Dollar-denominated emerging market bonds are marketed to investors as a vehicle for gaining exposure to emerging fixed income markets while avoiding exposure to currency risk. However, the development literature suggests that dollarization of debt leads to increased probability of financial...

United States Treasury securities are traditionally viewed in academics and practice as being free of default risk. In principle, nominal outstanding Treasury debt can always be repaid by issuing fiat currency. The same does not hold true, however, for inflation-indexed debt. This leads the...

We investigate the empirical implications of the investment-based model of asset pricing for the Hansen-Jagannathan and Kozak-Nagel-Santosh discount factors in the linear span of equity returns. Our methodology is based on the equivalence between investment and equity returns implied by the...

We combine self-collected historical data from 1867 to 1907 with CRSP data from 1926 to 2012, to examine the risk and return over the past 140 years of one of the most popular mechanical trading strategies - momentum. We find that momentum has earned abnormally high risk-adjusted returns - a...

We combine self-collected historical data from 1867 to 1907 with CRSP data from 1926 to 2012, to examine the risk and return over the past 140 years of one of the most popular mechanical trading strategies — momentum. We find that momentum has earned abnormally high risk-adjusted returns — a...

We combine self-collected historical data from 1867 to 1907 with CRSP data from 1926 to 2012, to examine the risk and return over the past 140 years of one of the most popular mechanical trading strategies — momentum. We find that momentum has earned abnormally high risk-adjusted returns — a...

The financial industry has eagerly adopted machine learning algorithms to improve on traditional predictive models. In this paper we caution against blindly applying such techniques. We compare forecasting ability of machine learning methods in evaluating future payoffs on synthetic variance...