We propose to pool alternative systemic risk rankings for financial institutions using the method of principal components. The resulting overall ranking is less affected by estimation uncertainty and model risk. We apply our methodology to disentangle the common signal and the idiosyncratic...

We develop a new targeted maximum likelihood estimation method that provides improved forecasting for misspecified linear autoregressive models. The method weighs data points in the observed sample and is useful in the presence of data generating processes featuring structural breaks, complex...

In a market in which sellers compete for heterogeneous buyers by posting mechanisms, we analyze how the properties of the meeting technology affect the allocation of buyers to sellers. We show that a separate submarket for each type of buyer is the efficient outcome if and only if meetings are...

We develop a multivariate unobserved components model to extract business cycle and financial cycle indicators from a panel of economic and financial time series of four large developed economies. Our model is flexible and allows for the inclusion of cycle components in different selections of...

This paper develops a model in which market structure is determined endogenously by the choice of intermediation mode. We consider two representative business modes of intermediation that are widely used in real-life markets: one is a middleman mode by which an intermediary holds inventories...

We propose a novel multivariate GARCH model that incorporates realized measures for the variance matrix of returns. The key novelty is the joint formulation of a multivariate dynamic model for outer-products of returns, realized variances and realized covariances. The updating of the variance...