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| Content Provider | Springer Nature Link |
|---|---|
| Author | Nakamura, buhiro |
| Copyright Year | 2006 |
| Abstract | In this paper employing two heuristic numerical schemes, we study the asset pricing models with stochastic differential utility (SDU), which is formulated by either of backward stochastic differential equations (BSDEs) or forward-backward stochastic differential equations (FBSDEs).The first scheme is based upon a traditional lattice algorithm of option pricing theories, involving the discretization scheme of coupled FBSDEs, which is combined with a technique of solving numerically a certain type of nonlinear equations with respect to the backward state variables. The second one is based upon the four step scheme of Ma et al. (1994) which solves quasi-linear partial differential equations associated with the FBSDEs. We demonstrate that our practical implementation algorithms can successfully solve the asset pricing models with generalized SDU and the large investor problem with market impact which are typical examples such that the usual four step scheme is difficult to implement. As other numerical applications we study the optimal consumption and investment policies of a representative agent with SDU, and the recoverability of preferences and beliefs from observed consumption data. |
| Starting Page | 267 |
| Ending Page | 300 |
| Page Count | 34 |
| File Format | |
| ISSN | 13872834 |
| Journal | Asia-Pacific Financial Markets |
| Volume Number | 11 |
| Issue Number | 3 |
| e-ISSN | 15736946 |
| Language | English |
| Publisher | Kluwer Academic Publishers-Plenum Publishers |
| Publisher Date | 2006-07-07 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | stochastic differential utility forward-backward stochastic differential equation lattice algorithm four step scheme Finance /Banking Financial Economics International Economics Economic Theory Econometrics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Finance |
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