docs(examples): add 3 end-to-end strategy examples (Rust + Python) (#65)
Wires real indicators into complete signal -> fill -> PnL -> equity loops over the checked-in BTCUSDT datasets, with per-trade Sharpe and max-drawdown reported on stdout. Closes the gap where existing examples showed only the mechanics of calling `update`/`batch` but not how Wickra plugs into a trading-system shape. Three strategies, each in Rust + Python (six files total): - strategy_rsi_mean_reversion — RSI(14) thresholds (30/70) on 1h BTCUSDT. Binary position, 0.1% per-trade fee. - strategy_macd_adx — MACD crossover entries gated by ADX(14) > 20 on 1h BTCUSDT. Trend-follower demo of multi-indicator gating. - strategy_bollinger_squeeze — Bollinger-bandwidth 180-day-low squeeze + upper-band breakout entry, ATR(14) * 2 stop. On 1d BTCUSDT for interpretable lookback. Each file is self-contained — print_summary is inlined per script so the example stays a single-file read. Every script prints a NOT-financial-advice notice next to its results. examples/README.md updated to list the new bins/scripts.
This commit is contained in:
kingchenc
@@ -0,0 +1,217 @@
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//! Strategy example: Bollinger-Squeeze breakout with ATR-based stop.
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//!
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//! Enters long when the Bollinger Bandwidth has just printed a fresh
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//! 6-month low (the *squeeze*) and price closes above the upper band
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//! (the *release*). Exits when price closes below the entry minus 2 *
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//! ATR(14), or when the upper band starts trailing below the entry
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//! price (the squeeze pattern has played out). 0.1% fees per trade.
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//!
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//! Educational example. **Not** a live trading recommendation.
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//!
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//! Build with:
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//! ```text
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//! cargo run --release -p wickra-examples --bin strategy_bollinger_squeeze
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//! ```
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//!
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//! Uses the checked-in `examples/data/btcusdt-1d.csv` dataset because
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//! daily bars give an interpretable "6-month low" lookback (≈180 bars).
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use std::collections::VecDeque;
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use wickra::{Atr, BollingerBands, Indicator};
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use wickra_data::csv::CandleReader;
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const FEE: f64 = 0.001;
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const BB_PERIOD: usize = 20;
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const BB_K: f64 = 2.0;
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const ATR_PERIOD: usize = 14;
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const ATR_STOP_MULT: f64 = 2.0;
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const SQUEEZE_LOOKBACK: usize = 180; // ≈ 6 months of daily bars
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fn main() -> Result<(), Box<dyn std::error::Error>> {
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let path = concat!(env!("CARGO_MANIFEST_DIR"), "/../data/btcusdt-1d.csv");
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let mut reader = CandleReader::open(path)?;
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let candles = reader.read_all()?;
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if candles.len() < SQUEEZE_LOOKBACK + BB_PERIOD {
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return Err(format!(
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"dataset has only {} bars; need at least {}",
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candles.len(),
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SQUEEZE_LOOKBACK + BB_PERIOD
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)
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.into());
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}
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let mut bb = BollingerBands::new(BB_PERIOD, BB_K)?;
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let mut atr = Atr::new(ATR_PERIOD)?;
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let mut bw_window: VecDeque<f64> = VecDeque::with_capacity(SQUEEZE_LOOKBACK);
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let mut in_position = false;
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let mut entry_price = 0.0_f64;
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let mut stop_level = 0.0_f64;
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let mut closed_trades: Vec<f64> = Vec::new();
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let mut equity = 1.0_f64;
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let mut equity_curve: Vec<f64> = Vec::with_capacity(candles.len());
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for candle in &candles {
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let bb_out = bb.update(candle.close);
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let atr_out = atr.update(*candle);
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let price = candle.close;
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let mtm_equity = if in_position {
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equity * (price / entry_price)
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} else {
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equity
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};
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equity_curve.push(mtm_equity);
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let Some(b) = bb_out else { continue };
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let Some(a) = atr_out else { continue };
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// Bandwidth = (upper - lower) / middle; track its rolling minimum
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// over the squeeze lookback so we know what "tight" looks like
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// in this regime.
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let bandwidth = if b.middle.abs() > f64::EPSILON {
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(b.upper - b.lower) / b.middle
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} else {
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f64::NAN
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};
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if bandwidth.is_finite() {
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if bw_window.len() == SQUEEZE_LOOKBACK {
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bw_window.pop_front();
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}
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bw_window.push_back(bandwidth);
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}
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if bw_window.len() < SQUEEZE_LOOKBACK || !bandwidth.is_finite() {
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continue;
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}
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let min_bw = bw_window.iter().copied().fold(f64::INFINITY, f64::min);
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if in_position {
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// Exit: hit ATR-stop OR upper-band has rolled back under
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// the entry (squeeze is exhausted).
