Houssam Mrah

Developed a commodity price forecasting interface and portfolio optimisation tool. Applied econometric models (ARMA/ARIMA) to analyse and forecast commodity price movements; implemented an LSTM model for deep-learning forecasting; calculated VaR, CVaR, Sharpe, and Sortino ratios to measure and mitigate risk and performance.

Built sector-based equity portfolios using Python and Modern Portfolio Theory. Evaluated risk-return profiles and analysed performance to support 5-year investment decisions.

Analysed the evolution of the Consumer Price Index (CPI) and its impact on purchasing power and inflation expectations. Built a forecasting model in Excel to project future rates.

Solid grounding in financial concepts, mastery of financial products, valuation methods, and programming.

Analysis of equities listed on the Casablanca Stock Exchange to build an efficient and optimal portfolio using mean-variance optimisation.

Priced vanilla options using the binomial tree model, the Black-Scholes model, and Monte Carlo simulation.