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...

This paper aims at increasing our insights into the way financial markets respond to news. We view the market as a (nonlinear) filter of news on fundamentals. A stylized version of this situation is obtained by considering by a time dependent dividend rate which is driving the market. To model...

We present an spectral numerical method for the numerical valuation of bonds with embedded options. We use a CIR model for the short term interest rate. The method is based in a Galerkin formulation of the relevant partial differential equation for the value of the bond discretized by means of...

We construct an empirical measure of market frictions in the corporate market based on the difference between the corporate bond spread and the credit default swap spread for a large number of firms in a new, large dataset that we construct. Under fairly standard assumptions, the two spreads...

This paper reports on the use of multi-agent games to model financial markets. Our research employs multi-agent games to address three questions which are of great practical importance in quantitative finance: how profit opportunities may be identified, large price movements predicted, and...

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...

While under recursive least squares learning the dynamics of the economy converges to rational expectations equilibria (REE) which are E–stable, some recent examples propose that E–stability is not a sufficient condition for learnability. In this paper, we provide some further...

We examine optimal policy in an open-economy model with uncertainty and learning, where monetary policy actions affect the economy through the real exchange rate channel. Our results show that the degree of caution or activism in optimal policy depends on whether central banks are in coordinated...

We provide sufficient conditions and necessary conditions for stability of an economy under structural mixed recursive least squares/stochastic gradient heterogeneous learning of agents with possibly different degrees of inertia. We have found a unifying condition which is sufficient for...

In this paper we perform an in—depth investigation of relative merits of two adaptive learning algorithms with constant gain, Recursive Least Squares (RLS) and Stochastic Gradient (SG), using the Phelps model of monetary policy as a testing ground. The behavior of the two learning...