The level, slope, and curve factor model for stocks

Charles Clarke

doi:10.1016/j.jfineco.2021.08.008

The level, slope, and curve factor model for stocks

Charles Clarke

Finance and Quantitative Methods

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

I develop a method to extract only the priced factors from stock returns. The first step estimates expected returns based on firm characteristics. The second step uses the estimated expected returns to form portfolios. The last step uses principal component analysis to extract factors from the portfolio returns. The procedure isolates and emphasizes the comovement across assets that is related to expected returns as opposed to firm characteristics. It produces three factors–level, slope, and curve–which perform as well or better than other leading models. The methodology performs well in out-of-sample tests. The new factors have macroeconomic risk interpretations.

Original language	English
Pages (from-to)	159-187
Number of pages	29
Journal	Journal of Financial Economics
Volume	143
Issue number	1
DOIs	https://doi.org/10.1016/j.jfineco.2021.08.008
State	Published - Jan 2022

Bibliographical note

Funding Information:
I am grateful to Daniel Andrei, Paul Borochin, John Campbell, Scott Cederburg, Igor Cunha, Kent Daniel, Assaf Eisdorfer, Mark Grinblatt, Joseph Golec, Valentin Haddad, Bernard Herskovic, Shiyang Huang, Mihai Ion, Bradford Jordan, Serhiy Kozak, Steven Kozlowski, Yan Liu, Matthew Linn, William Mann, Efdal Misirli, Stefan Nagel, Cesare Robotti, Richard Roll, Mark Schneider, Mihail Velikov, Chu Zhang and seminar participants at Fordham University, Southern Methodist University, Tulane University, University of California, Los Angeles, University of Connecticut, University of Kentucky, University of Massachusettes Amherst, Utah State University and conference participants at the American Finance Association 2016 Annual Meeting (San Francisco), European Finance Association 2015 Annual Meeting (Vienna) and Financial Management Association 2015 Annual Conference and Doctoral Consortium (Orlando) for helpful comments and suggestions. A special thanks to John Cochrane for discussing the paper on his weblog and his many helpful comments.

Publisher Copyright:
© 2021 Elsevier B.V.

Keywords

Anomaly
Arbitrage pricing theory
Cross-section of returns
Factor model

ASJC Scopus subject areas

Accounting
Finance
Economics and Econometrics
Strategy and Management

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10.1016/j.jfineco.2021.08.008

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abstract = "I develop a method to extract only the priced factors from stock returns. The first step estimates expected returns based on firm characteristics. The second step uses the estimated expected returns to form portfolios. The last step uses principal component analysis to extract factors from the portfolio returns. The procedure isolates and emphasizes the comovement across assets that is related to expected returns as opposed to firm characteristics. It produces three factors–level, slope, and curve–which perform as well or better than other leading models. The methodology performs well in out-of-sample tests. The new factors have macroeconomic risk interpretations.",

keywords = "Anomaly, Arbitrage pricing theory, Cross-section of returns, Factor model",

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note = "Funding Information: I am grateful to Daniel Andrei, Paul Borochin, John Campbell, Scott Cederburg, Igor Cunha, Kent Daniel, Assaf Eisdorfer, Mark Grinblatt, Joseph Golec, Valentin Haddad, Bernard Herskovic, Shiyang Huang, Mihai Ion, Bradford Jordan, Serhiy Kozak, Steven Kozlowski, Yan Liu, Matthew Linn, William Mann, Efdal Misirli, Stefan Nagel, Cesare Robotti, Richard Roll, Mark Schneider, Mihail Velikov, Chu Zhang and seminar participants at Fordham University, Southern Methodist University, Tulane University, University of California, Los Angeles, University of Connecticut, University of Kentucky, University of Massachusettes Amherst, Utah State University and conference participants at the American Finance Association 2016 Annual Meeting (San Francisco), European Finance Association 2015 Annual Meeting (Vienna) and Financial Management Association 2015 Annual Conference and Doctoral Consortium (Orlando) for helpful comments and suggestions. A special thanks to John Cochrane for discussing the paper on his weblog and his many helpful comments. Publisher Copyright: {\textcopyright} 2021 Elsevier B.V.",

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AB - I develop a method to extract only the priced factors from stock returns. The first step estimates expected returns based on firm characteristics. The second step uses the estimated expected returns to form portfolios. The last step uses principal component analysis to extract factors from the portfolio returns. The procedure isolates and emphasizes the comovement across assets that is related to expected returns as opposed to firm characteristics. It produces three factors–level, slope, and curve–which perform as well or better than other leading models. The methodology performs well in out-of-sample tests. The new factors have macroeconomic risk interpretations.

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KW - Cross-section of returns

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The level, slope, and curve factor model for stocks

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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