March 4, 2020
We extend the analysis of systematic investment approaches to emerging market (EM) fixed income. We find that systematic exposures linked to carry, defensive, momentum and valuation themes are well compensated and lowly correlated in EM markets, and that a systematic approach to EM debt may be a powerful diversifier.
February 17, 2020
Low-risk investing has received a lot of attention over the past decade. An intensive academic debate has spurred, and been spurred by, the growing market for low-risk strategies. This article presents five fact and dispels five fictions about low-risk investing.
December 17, 2019
Across a broad set of popular active fixed income categories, we find that passive exposures to traditional risk premia (especially exposure to credit risk) explain the majority of fixed income manager active returns.
October 11, 2019
Despite its unavoidable deficiency caused by current regulations, we believe that lot layering aligns tax and economics more closely than any of the “aggregation” methods presently used by most hedge funds.
June 7, 2019
The early evidence hints that machine learning tools can potentially improve investment portfolios. Application of machine learning techniques is a natural evolution for investment research, and one that will continue to be explored.
April 23, 2019
We present a framework for understanding the drivers of trend-following returns and show that recent performance challenges are primarily due to muted moves across global markets rather than a change in trend following’s ability to translate market trends into profits.
February 1, 2019
In this paper, we present a real example of how multiple testing information can be reported. We use that information to estimate the Deflated Sharpe Ratio of an investment strategy.
October 17, 2018
We show how the field of machine learning can be used to empirically investigate asset premia including momentum, liquidity, and volatility.
May 14, 2018
Despite its long and illustrious history, much confusion about the size effect remains. We examine common claims about the size effect and seek to clarify some of the misunderstanding surrounding it.