Developed Python-based pipelines to analyze equity market data, compute returns, volatility, drawdowns, and portfolio-level risk metrics. Built equity curves and risk dashboards to evaluate performance across assets and portfolios.

Focus: Market data analysis, PnL modeling, risk metrics

Tools: Python, Pandas, NumPy, Matplotlib, Yahoo Finance

Key Outcomes:

• Created reusable analytics pipelines for single-asset and portfolio-level evaluation
• Implemented industry-standard risk metrics (volatility, drawdowns, cumulative returns)
• Developed clean visual diagnostics for performance attribution

Links:

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