This paper analyzes the choice between limit and market orders in an imperfectly competitive noisy rational expectations economy. There is a unique insider, who takes into account the effect their trading has on prices. If the insider behaves as a price taker, she will choose market orders if...

This paper shows that information effects per se are not responsible for the Giffen goods anomaly affecting competitive traders’ demands in multi- asset, noisy rational expectations equilibrium models. The role that information plays in traders’ strategies also matters. In a market with risk...

This paper studies the relationship between the amount of public information that stock market prices incorporate and the equilibrium behavior of market participants. The analysis is framed in a static, NREE setup where traders exchange vectors of assets accessing multidimensional information...

I study the effects of the heterogeneity of traders' horizon in the context of a 2-period NREE model where all traders are risk averse. Owing to inventory effects, myopic trading behavior generates multiplicity of equilibria. In particular, two distinct patterns arise. Along the first...

We propose new methods for evaluating predictive densities in an environment where the estimation error of the parameters used to construct the densities is preserved asymptotically under the null hypothesis. The tests offer a simple way to evaluate the correct specification of predictive...

The goal of this paper is to develop formal tests to evaluate the relative in-sample per- formance of two competing, misspecified, non-nested models in the presence of possible data instability. Compared to previous approaches to model selection, which are based on measures of global...

This paper proposes new methodologies for evaluating out-of-sample forecasting performance that are robust to the choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over a wide range of window sizes. We show that the tests...

We evaluate conditional predictive densities for U.S. output growth and inflation using a number of commonly used forecasting models that rely on a large number of macroeconomic predictors. More specifically, we evaluate how well conditional predictive densities based on the commonly used...

We propose new methods for evaluating predictive densities. The methods include Kolmogorov-Smirnov and Cramér-von Mises-type tests for the correct specification of predictive densities robust to dynamic mis-specification. The novelty is that the tests can detect mis-specification in the...

This work proposes novel network analysis techniques for multivariate time series. We define the network of a multivariate time series as a graph where vertices denote the components of the process and edges denote non zero long run partial correlations. We then introduce a two step LASSO...