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let stop_hit = price < stop_level;
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let upper_collapse = b.upper < entry_price;
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if stop_hit || upper_collapse {
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let trade_ret = price / entry_price - 1.0;
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closed_trades.push(trade_ret);
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equity *= (1.0 + trade_ret) * (1.0 - FEE);
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in_position = false;
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}
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} else {
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// Entry trigger: current bandwidth is the new 6-month low AND
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// price has just punched above the upper band.
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let is_new_low = (bandwidth - min_bw).abs() < 1e-12;
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let breakout = price > b.upper;
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if is_new_low && breakout {
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entry_price = price;
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stop_level = price - ATR_STOP_MULT * a;
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equity *= 1.0 - FEE;
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in_position = true;
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}
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}
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}
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if in_position {
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let last_price = candles.last().expect("non-empty above").close;
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let trade_ret = last_price / entry_price - 1.0;
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closed_trades.push(trade_ret);
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equity *= (1.0 + trade_ret) * (1.0 - FEE);
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}
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print_summary(
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"Bollinger Squeeze Breakout (1d, BTCUSDT)",
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candles.first().unwrap().close,
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candles.last().unwrap().close,
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candles.len(),
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&closed_trades,
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equity,
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&equity_curve,
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);
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Ok(())
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}
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fn print_summary(
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name: &str,
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first_price: f64,
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last_price: f64,
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bars: usize,
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closed_trades: &[f64],
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final_equity: f64,
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equity_curve: &[f64],
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) {
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let buy_hold = last_price / first_price;
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let strat_return = final_equity - 1.0;
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let bh_return = buy_hold - 1.0;
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let mut wins = 0usize;
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let mut losses = 0usize;
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let mut best = f64::NEG_INFINITY;
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let mut worst = f64::INFINITY;
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let mut sum_ret = 0.0_f64;
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let mut sum_sq = 0.0_f64;
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for &r in closed_trades {
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if r > 0.0 {
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wins += 1;
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} else if r < 0.0 {
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losses += 1;
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}
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best = best.max(r);
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worst = worst.min(r);
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sum_ret += r;
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sum_sq += r * r;
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}
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let n = closed_trades.len() as f64;
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let mean_ret = if n > 0.0 { sum_ret / n } else { 0.0 };
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let var_ret = if n > 1.0 {
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(sum_sq - n * mean_ret * mean_ret) / (n - 1.0)
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} else {
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0.0
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};
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let sharpe = if var_ret > 0.0 {
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mean_ret / var_ret.sqrt()
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} else {
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0.0
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};
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let mut peak = equity_curve.first().copied().unwrap_or(1.0);
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let mut max_dd = 0.0_f64;
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for &eq in equity_curve {
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peak = peak.max(eq);
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let dd = (peak - eq) / peak;
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if dd > max_dd {
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max_dd = dd;
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}
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}
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println!("=== {name} ===");
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println!("Bars: {bars}");
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println!(
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"Trades: {} (W{wins} / L{losses})",
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closed_trades.len()
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);
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println!("Strategy return: {:+.2}%", strat_return * 100.0);
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println!("Buy & Hold return: {:+.2}%", bh_return * 100.0);
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println!(
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"Excess over BH: {:+.2}%",
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(strat_return - bh_return) * 100.0
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);
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println!("Max drawdown: {:.2}%", max_dd * 100.0);
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println!(
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"Per-trade Sharpe: {sharpe:.2} (mean {:+.4}, stddev {:.4})",
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mean_ret,
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var_ret.sqrt()
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);
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println!(
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"Best / worst trade: {:+.2}% / {:+.2}%",
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best * 100.0,
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worst * 100.0
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);
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println!();
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println!(
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"NOTE: Educational example — fees, slippage, funding costs and tax effects \
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are simplified or omitted. Past performance is not indicative of future results."
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);
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}
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@@ -0,0 +1,183 @@
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//! Strategy example: MACD crossover with ADX trend-strength filter.
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//!
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//! Long-only trend follower. Entries fire on a MACD-line-crosses-above-
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//! signal-line event while ADX(14) > 20 (i.e. a market with at least mild
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//! directional strength). Exits on the opposite MACD crossover regardless
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//! of ADX. 0.1% fees per trade.
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//!
