The Value-at-Risk (VaR) is one of the key risk measures to determine the risk levels of trading portfolios. The VaR gives information about the maximal future loss of the portfolio in a given time frame. However, determining a VaR for a given trading portfolio based on historical data of the stocks composing the portfolio results in a backwards-looking risk measurement. Such an approach is only appropriate if the past can be used as a proxy for the (near) future. However, given the dynamics behavior of financial markets, the information contained in past market data is deteriorating rapidly with the horizon and backwards-looking risk estimates are not always a good representation for the true risk levels. Moreover, the discrepancy between reality and model is large when a market is in distress, resulting in a bad risk estimate when it is needed the most.

Therefore, we investigate how option data on the components of a portfolio can be employed to determine the Value-at-Risk of the investment portfolio. Such an estimate is called an implied estimate.  Option prices are containing the aggregate view of the market on future price levels. Therefore, an implied portfolio Value-at-Risk is automatically forward-looking. Moreover, we investigate model-free approaches for determining the VaR. 

Students: Xuan Lin, Yifan Sun, Zixuan Wang

Supervisor: Daniël Linders
Graduate Supervisor: Elizaveta Sizova