Financial Uncertainty and Asset Volatility Dynamics: Insights from an Extended Stochastic Volatility Model

Abstract

This master’s thesis attempts to provide additional insights into the intricate relationship between financial uncertainty and asset volatility. Using the extended stochastic volatility model (SVX) of Ulm and Hambuckers (2022), we explore the effects of financial uncertainty on the conditional volatility of a diverse set of 12 financial assets. Our analysis is conducted over the period spanning from November 2017 to May 2023, and relies on a daily synthetic financial uncertainty index that we constructed by means of a principal component analysis. In our examination, we uncover that a higher financial uncertainty level generally reinforces volatility. However, this influence is heterogeneous in magnitude across the various categories of assets examined. Importantly, our study also unveils that a part of the effects of financial uncertainty is propagated to asset volatility through investor sentiment. Knowing that uncertainty rises sharply in times of market stress, our study also demonstrates that incorporating the financial uncertainty level substantially improves both in-sample and out-of-sample volatility modelling performance during these periods. Interestingly, this positive effect extends to normal market conditions as well, albeit to a lesser extent. This improvement also materializes in the construction of risk metrics that better capture tail events and extreme market conditions.