Measuring 'Dark Matter' in Asset Pricing Models

Journal of Finance, Forthcoming

NBER Working Paper Series

The Rodney L. White Center Working Papers Series at the Wharton School

The Jacobs Levy Equity Management Center for Quantitative Financial Research Working Papers Series

The Wharton School Research Paper

Jacobs Levy Equity Management Center for Quantitative Financial Research Paper

60 Pages Posted: 19 Sep 2013 Last revised: 25 Jan 2022

See all articles by Hui Chen

Hui Chen

Massachusetts Institute of Technology; National Bureau of Economic Research (NBER)

Winston Wei Dou

The Wharton School, University of Pennsylvania; National Bureau of Economic Research (NBER)

Leonid Kogan

Massachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER)

Multiple version iconThere are 2 versions of this paper

Date Written: January 25, 2022

Abstract

We formalize the concept of ``dark matter'' in asset pricing models by quantifying the additional informativeness of cross-equation restrictions about fundamental dynamics. The dark matter measure captures the degree of fragility for models that are potentially misspecified and unstable: a large dark matter measure signifies that the model lacks internal refutability (weak power of optimal specification tests) and external validity (high overfitting tendency and poor out-of-sample fit). The measure can be computed at low cost even for complex dynamic structural models. To illustrate its applications, we provide quantitative examples applying the measure to (time-varying) rare-disaster risk and long-run risk models.



Keywords: Fragile beliefs, Unstable models, Misspecification and robustness, Out-of-sample fit, Semiparametric information bounds.

JEL Classification: C52, G12, D81, E32

Suggested Citation

Chen, Hui and Dou, Winston Wei and Kogan, Leonid, Measuring 'Dark Matter' in Asset Pricing Models (January 25, 2022). Journal of Finance, Forthcoming, NBER Working Paper Series, The Rodney L. White Center Working Papers Series at the Wharton School, The Jacobs Levy Equity Management Center for Quantitative Financial Research Working Papers Series, The Wharton School Research Paper, Jacobs Levy Equity Management Center for Quantitative Financial Research Paper, Available at SSRN: https://ssrn.com/abstract=2326753 or http://dx.doi.org/10.2139/ssrn.2326753

Hui Chen

Massachusetts Institute of Technology ( email )

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617-324-3896 (Phone)

National Bureau of Economic Research (NBER) ( email )

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Winston Wei Dou

The Wharton School, University of Pennsylvania ( email )

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HOME PAGE: http://finance-faculty.wharton.upenn.edu/wdou/

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HOME PAGE: http://www.nber.org/people/winston_wei_dou?page=1&perPage=50

Leonid Kogan (Contact Author)

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

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617-253-2289 (Phone)
617-258-6855 (Fax)

HOME PAGE: http://web.mit.edu/lkogan2/www/

National Bureau of Economic Research (NBER)

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United States

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