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Measuring “Dark Matter” in Asset Pricing Models

Leonid Kogan - ; Hui Chen - ; Winston Wei Dou - ;

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 indicates 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.


Ketersediaan

Call NumberLocationAvailable
PSB lt.2 - Karya Akhir (Koleksi Majalah)1
PenerbitUSA: The American Finance Association 2024
EdisiVolume 79, Issue 2, April 2024, Pages 843-902
SubjekAsset pricing models
Long-Run Risk Models
Dynamic Structural Models
ISBN/ISSN1540-6261
KlasifikasiNONE
Deskripsi Fisikill, chart, table, grafik, 924 hal, 20 cm
Info Detail SpesifikThe Journal of Finance
Other Version/RelatedTidak tersedia versi lain
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