We review the literature on multi-horizon currency risk premiums. We show how the multi-horizon implications arise from the classic present-value relationship. We further show how these implications manifest themselves in the interaction between bond and currency risk premiums. This link is...

We review the literature on multi-horizon currency risk premiums. We show how the multi-horizon implications arise from the classic present-value relationship. We further show how these implications manifest themselves in the interaction between bond and currency risk premiums. This link is...

The conditional skewness of Treasury yields is an important indicator of the risks to the macroeconomic outlook. Positive skewness signals upside risk to interest rates during periods of accommodative monetary policy and an upward-sloping yield curve, and vice versa. Skewness has substantial...

This working paper was written by Patrick Augustin (McGill University and Canadian Derivatives Institute), Mikhail Chernov (University of California Los Angeles, NBER and CEPR), Lukas Schmid (University of Southern California and CEPR) and Dongho Song (Johns Hopkins University).We show...

Conditional yield skewness is an important summary statistic of the state of the economy. It exhibits pronounced variation over the business cycle and with the stance of monetary policy, and a tight relationship with the slope of the yield curve. Most importantly, variation in yield skewness has...

We explore the term structures of claims to a variety of cash flows: U.S. government bonds (claims to dollars), foreign government bonds (claims to foreign currency), inflation-adjusted bonds (claims to the price index), and equity (claims to future equity indexes or dividends). Average term...

In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and illustrate the major principles of corresponding Markov Chain Monte Carlo (MCMC) based statistical inference. We provide a hands-on ap proach which is easily implemented in empirical...

We propose a local adaptive multiplicative error model (MEM) accommodating timevarying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time....

In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and illustrate the major principles of corresponding Markov Chain Monte Carlo (MCMC) based statistical inference. We provide a hands-on ap proach which is easily implemented in empirical...

We propose a local adaptive multiplicative error model (MEM) accommodating timevarying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time....