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Latent State and Parameter Estimation of Stochastic Volatility/Jump Models via Particle Filtering
Particle filtering in stochastic volatility/jump models has gained significant attention in the last decade, with many distinguished researchers adding their contributions to this new field. Golightly (2009), Carvalho et al. (2010), Johannes et al. (2009) and Aihara et al. (2008) all attempt to exte...
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| Format: | Thesis |
| Language: | English |
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African Institute of Financial Markets and Risk Management
2019
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| _version_ | 1867613219280912384 |
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| access_status_str | Open Access |
| author | Soane, Andrew |
| author_browse | Soane, Andrew |
| author_facet | Soane, Andrew |
| author_sort | Soane, Andrew |
| collection | Thesis |
| description | Particle filtering in stochastic volatility/jump models has gained significant attention in the last decade, with many distinguished researchers adding their contributions to this new field. Golightly (2009), Carvalho et al. (2010), Johannes et al. (2009) and Aihara et al. (2008) all attempt to extend the work of Pitt and Shephard (1999) and Liu and Chen (1998) to adapt particle filtering to latent state and parameter estimation in stochastic volatility/jump models. This dissertation will review their extensions and compare their accuracy at filtering the Bates stochastic volatility model. Additionally, this dissertation will provide an overview of particle filtering and the various contributions over the last three decades. Finally, recommendations will be made as to how to improve the results of this paper and explore further research opportunities. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/29223 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:32:39.476Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | African Institute of Financial Markets and Risk Management |
| publisherStr | African Institute of Financial Markets and Risk Management |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/29223 Latent State and Parameter Estimation of Stochastic Volatility/Jump Models via Particle Filtering Soane, Andrew Mathematical Finance Particle filtering in stochastic volatility/jump models has gained significant attention in the last decade, with many distinguished researchers adding their contributions to this new field. Golightly (2009), Carvalho et al. (2010), Johannes et al. (2009) and Aihara et al. (2008) all attempt to extend the work of Pitt and Shephard (1999) and Liu and Chen (1998) to adapt particle filtering to latent state and parameter estimation in stochastic volatility/jump models. This dissertation will review their extensions and compare their accuracy at filtering the Bates stochastic volatility model. Additionally, this dissertation will provide an overview of particle filtering and the various contributions over the last three decades. Finally, recommendations will be made as to how to improve the results of this paper and explore further research opportunities. 2019-02-04T11:25:03Z 2019-02-04T11:25:03Z 2018 2019-02-04T08:03:17Z Master Thesis Masters MPhil http://hdl.handle.net/11427/29223 eng application/pdf African Institute of Financial Markets and Risk Management Faculty of Commerce University of Cape Town |
| spellingShingle | Mathematical Finance Soane, Andrew Latent State and Parameter Estimation of Stochastic Volatility/Jump Models via Particle Filtering |
| thesis_degree_str | Master's |
| title | Latent State and Parameter Estimation of Stochastic Volatility/Jump Models via Particle Filtering |
| title_full | Latent State and Parameter Estimation of Stochastic Volatility/Jump Models via Particle Filtering |
| title_fullStr | Latent State and Parameter Estimation of Stochastic Volatility/Jump Models via Particle Filtering |
| title_full_unstemmed | Latent State and Parameter Estimation of Stochastic Volatility/Jump Models via Particle Filtering |
| title_short | Latent State and Parameter Estimation of Stochastic Volatility/Jump Models via Particle Filtering |
| title_sort | latent state and parameter estimation of stochastic volatility jump models via particle filtering |
| topic | Mathematical Finance |
| url | http://hdl.handle.net/11427/29223 |
| work_keys_str_mv | AT soaneandrew latentstateandparameterestimationofstochasticvolatilityjumpmodelsviaparticlefiltering |