Regime-Switching Factor Investing with Hidden Markov Models

Matthew Wang, Yi-Hong Lin and Ilya Mikhelson
Additional contact information
Matthew Wang: Electrical and Computer Engineering, Northwestern University, Evanston, IL 60208, USA
Yi-Hong Lin: Media IC & System Lab, National Taiwan University, Taipei 10617, Taiwan
Ilya Mikhelson: Electrical and Computer Engineering, Northwestern University, Evanston, IL 60208, USA

JRFM, 2020, vol. 13, issue 12, 1-15

Abstract: This study uses the hidden Markov model (HMM) to identify different market regimes in the US stock market and proposes an investment strategy that switches factor investment models depending on the current detected regime. We first backtested an array of different factor models over a roughly 10.5 year period from January 2007 to September 2017, then we trained the HMM on S&P 500 ETF historical data to identify market regimes of that period. By analyzing the relationship between factor model returns and different market regimes, we are able to establish the basis of our regime-switching investing model. We then back-tested our model on out-of-sample historical data from September 2017 to April 2020 and found that it both delivers higher absolute returns and performs better than each of the individual factor models according to traditional portfolio benchmarking metrics.

Keywords: factor models; hidden Markov model; market regime (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1911-8074/13/12/311/pdf (application/pdf)
https://www.mdpi.com/1911-8074/13/12/311/ (text/html)

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:gam:jjrfmx:v:13:y:2020:i:12:p:311-:d:457386

Access Statistics for this article

JRFM is currently edited by Ms. Chelthy Cheng

More articles in JRFM from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().