Implied Value-at-Risk: Model-Free and Forward-Looking Risk Estimates for the US Banks

A rapid and persistent market value decline of the US bank equity, around 50% since January 2020, can be observed during the COVID-19 pandemic. While the economy as a whole is under stress, stock returns of banks have done worse than those of non-bank financial institutions such as broker-dealers and insurance companies, and non-financial firms. Bank equity returns have been shown to contain information about future macroeconomic consequences like credit contractions and output gaps, and can serve as an indicator of bank distress. However, given the dynamic behavior of financial markets, the information contained in stock returns is deteriorating rapidly with the horizon and equity-based risk estimates are not always a good representation for the true risk levels. Especially in times like now, when a market is in distress, the discrepancy between the expectation and the realized outcome is large resulting in a bad risk estimate when it is needed the most.

Therefore, we investigate how option data can be employed to determine the risk level of the US banks. Such an estimate is called an implied estimate. Option prices contain the aggregate view of the market on the future stock price level, i.e., not just on its expected value, but rather on the distribution around that expectation. Therefore, an option-implied estimate is automatically forward-looking. The selected risk estimate is the Value-at-Risk (VaR) measure which can be seen as the maximal future loss in a given time frame. We examine model-free approaches for determining the VaR such as the binomial tree option pricing.

Students: Chen Chen, Haoxuan Fu, Churui Li, Ruiqi Liu

Supervisor: Daniël Linders

Graduate Supervisor: Elizaveta Sizova