MATLAB Multi-Factor Stock Selection Model

The MATLAB multi-factor stock selection model is a quantitative investment approach that computes composite scores for individual stocks and divides them into n discrete intervals for portfolio construction. This model incorporates multiple factors in its calculation, including but not limited to financial ratios (e.g., P/E ratio, ROE), market performance metrics (e.g., momentum, volatility), and industry outlook indicators. Implementation typically involves normalizing factor values using z-score standardization or percentile ranking, then applying weighted combinations through functions like 'zscore' and 'wmean'. The scoring algorithm can be programmed to assign weights based on historical performance correlation analysis. Stocks are then partitioned into quantiles using MATLAB's 'quantile' or 'discretize' functions, where top-ranked buckets represent primary investment targets. This methodology enables systematic market analysis through objective quantification, facilitating investments in high-potential securities. The model supports portfolio optimization by allowing score-based position sizing and rebalancing strategies, thereby enhancing risk management through diversification and potential return maximization via concentrated exposure to high-scoring stocks. Investors can utilize this framework to conduct rigorous portfolio diagnostics and make data-driven investment decisions, with capabilities for backtesting performance using MATLAB's Financial Toolbox functions like 'backtest' and 'portfolio'.