Agenda

Ruonan Fu (Tilburg University) - Quantifying Ambigiuty in the Stock Markets Using Option Data

Abstract
I quantify the level of ambiguity in the US stock market using option data. Firstly, I set up a representative agent asset pricing model where ambiguity is modelled using the framework of recursive multiple-priors utility. This model serves as an economic foundation for a reduced-form model which keeps its main characteristics and is easy to estimate. Then, I derive a closed-form option pricing formula based on this reduced-form model of the market index. I also provide an asymptotic expansion for the corresponding short-maturity at-the-money implied volatility. I use these results to quantify the level of ambiguity with option data from 1996 to 2020. I find that the role of ambiguity is more pronounced for the recent stock market crash due to COVID-19 than for the 2008 Financial Crisis. Furthermore, the level of ambiguity spikes during crises and decreases to its normal level rapidly than risk.

Link zoom: unive.zoom.us/j/89353836221

ID riunione: 893 5383 6221