Abstract
This article surveys some of the recent developments in the modeling of heteroskedastic financial time series. Both discrete-time and continuous-time frameworks for some commonly used models and their estimating methodologies are discussed. In particular, the recently popularized long-memory heteroskedastic models are reviewed. A simulation-based Bayesian approach for long-memory stochastic volatility models is proposed. The paper concludes with an illustration of the proposed method applying to a value-weighted index from the Center for Research in Security Prices.
| Original language | English |
|---|---|
| Title of host publication | Statistics and Finance: An Interface |
| Subtitle of host publication | Proceedings of the Hong Kong International Workshop on Statistics in Finance, The University of Hong Kong, 4 – 8 July 1999 |
| Editors | Wai-Sum Chan , Wai Keung Li, Howell Tong |
| Publisher | Imperial College Press |
| Pages | 169-184 |
| ISBN (Electronic) | 978-1-78326-166-6, 978-1-84816-015-6 |
| ISBN (Print) | 978-1-86094-237-2 |
| DOIs | |
| Publication status | Published - 2000 |
| Externally published | Yes |
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