The Split-SV model
A modification of one of the most popular stochastic model in describing financial indexes dynamics is introduced. For describing a nonlinear behavior of volatility, a threshold noise indicator in the autoregressive time series of stochastic volatility is used. Toward this end, the model named the S...
Gespeichert in:
| Veröffentlicht in: | Computational statistics & data analysis 2016-08, Vol.100, p.560-581 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 581 |
|---|---|
| container_issue | |
| container_start_page | 560 |
| container_title | Computational statistics & data analysis |
| container_volume | 100 |
| creator | Stojanovica, Vladica S Popovicb, Biljana C Milovanovicc, Gradimir V |
| description | A modification of one of the most popular stochastic model in describing financial indexes dynamics is introduced. For describing a nonlinear behavior of volatility, a threshold noise indicator in the autoregressive time series of stochastic volatility is used. Toward this end, the model named the Split-SV model is introduced and its basic stochastic properties are investigated. Furthermore, the Empirical Characteristic Function (ECF) method is used for obtaining the parameter estimations of the model and a numerical simulation of the obtained estimates is given as well. Finally, the Split-SV model is applied for fitting the empirical data: the daily returns of the exchange rates of GBP and USD per euro. |
| doi_str_mv | 10.1016/j.csda.2014.08.010 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1825476824</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0167947314002424</els_id><sourcerecordid>1825476824</sourcerecordid><originalsourceid>FETCH-LOGICAL-c333t-4a1dbdfffd1f039181d8235468f55f2027c786eac3f42b8aede5de13fd8c14403</originalsourceid><addsrcrecordid>eNp9kL1PwzAQRy0EEqGwMDJ1ZEm4s53YlVhQxZdUiaGF1XLts3CVNsFOkfjvSVVmplve-0n3GLtBqBCwudtULntbcUBZga4A4YQVqBUvlaj5KStGSJUzqcQ5u8h5AwBcKl2w69UnTZd9G4dy-THddp7aS3YWbJvp6u9O2PvT42r-Ui7enl_nD4vSCSGGUlr0ax9C8BhAzFCj11zUstGhrgMHrpzSDVknguRrbclT7QlF8NqhlCAm7Pa426fua095MNuYHbWt3VG3zwY1r6VqNJcjyo-oS13OiYLpU9za9GMQzCGA2ZhDAHMIYECbMcAo3R8lGp_4jpRMdpF2jnxM5Abju_if_guHeWGq</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1825476824</pqid></control><display><type>article</type><title>The Split-SV model</title><source>Elsevier ScienceDirect Journals Complete</source><creator>Stojanovica, Vladica S ; Popovicb, Biljana C ; Milovanovicc, Gradimir V</creator><creatorcontrib>Stojanovica, Vladica S ; Popovicb, Biljana C ; Milovanovicc, Gradimir V</creatorcontrib><description>A modification of one of the most popular stochastic model in describing financial indexes dynamics is introduced. For describing a nonlinear behavior of volatility, a threshold noise indicator in the autoregressive time series of stochastic volatility is used. Toward this end, the model named the Split-SV model is introduced and its basic stochastic properties are investigated. Furthermore, the Empirical Characteristic Function (ECF) method is used for obtaining the parameter estimations of the model and a numerical simulation of the obtained estimates is given as well. Finally, the Split-SV model is applied for fitting the empirical data: the daily returns of the exchange rates of GBP and USD per euro.</description><identifier>ISSN: 0167-9473</identifier><identifier>EISSN: 1872-7352</identifier><identifier>DOI: 10.1016/j.csda.2014.08.010</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Contaminated Gaussian distribution ; Convolutions ; Empirical analysis ; Empirical characteristic function estimation ; Exchange ; Fittings ; Mathematical models ; Noise-indicator ; Nonlinear dynamics ; Split-SV process ; Statistics ; Stochasticity ; Volatility</subject><ispartof>Computational statistics & data analysis, 2016-08, Vol.100, p.560-581</ispartof><rights>2014 Elsevier B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c333t-4a1dbdfffd1f039181d8235468f55f2027c786eac3f42b8aede5de13fd8c14403</citedby><cites>FETCH-LOGICAL-c333t-4a1dbdfffd1f039181d8235468f55f2027c786eac3f42b8aede5de13fd8c14403</cites><orcidid>0000-0001-6504-6956 ; 0000-0002-3255-8127</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0167947314002424$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65534</link.rule.ids></links><search><creatorcontrib>Stojanovica, Vladica S</creatorcontrib><creatorcontrib>Popovicb, Biljana C</creatorcontrib><creatorcontrib>Milovanovicc, Gradimir V</creatorcontrib><title>The Split-SV model</title><title>Computational statistics & data analysis</title><description>A modification of one of the most popular stochastic model in describing financial indexes dynamics is introduced. For describing a nonlinear behavior of volatility, a threshold noise indicator in the autoregressive time series of stochastic volatility is used. Toward this end, the model named the Split-SV model is introduced and its basic stochastic properties are investigated. Furthermore, the Empirical Characteristic Function (ECF) method is used for obtaining the parameter estimations of the model and a numerical simulation of the obtained estimates is given as well. Finally, the Split-SV model is applied for fitting the empirical data: the daily returns of the exchange rates of GBP and USD per euro.