Aplikovaná finanční optimalizace

Abstract

This thesis examines the application of two optimization models, namely the Markowitz Mean-Variance Model and Two-Stage Stochastic Programming in optimizing commodity investments with a specific case study of Ghana. To maximize expected return while minimizing risk, we used export and import data from the Bank of Ghana (BOG) and commodity price data from the International Monetary Fund (IMF). While the Two-Stage Stochastic model uses time series data to account for future uncertainties, the Markowitz Mean-Variance model balances the trade-off between expected return and risk by using covariance and the efficient frontier in its analysis. The General Algebraic Modelling System (GAMS) software is used to implement the optimization models, and their results are then compared.This thesis examines the application of two optimization models, namely the Markowitz Mean-Variance Model and Two-Stage Stochastic Programming in optimizing commodity investments with a specific case study of Ghana. To maximize expected return while minimizing risk, we used export and import data from the Bank of Ghana (BOG) and commodity price data from the International Monetary Fund (IMF). While the Two-Stage Stochastic model uses time series data to account for future uncertainties, the Markowitz Mean-Variance model balances the trade-off between expected return and risk by using covariance and the efficient frontier in its analysis. The General Algebraic Modelling System (GAMS) software is used to implement the optimization models, and their results are then compared.