We present evidence that the growth of U.S.-dollar-denominated banking sector liabilities forecasts appreciations of the U.S. dollar, both in-sample and out-of-sample, against a large set of foreign currencies. We provide a theoretical foundation for a funding liquidity channel in a global...

We derive equilibrium pricing implications from an intertemporal capital asset pricing model where the tightness of financial intermediaries' funding constraints enters the pricing kernel. We test the resulting factor model in the cross-section of stock returns. Our empirical results show that...

We present evidence that the funding liquidity aggregates of U.S. financial intermediaries forecast exchange rate growth-at weekly, monthly, and quarterly horizons, both in-sample and out-of-sample, and for a large set of currencies. We estimate prices of risk using a cross-sectional asset...

This paper shows that the risk-bearing capacity of U.S. securities brokers and dealers is a strong determinant of risk premia in commodity markets. Commodity derivatives are the principal instrument used by producers and consumers of commodities to hedge against commodity price risk....

In a factor-augmented regression, the forecast of a variable depends on a few factors estimated from a large number of predictors. But how does one determine the appropriate number of factors relevant for such a regression? Existing work has focused on criteria that can consistently estimate the...

This paper revisits a number of data-rich prediction methods, like factor models, Bayesian ridge regression and forecast combinations, which are widely used in macroeconomic forecasting, and compares these with a lesser known alternative method: partial least squares regression. Under the...

Detection of structural change is a critical empirical activity, but continuous 'monitoring' of series, for structural changes in real time, raises well-known econometric issues that have been explored in a single series context. If multiple series co-break then it is possible that simultaneous...

In this paper, we seek to produce forecasts of commodity price movements that can systematically improve on naïve statistical benchmarks. We revisit how well changes in commodity currencies perform as potential efficient predictors of commodity prices, a view emphasized in the recent...

We compare a number of data-rich prediction methods that are widely used in macroeconomic forecasting with a lesser known alternative: partial least squares (PLS) regression. In this method, linear, orthogonal combinations of a large number of predictor variables are constructed such that the...

We suggest a way to perform parsimonious instrumental variables estimation in the presence of many, and potentially weak, instruments. In contrast to standard methods, our approach yields consistent estimates when the set of instrumental variables complies with a factor structure. In this sense,...