Module backtesting 

Backtesting engine for trading strategy simulation.

This module provides a complete backtesting framework with:

• Expression-based strategy builder for custom entry/exit conditions
• Pre-built strategies (SMA, RSI, MACD, Bollinger, SuperTrend, Donchian)
• Full technical indicator coverage (40+ indicators)
• Position tracking with long/short support
• Stop-loss, take-profit, and trailing stop management
• Comprehensive performance metrics

Quick Start

use finance_query::{Ticker, Interval, TimeRange};
use finance_query::backtesting::{SmaCrossover, BacktestConfig};

let ticker = Ticker::new("AAPL").await?;
let result = ticker.backtest(
    SmaCrossover::new(10, 20),
    Interval::OneDay,
    TimeRange::OneYear,
    None,
).await?;

println!("Return: {:.2}%", result.metrics.total_return_pct);
println!("Sharpe: {:.2}", result.metrics.sharpe_ratio);
println!("Max Drawdown: {:.2}%", result.metrics.max_drawdown_pct * 100.0);

Custom Strategies with StrategyBuilder

Build custom strategies using the fluent builder API:

use finance_query::backtesting::StrategyBuilder;
use finance_query::backtesting::refs::*;
use finance_query::backtesting::condition::*;

let strategy = StrategyBuilder::new("RSI Mean Reversion")
    .entry(
        rsi(14).crosses_below(30.0)
            .and(price().above_ref(sma(200)))
    )
    .exit(
        rsi(14).crosses_above(70.0)
            .or(stop_loss(0.05))
    )
    .build();

Configuration

use finance_query::backtesting::BacktestConfig;

let config = BacktestConfig::builder()
    .initial_capital(50_000.0)
    .commission_pct(0.001)      // 0.1% per trade
    .slippage_pct(0.0005)       // 0.05% slippage
    .stop_loss_pct(0.05)        // 5% stop-loss
    .take_profit_pct(0.15)      // 15% take-profit
    .allow_short(true)
    .build()
    .unwrap();

Pre-built Strategies

Strategy	Parameters	Description
SmaCrossover	fast, slow periods	Dual SMA crossover
RsiReversal	period, oversold, overbought	Mean reversion on RSI
MacdSignal	fast, slow, signal periods	MACD line crossover
BollingerMeanReversion	period, std_dev	Buy at lower band
SuperTrendFollow	period, multiplier	Trend following
DonchianBreakout	period	Channel breakout

Available Indicators

The strategy builder supports all indicators via refs:

• Moving Averages: sma, ema, wma, dema, tema, hma, vwma, alma, mcginley
• Oscillators: rsi, stochastic, stochastic_rsi, cci, williams_r, cmo, awesome_oscillator
• Trend: macd, adx, aroon, supertrend, ichimoku, parabolic_sar
• Volatility: atr, bollinger, keltner, donchian, choppiness_index
• Volume: obv, vwap, mfi, cmf, chaikin_oscillator, accumulation_distribution, balance_of_power

Available Conditions

Build conditions via condition:

• Comparisons: above(), below(), crosses_above(), crosses_below(), between(), equals()
• Composites: and(), or(), not()
• Position Management: stop_loss(), take_profit(), trailing_stop(), trailing_take_profit()
• Position State: has_position(), no_position(), is_long(), is_short(), in_profit(), in_loss()

Re-exports

pub use strategy::Strategy;

pub use strategy::StrategyContext;

pub use strategy::StrategyBuilder;

pub use strategy::BollingerMeanReversion;

pub use strategy::DonchianBreakout;

pub use strategy::MacdSignal;

pub use strategy::RsiReversal;

pub use strategy::SmaCrossover;

pub use strategy::SuperTrendFollow;

pub use strategy::EnsembleMode;

pub use strategy::EnsembleStrategy;

pub use optimizer::BayesianSearch;

pub use optimizer::GridSearch;

pub use optimizer::OptimizationReport;

pub use optimizer::OptimizationResult;

pub use optimizer::OptimizeMetric;

pub use optimizer::ParamRange;

pub use optimizer::ParamValue;

pub use walk_forward::WalkForwardConfig;

pub use walk_forward::WalkForwardReport;

pub use walk_forward::WindowResult;

pub use monte_carlo::MonteCarloConfig;

pub use monte_carlo::MonteCarloMethod;

pub use monte_carlo::MonteCarloResult;

pub use monte_carlo::PercentileStats;

pub use comparison::BacktestComparison;

pub use comparison::ComparisonReport;

pub use comparison::ComparisonRow;

pub use resample::resample;

Modules

comparison

Side-by-side comparison of multiple backtest results.

condition

Condition system for building strategy entry/exit rules.

monte_carlo

Monte Carlo simulation for backtesting results.

optimizer

Parameter optimisation for backtesting strategies.

portfolio

Multi-symbol portfolio backtesting.

refs

Indicator reference system for building strategy conditions.

resample

Higher-timeframe candle resampling.

strategy

Strategy trait and context for building trading strategies.

walk_forward

Walk-forward parameter optimisation for backtesting strategies.

Structs

BacktestConfig

Configuration for backtest execution.

BacktestConfigBuilder

Builder for BacktestConfig

BacktestEngine

Backtest execution engine.

BacktestResult

Complete backtest result

BenchmarkMetrics

Comparison of strategy performance against a benchmark.

EquityPoint

Point on the equity curve

PendingOrder

A queued limit or stop entry order awaiting price-level execution.

PerformanceMetrics

Performance metrics summary

Position

An open position

Signal

A trading signal generated by a strategy

SignalMetadata

Metadata attached to signals for analysis

SignalRecord

Record of a generated signal (for analysis)

SignalStrength

Signal strength/confidence (0.0 to 1.0)

Trade

A completed trade (closed position)

Enums

BacktestError

Backtest-specific errors

OrderType

Order type controlling how a signal’s entry is executed.

PositionSide

Position direction

SignalDirection

Trading signal direction

Type Aliases

Result

Result type for backtest operations