This chapter surveys the methods available for extracting information from option prices that
can be used in forecasting. We consider option-implied volatilities, skewness, kurtosis, and …

These lecture notes cover a major part of the crash course on financial modeling with jump
processes given by the author in Bologna on May 21–22, 2009. After a brief introduction, we …

Praise for The Volatility Surface" I'm thrilled by the appearance of Jim Gatheral's new book
The Volatility Surface. The literature on stochastic volatility is vast, but difficult to penetrate …

In this paper, we propose a general framework for the valuation of options in stochastic local
volatility (SLV) models with a general correlation structure, which includes the stochastic …

We propose a two‐sided jump model for credit risk by extending the Leland–Toft
endogenous default model based on the geometric Brownian motion. The model shows that …

We consider a class of asset pricing models, where the risk‐neutral joint process of log‐
price and its stochastic variance is an affine process in the sense of Duffie, Filipovic, and …

Since we will never really know why the prices of financial assets move, we should at least
make a faithful model of how they move. This was the motivation of Bachelier in 1900, when …

Asymptotic analysis of stochastic stock price models is the central topic of the present
volume. Special examples of such models are stochastic volatility models, that have been …

We present a neural network (NN) approach to fit and predict implied volatility surfaces
(IVSs). Atypically to standard NN applications, financial industry practitioners use such …

In a unified model-free framework that includes long-expiry, short-expiry, extreme-strike, and
jointly-varying strike-expiry regimes, we generate implied volatility and implied variance …