Measuring the “Dark Matter” in Asset Pricing Models

Joint with Hui Chen, Leonid Kogan

Journal of Finance (2024) Vol. 79, No. 2, 843-902

We formalize the concept of ``dark matter'' in asset pricing models by quantifying additional information the econometrician can obtain about the fundamental dynamics from asset pricing cross-equation restrictions. The dark matter measure essentially serves as an information-based fragility measure for models that are potentially misspecified and unstable: a large dark matter measure signifies a model's lack of internal refutability (weak power of specification tests) and external validity (high overfitting tendency and poor out-of-sample fit). It can be computed at low cost even for complex dynamic structural models. We illustrate its applications via (time-varying) rare-disaster risk and long-run risk models.