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5 Things Paper Trading Taught Me That Backtesting Can't

5 Things Paper Trading Taught Me That Backtesting Can't

via Dev.to PythonRay

5 Things Paper Trading Taught Me That Backtesting Can't ==================================================== As a quant beginner, I've spent countless hours studying trading strategies and backtesting them using popular libraries like TradeSight. However, there's one aspect of trading that backtesting often falls short: the reality of slippage. Slippage Reality Slippage is the difference between the expected price of a trade and the actual price at which it executes. Backtesting can't account for this because it assumes perfect execution, but in reality, markets move and prices fluctuate. TradeSight's implementation of slippage modeling helps to bridge this gap. For instance, you can configure it to simulate different slippage scenarios using parameters like slippage_type and slippage_amount . By incorporating this feature into your backtesting workflow, you'll get a more accurate picture of your strategy's performance in the wild. Emotional Discipline Simulation Another critical aspec

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