Abstract
We characterize when physical probabilities, marginal utilities, and the discount rate can be recovered from observed state prices for several future time periods. Our characterization makes no assumptions of the probability distribution, thus generalizing the time-homogeneous stationary model of Ross (2015). Our characterization is simple and intuitive, linking recovery to the relation
between the number of time periods on the number of states. When recovery is feasible, our model is easy to implement, allowing a closed-form linearized solution. We implement our model empirically, testing the predictive power of the recovered expected return, crash risk, and other recovered statistics.
between the number of time periods on the number of states. When recovery is feasible, our model is easy to implement, allowing a closed-form linearized solution. We implement our model empirically, testing the predictive power of the recovered expected return, crash risk, and other recovered statistics.
| Original language | English |
|---|---|
| Publication date | 2017 |
| Number of pages | 58 |
| Publication status | Published - 2017 |
| Event | The 77th Annual Meeting of American Finance Association. AFA 2017 - Sheraton Grand Chicago, Chicago, United States Duration: 6 Jan 2017 → 8 Jan 2017 Conference number: 77 http://www.afajof.org/details/page/8672741/Paper-Submission-2017.html |
Conference
| Conference | The 77th Annual Meeting of American Finance Association. AFA 2017 |
|---|---|
| Number | 77 |
| Location | Sheraton Grand Chicago |
| Country/Territory | United States |
| City | Chicago |
| Period | 06/01/2017 → 08/01/2017 |
| Internet address |