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/*
* SPDX-License-Identifier: MIT
*/
package ta4jexamples.backtesting;
import java.awt.GraphicsEnvironment;
import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.jfree.chart.JFreeChart;
import org.ta4j.core.AnalysisCriterion;
import org.ta4j.core.AnalysisCriterion.PositionFilter;
import org.ta4j.core.BarSeries;
import org.ta4j.core.BaseStrategy;
import org.ta4j.core.Rule;
import org.ta4j.core.Strategy;
import org.ta4j.core.TradingRecord;
import org.ta4j.core.backtest.BarSeriesManager;
import org.ta4j.core.criteria.ExpectancyCriterion;
import org.ta4j.core.criteria.PositionsRatioCriterion;
import org.ta4j.core.criteria.SqnCriterion;
import org.ta4j.core.criteria.drawdown.MaximumDrawdownCriterion;
import org.ta4j.core.criteria.drawdown.ReturnOverMaxDrawdownCriterion;
import org.ta4j.core.criteria.VersusEnterAndHoldCriterion;
import org.ta4j.core.criteria.pnl.NetProfitLossCriterion;
import org.ta4j.core.criteria.pnl.NetReturnCriterion;
import org.ta4j.core.indicators.RSIIndicator;
import org.ta4j.core.indicators.UltimateOscillatorIndicator;
import org.ta4j.core.indicators.VortexIndicator;
import org.ta4j.core.indicators.averages.SMAIndicator;
import org.ta4j.core.indicators.bollinger.BollingerBandsLowerIndicator;
import org.ta4j.core.indicators.bollinger.BollingerBandsMiddleIndicator;
import org.ta4j.core.indicators.bollinger.BollingerBandsUpperIndicator;
import org.ta4j.core.indicators.helpers.ClosePriceIndicator;
import org.ta4j.core.indicators.helpers.PreviousValueIndicator;
import org.ta4j.core.indicators.statistics.StandardDeviationIndicator;
import org.ta4j.core.indicators.volume.OnBalanceVolumeIndicator;
import org.ta4j.core.num.Num;
import org.ta4j.core.rules.AverageTrueRangeStopLossRule;
import org.ta4j.core.rules.CrossedDownIndicatorRule;
import org.ta4j.core.rules.CrossedUpIndicatorRule;
import org.ta4j.core.rules.OverIndicatorRule;
import org.ta4j.core.rules.UnderIndicatorRule;
import ta4jexamples.charting.workflow.ChartWorkflow;
import ta4jexamples.datasources.YahooFinanceHttpBarSeriesDataSource;
/**
* Yahoo Finance Data Source Backtest - Advanced Multi-Indicator Strategy
* <p>
* This example demonstrates advanced ta4j features beyond the Quickstart:
* <ul>
* <li>Loading historical OHLCV data from Yahoo Finance API</li>
* <li>Bollinger Bands for mean reversion signals</li>
* <li>ATR-based dynamic stop-loss (adapts to market volatility)</li>
* <li>RSI for momentum confirmation</li>
* <li>Volume analysis with On-Balance Volume (OBV)</li>
* <li>Trend confirmation with Vortex and Ultimate Oscillator</li>
* <li>Indicator composition using BinaryOperationIndicator</li>
* <li>Advanced performance metrics (Expectancy, SQN, Maximum Drawdown)</li>
* <li>Multi-subchart visualization</li>
* </ul>
* <p>
* <strong>Strategy Concept:</strong> 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.
* <p>
* <strong>Data Source:</strong> 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).
* <p>
* 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();
}
}