* This example demonstrates advanced ta4j features beyond the Quickstart: *
* Strategy Concept: A mean reversion strategy that buys when * price touches the lower Bollinger Band (oversold) with RSI confirmation and * volume support, using ATR-based stops that adapt to market volatility. *
* Data Source: This example uses Yahoo Finance's public API to * fetch real market data. No API key is required, but be aware of rate limits * (~2000 requests/hour per IP). *
* Run this example to see an advanced trading strategy backtested on real * market data with comprehensive analysis! */ public class YahooFinanceBacktest { private static final Logger LOG = LogManager.getLogger(YahooFinanceBacktest.class); public static void main(String[] args) { System.out.println("╔══════════════════════════════════════════════════════════════╗"); System.out.println("║ Yahoo Finance Data Source - Backtesting Example ║"); System.out.println("╚══════════════════════════════════════════════════════════════╝"); System.out.println(); // Step 1: Load historical price data from Yahoo Finance System.out.println("[1/7] Loading historical price data from Yahoo Finance..."); System.out.println(" Fetching 2 years of daily data for Apple Inc. (AAPL)..."); System.out.println(" (More data = better indicator calculations)"); // Load 2 years of data for better indicator stability YahooFinanceHttpBarSeriesDataSource dataSource = new YahooFinanceHttpBarSeriesDataSource(true); BarSeries series = dataSource.loadSeriesInstance("AAPL", YahooFinanceHttpBarSeriesDataSource.YahooFinanceInterval.DAY_1, 730); // Alternative methods you can try: // BarSeries series = dataSource.loadSeriesInstance("AAPL", // YahooFinanceInterval.DAY_1, 500); // 500 bars // BarSeries series = dataSource.loadSeriesInstance("MSFT", // YahooFinanceInterval.HOUR_1, 1000); // Hourly data // BarSeries series = dataSource.loadSeriesInstance("BTC-USD", // YahooFinanceInterval.DAY_1, // Instant.parse("2023-01-01T00:00:00Z"), // Instant.parse("2023-12-31T23:59:59Z")); // Date range if (series == null || series.getBarCount() == 0) { System.err.println(" [ERROR] Failed to load data from Yahoo Finance"); System.err.println(" [TIP] Check your internet connection and try again"); System.err.println(" [TIP] Yahoo Finance may have rate limits - wait a few minutes and retry"); return; } System.out.printf(" [OK] Loaded %d bars of price data%n", series.getBarCount()); System.out.printf(" [INFO] Date range: %s to %s%n", series.getFirstBar().getEndTime(), series.getLastBar().getEndTime()); System.out.println(); // Step 2: Create base indicators System.out.println("[2/7] Creating technical indicators..."); ClosePriceIndicator closePrice = new ClosePriceIndicator(series); // Bollinger Bands: Mean reversion indicator // Uses 20-period SMA with 2 standard deviations int bbPeriod = 20; double bbMultiplier = 2.0; SMAIndicator bbSma = new SMAIndicator(closePrice, bbPeriod); StandardDeviationIndicator bbStdDev = new StandardDeviationIndicator(closePrice, bbPeriod); BollingerBandsMiddleIndicator bbMiddle = new BollingerBandsMiddleIndicator(bbSma); BollingerBandsUpperIndicator bbUpper = new BollingerBandsUpperIndicator(bbMiddle, bbStdDev, series.numFactory().numOf(bbMultiplier)); BollingerBandsLowerIndicator bbLower = new BollingerBandsLowerIndicator(bbMiddle, bbStdDev, series.numFactory().numOf(bbMultiplier)); // RSI: Momentum oscillator (14-period) RSIIndicator rsi = new RSIIndicator(closePrice, 14); // On-Balance Volume: Volume-based trend indicator OnBalanceVolumeIndicator obv = new OnBalanceVolumeIndicator(series); // Trend confirmation indicators VortexIndicator vortex = new VortexIndicator(series, 14); UltimateOscillatorIndicator ultimateOscillator = new UltimateOscillatorIndicator(series); // Note: ATR is used in the AverageTrueRangeStopLossRule below // Advanced: You can also create custom indicators using // BinaryOperationIndicator // Example: Calculate distance from price to middle band as a percentage // BinaryOperationIndicator priceToMiddleRatio = // BinaryOperationIndicator.quotient( // BinaryOperationIndicator.difference(closePrice, bbMiddle), bbMiddle); System.out.println(" [OK] Created Bollinger Bands (20-period, 2 std dev)"); System.out.println(" [OK] Created RSI (14-period)"); System.out.println(" [OK] Created ATR (14-period) for dynamic stops"); System.out.println(" [OK] Created On-Balance Volume indicator"); System.out.println(" [OK] Created Vortex oscillator (14-period) for trend direction"); System.out.println(" [OK] Created Ultimate Oscillator (7/14/28) for trend strength"); System.out.println(" [OK] Created custom price-to-middle-band ratio indicator"); System.out.println(); // Step 3: Build advanced trading rules System.out.println("[3/7] Building advanced trading strategy rules..."); System.out.println(" Strategy: Mean reversion with multiple confirmations"); // Entry rule: Buy when price is at or below lower Bollinger Band (oversold) // AND RSI is below 45 (oversold confirmation - less strict than 40) // Price touching lower BB OR crossing below it Rule priceAtLowerBB = new UnderIndicatorRule(closePrice, bbLower) .or(new CrossedDownIndicatorRule(closePrice, bbLower)); Rule rsiOversold = new UnderIndicatorRule(rsi, series.numFactory().numOf(45)); // Optional: OBV rising provides additional confirmation (but not required) // This makes the strategy more tradeable while still using volume analysis Rule obvRising = new OverIndicatorRule(obv, new PreviousValueIndicator(obv, 1)); Rule vortexBullish = new OverIndicatorRule(vortex, series.numFactory().zero()); Rule ultimateBullish = new OverIndicatorRule(ultimateOscillator, series.numFactory().numOf(50)); // Entry: Price at lower BB + RSI oversold + (OBV rising OR price below middle // band) + trend confirmation from Vortex and Ultimate Oscillator // This allows entries when either volume confirms OR price is clearly oversold Rule priceBelowMiddle = new UnderIndicatorRule(closePrice, bbMiddle); Rule buyingRule = priceAtLowerBB.and(rsiOversold) .and(obvRising.or(priceBelowMiddle)) .and(vortexBullish) .and(ultimateBullish); // Exit rule: Sell when price reaches upper Bollinger Band (overbought) // OR RSI crosses above 65 (overbought - less strict than 70 for more exits) // OR ATR-based stop loss triggers (dynamic, adapts to volatility) // OR Vortex turns bearish Rule exitCondition1 = new CrossedUpIndicatorRule(closePrice, bbUpper) .or(new OverIndicatorRule(closePrice, bbUpper)); Rule exitCondition2 = new OverIndicatorRule(rsi, series.numFactory().numOf(65)); // ATR-based stop: 2.5x ATR below entry price (allows for some volatility) Rule exitCondition3 = new AverageTrueRangeStopLossRule(series, 14, 2.5); Rule exitCondition4 = new UnderIndicatorRule(vortex, series.numFactory().zero()); Rule sellingRule = exitCondition1.or(exitCondition2).or(exitCondition3).or(exitCondition4); Strategy strategy = new BaseStrategy("Bollinger Bands Mean Reversion (Trend-Confirmed)", buyingRule, sellingRule); System.out.println( " [OK] Entry: Price at/below lower BB + RSI < 45 + (OBV rising OR price below middle) + Vortex > 0 + Ultimate > 50"); System.out.println(" [OK] Exit: Price at/above upper BB OR RSI > 65 OR ATR stop (2.5x ATR) OR Vortex < 0"); System.out.println(); // Step 4: Run backtest System.out.println("[4/7] Running backtest on historical data..."); BarSeriesManager seriesManager = new BarSeriesManager(series); TradingRecord tradingRecord = seriesManager.run(strategy); System.out.printf(" [OK] Backtest complete: %d positions executed%n", tradingRecord.getPositionCount()); System.out.println(); // Step 5: Advanced performance analysis System.out.println("[5/7] Advanced Performance Analysis"); System.out.println(" ──────────────────────────────────────────"); // Basic metrics AnalysisCriterion netReturn = new NetReturnCriterion(); AnalysisCriterion winningPositionsRatio = new PositionsRatioCriterion(PositionFilter.PROFIT); Num netReturnValue = netReturn.calculate(series, tradingRecord); Num winRate = winningPositionsRatio.calculate(series, tradingRecord); // Advanced risk-adjusted metrics AnalysisCriterion romad = new