- Created data/examples/download_ml_training_data.rs using reqwest + Databento HTTP API - Downloaded 90 days × 4 symbols (ES.FUT, NQ.FUT, ZN.FUT, 6E.FUT) - Files saved to test_data/real/databento/ml_training/ - Total: 360 files, 15 MB compressed DBN format - Used existing Rust pattern from download_nq_fut.rs - API key loaded from .env file - 100% success rate (360/360 files) - Ready for ML training benchmarks Next: Create simplified training benchmark for RTX 3050 Ti GPU measurements
155 lines
4.8 KiB
Rust
155 lines
4.8 KiB
Rust
//! DBN Backtesting Integration Example
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//!
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//! This example demonstrates using DBN data with the backtesting service's
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//! MarketDataRepository interface.
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//!
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//! ## Usage
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//!
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//! ```bash
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//! cargo run --example dbn_backtesting_integration
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//! ```
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use backtesting_service::{
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dbn_repository::DbnMarketDataRepository,
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repositories::MarketDataRepository,
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};
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use chrono::{TimeZone, Utc};
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use std::collections::HashMap;
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#[tokio::main]
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async fn main() -> anyhow::Result<()> {
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println!("=== DBN Backtesting Integration Example ===\n");
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// 1. Setup repository with DBN data
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let mut file_mapping = HashMap::new();
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file_mapping.insert(
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"ES.FUT".to_string(),
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"test_data/real/databento/ES.FUT_ohlcv-1m_2024-01-02.dbn".to_string(),
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);
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println!("Creating MarketDataRepository with DBN backend...");
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let repo = DbnMarketDataRepository::new(file_mapping).await?;
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println!("Available symbols: {:?}", repo.available_symbols());
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// 2. Define backtest time range
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let start_time = Utc
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.with_ymd_and_hms(2024, 1, 2, 14, 30, 0)
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.unwrap()
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.timestamp_nanos_opt()
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.unwrap();
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let end_time = Utc
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.with_ymd_and_hms(2024, 1, 2, 16, 0, 0)
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.unwrap()
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.timestamp_nanos_opt()
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.unwrap();
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println!(
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"\nBacktest window: {} to {}",
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Utc.timestamp_nanos(start_time).format("%Y-%m-%d %H:%M:%S"),
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Utc.timestamp_nanos(end_time).format("%Y-%m-%d %H:%M:%S")
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);
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// 3. Load historical data via repository interface
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let symbols = vec!["ES.FUT".to_string()];
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println!("\nLoading historical data for {:?}...", symbols);
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let data = repo.load_historical_data(&symbols, start_time, end_time).await?;
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println!("✅ Loaded {} bars via repository interface\n", data.len());
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// 4. Check data availability
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println!("=== Data Availability Check ===");
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let availability = repo
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.check_data_availability(&symbols, start_time, end_time)
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.await?;
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for (symbol, available) in availability.iter() {
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println!(
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"{}: {}",
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symbol,
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if *available { "✅ Available" } else { "❌ Not available" }
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);
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}
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// 5. Simulate simple backtest logic
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println!("\n=== Simulating Simple Backtest ===");
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let mut position = 0i32;
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let mut pnl = 0.0;
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let mut trades = 0;
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for (i, bar) in data.iter().enumerate() {
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let close_f64 = bar.close.to_string().parse::<f64>().unwrap();
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// Simple strategy: Buy when price drops, sell when price rises
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if i > 0 {
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let prev_close = data[i - 1].close.to_string().parse::<f64>().unwrap();
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let price_change = close_f64 - prev_close;
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if position == 0 && price_change < -1.0 {
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// Buy signal
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position = 1;
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pnl -= close_f64; // Entry cost
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trades += 1;
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println!(" [{}] BUY @ {:.2}", bar.timestamp.format("%H:%M"), close_f64);
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} else if position == 1 && price_change > 1.0 {
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// Sell signal
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position = 0;
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pnl += close_f64; // Exit proceeds
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trades += 1;
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println!(" [{}] SELL @ {:.2}", bar.timestamp.format("%H:%M"), close_f64);
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}
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}
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}
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// Close any open position
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if position != 0 {
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let last_close = data.last().unwrap().close.to_string().parse::<f64>().unwrap();
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pnl += last_close * position as f64;
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trades += 1;
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println!(
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" [{}] CLOSE @ {:.2}",
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data.last().unwrap().timestamp.format("%H:%M"),
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last_close
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);
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}
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println!("\n=== Backtest Results ===");
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println!("Total trades: {}", trades);
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println!("Final PnL: ${:.2}", pnl);
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// 6. Advanced repository features
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println!("\n=== Advanced Repository Features ===");
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// Load with volume filter
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let min_volume = rust_decimal::Decimal::from(50);
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let high_volume_bars = repo
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.load_with_volume_filter(&symbols, min_volume, start_time, end_time)
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.await?;
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println!(
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"High-volume bars (volume >= {}): {}",
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min_volume,
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high_volume_bars.len()
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);
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// Get date range
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let (first_ts, last_ts) = repo.get_date_range("ES.FUT").await?;
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println!("Data range: {} to {}", first_ts, last_ts);
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// Generate summary statistics
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let stats = repo.generate_summary_stats(&data);
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println!("\nSummary Statistics:");
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println!(" Count: {}", stats.get("count").unwrap());
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println!(" Mean close: ${:.2}", stats.get("mean_close").unwrap());
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println!(" Std close: ${:.2}", stats.get("std_close").unwrap());
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println!(" Min close: ${:.2}", stats.get("min_close").unwrap());
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println!(" Max close: ${:.2}", stats.get("max_close").unwrap());
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println!("\n✅ Example completed successfully!");
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Ok(())
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}
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