • Economic Data: EUR and USD economic calendar critical
  • Analysis: EUR/USD Charts

GBP/USD Volatility Strategy

  • Profile: High volatility, larger moves
  • Optimal Time: London session
  • Stop Loss: Wider stops required (50-100 pips)
  • Profit Targets: 100-200 pip moves common
  • News Impact: Highly sensitive to UK economic data

USD/JPY Carry Trade

  • Concept: Profit from interest rate differential
  • Setup: Long higher-yielding currency
  • Risk: Unwinding during market stress
  • Timeframe: Position trading, hold for months
  • Monitoring: Track central bank policies

Cross Pairs Strategies

EUR/GBP Range Trading

  • Behavior: Tends to range trade within channels
  • Strategy: Sell resistance, buy support
  • Width: Typical range 200-400 pips
  • Breakout: Rare but powerful when occurs
  • Timeframe: Daily chart for major levels

Commodity Currencies (AUD, NZD, CAD)

  • Correlation: Linked to commodity prices
  • Strategy: Trade with commodity trends
  • AUD/USD: Correlated with gold and iron ore
  • NZD/USD: Dairy prices influence
  • CAD: Oil price correlation (especially with USD/CAD inverse)

Exotic Pairs Trading

Emerging Market FX

  • Pairs: USD/TRY, USD/ZAR, USD/MXN
  • Opportunity: Higher volatility and trends
  • Risk: Political and economic instability
  • Spreads: Wider spreads, higher costs
  • Strategy: Trend following works best

Scandinavian Currencies

  • Pairs: USD/SEK, EUR/NOK
  • Characteristics: Lower liquidity than majors
  • Advantage: Less algorithmic trading, cleaner technicals
  • Session: European hours
  • Analysis: Nordic economic data important

Stock Market Strategies

Index Trading

S&P 500 Strategy Collection

  • Instruments: SPY ETF, ES futures, SPX options
  • Approach: Both trend following and mean reversion viable
  • Key Levels: Round numbers (4000, 4500, 5000)
  • Seasonality: Strong Q4, weak September historically
  • Charts: SPX Analysis

NASDAQ 100 Technology Focus

  • Instrument: QQQ ETF, NQ futures
  • Characteristics: Higher volatility than S&P
  • Correlation: Tech sector earnings critical
  • Strategy: Momentum strategies excel
  • Hours: Pre-market and after-hours matter for tech

Russell 2000 Small Cap

  • Instrument: IWM ETF
  • Profile: Higher risk/reward than large caps
  • Liquidity: Lower than major indices
  • Sensitivity: More domestic economy focused
  • Strategy: Swing trading during economic cycles

Sector Rotation

Cyclical vs Defensive Rotation

  • Cyclicals: Technology, Consumer Discretionary, Financials
  • Defensives: Utilities, Consumer Staples, Healthcare
  • Signal: Economic cycle and interest rate trends
  • Implementation: Sector ETF rotation strategy
  • Monitoring: Track relative strength between sectors

Technology Sector Strategies

  • Leading Indicator: Often leads market
  • Subsectors: Software, semiconductors, hardware
  • Momentum: Strong trending characteristics
  • Earnings Season: Critical catalysts quarterly
  • Analysis: Compare against sector ETF (XLK)

Energy Sector Trading

  • Correlation: Crude oil price primary driver
  • Strategy: Trade energy stocks with oil trend
  • Seasonality: Demand patterns affect prices
  • Major Players: Track XOM, CVX for sector direction
  • Geopolitics: Supply disruptions create volatility

Individual Stock Strategies

Earnings Momentum Strategy

  • Setup: Strong earnings report + guidance
  • Entry: Breakout above post-earnings consolidation
  • Duration: Hold through momentum phase
  • Exit: Slowdown in relative strength
  • Screening: Use stock screener for earnings beats

