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Financial theory and econometric methodology both struggle in formulating models that are logically sound in reconciling short-run martingale behavior for financial assets with predictable long-run behavior, leaving much of the research to be empirically driven. The present article overviews...
This article analyzes multifactor models in the presence of a large number of potential observable risk factors and unobservable common and group-specific factors. We show how relevant observable factors can be found from a large given set and how to determine the number of common and...
Most studies of the predictability of returns are based on time series data, and whenever panel data are used, the testing is almost always conducted in an unrestricted unit-by-unit fashion, which makes for a very heavy parametrization of the model. On the other hand, the few panel tests that...
A multivariate positive definite estimator of the integrated covariance matrix of noisy and asynchronously observed asset returns is proposed. We adopt a Bayesian Dynamic Linear Model where microstructure noise is interpreted as measurement error, and asynchronous trading as missing observations...
Economic data are collected at various frequencies but econometric estimation typically uses the coarsest frequency. This article develops a Gibbs sampler for estimating vector autoregression (VAR) models with mixed and irregularly sampled data. The Gibbs sampler allows efficient likelihood...
We propose a new method for simulation smoothing in state space models with univariate states and conditional dependence between the observation yt and the contemporaneous innovation of the state equation. Stochastic volatility models with the leverage effect are a leading example. Our method...
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