Closed-form likelihood expansions for multivariate diffusions
About
This paper provides closed-form expansions for the log-likelihood function of multivariate diffusions sampled at discrete time intervals. The coefficients of the expansion are calculated explicitly by exploiting the special structure afforded by the diffusion model. Examples of interest in financial statistics and Monte Carlo evidence are included, along with the convergence of the expansion to the true likelihood function.
Yacine A\"it-Sahalia• 2008
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Likelihood Approximation | Heston model 19 (test) | Relative Log-LH Error (mu*)0.0064 | 3 | |
| Likelihood Estimation | SVCEV model at mu* | Relative Error of Log-Likelihood0.63 | 3 | |
| Likelihood Approximation | Heston model n=200, Δ=1, Ntest=100 19 | Relative Error (log-lh)19.34 | 3 | |
| Likelihood Estimation | SVCEV model parameters {mu_i} (test) | Average Relative Error (Log-Likelihood)94.1 | 3 |
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