Department of Mathematics Calendar
Andrew Papanicolaou, NYU, Principal component analysis for implied volatility surfaces
- This event has passed.
Principal component analysis (PCA) is a useful tool when trying to uncover factor models from historical asset returns. For the implied volatilities of U.S. equities there is a PCA-based model with a principal eigenportfolio whose return time series lies close to that of an overarching market factor. Specifically, this market factor is the index resulting from the daily compounding of a weighted average of implied-volatility returns, with weights based on the options’ open interest (OI). We analyze the singular values derived from the tensor structure of the implied volatilities of S&P500 constituents, and find evidence indicating that the OI-weighted index is one of at least two significant factors in this market.
February 13, 2020
3:00 pm - 4:00 pm
- Event Category:
- Special Seminar
- SAS 4201