This project offers a robust, multi-dimensional framework for portfolio risk modeling and optimization using real market data. It combines classical volatility and market beta with a novel Filing Shock Factor (FSF), capturing stock sensitivity to SEC 10-Q filings. Each risk metric is normalized and blended into a tunable composite score, enabling flexible portfolio construction. Additional modules explore the (non)-normality in historical stock returns, sensitivity of call and put options to time and spot prices, and hedging using the Heston model. Using a Heston Delta over Black-Scholes shows improved performance in terms of expected returns.