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//! The ADX filter is the whole point of the strategy: pure MACD on
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//! sideways markets chops in and out; gating entries on directional-
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//! strength cuts the worst losing streak.
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//!
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//! Educational example. **Not** a live trading recommendation.
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//!
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//! Build with:
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//! ```text
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//! cargo run --release -p wickra-examples --bin strategy_macd_adx
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//! ```
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//!
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//! Uses the checked-in `examples/data/btcusdt-1h.csv` dataset.
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use wickra::{Adx, Indicator, MacdIndicator};
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use wickra_data::csv::CandleReader;
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const FEE: f64 = 0.001;
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const ADX_FLOOR: f64 = 20.0;
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fn main() -> Result<(), Box<dyn std::error::Error>> {
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let path = concat!(env!("CARGO_MANIFEST_DIR"), "/../data/btcusdt-1h.csv");
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let mut reader = CandleReader::open(path)?;
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let candles = reader.read_all()?;
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if candles.is_empty() {
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return Err("CSV is empty".into());
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}
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let mut macd = MacdIndicator::classic();
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let mut adx = Adx::new(14)?;
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let mut in_position = false;
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let mut entry_price = 0.0_f64;
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let mut closed_trades: Vec<f64> = Vec::new();
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let mut equity = 1.0_f64;
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let mut equity_curve: Vec<f64> = Vec::with_capacity(candles.len());
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// Track the previous histogram sign to detect MACD-line crossovers.
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let mut prev_hist_sign: Option<bool> = None;
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for candle in &candles {
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let macd_out = macd.update(candle.close);
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let adx_out = adx.update(*candle);
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let price = candle.close;
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let mtm_equity = if in_position {
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equity * (price / entry_price)
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} else {
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equity
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};
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equity_curve.push(mtm_equity);
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let Some(m) = macd_out else { continue };
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let Some(a) = adx_out else { continue };
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let hist_sign = m.histogram > 0.0;
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let cross_up = prev_hist_sign == Some(false) && hist_sign;
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let cross_down = prev_hist_sign == Some(true) && !hist_sign;
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prev_hist_sign = Some(hist_sign);
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if !in_position && cross_up && a.adx > ADX_FLOOR {
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// Enter long: directional regime with positive momentum.
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entry_price = price;
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equity *= 1.0 - FEE;
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in_position = true;
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} else if in_position && cross_down {
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// Exit on opposite cross — ADX gating only the entries
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// keeps us from being trapped in a long trade as a trend dies.
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let trade_ret = price / entry_price - 1.0;
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closed_trades.push(trade_ret);
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equity *= (1.0 + trade_ret) * (1.0 - FEE);
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in_position = false;
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}
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}
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if in_position {
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let last_price = candles.last().expect("non-empty above").close;
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let trade_ret = last_price / entry_price - 1.0;
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closed_trades.push(trade_ret);
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equity *= (1.0 + trade_ret) * (1.0 - FEE);
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}
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print_summary(
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"MACD + ADX Trend Filter (1h, BTCUSDT)",
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candles.first().unwrap().close,
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candles.last().unwrap().close,
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candles.len(),
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&closed_trades,
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equity,
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&equity_curve,
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);
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Ok(())
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}
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fn print_summary(
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name: &str,
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first_price: f64,
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last_price: f64,
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bars: usize,
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closed_trades: &[f64],
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final_equity: f64,
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equity_curve: &[f64],
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) {
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let buy_hold = last_price / first_price;
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let strat_return = final_equity - 1.0;
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let bh_return = buy_hold - 1.0;
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let mut wins = 0usize;
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let mut losses = 0usize;
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let mut best = f64::NEG_INFINITY;
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let mut worst = f64::INFINITY;
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let mut sum_ret = 0.0_f64;
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let mut sum_sq = 0.0_f64;
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for &r in closed_trades {
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if r > 0.0 {
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wins += 1;
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} else if r < 0.0 {
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losses += 1;
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}
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best = best.max(r);
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worst = worst.min(r);
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sum_ret += r;
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sum_sq += r * r;
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}
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let n = closed_trades.len() as f64;
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let mean_ret = if n > 0.0 { sum_ret / n } else { 0.0 };
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let var_ret = if n > 1.0 {
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(sum_sq - n * mean_ret * mean_ret) / (n - 1.0)
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} else {
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0.0
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};
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let sharpe = if var_ret > 0.0 {
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mean_ret / var_ret.sqrt()
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} else {
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0.0
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};
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let mut peak = equity_curve.first().copied().unwrap_or(1.0);
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let mut max_dd = 0.0_f64;
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for &eq in equity_curve {
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peak = peak.max(eq);
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let dd = (peak - eq) / peak;
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if dd > max_dd {
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max_dd = dd;
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}
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}
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println!("=== {name} ===");
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println!("Bars: {bars}");
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println!(
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"Trades: {} (W{wins} / L{losses})",
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closed_trades.len()
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);
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println!("Strategy return: {:+.2}%", strat_return * 100.0);
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println!("Buy & Hold return: {:+.2}%", bh_return * 100.0);
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println!(
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"Excess over BH: {:+.2}%",
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(strat_return - bh_return) * 100.0
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);
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println!("Max drawdown: {:.2}%", max_dd * 100.0);
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println!(
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"Per-trade Sharpe: {sharpe:.2} (mean {:+.4}, stddev {:.4})",
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mean_ret,
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var_ret.sqrt()
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);
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println!(
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"Best / worst trade: {:+.2}% / {:+.2}%",
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best * 100.0,
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worst * 100.0
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);
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println!();
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println!(
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"NOTE: Educational example — fees, slippage, funding costs and tax effects \
|
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are simplified or omitted. Past performance is not indicative of future results."
