Backtested Trading Data & Strategies
BacktestCart provides rules-based trading strategy research using historical market data, defined trading rules, trade results and performance metrics for U.S. stocks and ETFs.
This is more than historical price data. The research is designed around defined trading approaches so traders and researchers can study how specific rules performed during the tested historical period.
| # | Research Area | What You Can Explore |
|---|---|---|
| 01 | Backtested Trading Strategies | Explore historical results from defined rules-based trading strategies across supported assets and timeframes. |
| 02 | Trading Rules | Research entry conditions, exit conditions, stop-loss rules, trading timeframe and other defined strategy parameters. |
| 03 | Historical Backtest Results | Review available returns, drawdowns, number of trades, historical periods and other performance information. |
| 04 | U.S. Stocks & ETFs | Research backtested strategies and historical results for supported U.S. stocks and ETFs. |
Use the filters below to explore available backtested data, trading strategies, timeframes, historical periods and performance characteristics.
Backtested Data
Historical trading research for U.S. stocks and ETFs — structured for independent analysis.
How the Backtest Is Calculated
BacktestCart uses a consistent methodology so that historical trading strategies can be compared on a standardized basis. Each backtest applies defined trading rules to historical market data and reports the resulting trades and performance metrics.
| Methodology | BacktestCart Assumption | Typical Real-World Trading |
|---|---|---|
| Position Size | $100,000 fixed position | Depends on trader |
| Trading / Regulatory Costs | $9.00 per trade | Depends on broker and transaction |
| Execution Buffer | 0.10% entry/stop execution buffer | Depends on actual fill |
| Compounding | No | Depends on trader |
Trading-cost assumption: BacktestCart applies a standardized $9 trading cost per completed trade for research consistency. This is a methodology assumption used across the backtests and is not intended to represent the exact cost charged by any particular broker.
Backtested Trading Strategies
BacktestCart research covers rules-based trading strategies designed to be tested against historical U.S. stock and ETF price data. Depending on the dataset, strategies may focus on intraday trading, swing trading, scalping, trend-following, momentum, technical indicators, breakouts, reversals and other systematic trading approaches.
| Strategy Research | What Is Tested |
|---|---|
| Rules-Based Strategies | Clearly defined conditions for entering and exiting trades |
| Intraday Strategies | Entry and exit rules within the same trading session |
| Swing Trading Strategies | Multi-day and multi-week historical trade setups |
| Scalping Strategies | Short-duration trades based on defined market conditions |
| Technical Strategies | Indicators, price action, trend, momentum and volume conditions |
| Breakout & Reversal Strategies | Historical performance of predefined breakout or reversal setups |
What Is Included in the Backtest
| Component | Details |
|---|---|
| Trading Rules | Defined entry, exit and trade-management conditions |
| Historical Market Data | Historical price data used to evaluate the strategy |
| Entry Rules | Conditions required before a historical trade is initiated |
| Stop-Loss Rules | Defined risk-management or stop conditions where applicable |
| Exit Rules | Conditions used to close historical positions |
| Trade Results | Historical trade-by-trade outcomes generated by the rules |
| Performance Metrics | Returns, drawdowns, number of trades and other reported statistics |
| Timeframe & Period | The tested trading timeframe and historical period |
Key Backtest Metrics
| Metric | Purpose |
|---|---|
| Total Return | Measures the cumulative historical result of the tested strategy |
| Maximum Drawdown | Shows the largest historical decline experienced during the test |
| Number of Trades | Shows how many historical trades were generated |
| Winning & Losing Trades | Shows the distribution of historical trade outcomes |
| Trade-Level Results | Allows users to examine individual historical trades |
| Timeframe | Identifies the trading frequency used in the strategy |
Why Backtest a Trading Strategy?
Backtesting allows traders and researchers to examine how a defined set of trading rules would have behaved under historical market conditions. Instead of relying only on theoretical strategy descriptions, users can review actual historical trade outcomes and performance statistics generated by the tested rules.
Historical backtest results can be useful for comparing strategies, studying risk and drawdown, examining trade frequency, researching different timeframes and developing a more systematic approach to trading research.
U.S. Stocks & ETFs Trading Research
BacktestCart focuses on backtested trading strategy research for U.S. stocks and ETFs. The research is designed for traders, investors, analysts and researchers who want structured historical evidence when studying rules-based trading strategies.
How to Use Backtest Results
Backtest results should be treated as historical research rather than a prediction of future performance. Users can compare the trading rules, historical returns, drawdowns, trade counts and other available metrics before deciding whether a strategy is suitable for further research or live testing.
Disclaimer: Backtested results are based on historical data and defined assumptions. Historical performance does not guarantee future results. Actual trading costs, spreads, liquidity, slippage, execution prices and other market conditions may differ from the assumptions used in the backtest. BacktestCart provides research and educational information and does not provide investment advice.