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hilothefunnydog123-coder/quant-research
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Help me design a quantitative trading experiment that follows the Martingale methodology: pre-state a hypothesis, use only past data, reserve untouched data, count strategies tried, charge realistic costs, and be reproducible from one script.
I want to submit a strategy to the Out-of-Sample Registry. Help me write the code to lock in my trading rules today so they can only be evaluated on future price data, one day at a time, with no peeking ahead.
Explain the concept of lookahead bias using the example from Martingale Note 001, where a single line of lookahead code inflates performance numbers. Then show me how to make sure my Python backtest avoids this mistake.
Using the findings from Martingale Note 003, help me understand why neither momentum nor mean reversion beats buy-and-hold after costs, and write a Python script that compares all three approaches on S&P 500 data.
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