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| Content Provider | Springer Nature Link |
|---|---|
| Author | Lux, Thomas |
| Copyright Year | 2012 |
| Abstract | Maximum likelihood estimation of discretely observed diffusion processes is mostly hampered by the lack of a closed form solution of the transient density. It has recently been argued that a most generic remedy to this problem is the numerical solution of the pertinent Fokker–Planck (FP) or forward Kolmogorov equation. Here we expand existing work on univariate diffusions to higher dimensions. We find that in the bivariate and trivariate cases, a numerical solution of the FP equation via alternating direction finite difference schemes yields results surprisingly close to exact maximum likelihood in a number of test cases. After providing evidence for the efficiency of such a numerical approach, we illustrate its application for the estimation of a joint system of short-run and medium-run investor sentiment and asset price dynamics using German stock market data. |
| Starting Page | 217 |
| Ending Page | 248 |
| Page Count | 32 |
| File Format | |
| ISSN | 16142446 |
| Journal | Annals of Finance |
| Volume Number | 9 |
| Issue Number | 2 |
| e-ISSN | 16142454 |
| Language | English |
| Publisher | Springer-Verlag |
| Publisher Date | 2012-12-11 |
| Publisher Place | Berlin, Heidelberg |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Stochastic differential equations Numerical maximum likelihood Fokker–Planck equation Finite difference schemes Asset pricing Finance/Investment/Banking Macroeconomics/Monetary Economics Quantitative Finance |
| Content Type | Text |
| Resource Type | Article |
| Subject | Finance |
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