In this survey, we review econometric models for conducting statistical inference on option price data. We limit our review to European options on a stock index as well as to statistical methods which have been specifically developped for options. Emphasis is put on the synthesis of the various...

This paper presents an innovative approach to extracting factors which are shown to predict the VIX, the S&P 500 Realized Volatility and the Variance Risk Premium. The approach is innovative along two different dimensions, namely: (1) we extract factors from panels of filtered volatilities - in...

This paper presents an innovative approach to extracting factors which are shown to predict the VIX, the S&P 500 Realized Volatility and the Variance Risk Premium. The approach is innovative along two different dimensions, namely: (1) we extract factors from panels of filtered volatilities - in...

The financial industry has eagerly adopted machine learning algorithms to improve on traditional predictive models. In this paper we caution against blindly applying such techniques. We compare forecasting ability of machine learning methods in evaluating future payoffs on synthetic variance...

Several estimation procedures such as the Efficient Method of Moments (EMM) of Gallant and Tauchen (1996) and Indirect Inference procedure of Gouriéroux, Monfort and Renault (1993) involve two models, an auxiliary one and a model of interest. The role played by both models poses challenges and...

Simulation-based estimation methods have become more widely used in recent years. We propose a set of tests for structural change in models estimates via Simulated Method of Moments (see Duffie and Singleton (1993)). These tests extend the recent work of Andrews (1993) and Sowell (1996a, b)...

Several estimation procedures such as the Efficient Method of Moments (EMM) of Gallant and Tauchen (1996) and Indirect Inference procedure of Gouriéroux, Monfort and Renault (1993) involve two models, an auxiliary one and a model of interest. The role played by both models poses challenges and...

We introduce a new approximation method for the distribution of functions of random variables that are real-valued. The approximation involves moment matching and exploits properties of the class of normal inverse Gaussian distributions. In the paper we we examine the how well the different...

This paper reviews the literature on structural breaks in financial time series. First we discuss the implications of structural breaks in financial time series for statistical inference purposes. In the second section we discuss the relevant asymptotic results and issues involved in general...