A method to price American-style option contracts in a limited information framework is introduced. The pricing methodology is based on sequential Monte Carlo techniques, as presented in Doucet, de Freitas, and Gordon's text "Sequential Monte Carlo Methods in Practice", and the least-squares...

This book presents in detail methodologies for the Bayesian estimation of single-regime and regime-switching GARCH models. These models are widespread and essential tools in financial econometrics and have, until recently, mainly been estimated using the classical Maximum Likelihood technique....

We compare more than 1000 different volatility models in terms of their fit to the historical ISE-100 Index data and their forecasting performance of the conditional variance in an out-of-sample setting. Exponential GARCH model of Nelson (1991) with “constant mean, t-distribution, one lag...

In this paper we analyze the limiting properties of the estimated parameters in a general class of asymmetric volatility models which are closely related to the traditional exponential GARCH model. The new representation has three main advantages over the traditional EGARCH: (1) It allows a much...

I introduce the time-varying GARCH-in-mean (TVGARCH-in-mean) model and propose an estimation strategy for the stochastic time-varying risk premium parameter. A Monte Carlo study shows that the proposed algorithm has good finite sample properties. Using monthly excess returns on the CRSP index, I...

Daily returns of financial assets are frequently found to exhibit positive autocorrelation at lag 1. When specifying a linear AR(l) conditional mean, one may ask how this predictability affects option prices. We investigate the dependence of option prices on autoregressive dynamics under...

We implement a flexible simulation-based approach for the fair value of employee stock option (ESO) that accounts for the vesting period, departure risk and voluntary suboptimal early exercise. We introduce GARCH effects on the underlying asset and we analyze the price bias with respect to the...

Structural breaks in GARCH processes do matter for applications and model-based inference. To show this, I first propose a new approach to estimate change-point GARCH models with maximum likelihood, for which no method exists so far. Practical implementation of the proposed algorithm is...

This paper shows how one can compute option prices from a Bayesian inference viewpoint, using a GARCH model for the dynamics of the volatility of the underlying asset. The proposed evaluation of an option is the predictive expectation of its payoff function. The predictive distribution of this...

In recent years multivariate models for asset returns have received much attention, in particular this is the case for models with time varying volatility. In this paper we consider models of this class and examine their potential when it comes to option pricing. Specifically, we derive the risk...