|
||||
);
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||||
}
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@@ -0,0 +1,180 @@
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//! Strategy example: RSI mean-reversion on hourly BTCUSDT data.
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//!
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//! Goes long when RSI(14) crosses below 30 (oversold), exits when RSI
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//! crosses above 70 (overbought). Position is binary (full-in / full-out),
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//! fees are 0.1% per trade (Binance maker tier), no stop-loss.
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//!
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//! Educational example. **Not** a recommended trading strategy in real
|
||||
//! markets — mean reversion on BTC has been historically losing over long
|
||||
//! horizons. The point is to show how Wickra streaming indicators wire up
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//! into a complete signal → fill → `PnL` → equity loop in a single file.
|
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//!
|
||||
//! Build with:
|
||||
//! ```text
|
||||
//! cargo run --release -p wickra-examples --bin strategy_rsi_mean_reversion
|
||||
//! ```
|
||||
//!
|
||||
//! Uses the checked-in `examples/data/btcusdt-1h.csv` dataset.
|
||||
|
||||
use wickra::{Indicator, Rsi};
|
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use wickra_data::csv::CandleReader;
|
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|
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const FEE: f64 = 0.001; // 0.1% per trade (Binance maker)
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const RSI_PERIOD: usize = 14;
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const OVERSOLD: f64 = 30.0;
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const OVERBOUGHT: f64 = 70.0;
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||||
fn main() -> Result<(), Box<dyn std::error::Error>> {
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let path = concat!(env!("CARGO_MANIFEST_DIR"), "/../data/btcusdt-1h.csv");
|
||||
let mut reader = CandleReader::open(path)?;
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let candles = reader.read_all()?;
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||||
if candles.len() < RSI_PERIOD * 4 {
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return Err(format!("dataset too small: {}", candles.len()).into());
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||||
}
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||||
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||||
let mut rsi = Rsi::new(RSI_PERIOD)?;
|
||||
|
||||
// Walk through bars, generate signals, track an equity curve.
|
||||
let mut in_position = false;
|
||||
let mut entry_price = 0.0_f64;
|
||||
let mut closed_trades: Vec<f64> = Vec::new(); // per-trade returns
|
||||
let mut equity = 1.0_f64;
|
||||
let mut equity_curve: Vec<f64> = Vec::with_capacity(candles.len());
|
||||
|
||||
for candle in &candles {
|
||||
let rsi_val = rsi.update(candle.close);
|
||||
let price = candle.close;
|
||||
|
||||
// Mark-to-market the open position so the equity curve moves
|
||||
// bar-by-bar even between trades.
|
||||
let mtm_equity = if in_position {
|
||||
equity * (price / entry_price)
|
||||
} else {
|
||||
equity
|
||||
};
|
||||
equity_curve.push(mtm_equity);
|
||||
|
||||
let Some(r) = rsi_val else { continue };
|
||||
|
||||
if !in_position && r < OVERSOLD {
|
||||
// Enter long. Pay entry fee out of equity.
|
||||
entry_price = price;
|
||||
equity *= 1.0 - FEE;
|
||||
in_position = true;
|
||||
} else if in_position && r > OVERBOUGHT {
|
||||
// Exit long. Realise trade PnL, pay exit fee.
