Learning and Index Option Returns
Bibliographic Data
| ID | 19418998 |
|---|---|
| Authors | Alejandro Bernales (0000-0003-1539-966X, Universidad de Chile, Centro de Economía Aplicada and Centro de Finanzas, DII, Republica 701, Santiago, Chile (), corresponding author), Gonzalo Cortazar (Pontificia Universidad Católica de Chile), Luka Salamunic (Pontificia Universidad Católica de Chile), George Skiadopoulos (0000-0002-9111-2280, Department of Banking and Financial Management, University of Piraeus, Karaoli and Dimitriou 80, Piraeus 18534, Greece, and School of Economics and Finance, Queen Mary University of London, Mile End Road. E1 4NS, London, United Kingdom. (, )) |
| Year | 2020 |
| Volume | 38 |
| Issue | 2 |
| Pages | 327-339 |
| Publication date | 2020-04-02 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07350015.2018.1505629 |
| OpenAlex | W2885851700 |
| Language | EN |
| References cited | 36 |
Little is known about the economic sources that may generate the abnormal returns observed in put index options. We show that the learning process followed by investors may be one such source. We develop an equilibrium model under partial information in which a rational Bayesian learner prices put option contracts. Our model generates put option returns similar to the empirical returns of S&P 500 put index options. This result is not obtained when we analyze alternative setups of the model in which no learning process exists
Bayesian inference · Bayesian probability · Econometrics · Economics · Capital Investment and Risk Analysis · Computer Science · Economic theories and models · Stochastic processes and financial applications · Artificial Intelligence
| Highly cited | No |
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