Investor Risk Aversion in Emerging Markets

Abstract

This thesis aims to investigate the investors risk aversion level in the Saudi market by identifying the degree of impact for seven key determinants that are broadly categorized under economic and financial indicator. Methodology- Using vector autoregression model (VAR) to estimate the impact on the degree of investor risk aversion market in the Saudi Market through capturing interdependencies among the following multiple time series; (1) stock market returns, (2) volatility index, (3) country political risk, (4) oil prices, (5) Federal funds rate, (6) real GDP, and (7) public debt. The model uses data with monthly frequency for 13 years, January 2006 - December 2019, and uses stock returns as the proxy for the risk aversion. Findings- The primary findings of the study are as follows: (1) only oil prices had significant influence on the risk aversion degree using (VAR); (2) all responses to shocks last around two months in the market; (3) the investors will have “ flight-to quality” response to shocks in stock market; (4) the investor risk aversion degree in Saudi market is largely independent of the other variables; and (5) when applying ARDL, Federal funds rate had significantly high influence on risk aversion proxy.