Presenting a Capital Asset Pricing Model under Economic Uncertainty Using Multivariate Factor Models and Monte Carlo Simulation

Mohammad Astaraki¹ Mohammad mehrabioun²

1) PostDBA Student, Center for Open Specialized Education and Skill Development, Allameh Tabatabaei University, Tehran, Iran
2) Assistant Professor, Faculty of Management, Kharazmi University, Tehran, Iran

IOI Code : AAHD-ABKFKH
Publication : National Conference on Information Technology, Nanotechnology, Artificial Intelligence and Technological Futures Studies(itnaf.ir)
Abstract :
    Economic uncertainty has been raised as one of the most important challenges facing financial markets in the last decade. The present study aims to present a capital asset pricing model under economic uncertainty using multivariate factor models and Monte Carlo simulation. In this study, first, using the Bayesian Model Averaging (BMA) approach, the model uncertainty in the selection of pricing factors is examined, and then, using Monte Carlo simulation, the distribution of future returns under different scenarios of economic uncertainty is simulated. The proposed model combines the five-factor model of Fama and French, the economic policy uncertainty index (EPU) introduced by Baker et al., and the composite ambiguity index as pricing factors. The simulation results show that economic uncertainty significantly affects the correlation structure between factors and expected returns of assets, and the pricing pattern in periods of high uncertainty is fundamentally different from periods of economic stability. The proposed model is tested using US stock market data for the period 2015 to 2025, and the results indicate the superior performance of the proposed model compared to traditional asset pricing models. The findings of this study have important implications for investors, portfolio managers, and policymakers in conditions of economic uncertainty.

Keywords : capital asset pricing economic uncertainty multivariate factor models