Beginning in 1998, commercial banks may determine their regulatory capital requirements for market risk exposure using value-at-risk (VaR) models; i.e., time-series models of the distributions of portfolio returns. Currently, regulators have available three statistical methods for evaluating the...

Beginning in 1998, U.S. commercial banks may determine their regulatory capital requirements for financial market risk exposure using value-at-risk (VaR) models i.e., models of the time-varying distributions of portfolio returns. Currently, regulators have available three hypothesis-testing...

Covariance matrix forecasts of financial asset returns are an important component of current practice in financial risk management. A wide variety of models, ranging from matrices of simple summary measures to covariance matrices implied from option prices, are available for generating such...

Covariance matrix forecasts of financial asset returns are an important component of current practice in financial risk management. A wide variety of models, ranging from matrices of simple summary measures to covariance matrices implied from option prices, are available for generating such...

We provide an overview of data requirements necessary to monitor repurchase agreements (repos) and securities lending (sec lending) markets for the purposes of informing policymakers and researchers about firm-level and systemic risk. We start by explaining the functioning of these markets, and...

We develop a model of the market for federal funds that explicitly accounts for its two distinctive features: banks have to search for a suitable counterparty, and once they have met, both parties negotiate the size of the loan and the repayment. The theory is used to answer a number of positive...

This paper outlines a simple Bayesian methodology for estimating tax and spending multipliers in a dynamic stochastic general equilibrium (DSGE) model. After forming priors about the parameters of the model and the relevant shock, we used the model to exactly match only one data point: the...

This paper uses multi-level factor models to characterize within- and between-block variations as well as idiosyncratic noise in large dynamic panels. Block-level shocks are distinguished from genuinely common shocks, and the estimated block-level factors are easy to interpret. The framework...