Boosting the Equity Momentum Factor in Credit

Hendrik Kaufmann, Philip Messow and Jonas Vogt

Financial Analysts Journal, 2021, vol. 77, issue 4, 83-103

Abstract: Machine learning techniques have gained popularity in recent years but only to a limited extent in fixed-income research. This article shows some new work in the application of “boosted regression trees” for the equity momentum factor in the corporate bond market. We report significant performance gains to investors from using machine learning–driven forecasts, roughly doubling the alpha and information ratio of better known equity momentum strategies. In addition to past equity returns, we include size and liquidity of stocks and bonds in our model framework.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/0015198X.2021.1954377 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:ufajxx:v:77:y:2021:i:4:p:83-103

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/ufaj20

DOI: 10.1080/0015198X.2021.1954377

Access Statistics for this article

Financial Analysts Journal is currently edited by Maryann Dupes

More articles in Financial Analysts Journal from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().