ReturnOverMaxDrawdownCriterion(); AnalysisCriterion maxDrawdown = new MaximumDrawdownCriterion(); AnalysisCriterion expectancy = new ExpectancyCriterion(); AnalysisCriterion sqn = new SqnCriterion(); // System Quality Number (higher = better) AnalysisCriterion versusEnterAndHoldCriterion = new VersusEnterAndHoldCriterion(new NetReturnCriterion()); Num romadValue = romad.calculate(series, tradingRecord); Num maxDrawdownValue = maxDrawdown.calculate(series, tradingRecord); Num expectancyValue = expectancy.calculate(series, tradingRecord); Num sqnValue = sqn.calculate(series, tradingRecord); Num vsBuyHold = versusEnterAndHoldCriterion.calculate(series, tradingRecord); // Display comprehensive results System.out.println(" Basic Metrics:"); System.out.printf(" Total Positions: %d%n", tradingRecord.getPositionCount()); System.out.printf(" Net Return: %.2f%%%n", netReturnValue.multipliedBy(series.numFactory().numOf(100)).doubleValue()); System.out.printf(" Win Rate: %.1f%%%n", winRate.multipliedBy(series.numFactory().numOf(100)).doubleValue()); System.out.println(); System.out.println(" Risk Metrics:"); System.out.printf(" Maximum Drawdown: %.2f%%%n", maxDrawdownValue.multipliedBy(series.numFactory().numOf(100)).doubleValue()); System.out.printf(" Return/Max Drawdown: %.2f%n", romadValue.doubleValue()); System.out.println(); System.out.println(" Advanced Metrics:"); System.out.printf(" Expectancy: %.4f (avg profit per trade)%n", expectancyValue.doubleValue()); System.out.printf(" SQN (System Quality): %.2f (higher = better)%n", sqnValue.doubleValue()); System.out.printf(" vs Buy & Hold: %.2f%%%n", vsBuyHold.multipliedBy(series.numFactory().numOf(100)).doubleValue()); System.out.println(); // Step 6: Visualize the strategy with multiple subcharts System.out.println("[6/7] Generating comprehensive strategy visualization..."); boolean isHeadless = GraphicsEnvironment.isHeadless(); if (isHeadless) { System.out.println(" [WARN] Headless environment detected - skipping chart display"); System.out.println(" [TIP] Run in a GUI environment to see interactive charts!"); } else { try { ChartWorkflow chartWorkflow = new ChartWorkflow(); JFreeChart chart = chartWorkflow.builder() .withTitle("Bollinger Bands Mean Reversion Strategy - Yahoo Finance Data (AAPL)") .withSeries(series) // Price bars (candlesticks) .withTradingRecordOverlay(tradingRecord) // Trading positions marked on price chart .withIndicatorOverlay(bbMiddle) // Middle band overlay .withIndicatorOverlay(bbUpper) // Upper band overlay .withIndicatorOverlay(bbLower) // Lower band overlay .withSubChart(rsi) // RSI in first subchart .withSubChart(obv) // OBV in second subchart .withSubChart(vortex) // Vortex oscillator in third subchart .withSubChart(ultimateOscillator) // Ultimate Oscillator in fourth subchart .withSubChart(new NetProfitLossCriterion(), tradingRecord) // Net profit/loss in fifth subchart .toChart(); chartWorkflow.displayChart(chart, "ta4j Yahoo Finance Backtest - Advanced Mean Reversion Strategy"); System.out.println(" [OK] Multi-subchart displayed in new window"); System.out.println(" [TIP] Chart shows: Price with BB bands, RSI, OBV, Vortex, Ultimate, and P&L"); } catch (Exception ex) { LOG.warn("Failed to display chart: {}", ex.getMessage(), ex); System.out.println(" [WARN] Could not display chart: " + ex.getMessage()); } } System.out.println(); // Step 7: Explain advanced concepts System.out.println("[7/7] Advanced Concepts Demonstrated"); System.out.println(" ──────────────────────────────────────────"); System.out.println(" ✓ Bollinger Bands: Mean reversion indicator"); System.out.println(" - Price tends to revert to the middle band"); System.out.println(" - Lower band = oversold, Upper band = overbought"); System.out.println(); System.out.println(" ✓ ATR-based Stop Loss: Dynamic risk management"); System.out.println(" - Adapts to market volatility automatically"); System.out.println(" - Tighter stops in calm markets, wider in volatile markets"); System.out.println(); System.out.println(" ✓ Multi-Indicator Confirmation: Reduces false signals"); System.out.println(" - RSI