Using an audit trail transaction data set compiled by the Commodity Futures Trading Commission (CFTC), we seek to ascertain directly the motives behind dual traders’ own account trading and whether or not they are informed traders. We estimate our system of equations on each of the 101 most...

We present and estimate a Bayesian Hierarchical model of mutual fund returns. In our model, a fund's alpha reflects not only that fund's return history, but also information from other fund returns. Because parameters are estimated simultaneously for all funds, we can identify common residual...

This paper utilizes a Bayesian hierarchical model to study the distribution of skill (alphas) among mutual funds. The hierarchical model specifies a probability distribution over all parameters and funds, making it possible to formally analyze the variability of alphas across funds. In addition,...

We take a closer look at the question of whether dual traders in futures markets are indeed informed traders. Underpinning this question is the intuition that a dual trader's decision to trade on his own account is not random, but is endogenously determined by his expectations of trading profits...

Using audit trail transaction data compiled by the Commodity Futures Trading Commission (CFTC), we seek to ascertain directly the motives behind dual traders' own account trading and whether or not they are informed traders. We estimate our system of equations on each of the 101 most active dual...

We take a closer look at the question of whether dual traders in futures markets are indeed informed traders. Underpinning this question is the intuition that a dual trader's decision to trade on his own account is not random, but is endogenously determined by his expectations of trading profits...

We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to study whether U.S. Survey of Professional Forecasters density projections for output growth and inflation are consistent with the noisy rational expectations hypothesis. We...

This paper proposes a framework for modelling financial contagion that is based on SIR (Susceptible-Infected-Recovered) transmission models from epidemic theory. This class of models addresses two important features of contagion modelling, which are a common shortcoming of most existing...

To measure contagion empirically, we propose using a Bayesian time-varying coefficient model estimated with Markov ChainMonte Carlo methods. The proposed measure works in the joint presence of heteroskedasticity and omitted variables and does not require knowledge of the timing of the crisis. It...