Strategy Backtesting
Data Replay
Replays historical tick and order book data in original timestamp order to faithfully recreate the live market environment. Replayed data is injected into stream tables, allowing backtesting frameworks and strategy platforms to operate as if connected to a live feed. Supports single table (1-to-1), and multi-table (N-to-N, N-to-1) replay modes at real-time or accelerated speed.
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Mid-to-High Frequency Backtesting Framework
An integrated event-driven engine combining data replay, simulated matching, and backtesting in one. Historical data streams simultaneously to the matching engine and strategy callbacks — strategies generate signals, the engine enforces risk checks, and approved orders flow into the matching engine for execution simulation, with account state updated in real time.
Built on a C++ core and covering equities, options, futures, interbank bonds, and digital assets, DolphinDB delivers up to tens of times the performance of Python-based frameworks like Backtrader and MetaTrader4 at full-market, mid-to-high frequency scale.
Featured Tutorials & Best Practices:
- Quick Start with DolphinDB Backtesting
- Performance and Feature Comparison of DolphinDB Backtesting Framework and Other Backtesting Products
Order Matching Simulation
DolphinDB's Matching Engine Simulator accurately simulates real-market order execution — accepting live snapshot or tick data and strategy orders (limit, market, cancellations), building a virtual order book on price-time priority, and dynamically computing fill price, quantity, and timestamp for each order.
Configurable latency and fill ratio parameters support evaluation across different market conditions. Multiple matching algorithms are available, from proportional fills based on last price and best quote, to execution simulation layered with order book depth and interval trade details.
The result: a more accurate bridge between idealized backtest returns and real-world achievable performance — with precise quantification of slippage, liquidity constraints, and market impact.
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Margin Financing & Securities Lending Backtesting
Native support for A-share margin financing and securities lending enables unified modeling of margin purchases, short selling, collateral trades, and ordinary trades within a single framework. Configurable financing rates, lending fees, credit limits, and conversion ratios accurately reflect real costs and trading constraints, closing the gap between spot backtests and leveraged live trading.
Built-in maintenance margin, concentration, and net short liability controls enable quantitative assessment of forced liquidation risk under extreme conditions — giving hedge funds a more reliable risk-return profile for long-short, hedging, and enhanced return strategies.
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Crypto Backtesting
A dedicated engine for 24/7 crypto markets — spot, delivery futures, perpetual contracts, and options in one framework, with multi-account support across snapshot, minute-level, and daily data. Per-exchange modeling of fees, margin rules, and funding rates, with configurable matching modes and latency for realistic return evaluation across varying market conditions.
Cross-Asset & Multi-Account Backtesting
One engine for equities, futures, options, crypto, and interbank bonds — with unified management of capital, margin, transaction costs, and risk constraints across all asset classes. Built to replicate the complexity of real-world multi-asset, multi-strategy, multi-account operations.
Flexible multi-account and portfolio-level views let you simulate a single strategy split across accounts, or evaluate how multiple strategies interact at the portfolio level — across returns, volatility, drawdown, and risk contribution. Covers asset allocation, index enhancement, long-short neutral, options hedging, spot-futures arbitrage, and more.
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