Strategy lab

EUR/USD Strategy Backtesting

Test your trading strategies against historical data from 2009 to present — right in your browser.

100,000+ data points · 15 years of history

Running Backtest Analysis

Processing historical data and calculating performance metrics...

Strategy Configuration JavaScript

My strategies

Strategy Name

Timeframe

Strategy Code

// Bollinger Bands + Stochastic Strategy for EUR/USD
const bb_period = 20;           // Bollinger Bands period
const bb_stddev = 2;            // Standard deviation
const stoch_k_period = 14;      // Stochastic %K period
const stoch_d_period = 3;       // Stochastic %D period
const overbought = 80;          // Stochastic overbought threshold
const oversold = 20;            // Stochastic oversold threshold
const trade_size_percent = 0.1; // 10% of capital per trade

// Strategy Logic - This function must return: 'buy', 'sell', or 'hold'
function executeStrategy(data, context) {
    // data: { open, high, low, close, volume, timestamp }
    // context: { position, cash, equity, history }

    // Need enough data for both indicators
    const minBars = Math.max(bb_period, stoch_k_period + stoch_d_period);
    if (context.history.length < minBars) return 'hold';

    // Get price data from history
    const closes = context.history.map(h => h.close);
    const highs = context.history.map(h => h.high);
    const lows = context.history.map(h => h.low);
    const current_price = data.close;

    // Calculate Bollinger Bands
    const sma = calculateSMA(closes, bb_period);
    const std = calculateStandardDeviation(closes, bb_period, sma);
    const upper_band = sma + bb_stddev * std;
    const lower_band = sma - bb_stddev * std;

    // Calculate Stochastic Oscillator
    const stoch = calculateStochastic(highs, lows, closes, stoch_k_period, stoch_d_period);

    // Trading logic with dual confirmation
    if (current_price < lower_band && stoch.k < oversold && context.position <= 0) {
        // Buy signal (price below lower BB AND stochastic oversold)
        return 'buy';
    } else if (current_price > upper_band && stoch.k > overbought && context.position >= 0) {
        // Sell signal (price above upper BB AND stochastic overbought)
        return 'sell';
    }

    return 'hold';
}

// Helper function for Simple Moving Average
function calculateSMA(data, period) {
    const slice = data.slice(-period);
    return slice.reduce((sum, value) => sum + value, 0) / period;
}

// Helper function for Standard Deviation
function calculateStandardDeviation(data, period, sma) {
    const slice = data.slice(-period);
    const squaredDiffs = slice.map(price => Math.pow(price - sma, 2));
    const variance = squaredDiffs.reduce((sum, value) => sum + value, 0) / period;
    return Math.sqrt(variance);
}

// Helper function for Stochastic Oscillator
function calculateStochastic(highs, lows, closes, k_period, d_period) {
    const currentClose = closes[closes.length - 1];

    // Get the most recent periods for calculation
    const recentHighs = highs.slice(-k_period);
    const recentLows = lows.slice(-k_period);

    // Calculate highest high and lowest low
    const highest_high = Math.max(...recentHighs);
    const lowest_low = Math.min(...recentLows);

    // Calculate %K
    const stoch_k = 100 * (currentClose - lowest_low) / (highest_high - lowest_low);

    // Calculate %D (simple moving average of %K)
    // We need previous %K values for this
    const k_values = [];
    for (let i = closes.length - k_period; i < closes.length; i++) {
        const periodHighs = highs.slice(i - k_period + 1, i + 1);
        const periodLows = lows.slice(i - k_period + 1, i + 1);
        const periodHighest = Math.max(...periodHighs);
        const periodLowest = Math.min(...periodLows);
        const k_val = 100 * (closes[i] - periodLowest) / (periodHighest - periodLowest);
        k_values.push(k_val);
    }

    // Calculate %D as SMA of the last d_period %K values
    const recent_k_values = k_values.slice(-d_period);
    const stoch_d = recent_k_values.reduce((sum, val) => sum + val, 0) / d_period;

    return {
        k: stoch_k,
        d: stoch_d
    };
}

Performance Summary

Total Return

+0.0%

Overall performance

Sharpe Ratio

0.00

Risk-adjusted return

Max Drawdown

-0.0%

Largest peak-to-trough

Win Rate

0.0%

Winning trades

Backtest Parameters

Symbol

Start Date

End Date

Initial Capital ($)

Commission per Trade ($)

Risk per Trade (%) Percentage of capital to risk per trade

Strategy Tips

Use realistic position sizing
Include commission costs
Test different market conditions
Consider risk management

Backtest Results

Equity Curve

Performance Metrics

Total Return	0.0%
Annual Return	0.0%
Volatility (Annual)	0.0%
Sharpe Ratio	0.00
Sortino Ratio	0.00
Max Drawdown	-0.0%
Calmar Ratio	0.00

Trade Analysis

Total Trades	0
Win Rate	0.0%
Avg Win / Avg Loss	0.00
Profit Factor	0.00
Avg Trade Duration	0 days
Expectancy per Trade	$0.00
Total Commission	$0.00
Best Trade	+$0.00
Worst Trade	-$0.00

Trade History

Last 20 Trades

Date	Type	Entry Price	Exit Price	Quantity	PnL ($)	Return (%)
No trades executed yet