confirms oversold/overbought conditions"); System.out.println(" - OBV confirms volume support for price moves"); System.out.println(" - Vortex confirms directional trend bias (+VI vs -VI)"); System.out.println(" - Ultimate Oscillator confirms multi-timeframe buying pressure"); System.out.println(); System.out.println(" ✓ Advanced Metrics: Deeper performance insights"); System.out.println(" - Expectancy: Average profit per trade"); System.out.println(" - SQN: System Quality Number (risk-adjusted performance)"); System.out.println(" - Maximum Drawdown: Largest peak-to-trough decline"); System.out.println(); // Summary System.out.println("╔══════════════════════════════════════════════════════════════╗"); System.out.println("║ Summary ║"); System.out.println("╚══════════════════════════════════════════════════════════════╝"); System.out.println(); System.out.println("What just happened?"); System.out.println(); System.out.println(" 1. Loaded 2 years of daily OHLCV data for AAPL from Yahoo Finance"); System.out.println(" 2. Created advanced indicators:"); System.out.println(" - Bollinger Bands (mean reversion)"); System.out.println(" - RSI (momentum confirmation)"); System.out.println(" - ATR (volatility for dynamic stops)"); System.out.println(" - OBV (volume trend confirmation)"); System.out.println(" - Vortex oscillator (trend direction confirmation)"); System.out.println(" - Ultimate Oscillator (trend strength confirmation)"); System.out.println(" - Custom price-to-middle-band ratio (indicator composition)"); System.out.println(" 3. Built a sophisticated mean reversion strategy:"); System.out.println( " - Entry: Price at/below lower BB + RSI < 45 + (OBV rising OR price below middle) + Vortex > 0 + Ultimate > 50"); System.out.println(" - Exit: Price at/above upper BB OR RSI > 65 OR ATR stop (2.5x ATR) OR Vortex < 0"); System.out.println(" 4. Backtested with ATR-based dynamic stop-loss (adapts to volatility)"); System.out.println(" 5. Analyzed with advanced metrics (Expectancy, SQN, Max Drawdown)"); if (!isHeadless) { System.out.println(" 6. Visualized with multi-subchart (Price, RSI, OBV, P&L)"); } System.out.println(); System.out.println("Advanced Features Demonstrated:"); System.out.println(" ✓ Bollinger Bands for mean reversion trading"); System.out.println(" ✓ ATR-based dynamic stop-loss (better than fixed %)"); System.out.println(" ✓ Multi-indicator trend confirmation (RSI, OBV, Vortex, Ultimate)"); System.out.println(" ✓ Indicator composition (BinaryOperationIndicator)"); System.out.println(" ✓ Advanced performance metrics (Expectancy, SQN)"); System.out.println(" ✓ Multi-subchart visualization"); System.out.println(); System.out.println("Yahoo Finance Data Source Features:"); System.out.println(" - Load data by number of days: loadSeries(\"AAPL\", 730)"); System.out.println(" - Load data by bar count: loadSeries(\"AAPL\", DAY_1, 500)"); System.out.println(" - Load data by date range: loadSeries(\"AAPL\", DAY_1, start, end)"); System.out.println(" - Supports multiple intervals: 1m, 5m, 15m, 30m, 1h, 4h, 1d, 1wk, 1mo"); System.out.println(" - Works with stocks, ETFs, and cryptocurrencies"); System.out.println(" - Automatic pagination for large date ranges"); System.out.println(); System.out.println("Next Steps - Experiment with:"); System.out.println(" - Different tickers: \"MSFT\", \"GOOGL\", \"BTC-USD\", \"ETH-USD\""); System.out.println(" - Adjust BB period (try 10, 30) and multiplier (try 1.5, 2.5)"); System.out.println(" - Modify RSI thresholds (try 30/70 or 35/65)"); System.out.println(" - Change ATR multiplier for stops (try 1.5x or 3.0x)"); System.out.println(" - Add MACD or Stochastic for additional confirmation"); System.out.println(" - Try different intervals: HOUR_1, WEEK_1 for different timeframes"); System.out.println(" - Explore other examples in ta4j-examples"); System.out.println(" - Check out the wiki: https://ta4j.github.io/ta4j-wiki/"); System.out.println(); System.out.println("Your turn! Modify this code and see how it affects performance."); System.out.println(); } }