Abstract
Ross (2015) introduced a remarkable theorem, named the “Recovery Theorem.” It enables us to estimate the real world distribution from the risk neutral distribution derived from option prices under a particular assumption about a representative investor's risk preferences. The real world distribution estimated with the Recovery Theorem is suitable for many financial problems such as market risk management and portfolio optimization due to its forward looking nature. However, it is not easy to derive the appropriate estimators because of an ill-posed problem in the estimation process. We propose a new method to derive the accurate solution by formulating the regularization term involving prior information. Previous studies propose methods to estimate the real world distribution, but they do not investigate the estimation accuracy. We show the effectiveness of the proposed method through the numerical analysis with hypothetical data.
Original language | English |
---|---|
Pages (from-to) | 83-107 |
Number of pages | 25 |
Journal | Journal of the Operations Research Society of Japan |
Volume | 62 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2019 |
Keywords
- Estimation
- Finance
- Recovery Theorem
- Regularization
ASJC Scopus subject areas
- Decision Sciences(all)
- Management Science and Operations Research