General aggregation of misspecified asset pricing models

Arbeitspapier

This paper proposes an entropy-based approach for aggregating information from misspecified asset pricing models. The statistical paradigm is shifted away from parameter estimation of an optimally selected model to stochastic optimization based on a risk function of aggregation across models. The proposed method relaxes the perfect substitutability of the candidate models, which is implicitly embedded in the linear pooling procedures, and ensures that the aggregation weights are selected with a proper (Hellinger) distance measure that satisfies the triangle inequality. The empirical results illustrate the robustness and the pricing ability of the aggregation approach to stochastic discount factor models.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Working Paper ; No. 2017-10

Classification and Topics

• Classification: Wirtschaft ; Estimation: General ; Model Evaluation, Validation, and Selection ; Asset Pricing; Trading Volume; Bond Interest Rates
• Subject: entropy ; model aggregation ; asset pricing ; misspecified models ; oracle inequality ; Hellinger distance

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Gospodinov, Nikolaj ; Maasoumi, Esfandiar
• Event: Veröffentlichung
• (who): Federal Reserve Bank of Atlanta
• (where): Atlanta, Ga.
• (when): 2017

Further information

• Handle: http://hdl.handle.net/10419/200522
• Last update: 10.03.2025, 11:43 AM CET