Package com.quantfinlib.backtest

package com.quantfinlib.backtest

Bar-based backtesting. Backtester is the classic engine (fills at the close, intrabar gap-aware stops); ExecutionAwareBacktester upgrades signals to parent orders worked through a pluggable ExecutionModel (InstantExecution, SorExecution, IcebergExecution, LastLookExecution — FX last-look rejects on adverse hold-window moves) with multi-bar fills and one-call TCA per ParentOrder; ExecutionAlgoBacktester answers the execution desk's own question — which benchmark algorithm, at what cost — by replaying execution.BenchmarkExecutor over a session's bars and grading it TCA-style (shortfall vs arrival, slippage vs session VWAP), with its simplifications stated in the javadoc. BenchmarkComparison scores a strategy the way an allocator does — alpha, beta, tracking error, information ratio, up/down capture against a benchmark — and DrawdownAnalytics reports drawdown STRUCTURE (episode depth and duration, time under water), because the number that fires clients is how long the pain lasted, not just how deep it went. Sub-packages: strategies (built-ins), validation (walk-forward, purged K-fold, CSCV overfit probability, deflated Sharpe), portfolio (multi-asset), and tick (event-driven tick-level engine).

Related Packages

Package	Description
com.quantfinlib.backtest.portfolio	Multi-asset backtesting: PortfolioBacktester rebalances long/short weight targets from a PortfolioStrategy with commission and turnover tracking (input series must be index-aligned — see data.SeriesAligner), and in its survivorship-aware overload consumes a data.PointInTimeUniverse (delistings terminate at the delisting return, mergers convert at deal terms, index drops force sales) plus explicit ex-date cash dividends; CrossSectionalMomentum is the built-in point-in-time factor strategy (12-1 momentum ranked over the members alive at each rebalance); PositionSizing supplies Kelly, fixed-fractional risk, inverse-volatility weights and vol-target leverage.
com.quantfinlib.backtest.strategies	Built-in TradingStrategy implementations: SMA/EMA crossovers, RSI mean reversion, MACD signal-line cross, and Bollinger band reversion.
com.quantfinlib.backtest.tick	Event-driven tick-level backtesting — the level below bars, where queue position decides whether a passive order actually trades: TickBacktester replays QFLT tick files through a TickStrategy with microstructure-aware fills (market orders pay half the spread; limit orders fill on trade-through or earn fills print-by-print against a simulated queue; optional tick-size grid for real-world prices; no fills against the triggering print).
com.quantfinlib.backtest.validation	The defense against overfit backtests: ParameterGrid + GridSearchOptimizer enumerate and rank parameter combinations; WalkForwardAnalyzer optimizes on rolling train windows and evaluates on unseen test windows, stitching out-of-sample equity (capital carries across folds) and reporting the walk-forward efficiency ratio; SharpeValidation applies the Bailey/López de Prado probabilistic and deflated Sharpe — the multiple-testing haircut for grid-picked winners — plus the minimum track record length (how many periods before the record MEANS something, in closed form); BlockBootstrap hands the backtest Sharpe its sampling DISTRIBUTION (stationary Politis-Romano blocks — an iid resample destroys the autocorrelation and understates the uncertainty, the classic route to false confidence): the honest question is whether the 5th percentile is still positive, not whether 1.2 is a good number.

Class	Description
BacktestConfig	Backtest execution parameters.
Backtester	Event-driven, single-instrument, long-only backtesting engine.
BacktestResult	Result of a backtest run: full equity curve (one point per bar), completed trade history, and derived performance metrics.
BenchmarkComparison	BENCHMARK-RELATIVE performance — the numbers an allocator actually asks for.
BenchmarkComparison.Result
DrawdownAnalytics	DRAWDOWN structure — because "max drawdown 18%" hides the number that actually fires clients: how LONG the pain lasted.
DrawdownAnalytics.Drawdown	One peak-to-recovery episode.
DrawdownAnalytics.Result
ExecutionAlgoBacktester	Backtests the DYNAMIC execution stack over bar data — the bridge between execution.BenchmarkExecutor (built for live intervals) and the backtest lane: replay a session's bars, let the executor re-decide each bar exactly as it would live, fill against the bar with a TradeCostModel, and grade the result the way a TCA desk would (implementation shortfall vs arrival, slippage vs the session VWAP).
ExecutionAlgoBacktester.Config
ExecutionAlgoBacktester.Result	The TCA-style verdict for one parent worked over one session.
ExecutionAwareBacktester	Execution-aware backtesting engine: strategy signals create parent orders that are worked through an ExecutionModel — routed by SorExecution, sliced by IcebergExecution, or filled instantly by InstantExecution.
ExecutionAwareResult	Result of an execution-aware backtest: the standard BacktestResult (equity curve, trades, performance metrics) plus the full parent-order / child-fill history, with one-call TCA per parent order.
ExecutionModel	How parent orders turn into fills in an execution-aware backtest (ExecutionAwareBacktester).
IcebergExecution	Iceberg execution: wraps another ExecutionModel and caps each bar's execution at the IcebergOrder state machine's visible tranche (optionally randomized), plus an optional participation cap versus the bar's volume.
InstantExecution	Baseline execution model: the full quantity fills at the bar close with commission and slippage folded into the all-in price — equivalent to the classic Backtester fill assumption.
LastLookExecution	Last-look execution model — the missing realism for FX backtests: on ECN and single-dealer FX liquidity, the provider holds your order briefly and may reject it if the price moves against them during the hold.
ParentOrder	One parent order worked by the ExecutionAwareBacktester: the signal that created it, the arrival price (close at signal time — the TCA benchmark), and the child fills with the bar index each filled on.
PerformanceAnalytics	Computes PerformanceMetrics from an equity curve and trade history.
PerformanceMetrics	Strategy performance analytics.
Signal	Trading signal emitted by a strategy for a single bar.
SorExecution	Smart-order-routed execution over a synthetic fragmented market.
SorExecution.VenueConfig
Trade	A completed round-trip trade.
TradeAnalytics	TRADE-LEVEL analytics — the numbers a discretionary reviewer asks for that a Sharpe ratio hides.
TradeAnalytics.Result
TradeCostModel	A pluggable per-trade cost model — the ONE definition of "what a trade costs" shared by the backtest engines, so an execution-aware number and a survivorship-aware number can come out of the same run: TradeCostModel.flat(double) — a fixed all-in bps (the classic commission assumption, and the exact equivalent of the legacy commissionRate configs); TradeCostModel.institutional(double, double, double, int) — commission + half-spread + slippage + square-root market impact, with per-symbol ADV/vol estimated from the trailing bars via MarketImpactModel.estimate(com.quantfinlib.core.BarSeries, int, int).
TradingStrategy	A bar-driven trading strategy.