Directional Movement System

Optimization Output Example

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

Best Directional Movement System parameters found:
period = 5
model = ExponentialMovingAverage
adx_threshold = 30
Rating: 0.09324324324324322
Best Indicator values: [(33.8994519250288, 41.7957913255289, 20.458357588402144, 26.497885766558245), (16.144945735043468, 49.367656292043584, 32.416657092614244, 27.7809871335861), (7.589617730179923, 40.93410679756024, 47.42070636594339, 33.29236677142793), (7.960528881781621, 36.45227973009842, 55.31128591983033, 41.39491025071076), (6.892243271536098, 28.663087157667267, 58.207367953359444, 39.332862770880794), (0.0, 35.47830701870767, 76.66618205347048, 54.54141957304236), (12.634490074253465, 22.219275647825633, 59.10402336386252, 53.26236486490295), (12.53382441370996, 33.62898376428195, 53.471358493336105, 54.39132220658322), (9.268523150463952, 40.28403090434119, 56.43237384248714, 57.319870897923295), (9.9315068493149, 36.03930911256711, 56.327897711304765, 66.49703988238763), (9.09264409182602, 35.85800752494698, 55.354717879305106, 57.22937062158381), (0.0, 39.272393412520834, 73.90156547403906, 63.68646198368758), (0.0, 44.501455708973296, 85.34620357511754, 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22.35992648791273, 23.63470294519106, 29.590129996162844), (40.70354245002974, 17.153176330892055, 29.022759489405466, 27.691806258112198), (11.698704727332965, 45.664549129609306, 41.692845513619474, 33.74600441836271), (6.172197371614903, 49.04122889143163, 56.27318558065797, 39.06886703334553), (5.1981426860964906, 59.18289869462379, 68.82802933784869, 46.23136614151987), (4.479753704863318, 52.875182634105734, 76.92026588679686, 52.97151268810116), (3.66660972067996, 53.388998035363635, 82.67706727951358, 62.18495639656653), (3.5492806350256525, 40.32991566065831, 84.30301466757348, 70.28810012411573), (2.8948610736444693, 32.222821688697046, 84.33659456445822, 76.58231195115346), (2.6767479928287594, 31.194948943799126, 84.3066545710812, 80.61346022893903), (0.0, 29.31610407876225, 90.32746509765481, 86.5022661885842), (0.0, 24.209600518446482, 94.20138790093273, 89.2522012842531), (0.0, 28.166451552708132, 96.9520790000044, 90.6443367822313), (0.0, 42.12625566279301, 98.80149995735536, 91.55407726421828), (0.0, 36.593459222769695, 100.00000000000001, 95.16373254882741), (1.0471111111110094, 38.03377777777793, 97.94287399591218, 96.07213094842245), (1.0608980709305682, 40.467227435652866, 96.66719296287177, 96.80963598143808), (10.267556598511256, 34.49191175056278, 80.16588253857785, 89.4836912479666)]

Analysis

The optimized Directional Movement System parameters (period=5, EMA, ADX threshold=30) generated more trading signals compared to the default parameters (period=14, SMA, ADX threshold=25). The trading simulation shows that the optimized strategy achieved a profit of $11.63 with 22 trades, while the default strategy resulted in a loss of $-31.07 with only 10 trades. The higher ADX threshold in the optimized parameters helps filter out weaker trends, and the shorter period with EMA provides more responsive signals, leading to better overall performance in this simulation.

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, f64)],
    best_period: usize,
    close: &[f64],
    adx_threshold: 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} | {:<8} | {:<8} | {:<8} | {:<10} | {:<12} | {:<15} | {:<10}",
        "Day", "Event", "+DI", "-DI", "ADX", "Price", "Shares", "Capital", "P/L"
    );
    println!("{}", "-".repeat(115));

    for i in 1..best_indicator.len() {
        let price_location = i + (3 * best_period) - 2;
        if price_location >= close.len() {
            break;
        }

        let (plus_di, minus_di, adx, _adxr) = best_indicator[i];
        let (prev_plus_di, prev_minus_di, _prev_adx, _prev_adxr) = best_indicator[i - 1];
        let current_price = close[price_location];
        let day = price_location;

        // Only trade when trend is strong enough (ADX above threshold)
        if adx < adx_threshold {
            // Keep existing positions but don't open new ones
            if let Some(pos) = open_long.as_ref() {
                open_long = Some(Position {
                    entry_price: pos.entry_price,
                    shares: pos.shares,
                });
            }
            if let Some(pos) = open_short.as_ref() {
                open_short = Some(Position {
                    entry_price: pos.entry_price,
                    shares: pos.shares,
                });
            }
            continue;
        }

        // --- Handle Long Position ---
        if let Some(long_pos) = open_long.take() {
            // Sell signal: -DI crosses above +DI
            if minus_di > plus_di && prev_minus_di <= prev_plus_di {
                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} | {:<8.2} | {:<8.2} | {:<8.2} | ${:<9.2} | {:<12.4} | ${:<14.2} | ${:<9.2}",
                    day,
                    "Sell (Close Long)",
                    plus_di,
                    minus_di,
                    adx,
                    current_price,
                    long_pos.shares,
                    capital,
                    profit
                );
            } else {
                open_long = Some(long_pos); // Put it back if not selling
            }
        } else if plus_di > minus_di && prev_plus_di <= prev_minus_di && open_short.is_none() {
            // Buy signal: +DI crosses above -DI
            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} | {:<8.2} | {:<8.2} | {:<8.2} | ${:<9.2} | {:<12.4} | ${:<14.2} | {}",
                day,
                "Buy (Open Long)",
                plus_di,
                minus_di,
                adx,
                current_price,
                shares_bought,
                capital,
                "-"
            );
        }

        // --- Handle Short Position ---
        if let Some(short_pos) = open_short.take() {
            // Cover signal: +DI crosses above -DI
            if plus_di > minus_di && prev_plus_di <= prev_minus_di {
                let cost_to_cover = short_pos.shares * current_price;
                let profit = (short_pos.shares * short_pos.entry_price) - cost_to_cover;
                capital += profit;
                println!(
                    "{:<5} | {:<19} | {:<8.2} | {:<8.2} | {:<8.2} | ${:<9.2} | {:<12.4} | ${:<14.2} | ${:<9.2}",
                    day,
                    "Cover (Close Short)",
                    plus_di,
                    minus_di,
                    adx,
                    current_price,
                    short_pos.shares,
                    capital,
                    profit
                );
            } else {
                open_short = Some(short_pos); // Put it back if not covering
            }
        } else if minus_di > plus_di && prev_minus_di <= prev_plus_di && open_long.is_none() {
            // Short signal: -DI crosses above +DI
            let short_value = capital * investment_pct;
            let shares_shorted = short_value / current_price;
            open_short = Some(Position {
                entry_price: current_price,
                shares: shares_shorted,
            });
            println!(
                "{:<5} | {:<19} | {:<8.2} | {:<8.2} | {:<8.2} | ${:<9.2} | {:<12.4} | ${:<14.2} | {}",
                day,
                "Short (Open Short)",
                plus_di,
                minus_di,
                adx,
                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
    // Run trading simulation with optimized parameters
        simulate_trading(&best_indicators, best_period, &close, best_adx_threshold);

        // Compare with default parameters (typically period=14, SimpleMovingAverage, ADX threshold=25)
        println!("

Default Indicator values for comparison:");
        let default_dms = directional_movement_system(
            &high,
            &low,
            &close,
            14,
            ConstantModelType::SimpleMovingAverage,
        );
        println!("{:?}", default_dms);
        simulate_trading(&default_dms, 14, &close, 25.0);
}