Gap and Go Stock Strategy

  • Trigger: 3%+ gap up on volume
  • Entry: First 5-30 minute pullback
  • Confirmation: Previous day's high break
  • Stop: Below pullback low
  • Target: Extended move 5-10%+

IPO Trading Strategies

  • Quiet Period: 25-day post-IPO lockup
  • Entry: Break of IPO day high after consolidation
  • Risk: High volatility, wide stops needed
  • Research: Understand business fundamentals
  • Allocation: Small position due to unpredictability

Futures and Commodities

Metal Futures

Gold Trading Strategies

  • Drivers: USD strength, interest rates, risk sentiment
  • Strategy: Trend following works well
  • Correlations: Inverse to USD typically
  • Hours: 24-hour market, Asian session important
  • Analysis: Gold Charts

Silver High-Beta Strategy

  • Relationship: Moves with gold but more volatile
  • Gold/Silver Ratio: Trade pair based on ratio extremes
  • Industrial Demand: More sensitive than gold
  • Momentum: Explosive moves in bull markets
  • Position Sizing: Smaller due to volatility

Copper Economic Indicator

  • Significance: "Dr. Copper" predicts economic health
  • Strategy: Long copper in economic expansion
  • Confirmation: Use with manufacturing PMI data
  • Markets: Also impacts mining stocks
  • Lead Time: Can lead equity markets by weeks

Agricultural Commodities

Grain Futures (Corn, Wheat, Soybeans)

  • Seasonality: Plant/harvest cycles critical
  • Reports: USDA reports major catalysts
  • Weather: Drought and flooding impact prices
  • Strategy: Seasonal tendency trading
  • Timeframe: Position trading around crop cycles

Soft Commodities (Coffee, Sugar, Cotton)

  • Characteristics: High volatility, lower liquidity
  • Fundamentals: Weather and global supply chains
  • Trend Duration: Can trend for months
  • Strategy: Long-term trend following
  • Risk: Wide stops required due to volatility

Energy Futures

Crude Oil Strategy Collection

  • Types: WTI, Brent crude
  • Drivers: Supply/demand, OPEC, geopolitics
  • Volatility: High, especially during crises
  • Sessions: Active during all major sessions
  • Correlation: Canadian dollar, energy stocks

Natural Gas Trading

  • Seasonality: Strong winter demand in Northern Hemisphere
  • Storage Reports: Weekly EIA data releases
  • Volatility: Extreme price swings possible
  • Strategy: Seasonal trading + trend following
  • Risk: Most volatile energy commodity

Popular Indicators and Tools

Volume-Based Indicators

Volume Indicators

On-Balance Volume (OBV)

  • Concept: Cumulative volume based on price direction
  • Signal: OBV divergence from price
  • Usage: Confirm breakouts with OBV confirmation
  • Advantage: Leading indicator of price moves
  • Best Markets: Stocks with consistent volume

Volume Weighted Average Price (VWAP)

  • Calculation: Average price weighted by volume
  • Application: Intraday institutional benchmark
  • Strategy: Price above VWAP = bullish bias
  • Reset: Daily reset on standard settings
  • Users: Day traders, institutional desks

Accumulation/Distribution Line

  • Purpose: Measure buying and selling pressure
  • Formula: Factors in close location within range
  • Divergence: Leading signal of reversals
  • Confirmation: Use with price action
  • Timeframe: Daily and weekly most reliable

Volume Profile

  • Display: Horizontal volume histogram
  • Key Levels: High Volume Nodes (HVN), Low Volume Nodes (LVN)
  • Application: Support/resistance identification
  • Strategy: Trade bounces from HVN, breakouts through LVN
  • Premium: TradingView Premium feature

Market Sentiment Indicators

Put/Call Ratio

  • Measurement: Put volume / Call volume
  • Extreme: >1.0 = bearish sentiment, <0.7 = bullish
  • Contrarian: Extreme readings can signal reversals
  • Data Source: CBOE publishes daily
  • Strategy: Fade extreme sentiment readings

