| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 5129911 | Statistics & Probability Letters | 2017 | 5 Pages |
Abstract
We propose a new non-iterative, very simple but accurate, Bayesian inference procedure for the stochastic volatility model. The only requirement of our approach is to solve a large, sparse linear system which we avoid by iteration.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Mike G. Tsionas,