A Estimation of Stochastic Volatility Models Using Optimized Filtering Algorithms
In this paper, we describe and implement two recursive filtering algorithms, the optimized particle filter, and the Viterbi algorithm, which allow the joint estimation of states and parameters of continuous-time stochastic volatility models, such as the Cox Ingersoll Ross and Heston model. In practi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Austrian Statistical Society
2019-01-01
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| Series: | Austrian Journal of Statistics |
| Online Access: | http://www.ajs.or.at/index.php/ajs/article/view/803 |