23
NOV

Option Return Predictability with Machine Learning and Big Data

Conférence
Ouvert au grand public
23.11.2021 17:15 - 18:45
Présentiel

Séminaire de recherche
Drawing upon more than 12 million observations over the period from 1996 to 2020, we find that allowing for nonlinearities significantly increases the out-of-sample performance of option and stock characteristics in predicting future option returns. Besides statistical significance, the nonlinear machine learning models generate economically sizeable profits in the long-short portfolios of equity options even after accounting for transaction costs. Although option-based characteristics are the most important standalone predictors, stock-based measures offer substantial incremental predictive power when considered alongside option-based characteristics. Finally, we provide compelling evidence that option return predictability is driven by informational frictions, costly arbitrage, and option mispricing.
Quand?
23.11.2021 17:15 - 18:45
Où?
Site PER 22 / Salle D230
Bd de Pérolles 90, 1700 Fribourg
Organisation
Chaire de Chaire de Finance et Gouvernance d'Entreprise
Intervenants
Pr. Florian Weigert (Université de Neuchâtel)
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