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Bayesian Solutions for the Factor Zoo : We Just Ran Two Quadrillion Models
We propose a novel framework for analyzing linear asset pricing models: simple, robust, and applicable to high-dimensional problems. For a (potentially misspecified) stand-alone model, it provides reliable price of risk estimates for both tradable and nontradable factors, and detects those weakly identified. For competing factors and (possibly nonnested) models, the method automatically selects the best specification—if a dominant one exists—or provides a Bayesian model averaging–stochastic discount factor (BMA-SDF), if there is no clear winner. We analyze 2.25 quadrillion models generated by a large set of factors and find that the BMA-SDF outperforms existing models in- and out-of-sample.
Ketersediaan
| Call Number | Location | Available |
|---|---|---|
| PSB lt.dasar - Pascasarjana (Koleksi Majalah) | 1 |
| Penerbit | USA: The American Finance Association 2023 |
|---|---|
| Edisi | Volume 78, Issue 1, February 2023, Pages 487-557 |
| Subjek | Bayesian model Asset pricing models Quadrillion Models |
| ISBN/ISSN | 1540-6261 |
| Klasifikasi | NONE |
| Deskripsi Fisik | First Published: 10 December 2022 |
| Info Detail Spesifik | The Journal of Finance |
| Other Version/Related | Tidak tersedia versi lain |
| Lampiran Berkas |