Unbiased Simulation Estimators for Multivariate Jump-Diffusions

Unbiased Simulation Estimators for Multivariate Jump-Diffusions

We develop and analyze a class of unbiased Monte Carlo estimators for multivariate jump-diffusion processes with state-dependent drift, volatility, jump intensity and jump size. A change of measure argument is used to extend existing unbiased estimators for the inter-arrival diffusion to include sta...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Chen, Guanting, Shkolnik, Alex, Giesecke, Kay
Format: Artikel
Sprache:eng
Schlagworte:
Mathematics - Probability
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator Chen, Guanting
Shkolnik, Alex
Giesecke, Kay
description We develop and analyze a class of unbiased Monte Carlo estimators for multivariate jump-diffusion processes with state-dependent drift, volatility, jump intensity and jump size. A change of measure argument is used to extend existing unbiased estimators for the inter-arrival diffusion to include state-dependent jumps. Under standard regularity conditions on the coefficient and target functions, we prove the unbiasedness and finite variance properties of the resulting jump-diffusion estimators. Numerical experiments illustrate the efficiency of our estimators.
doi_str_mv 10.48550/arxiv.2111.01846
format Article
fullrecord <record><control><sourceid>arxiv_GOX</sourceid><recordid>TN_cdi_arxiv_primary_2111_01846</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2111_01846</sourcerecordid><originalsourceid>FETCH-LOGICAL-a676-7ac286f0de31b12d42d049281e3aed4d26a64242d9044ebee1463bf063b4569a3</originalsourceid><addsrcrecordid>eNotj81OwzAQhH3hgAoPwKl-gQSvvXGTE0Kl_KmIQ8s52uC1ZClpKtup4O0JhcuMNBqN5hPiBlSJdVWpW4pf4VRqACgV1Ggvxd3HoQuU2MldGKaechgPcpNyGCiPMUk_Rvk29TmcKAbKLF-n4Vg8BO-nNFfTlbjw1Ce-_veF2D9u9uvnYvv-9LK-3xZkV7ZY0aeurVeODXSgHWqnsNE1sCF26LQli3pOG4XIHTOgNZ1Xs2BlGzILsfybPRO0xzj_i9_tL0l7JjE_F7NDsA</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Unbiased Simulation Estimators for Multivariate Jump-Diffusions</title><source>arXiv.org</source><creator>Chen, Guanting ; Shkolnik, Alex ; Giesecke, Kay</creator><creatorcontrib>Chen, Guanting ; Shkolnik, Alex ; Giesecke, Kay</creatorcontrib><description>We develop and analyze a class of unbiased Monte Carlo estimators for multivariate jump-diffusion processes with state-dependent drift, volatility, jump intensity and jump size. A change of measure argument is used to extend existing unbiased estimators for the inter-arrival diffusion to include state-dependent jumps. Under standard regularity conditions on the coefficient and target functions, we prove the unbiasedness and finite variance properties of the resulting jump-diffusion estimators. Numerical experiments illustrate the efficiency of our estimators.</description><identifier>DOI: 10.48550/arxiv.2111.01846</identifier><language>eng</language><subject>Mathematics - Probability</subject><creationdate>2021-11</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2111.01846$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2111.01846$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Chen, Guanting</creatorcontrib><creatorcontrib>Shkolnik, Alex</creatorcontrib><creatorcontrib>Giesecke, Kay</creatorcontrib><title>Unbiased Simulation Estimators for Multivariate Jump-Diffusions</title><description>We develop and analyze a class of unbiased Monte Carlo estimators for multivariate jump-diffusion processes with state-dependent drift, volatility, jump intensity and jump size. A change of measure argument is used to extend existing unbiased estimators for the inter-arrival diffusion to include state-dependent jumps. Under standard regularity conditions on the coefficient and target functions, we prove the unbiasedness and finite variance properties of the resulting jump-diffusion estimators. Numerical experiments illustrate the efficiency of our estimators.</description><subject>Mathematics - Probability</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotj81OwzAQhH3hgAoPwKl-gQSvvXGTE0Kl_KmIQ8s52uC1ZClpKtup4O0JhcuMNBqN5hPiBlSJdVWpW4pf4VRqACgV1Ggvxd3HoQuU2MldGKaechgPcpNyGCiPMUk_Rvk29TmcKAbKLF-n4Vg8BO-nNFfTlbjw1Ce-_veF2D9u9uvnYvv-9LK-3xZkV7ZY0aeurVeODXSgHWqnsNE1sCF26LQli3pOG4XIHTOgNZ1Xs2BlGzILsfybPRO0xzj_i9_tL0l7JjE_F7NDsA</recordid><startdate>20211102</startdate><enddate>20211102</enddate><creator>Chen, Guanting</creator><creator>Shkolnik, Alex</creator><creator>Giesecke, Kay</creator><scope>AKZ</scope><scope>GOX</scope></search><sort><creationdate>20211102</creationdate><title>Unbiased Simulation Estimators for Multivariate Jump-Diffusions</title><author>Chen, Guanting ; Shkolnik, Alex ; Giesecke, Kay</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a676-7ac286f0de31b12d42d049281e3aed4d26a64242d9044ebee1463bf063b4569a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Mathematics - Probability</topic><toplevel>online_resources</toplevel><creatorcontrib>Chen, Guanting</creatorcontrib><creatorcontrib>Shkolnik, Alex</creatorcontrib><creatorcontrib>Giesecke, Kay</creatorcontrib><collection>arXiv Mathematics</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Chen, Guanting</au><au>Shkolnik, Alex</au><au>Giesecke, Kay</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Unbiased Simulation Estimators for Multivariate Jump-Diffusions</atitle><date>2021-11-02</date><risdate>2021</risdate><abstract>We develop and analyze a class of unbiased Monte Carlo estimators for multivariate jump-diffusion processes with state-dependent drift, volatility, jump intensity and jump size. A change of measure argument is used to extend existing unbiased estimators for the inter-arrival diffusion to include state-dependent jumps. Under standard regularity conditions on the coefficient and target functions, we prove the unbiasedness and finite variance properties of the resulting jump-diffusion estimators. Numerical experiments illustrate the efficiency of our estimators.</abstract><doi>10.48550/arxiv.2111.01846</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier DOI: 10.48550/arxiv.2111.01846
ispartof
issn
language eng
recordid cdi_arxiv_primary_2111_01846
source arXiv.org
subjects Mathematics - Probability
title Unbiased Simulation Estimators for Multivariate Jump-Diffusions
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-11T16%3A16%3A33IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-arxiv_GOX&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Unbiased%20Simulation%20Estimators%20for%20Multivariate%20Jump-Diffusions&rft.au=Chen,%20Guanting&rft.date=2021-11-02&rft_id=info:doi/10.48550/arxiv.2111.01846&rft_dat=%3Carxiv_GOX%3E2111_01846%3C/arxiv_GOX%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true