Designed and backtested momentum-based trading strategies using long-horizon historical data. Evaluated performance using Sharpe ratio, drawdowns, turnover, and robustness checks under realistic assumptions.

Focus: Strategy research, backtesting, performance evaluation

Tools: Python, Pandas, Time-Series Analysis

Key Outcomes:

• Built signal-generation and backtesting frameworks from scratch
• Applied realistic evaluation metrics beyond headline returns
• Emphasized robustness and stability across market regimes

Links:

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