|
||||
let trade_ret = price / entry_price - 1.0;
|
||||
closed_trades.push(trade_ret);
|
||||
equity *= (1.0 + trade_ret) * (1.0 - FEE);
|
||||
in_position = false;
|
||||
}
|
||||
}
|
||||
|
||||
// If we ended a still open trade, mark it closed at the last bar so
|
||||
// metrics don't omit a half-trade.
|
||||
if in_position {
|
||||
let last_price = candles.last().expect("non-empty by guard above").close;
|
||||
let trade_ret = last_price / entry_price - 1.0;
|
||||
closed_trades.push(trade_ret);
|
||||
equity *= (1.0 + trade_ret) * (1.0 - FEE);
|
||||
}
|
||||
|
||||
print_summary(
|
||||
"RSI Mean-Reversion (1h, BTCUSDT)",
|
||||
candles.first().unwrap().close,
|
||||
candles.last().unwrap().close,
|
||||
candles.len(),
|
||||
&closed_trades,
|
||||
equity,
|
||||
&equity_curve,
|
||||
);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// Print a one-screen summary of an equity-curve plus per-trade list.
|
||||
/// Kept inline (not factored out) so each strategy example stays a
|
||||
/// single-file read.
|
||||
fn print_summary(
|
||||
name: &str,
|
||||
first_price: f64,
|
||||
last_price: f64,
|
||||
bars: usize,
|
||||
closed_trades: &[f64],
|
||||
final_equity: f64,
|
||||
equity_curve: &[f64],
|
||||
) {
|
||||
let buy_hold = last_price / first_price;
|
||||
let strat_return = final_equity - 1.0;
|
||||
let bh_return = buy_hold - 1.0;
|
||||
|
||||
let mut wins = 0usize;
|
||||
let mut losses = 0usize;
|
||||
let mut best = f64::NEG_INFINITY;
|
||||
let mut worst = f64::INFINITY;
|
||||
let mut sum_ret = 0.0_f64;
|
||||
let mut sum_sq = 0.0_f64;
|
||||
for &r in closed_trades {
|
||||
if r > 0.0 {
|
||||
wins += 1;
|
||||
} else if r < 0.0 {
|
||||
losses += 1;
|
||||
}
|
||||
best = best.max(r);
|
||||
worst = worst.min(r);
|
||||
sum_ret += r;
|
||||
sum_sq += r * r;
|
||||
}
|
||||
let n = closed_trades.len() as f64;
|
||||
let mean_ret = if n > 0.0 { sum_ret / n } else { 0.0 };
|
||||
let var_ret = if n > 1.0 {
|
||||
(sum_sq - n * mean_ret * mean_ret) / (n - 1.0)
|
||||
} else {
|
||||
0.0
|
||||
};
|
||||
let sharpe = if var_ret > 0.0 {
|
||||
mean_ret / var_ret.sqrt()
|
||||
} else {
|
||||
0.0
|
||||
};
|
||||
|
||||
// Max-drawdown on the equity curve.
|
||||
let mut peak = equity_curve.first().copied().unwrap_or(1.0);
|
||||
let mut max_dd = 0.0_f64;
|
||||
for &eq in equity_curve {
|
||||
peak = peak.max(eq);
|
||||
let dd = (peak - eq) / peak;
|
||||
if dd > max_dd {
|
||||
max_dd = dd;
|
||||
}
|
||||
}
|
||||
|
||||
println!("=== {name} ===");
|
||||
println!("Bars: {bars}");
|
||||
println!(
|
||||
"Trades: {} (W{wins} / L{losses})",
|
||||
closed_trades.len()
|
||||
);
|
||||
println!("Strategy return: {:+.2}%", strat_return * 100.0);
|
||||
println!("Buy & Hold return: {:+.2}%", bh_return * 100.0);
|
||||
println!(
|
||||
"Excess over BH: {:+.2}%",
|
||||
(strat_return - bh_return) * 100.0
|
||||
);
|
||||
println!("Max drawdown: {:.2}%", max_dd * 100.0);
|
||||
println!(
|
||||
"Per-trade Sharpe: {sharpe:.2} (mean {:+.4}, stddev {:.4})",
|
||||
mean_ret,
|
||||
var_ret.sqrt()
|
||||
);
|
||||
println!(
|
||||
"Best / worst trade: {:+.2}% / {:+.2}%",
|
||||
best * 100.0,
|
||||
worst * 100.0
|
||||
);
|
||||
println!();
|
||||
println!(
|
||||
"NOTE: Educational example — fees, slippage, funding costs and tax effects \
|
||||
are simplified or omitted. Past performance is not indicative of future results."
|
||||
);
|
||||
}
|
||||
Reference in New Issue
Block a user