Rough Volatility Modelling

Supervisor: Jean-François Bégin

The number of financial derivatives available in the markets has increased dramatically in recent years. As argued in Renault (1997), it is a good idea to combine primitive and derivative asset prices because the information about the stochastic properties of an asset is contained both in the history of the underlying series and the price of any option written on it.  

This USRA project (May 2020 to August 2020) investigates the use of financial derivatives as an additional source of information in the context of rough volatility models (e.g., Gatheral, Jaisson and Rosenbaum, 2014). Specifically, the student will put forward an estimation method for rough volatility models that combines both return and option data. The student will be responsible for:

  1. Familiarizing themselves with the current literature on rough volatility modelling.
  2. Proposing an estimation methodology for rough volatility models that combines both returns and options.
  3. Extracting data from commonly used datasets in finance.
  4. Writing code to implement the model and its estimation.
  5. Documenting all work.