Conditional Value at Risk Portfolio Optimization With Macroeconomic Factor Models

The objective of this paper is to study the possibility of applying factor models with macro variables to optimize the equity portfolio of the main selected capital markets (US, UK, Germany). In comparison with traditional optimization methods and basic factor models. To find the macro variables that affect the selected equity universe, I settled on the factors from Axioma Worldwide Macroeconomic Projection Equity Factor Risk Model (98 potential factors) using factor analysis to determine the leading 10 factors and solve the portfolio optimization problem by assessing the level of risk and return optimum Сonditional Sharpe ratio portfolio with minimization risk strategy to avoid tail risk. The research shows that a strategy with a macroeconomic factor model compared with the classic equity portfolio optimization in the 2021-2022 interval showed a lower Expected Shortfall (CVaR) risk value in 87.4% of cases and a higher expected return in 56.3% of cases. Based on the factorial model, testing the logic of the model on more factors (>50) and a longer time interval (>2 years) will improve the results of the optimization model. The paper's findings can interest portfolio optimization/risk analysis software development as an additional portfolio risk analysis and decomposition model.