Measuring “Dark Matter” in Asset Pricing Models
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...
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| Veröffentlicht in: | NBER Working Paper Series 2019-11, p.26418 |
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| creator | Chen, Hui Dou, Winston Wei Kogan, Leonid |
| description | 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. |
| doi_str_mv | 10.3386/w26418 |
| format | Article |
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| identifier | ISSN: 0898-2937 |
| ispartof | NBER Working Paper Series, 2019-11, p.26418 |
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| language | eng |
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| source | National Bureau of Economic Research Publications; Alma/SFX Local Collection |
| subjects | Asset Pricing Capital markets Cosmology Dark matter Economic models Economic theory Sensitivity analysis |
| title | Measuring “Dark Matter” in Asset Pricing Models |
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