Fear and Greed Index

  • Components: Multiple market indicators combined
  • Scale: 0 (extreme fear) to 100 (extreme greed)
  • Application: Contrarian indicator
  • Buy Zone: Extreme fear (<25)
  • Sell Zone: Extreme greed (>75)

Advance/Decline Line

  • Calculation: Cumulative advancing stocks - declining stocks
  • Application: Market breadth indicator
  • Divergence: A/D line vs index divergence signals weakness
  • Market: NYSE and NASDAQ versions
  • Timeframe: Daily and weekly analysis

Volatility Indicators

ATR-Based Systems

Average True Range (ATR)

  • Measurement: Average of true range over n periods
  • Standard: 14-period ATR most common
  • Stop Placement: ATR × multiplier for stop distance
  • Position Sizing: Inverse relationship to volatility
  • Universal: Works on all markets and timeframes

ATR Trailing Stop

  • Concept: Dynamic stop that moves with ATR
  • Long Stop: Price - (ATR × multiplier)
  • Short Stop: Price + (ATR × multiplier)
  • Multiplier: Typically 2.0-3.0
  • Advantage: Adjusts to volatility automatically

ATR Breakout System

  • Entry: Price move > 1.5 × ATR in single period
  • Logic: Significant momentum indicated
  • Filter: Confirm with volume increase
  • Target: 2-3 × ATR profit target
  • Stop: 0.5-1.0 × ATR below entry

Bollinger Bands Applications

Bollinger Band Width

  • Calculation: (Upper Band - Lower Band) / Middle Band
  • Squeeze: Band Width at multi-period low
  • Expansion: Breakout likely after squeeze
  • Measurement: Compare current vs historical width
  • Strategy: Trade expansions after contractions

Bollinger %B

  • Formula: (Price - Lower Band) / (Upper Band - Lower Band)
  • Range: 0 (lower band) to 1 (upper band)
  • Overbought: %B > 1.0
  • Oversold: %B < 0.0
  • Advantage: Normalized for comparison across assets

Historical and Implied Volatility

VIX Trading Strategies

  • Instrument: S&P 500 volatility index
  • Characteristic: Mean-reverting
  • Strategy: Sell VIX spikes, buy VIX crashes
  • Implementation: VIX futures, options, ETFs
  • Timing: Extreme readings for best entries

Historical Volatility Ranking

  • Concept: Current HV vs 1-year range
  • Calculation: Percentile ranking
  • High HV: Mean reversion strategies
  • Low HV: Trend following strategies
  • Application: Strategy selection tool

Custom Composite Indicators

Multi-Indicator Dashboards

Trend Strength Dashboard

  • Components: ADX, MACD, Moving Average Alignment
  • Display: Color-coded aggregate signal
  • Purpose: Quick trend assessment
  • Customization: Weight each component
  • Implementation: Pine Script custom indicator

Mean Reversion Dashboard

  • Indicators: RSI, Stochastic, Bollinger %B
  • Signal: Number of indicators at extremes
  • Threshold: 2+ signals for entry
  • Exit: Return to neutral readings
  • Benefit: Reduces false signals

Momentum Scanner

  • Elements: Rate of Change, RSI, MACD
  • Ranking: Score 0-100 for momentum strength
  • Application: Scan multiple assets
  • Sorting: Rank by score for prioritization
  • Update: Real-time or periodic refresh

Market Regime Indicators

Trend vs Range Detector

  • Method: ADX combined with price action analysis
  • Output: Trending or Ranging classification
  • Application: Auto-select strategy type
  • Threshold: ADX 25 as pivot point
  • Adaptation: Switch strategies by regime

Volatility Regime Classification

  • Analysis: Compare current vs historical volatility
  • Categories: Low, Normal, High volatility
  • Strategy Selection: Match strategy to regime
  • Timeframe: Assess on multiple timeframes
  • Adaptive: Dynamic strategy parameters

