Optimization Output Example

Example output from running the optimization code above on a year of S&P data.

Best Indicator parameters found:
period = 15
Rating: 0.2584229390681003
Best Indicator values: [(5104.35, 5184.6, 5264.85), (5104.35, 5184.6, 5264.85), (5131.59, 5198.22, 5264.85), ...]

Analysis

The optimized Donchian Channels (15-period) generated more frequent trading signals compared to the default 20-period configuration. A trading simulation was conducted with both parameter sets, starting with $1000 initial capital and investing 20% per trade. Long positions were opened when price dropped below the lower channel band and closed when price exceeded the upper band, while short positions were opened when price broke above the upper band and covered when price fell below the lower band.

The results demonstrate the effectiveness of the optimized parameters. The 15-period Donchian Channels strategy achieved a profit of $33.62 with a $200.72 open long position, significantly outperforming the default 20-period strategy which resulted in a loss of $2.20 (with a $193.77 open long position). The tighter 15-period channels provided more responsive signals that better captured short-term price movements in this dataset.

Optimized Trading Simulation

Default Trading Simulation

Trading Simulation Code

For those who want to run their own simulation to compare results.

fn simulate_trading(best_indicator: &[(f64, f64, f64)], best_period: usize, close: &[f64]) {
    println!("
--- Trading Simulation ---");

    let initial_capital = 1000.0;
    let mut capital = initial_capital;
    let investment_pct = 0.20;

    struct Position {
        entry_price: f64,
        shares: f64,
    }

    let mut open_long: Option<Position> = None;
    let mut open_short: Option<Position> = None;

    // Print table header
    println!("{:<5} | {:<19} | {:<10} | {:<10} | {:<12} | {:<15} | {:<10}",
             "Day", "Event", "Indicator", "Price", "Shares", "Capital", "P/L");
    println!("{}", "-".repeat(95));

    for i in 0..best_indicator.len() {
        let price_index = i + best_period + 1;
        if price_index >= close.len() { break; }

        let indicator_overbought = best_indicator[i].2;
        let indicator_oversold = best_indicator[i].0;
        let current_price = close[price_index];
        let day = price_index;

        // --- Handle Long Position ---
        if let Some(long_pos) = open_long.take() {
            if current_price > indicator_overbought as f64 {
                let sale_value = long_pos.shares * current_price;
                let profit = sale_value - (long_pos.shares * long_pos.entry_price);
                capital += sale_value;
                println!("{:<5} | {:<19} | {:<10.2} | ${:<9.2} | {:<12.4} | ${:<14.2} | ${:<9.2}",
                         day, "Sell (Close Long)", indicator_overbought, current_price, long_pos.shares, capital, profit);
            } else {
                open_long = Some(long_pos); // Put it back if not selling
            }
        } else if current_price < indicator_oversold as f64 && open_short.is_none() { // Don't buy if short is open
            let investment = capital * investment_pct;
            let shares_bought = investment / current_price;
            open_long = Some(Position { entry_price: current_price, shares: shares_bought });
            capital -= investment;
            println!("{:<5} | {:<19} | {:<10.2} | ${:<9.2} | {:<12.4} | ${:<14.2} | {}",
                     day, "Buy (Open Long)", indicator_oversold, current_price, shares_bought, capital, "-");
        }

        // --- Handle Short Position ---
        if let Some(short_pos) = open_short.take() {
            if current_price < indicator_oversold as f64 {
                let cost_to_cover = short_pos.shares * current_price;
                let profit = (short_pos.shares * short_pos.entry_price) - cost_to_cover;
                capital += profit; // Add profit to capital
                println!("{:<5} | {:<19} | {:<10.2} | ${:<9.2} | {:<12.4} | ${:<14.2} | ${:<9.2}",
                         day, "Cover (Close Short)", indicator_oversold, current_price, short_pos.shares, capital, profit);
            } else {
                open_short = Some(short_pos); // Put it back if not covering
            }
        } else if current_price > indicator_overbought as f64 && open_long.is_none() { // Don't short if long is open
            let short_value = capital * investment_pct;
            let shares_shorted = short_value / current_price;
            open_short = Some(Position { entry_price: current_price, shares: shares_shorted });
            // Capital doesn't change when opening a short, it's held as collateral
            println!("{:<5} | {:<19} | {:<10.2} | ${:<9.2} | {:<12.4} | ${:<14.2} | {}",
                     day, "Short (Open Short)", indicator_overbought, current_price, shares_shorted, capital, "-");
        }
    }

    println!("
--- Final Results ---");
    if let Some(pos) = open_long {
        println!("Simulation ended with an OPEN LONG position:");
        println!("  - Shares: {:.4}", pos.shares);
        println!("  - Entry Price: ${:.2}", pos.entry_price);
        let last_price = close.last().unwrap_or(&0.0);
        let current_value = pos.shares * last_price;
        capital += current_value;
        println!("  - Position value at last price (${:.2}): ${:.2}", last_price, current_value);
    }
    if let Some(pos) = open_short {
        println!("Simulation ended with an OPEN SHORT position:");
        println!("  - Shares: {:.4}", pos.shares);
        println!("  - Entry Price: ${:.2}", pos.entry_price);
        let last_price = close.last().unwrap_or(&0.0);
        let cost_to_cover = pos.shares * last_price;
        let pnl = (pos.shares * pos.entry_price) - cost_to_cover;
        capital += pnl;
        println!("  - Unrealized P/L at last price (${:.2}): ${:.2}", last_price, pnl);
    }

    let final_pnl = capital - initial_capital;
    println!("
Initial Capital: ${:.2}", initial_capital);
    println!("Final Capital:   ${:.2}", capital);
    println!("Total P/L:       ${:.2}", final_pnl);

}

fn main() {
    // Fetch data and perform optimization as shown in the optimization code above
    simulate_trading(&best_indicators, best_period, &close);

    println!("
Default Indicator values for comparison:");
    let default_dc = donchian_channels(&high, &low, 20);
    println!("{:?}", default_dc);
    simulate_trading(&default_dc, 20, &close);
}