A volatility surface is an important tool for pricing and hedging derivatives. The surface
shows the volatility that is implied by the market price of an option on an asset as a function …

We present a computationally tractable method for simulating arbitrage-free implied volatility
surfaces. We illustrate how our method may be combined with a data-driven model based …

It is a common practice to conduct principal component analysis (PCA) using standardized
data, which is equivalent to applying PCA to the correlation matrix rather than the covariance …

We analyze portfolios constructed from the principal eigenvector of the equity returns'
correlation matrix and compare these portfolios with the capitalization weighted market …

Abstract Marco Avellaneda (1955–2022) was a leading figure in the development of
mathematical modeling in finance and its dissemination among market practitioners. We …

We introduce VolGAN, a generative model for arbitrage-free implied volatility surfaces. The
model is trained on a time series of implied volatility surfaces and underlying prices and is …

Abstract We augment the Heterogeneous Autoregressive Regression model for forecasting
realized volatility, using various measurements for the daily, weekly, and monthly volatilities …

The task of imputing the missing entries of a partially observed matrix, often dubbed as
matrix completion, is widely applicable in various areas. In addition to the wellknown …

Abstract The Implied Volatility Surface (IVS) is a key component for pricing and hedging
options. We compare the performance of three different dimension reduction methods for …

We introduce VolGAN, a generative model for arbitrage-free implied volatility surfaces. The
model is trained on time series of implied volatility surfaces and underlying prices and is …