Option pricing model with non-constant volatility models are compared to stochastic volatility ones. The non-constant volatility models considered are the Dupire's local volatility and Hobson and Rogers path-dependent volatility models. These approaches have the theoretical advantage of...

In this paper we explore ways that alleviate problems of nonparametric (artificial neural networks) and parametric option pricing models by combining the two. The resulting enhanced network model is compared to standard artificial neural networks and to parametric models with several historical...

We have developed an agent-based computational model, extension of an analytical model1 that studies the structure of coalitions of B-to-C web sites, when Internet buyers incur search costs for finding the good that matches their preferences, and coalitions of sites reduce this cost through...

This paper provides formulae for computing perturbation method approximations of unconditional variances of variables in nonlinear DSGE models. Spurious higher order terms that creep into multi-step ahead forecasts can produce explosive time paths frustrating traditional approaches to estimating...

This paper characterizes the optimal long-run rate of inflation, consistent with an occasionally binding zero lower bound on nominal interest rates, in a stochastic New Keynesian sticky-price model calibrated to the U.S. economy. This may serve to inform discussions on the design of an...

Though multivariate GARCH models are widely used in empirical research, their computational aspects still represent a major hurdle, especially when these specifications are introduced in structural models. One such extension namely the simultaneous equations model (SEM) with GARCH errors was...

This paper studies a Monte Carlo algorithm for computing distributions of state variables when the underlying model is a Markov process. It is shown that the $L_1$ error of the estimator always converges to zero with probability one, and often at a parametric rate. A related technique for...

The paper deals with the efficient computation of general equilibrium models with a continuum of heterogenous agents. It compares an improved version of the Krusell-Smith algorithm to a backward-induction algorithm. The Krusell-Smith algorithm I use in the paper modifies the original algorithm...

This paper builds on our previous work that used a non linear stochastic dynamic programming problem to solve for the optimal level of phosphorus discharged into a watershed. Typically, there is a trade off between profits from agriculture and environmental damage due to excessive levels of...

The Efficient Market Hypothesis (EMH) is one of the most investigated questions in Finance. Nevertheless, it is still a puzzle, despite the enormous amount of research it has provoked. For instance, it is still discussed that market cannot be outperformed in the long run (Detry and Gregoire,...