Measuring "Dark Matter" in Asset Pricing Models / Hui Chen, Winston Wei Dou, Leonid Kogan.

Format:

Book

Author/Creator:

Chen, Hui.

Contributor:

National Bureau of Economic Research.

Dou, Winston Wei.

Kogan, Leonid.

Series:

Working Paper Series (National Bureau of Economic Research) no. w26418.

NBER working paper series no. w26418

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2019.

Summary:

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.

Notes:

Print version record

November 2019.