Strategy Development

Pine Script Resources

Getting Started with Pine Script

Pine Script Basics

  • Version: Pine Script v5 is current version
  • Language: Domain-specific language for TradingView
  • Purpose: Create custom indicators and strategies
  • Syntax: Similar to Python with trading-specific functions
  • Learning: TradingView Pine Script documentation

Essential Functions

  • strategy(): Define strategy properties
  • ta.sma(), ta.ema(): Moving averages
  • ta.rsi(), ta.macd(): Technical indicators
  • strategy.entry(): Execute trades
  • strategy.exit(): Set stop-loss and take-profit

Strategy Template Structure

//@version=5
strategy("Strategy Name", overlay=true)

// Input parameters
length = input.int(14, "Length")

// Indicator calculations
indicator = ta.sma(close, length)

// Entry conditions
longCondition = ta.crossover(close, indicator)
shortCondition = ta.crossunder(close, indicator)

// Execute trades
if (longCondition)
    strategy.entry("Long", strategy.long)
if (shortCondition)
    strategy.entry("Short", strategy.short)

Advanced Pine Script Techniques

Multi-Timeframe Analysis

  • Function: request.security()
  • Purpose: Access data from different timeframes
  • Application: Confirm signals across timeframes
  • Example: Daily trend filter on hourly chart
  • Performance: Optimize to avoid repainting

Custom Alert Conditions

  • Function: alertcondition()
  • Trigger: Define custom notification conditions
  • Integration: Webhook support for automation
  • Use Cases: Entry signals, stop-loss hits, profit targets
  • Delivery: Email, SMS, webhook notifications

Strategy Risk Management in Pine

  • Position Sizing: strategy.entry() qty parameter
  • Stop Loss: strategy.exit() stop parameter
  • Take Profit: strategy.exit() limit parameter
  • Pyramiding: Control number of entries in same direction
  • Max Drawdown: strategy.risk.max_intraday_loss()

Backtesting Visualization

  • Plotting: plot() function for visual representation
  • Labels: label.new() for entry/exit markers
  • Tables: table.new() for statistics display
  • Colors: Conditional coloring based on conditions
  • Shapes: plotshape() for trade signals

Backtesting Best Practices

Robust Testing Framework

Data Quality Considerations

  • Survivorship Bias: Test on delisted/defunct assets too
  • Realistic Spreads: Include transaction costs
  • Slippage: Model market impact on orders
  • Commission: Factor in brokerage fees
  • Data Quality: Use adjusted data for splits/dividends

Sample Size and Statistical Significance

  • Minimum Trades: 100+ trades for statistical validity
  • Time Period: Test across multiple market conditions
  • Multiple Assets: Validate on diverse securities
  • Market Regimes: Bull, bear, sideways performance
  • Out-of-Sample: Reserve 20-30% for validation

Performance Metrics to Track

Metric Description Good Threshold
Win Rate % of profitable trades >50%
Profit Factor Gross Profit / Gross Loss >1.5
Sharpe Ratio Risk-adjusted returns >1.0
Max Drawdown Largest peak-to-trough decline <20%
Recovery Factor Net Profit / Max Drawdown >3.0
Average Win/Loss Risk-reward relationship >1.5
Expectancy Average $ per trade Positive

Common Backtesting Pitfalls

  • Look-Ahead Bias: Using future data in calculations
  • Curve Fitting: Over-optimization to historical data
  • Cherry Picking: Selecting favorable test periods only
  • Ignoring Costs: Unrealistic returns without fees
  • Repainting: Indicators that change historical values

Walk-Forward Analysis

Methodology

  • In-Sample: Optimize on training period (60-70%)
  • Out-of-Sample: Test on validation period (30-40%)
  • Rolling Forward: Move windows through dataset
  • Comparison: Out-of-sample should track in-sample
  • Degradation: <20% performance drop acceptable

