124 lines
3.6 KiB
Rust
124 lines
3.6 KiB
Rust
//! Benchmark for RaptorBT backtesting performance.
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use criterion::{black_box, criterion_group, criterion_main, BenchmarkId, Criterion};
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use raptorbt::core::types::{BacktestConfig, CompiledSignals, Direction, OhlcvData};
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use raptorbt::indicators::trend::{ema, sma};
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use raptorbt::portfolio::engine::PortfolioEngine;
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/// Generate sample OHLCV data.
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fn generate_sample_data(n: usize) -> OhlcvData {
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let mut open = vec![100.0; n];
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let mut high = vec![101.0; n];
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let mut low = vec![99.0; n];
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let mut close = vec![100.0; n];
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// Create a trending pattern
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for i in 1..n {
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let change = (i as f64 * 0.1).sin() * 2.0;
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close[i] = close[i - 1] + change;
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open[i] = close[i - 1];
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high[i] = close[i].max(open[i]) + 1.0;
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low[i] = close[i].min(open[i]) - 1.0;
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}
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OhlcvData {
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timestamps: (0..n as i64).collect(),
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open,
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high,
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low,
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close,
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volume: vec![1000.0; n],
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}
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}
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/// Generate sample trading signals based on SMA crossover.
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fn generate_sample_signals(
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close: &[f64],
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fast_period: usize,
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slow_period: usize,
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) -> CompiledSignals {
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let n = close.len();
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let fast_sma = sma(close, fast_period).unwrap_or_else(|_| vec![0.0; n]);
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let slow_sma = sma(close, slow_period).unwrap_or_else(|_| vec![0.0; n]);
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let mut entries = vec![false; n];
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let mut exits = vec![false; n];
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for i in 1..n {
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// Entry: fast crosses above slow
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if fast_sma[i] > slow_sma[i] && fast_sma[i - 1] <= slow_sma[i - 1] {
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entries[i] = true;
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}
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// Exit: fast crosses below slow
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if fast_sma[i] < slow_sma[i] && fast_sma[i - 1] >= slow_sma[i - 1] {
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exits[i] = true;
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}
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}
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CompiledSignals {
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symbol: "BENCH".to_string(),
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entries,
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exits,
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position_sizes: None,
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direction: Direction::Long,
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weight: 1.0,
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}
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}
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fn bench_single_backtest(c: &mut Criterion) {
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let mut group = c.benchmark_group("single_backtest");
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for size in [1000, 5000, 10000, 50000].iter() {
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group.bench_with_input(BenchmarkId::new("bars", size), size, |b, &size| {
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let ohlcv = generate_sample_data(size);
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let signals = generate_sample_signals(&ohlcv.close, 10, 30);
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let config = BacktestConfig::default();
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let engine = PortfolioEngine::new(config);
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b.iter(|| {
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let result = engine.run_single(black_box(&ohlcv), black_box(&signals));
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black_box(result)
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});
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});
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}
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group.finish();
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}
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fn bench_sma(c: &mut Criterion) {
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let mut group = c.benchmark_group("sma");
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for size in [1000, 5000, 10000, 50000].iter() {
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group.bench_with_input(BenchmarkId::new("data_size", size), size, |b, &size| {
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let ohlcv = generate_sample_data(size);
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b.iter(|| {
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let result = sma(black_box(&ohlcv.close), black_box(20));
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black_box(result)
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});
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});
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}
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group.finish();
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}
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fn bench_ema(c: &mut Criterion) {
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let mut group = c.benchmark_group("ema");
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for size in [1000, 5000, 10000, 50000].iter() {
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group.bench_with_input(BenchmarkId::new("data_size", size), size, |b, &size| {
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let ohlcv = generate_sample_data(size);
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b.iter(|| {
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let result = ema(black_box(&ohlcv.close), black_box(20));
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black_box(result)
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});
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});
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}
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group.finish();
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}
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criterion_group!(benches, bench_single_backtest, bench_sma, bench_ema);
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criterion_main!(benches);
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