</description><subject>Contaminated Gaussian distribution</subject><subject>Convolutions</subject><subject>Empirical analysis</subject><subject>Empirical characteristic function estimation</subject><subject>Exchange</subject><subject>Fittings</subject><subject>Mathematical models</subject><subject>Noise-indicator</subject><subject>Nonlinear dynamics</subject><subject>Split-SV process</subject><subject>Statistics</subject><subject>Stochasticity</subject><subject>Volatility</subject><issn>0167-9473</issn><issn>1872-7352</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNp9kL1PwzAQRy0EEqGwMDJ1ZEm4s53YlVhQxZdUiaGF1XLts3CVNsFOkfjvSVVmplve-0n3GLtBqBCwudtULntbcUBZga4A4YQVqBUvlaj5KStGSJUzqcQ5u8h5AwBcKl2w69UnTZd9G4dy-THddp7aS3YWbJvp6u9O2PvT42r-Ui7enl_nD4vSCSGGUlr0ax9C8BhAzFCj11zUstGhrgMHrpzSDVknguRrbclT7QlF8NqhlCAm7Pa426fua095MNuYHbWt3VG3zwY1r6VqNJcjyo-oS13OiYLpU9za9GMQzCGA2ZhDAHMIYECbMcAo3R8lGp_4jpRMdpF2jnxM5Abju_if_guHeWGq</recordid><startdate>201608</startdate><enddate>201608</enddate><creator>Stojanovica, Vladica S</creator><creator>Popovicb, Biljana C</creator><creator>Milovanovicc, Gradimir V</creator><general>Elsevier B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-6504-6956</orcidid><orcidid>https://orcid.org/0000-0002-3255-8127</orcidid></search><sort><creationdate>201608</creationdate><title>The Split-SV model</title><author>Stojanovica, Vladica S ; Popovicb, Biljana C ; Milovanovicc, Gradimir V</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c333t-4a1dbdfffd1f039181d8235468f55f2027c786eac3f42b8aede5de13fd8c14403</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Contaminated Gaussian distribution</topic><topic>Convolutions</topic><topic>Empirical analysis</topic><topic>Empirical characteristic function estimation</topic><topic>Exchange</topic><topic>Fittings</topic><topic>Mathematical models</topic><topic>Noise-indicator</topic><topic>Nonlinear dynamics</topic><topic>Split-SV process</topic><topic>Statistics</topic><topic>Stochasticity</topic><topic>Volatility</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Stojanovica, Vladica S</creatorcontrib><creatorcontrib>Popovicb, Biljana C</creatorcontrib><creatorcontrib>Milovanovicc, Gradimir V</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computational statistics & data analysis</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Stojanovica, Vladica S</au><au>Popovicb, Biljana C</au><au>Milovanovicc, Gradimir V</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Split-SV model</atitle><jtitle>Computational statistics & data analysis</jtitle><date>2016-08</date><risdate>2016</risdate><volume>100</volume><spage>560</spage><epage>581</epage><pages>560-581</pages><issn>0167-9473</issn><eissn>1872-7352</eissn><abstract>A modification of one of the most popular stochastic model in describing financial indexes dynamics is introduced. For describing a nonlinear behavior of volatility, a threshold noise indicator in the autoregressive time series of stochastic volatility is used. Toward this end, the model named the Split-SV model is introduced and its basic stochastic properties are investigated. Furthermore, the Empirical Characteristic Function (ECF) method is used for obtaining the parameter estimations of the model and a numerical simulation of the obtained estimates is given as well. Finally, the Split-SV model is applied for fitting the empirical data: the daily returns of the exchange rates of GBP and USD per euro.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.csda.2014.08.010</doi><tpages>22</tpages><orcidid>https://orcid.org/0000-0001-6504-6956</orcidid><orcidid>https://orcid.org/0000-0002-3255-8127</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0167-9473 |
| ispartof | Computational statistics & data analysis, 2016-08, Vol.100, p.560-581 |
| issn | 0167-9473 1872-7352 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1825476824 |
| source | Elsevier ScienceDirect Journals Complete |
| subjects | Contaminated Gaussian distribution Convolutions Empirical analysis Empirical characteristic function estimation Exchange Fittings Mathematical models Noise-indicator Nonlinear dynamics Split-SV process Statistics Stochasticity Volatility |
| title | The Split-SV model |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-19T06%3A04%3A24IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=The%20Split-SV%20model&rft.jtitle=Computational%20statistics%20&%20data%20analysis&rft.au=Stojanovica,%20Vladica%20S&rft.date=2016-08&rft.volume=100&rft.spage=560&rft.epage=581&rft.pages=560-581&rft.issn=0167-9473&rft.eissn=1872-7352&rft_id=info:doi/10.1016/j.csda.2014.08.010&rft_dat=%3Cproquest_cross%3E1825476824%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1825476824&rft_id=info:pmid/&rft_els_id=S0167947314002424&rfr_iscdi=true |