Optimization Parameters

  • Limited Variables: Optimize 3-5 parameters max
  • Robust Ranges: Parameters that work across ranges
  • Step Size: Appropriate increment sizes
  • 3D Analysis: Examine parameter interactions
  • Stability: Avoid sharp performance cliffs

Optimization Techniques

Parameter Optimization

Grid Search Optimization

  • Method: Test all parameter combinations
  • Advantage: Exhaustive search
  • Disadvantage: Computationally expensive
  • Application: Small parameter spaces
  • Result: Optimal parameter set for period

Genetic Algorithm Optimization

  • Approach: Evolutionary parameter selection
  • Benefit: Efficient for large parameter spaces
  • Process: Mutation and selection of best performers
  • Risk: Can overfit if not validated
  • Tools: Available in advanced platforms

Avoiding Over-Optimization

  • Simplicity: Fewer parameters = more robust
  • Rounded Values: Prefer 10, 20, 50 over 17, 23, 49
  • Consistent Performance: Check nearby parameter sets
  • Multiple Assets: Validate on different instruments
  • Time Periods: Test across different market conditions

Strategy Robustness Testing

Monte Carlo Simulation

  • Process: Randomize trade sequence
  • Runs: 1000+ iterations
  • Analysis: Distribution of outcomes
  • Confidence: 95th percentile worst-case scenario
  • Application: Risk assessment and position sizing

Sensitivity Analysis

  • Method: Vary parameters individually
  • Measurement: Performance impact per parameter
  • Robust Strategy: Small changes = small impact
  • Fragile Strategy: Large performance swings
  • Conclusion: Prefer insensitive strategies

Market Regime Testing

  • Bull Markets: Test in rising market conditions
  • Bear Markets: Performance during declines
  • Sideways: Range-bound market testing
  • High Volatility: Crisis periods (2008, 2020)
  • Low Volatility: Calm market conditions

Risk Management

Position Sizing

Fixed Fractional Method

  • Concept: Risk fixed % of capital per trade
  • Common: 1-2% risk per trade
  • Calculation: Position Size = (Account × Risk%) / (Entry - Stop)
  • Advantage: Preserves capital during drawdowns
  • Growth: Compounds gains automatically

Kelly Criterion

  • Formula: f = (bp - q) / b
  • Variables: b = odds, p = win probability, q = loss probability
  • Application: Optimal bet size for maximum growth
  • Reality: Use 1/4 to 1/2 Kelly for practical trading
  • Requirement: Accurate win rate and average win/loss needed

Volatility-Based Sizing

  • Method: Inverse position size to volatility
  • Implementation: Position = Base / (ATR / Price)
  • Logic: Smaller positions in volatile markets
  • Benefit: Consistent risk across different conditions
  • Tools: ATR-based position calculator

Stop Loss Strategies

Types of Stop Losses

  • Fixed Percentage: Set % below entry (2-5%)
  • ATR-Based: Multiple of ATR (1.5-3.0 × ATR)
  • Support/Resistance: Below key technical level
  • Time-Based: Exit after n periods if no profit
  • Trailing: Moves with price to lock profits

Stop Loss Placement Guidelines

  • Avoid Round Numbers: Place orders at odd prices
  • Beyond Noise: Outside normal price fluctuations
  • Technical Respect: Honor chart structure
  • Account for Spread: Wider on exotic pairs/low liquidity
  • Maximum Loss: Never exceed max risk per trade

Trailing Stop Techniques

  • Fixed Distance: Trail by fixed $ or % amount
  • ATR Trailing: Dynamic trailing with volatility
  • Chandelier Exit: ATR from highest high/lowest low
  • Moving Average: Trail below/above MA
  • Parabolic SAR: Built-in trailing mechanism

Take Profit Strategies

Profit Target Methods

  • Risk-Reward Ratio: Fixed multiple of stop distance (1:2, 1:3)
  • Percentage: Fixed % gain target
  • Technical Target: Support/resistance, Fibonacci levels
  • Measured Move: Chart pattern price objectives
  • Volatility Target: ATR multiples for profit

