Portfolio Optimization

Portfolio optimization is the process of converting stock signals into actual portfolio weights while balancing expected returns and risk. This is typically done using mathematical techniques such as mean-variance optimization. Optimization considers constraints like position limits, sector caps, liquidity requirements, and target volatility. These rules ensure portfolios remain diversified and practical to execute. Rather than simply holding top-ranked stocks equally, optimization allocates capital based on risk contributions and correlations. This helps avoid excessive concentration and unintended exposures. Modern quant frameworks also incorporate transaction costs and turnover penalties into optimization to reduce trading impact. Portfolio optimization plays a critical role in translating theoretical signals into investable strategies. Poor optimization can negate the benefits of strong alpha signals. Effective optimization seeks a balance between return potential, risk control, and implementation efficiency.