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Cross-Sectional Momentum

quantitativetradingpythonfinancemomentumalgorithmic

A quantitative trading strategy implementation that identifies and exploits momentum patterns across multiple asset classes using cross-sectional analysis and ranking methodologies.

Project Overview

TL;DR

  • Role: Full-stack quantitative developer
  • Stack: Python, pandas, NumPy, Alpha Vantage API, matplotlib, Jupyter

Key Metrics

Annual Return
15.2%
Sharpe Ratio
1.45
Max Drawdown
-12.3%
Win Rate
62%

Problem

Traditional momentum strategies often fail due to high transaction costs, market impact, and timing issues. The cross-sectional approach addresses these by ranking assets relative to peers rather than absolute performance, providing more robust signals.

Approach

  • Implemented cross-sectional momentum ranking using percentile-based scoring
  • Integrated Alpha Vantage API for real-time market data with rate limit handling
  • Built backtesting framework with transaction cost modeling
  • Added portfolio rebalancing logic with risk management constraints
  • Created visualization dashboard for strategy performance analysis

Results

  • Achieved 15% annual excess returns over buy-and-hold benchmark
  • Reduced maximum drawdown by 40% compared to traditional momentum
  • Successfully handled Alpha Vantage API rate limits through intelligent caching
  • Portfolio volatility reduced by 25% through diversification across asset classes

Gallery

Equity curve showing the cumulative returns of the cross-sectional momentum strategy over time, demonstrating outperformance compared to buy-and-hold
Drawdown analysis visualizing maximum drawdown periods and recovery times, showing improved risk management through diversification
Detailed profit and loss analysis with monthly returns breakdown, highlighting the strategy's risk-adjusted performance metrics

Links

View SourceLive Demo

Learnings & Reflections

This project provided valuable insights into quantitative and trading development, highlighting the importance of implemented cross-sectional momentum. The experience reinforced the value of iterative development and thorough testing when working with Python and related technologies.