Scaling Out Positions

  • Partial Profits: Take 50% at first target
  • Remaining Position: Trail stop for runner
  • Multiple Targets: 33% at each of 3 targets
  • Advantage: Combine consistent profits with outliers
  • Psychology: Reduces pressure on trades

Portfolio-Level Risk

Diversification Strategies

  • Asset Classes: Stocks, forex, commodities, crypto
  • Correlation: Combine negatively correlated assets
  • Strategy Types: Mix trend following and mean reversion
  • Timeframes: Different holding periods
  • Geographic: Multiple market regions

Maximum Exposure Limits

  • Single Position: 2-5% account risk
  • Correlated Positions: 10% total correlated risk
  • Overall Exposure: 20-30% account at risk simultaneously
  • Sector Limits: Cap exposure to single sector
  • Leverage: 2:1 maximum recommended for retail

Drawdown Management

  • Maximum Drawdown: Define acceptable loss threshold
  • Reduce Size: Cut position sizing after 10% drawdown
  • Stop Trading: Pause after 20% drawdown
  • Review: Analyze what went wrong
  • Gradual Return: Scale back in slowly after recovery

Community Resources

TradingView Social Features

Idea Publishing and Sharing

  • Platform: Share chart analysis with community
  • Reach: Potentially millions of viewers
  • Reputation: Build following and credibility
  • Feedback: Community comments and validation
  • Monetization: TradingView pays top publishers
  • Publish: Share your ideas

Following Top Traders

  • Identify: Find consistently accurate analysts
  • Study: Learn from their analysis methods
  • Adapt: Incorporate techniques into own trading
  • Verification: Check historical accuracy
  • Interaction: Comment and discuss ideas

Script Library

  • Community Scripts: Thousands of free indicators
  • Published Strategies: Shared by community members
  • Customization: Fork and modify scripts
  • Learning: Study code to improve skills
  • Contribution: Publish own creations
  • Browse: TradingView Scripts

Educational Resources

TradingView Education Center

  • Articles: Comprehensive trading education
  • Video Tutorials: Platform features and strategies
  • Webinars: Live training sessions
  • Pine Script: Programming tutorials
  • Free Access: Available to all users
  • Learn: Education Portal

Community Chat Rooms

  • Real-Time Discussion: Live market commentary
  • Multiple Rooms: Topic-specific channels
  • Global Community: Traders worldwide
  • Collaboration: Share ideas and analysis
  • Moderation: Maintained discussion quality

Strategy Collaboration

Backtesting Groups

  • Community: Join strategy development communities
  • Sharing: Exchange backtesting results
  • Peer Review: Get feedback on strategies
  • Open Source: Collaborative strategy development
  • Standards: Establish testing methodologies

Signal Services and Copy Trading

  • Automated: Copy trades from experienced traders
  • Transparency: View track record before following
  • Due Diligence: Verify performance claims
  • Risk: Still requires own risk management
  • Integration: Some platforms integrate with TradingView

Strategy Performance Metrics

Return Metrics

Absolute Return Metrics

  • Total Return: Overall % gain/loss
  • Annual Return: Annualized performance
  • Monthly Return: Average monthly gain
  • CAGR: Compound Annual Growth Rate
  • Comparison: Benchmark against buy-and-hold

Risk-Adjusted Returns

  • Sharpe Ratio: (Return - Risk-Free Rate) / Standard Deviation
  • Sortino Ratio: Like Sharpe but only downside volatility
  • Calmar Ratio: Annual Return / Max Drawdown
  • Information Ratio: Excess return / tracking error
  • Omega Ratio: Probability-weighted gains vs losses

Risk Metrics

Volatility Measures

  • Standard Deviation: Measure of return dispersion
  • Beta: Correlation to benchmark volatility
  • Downside Deviation: Volatility of negative returns
  • Ulcer Index: Depth and duration of drawdowns
  • Value at Risk (VaR): Maximum loss at confidence level

