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Facts About Factors

24 Pages Posted: 17 Apr 2015  

Paula Cocoma

State Street Corporation

Megan Czasonis

State Street Corporation

Mark Kritzman

Massachusetts Institute of Technology (MIT) - Sloan School of Management

David Turkington

State Street Associates

Date Written: April 6, 2015

Abstract

It has become fashionable to allocate portfolios to factors rather than to assets. The often stated motivation for this approach is that factors are less correlated with each other than assets; therefore, factors afford greater opportunity for diversification. This argument is specious, of course, because ultimately the portfolio must be invested in assets. It is, therefore, impossible to produce a better in-sample portfolio by describing the portfolio as a set of factors than assets. There are several potentially legitimate arguments, though, for favoring factor stratification over asset stratification. It could be that factors are easier to forecast than assets, because investors are better able to relate current information to future factor behavior than to future asset behavior. Unfortunately, we have no way of testing this conjecture generically. But there are several testable conjectures. Perhaps risk estimated from high-frequency returns predicts risk over longer horizons more reliably for factors than for assets. Or the statistical properties of large samples may predict the statistical properties of small samples more reliably for factors than for assets. Or, for the same sample size, the statistical properties of factors may be more stationary from one sample to the next than they are for assets. Finally, it may be that reducing the dimensionality of a large set of assets to a smaller set of factors reduces noise more effectively than reducing dimensionality to a smaller set of assets. We offer empirical evidence of the validity, or lack thereof, of these testable conjectures.

Keywords: Asset allocation, Asset classes, Auto-correlation, Dimensionality, Diversification, Estimation error, Estimation sample, Factor, Factor allocation, Fundamental factor, GICS classification, High-frequency return, Independent-sample error, Interval error, Lagged cross-correlation, Low-frequency return

JEL Classification: C13, C40, D80, D84, G10, G11

Suggested Citation

Cocoma, Paula and Czasonis, Megan and Kritzman, Mark and Turkington, David, Facts About Factors (April 6, 2015). MIT Sloan Research Paper No. 5128-15. Available at SSRN: https://ssrn.com/abstract=2594485 or http://dx.doi.org/10.2139/ssrn.2594485

Paula Cocoma

State Street Corporation ( email )

1 Lincoln Street
Boston, MA 02111
United States

Megan Czasonis

State Street Corporation ( email )

1 Lincoln Street
Boston, MA 02111
United States

Mark Kritzman (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-416
Cambridge, MA 02142
United States

David Turkington

State Street Associates ( email )

United States

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