Tag: Backtesting
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Trading Fees Kill 73% of Backtest Alpha: Real Slippage Data
Trading fees destroy most backtest profits. Learn how slippage models reveal the 3 hidden costs pros trackโand retail traders miss.
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Walk-Forward Optimization: When Retraining Loops Work
Learn walk-forward optimization techniques that prevent overfitting in trading systems. Build retraining loops that adapt to market regime changes.
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Walk-Forward Optimization: Avoiding Lookahead Bias in 3 Steps
Fix lookahead bias in your backtest: walk-forward optimization prevents curve-fitting by testing on unseen future data. Real code, real SPY results.
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Why Most Beginners Lose Money on Algo Trading (Try This)
Discover why algo trading fails for beginners and learn the proven strategy professional traders use to build profitable systems from day one.
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Backtest.py to Vectorbt: 3x Faster Parallel Strategies
Migrate from Backtest.py to Vectorbt for 3x faster parallel backtesting. Optimize multi-strategy portfolios with vectorized operations.
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QuantConnect vs Backtrader API: First Strategy in 45 Min
QuantConnect took 45 min to first working backtest, Backtrader 25 min. But setup time isn't the real cost โ here's where each API actually breaks.
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Backtrader Memory Leak on Multi-Year Tests: 3 Debug Fixes
Fix Backtrader memory leaks in long backtests with 3 proven solutions: cerebro tuning, data cleanup, and RAM monitoring to scale your strategy tests.
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Backtrader vs Zipline: 5-Year S&P 500 Speed & Memory Test
Compare Backtrader vs Zipline in our 5-year S&P 500 benchmark. See which Python backtesting framework wins on speed, memory usage, and efficiency.