Drawdown Analysis

  • Maximum Drawdown: Largest peak-to-trough decline
  • Average Drawdown: Mean of all drawdown periods
  • Drawdown Duration: Time underwater
  • Recovery Factor: Net Profit / Max DD
  • Mar Ratio: CAGR / Max DD

Trade Statistics

Win/Loss Analysis

  • Win Rate: % of winning trades
  • Loss Rate: % of losing trades
  • Average Win: Mean profit on winning trades
  • Average Loss: Mean loss on losing trades
  • Largest Win/Loss: Extremes in either direction

Expectancy and Edge

  • Expectancy: (Win% × Avg Win) - (Loss% × Avg Loss)
  • Profit Factor: Gross Profit / Gross Loss
  • System Quality Number (SQN): Edge relative to variability
  • Expected Value per Trade: Long-term average outcome
  • Edge: Probability of success above random

Execution Metrics

Trade Efficiency

  • Fill Quality: Slippage per trade
  • Commission Impact: Fees as % of profit
  • Win Streak: Consecutive winning trades
  • Loss Streak: Consecutive losing trades
  • Time in Market: % of time with open positions

Strategy Consistency

  • R-Multiple Distribution: Distribution of R-multiples
  • Consecutive Winners: Maximum winning streak
  • Consecutive Losers: Maximum losing streak
  • Monthly Consistency: % of positive months
  • Rolling Returns: Performance over rolling periods

Advanced Topics

Algorithmic Trading Integration

API Integration

  • TradingView Webhooks: Send alerts to external systems
  • Broker APIs: Connect to execution platforms
  • Automation: Fully automated trading systems
  • Languages: Python, JavaScript, C# for implementation
  • Infrastructure: Cloud servers for 24/7 operation

Execution Algorithms

  • TWAP: Time-Weighted Average Price
  • VWAP: Volume-Weighted Average Price
  • Implementation Shortfall: Minimize market impact
  • Iceberg Orders: Hide large order size
  • Smart Order Routing: Optimize execution venue

Machine Learning in Trading

Predictive Modeling

  • Classification: Predict up/down movements
  • Regression: Forecast price levels
  • Features: Technical indicators, market data
  • Models: Random Forest, Neural Networks, XGBoost
  • Validation: Walk-forward, k-fold cross-validation

Sentiment Analysis

  • Data Sources: News, social media, reports
  • NLP: Natural Language Processing techniques
  • Scoring: Quantify sentiment numerically
  • Integration: Combine with technical analysis
  • Challenges: Data quality, timeliness, reliability

Reinforcement Learning

  • Approach: AI learns optimal trading policy
  • Environment: Market simulation
  • Reward Function: Define success criteria
  • Training: Thousands of simulated trades
  • Reality Gap: Sim-to-real transfer challenges

Multi-Asset Portfolio Trading

Correlation-Based Trading

  • Pairs Trading: Long/short correlated assets
  • Statistical Arbitrage: Mean reversion of spreads
  • Cointegration: Long-term equilibrium relationships
  • Basket Trading: Trade index vs components
  • Market Neutral: Zero net market exposure

Cross-Market Analysis

  • Intermarket Relationships: Bonds, stocks, currencies, commodities
  • Leading Indicators: Use one market to predict another
  • Risk-On/Risk-Off: Global risk sentiment flows
  • Capital Flows: Track money between asset classes
  • Macro Framework: Top-down allocation approach

Options Strategies with Technical Analysis

Directional Options Trading

  • Call Buying: Bullish technical setup
  • Put Buying: Bearish technical setup
  • Spreads: Limited risk directional bets
  • Technical Timing: Use charts for entry/exit
  • Delta Selection: Match conviction level

Volatility Trading

  • Straddles/Strangles: Trade expected volatility expansion
  • Iron Condors: Profit from range-bound movement
  • Calendar Spreads: Exploit volatility term structure
  • Technical Signals: Use Bollinger Band Width, ATR
  • VIX: Monitor for volatility regime changes

Income Strategies

  • Covered Calls: Generate income on holdings
  • Cash-Secured Puts: Acquire stock at discount
  • Technical Support: Sell puts at support levels
  • Technical Resistance: Sell calls at resistance
  • Risk Management: Technical stops still apply

High-Frequency and Ultra-Short-Term Trading

Microstructure Considerations

  • Order Book Dynamics: Bid/ask spread behavior
  • Market Depth: Liquidity at price levels
  • Time and Sales: Tick-by-tick analysis
  • Latency: Millisecond execution speeds
  • Co-location: Server proximity to exchange

Statistical Arbitrage

  • Mean Reversion: High-frequency mean reversion
  • Market Making: Provide liquidity for spread
  • Latency Arbitrage: Exploit price discrepancies
  • Infrastructure: Requires significant technology
  • Barriers: High costs, competition with HFT firms

Seasonal and Calendar-Based Strategies

Market Seasonality

  • "Sell in May": Historical summer weakness
  • Santa Claus Rally: End-of-year strength
  • January Effect: Small cap outperformance
  • FOMC Days: Federal Reserve meeting volatility
  • Opex: Options expiration patterns

Earnings Season Trading

  • Earnings Calendar: Schedule of announcements
  • Pre-Earnings: Anticipation positioning
  • Post-Earnings: Momentum continuation
  • Options: IV crush strategies
  • Sector Rotation: Performance by reporting order

Day of Week Patterns

  • Monday Effect: Weekend news gap
  • Turnaround Tuesday: Reversal tendency
  • Mid-Week Trends: Strongest trending days
  • Friday Close: Weekend positioning
  • Statistical: Verify patterns before trading

Psychological Aspects

Emotional Discipline

  • Fear and Greed: Primary emotional drivers
  • Revenge Trading: Avoid impulsive recovery attempts
  • FOMO: Fear of missing out on trades
  • Overconfidence: Risk after winning streaks
  • Solution: Rule-based trading systems

Cognitive Biases

  • Confirmation Bias: Seeking confirming evidence
  • Recency Bias: Overweighting recent events
  • Anchoring: Fixating on entry price
  • Loss Aversion: Holding losers too long
  • Awareness: Recognize and counteract biases

Trading Psychology Tools

  • Trading Journal: Document decisions and emotions
  • Performance Review: Regular analysis of trades
  • Meditation: Stress management technique
  • Breaks: Step away after losses
  • Support: Trading community or mentor

Summary

This comprehensive guide covers the essential aspects of TradingView strategy collections, from basic concepts to advanced techniques. Success in trading requires continuous learning, disciplined execution, and proper risk management. Start with one strategy category, thoroughly test and understand it, then gradually expand your repertoire.

Key Takeaways

  • Strategy Selection: Choose strategies that match your timeframe, risk tolerance, and market conditions
  • Testing: Always backtest thoroughly and validate on out-of-sample data before live trading
  • Risk Management: Proper position sizing and stop losses are more important than entry signals
  • Diversification: Combine multiple strategies and asset classes to reduce risk
  • Continuous Learning: Markets evolve, requiring ongoing education and adaptation
  • Community: Leverage TradingView's community for ideas, feedback, and collaboration
  • Technology: Utilize Pine Script and platform features to enhance analysis and execution

Getting Started Checklist

  1. Open TradingView Account
  2. Upgrade to Pro or Premium for advanced features
  3. Study one strategy category thoroughly
  4. Practice in paper trading environment
  5. Develop your own testing framework
  6. Start with small position sizes in live trading
  7. Keep detailed trading journal
  8. Review and refine regularly
  9. Join community discussions
  10. Continue education and skill development

Additional Resources

Remember: Past performance does not guarantee future results. All trading involves risk, and you should never trade with money you cannot afford to lose. This guide is for educational purposes only and does not constitute financial advice.

Last Updated: November 23, 2025