An iterative algorithm to determine the number of time steps in path generation methods
The construction of Brownian motion paths is the most important part of simulation methods for option pricing. Particularly, there are several commonly used path generation methods in the context of quasi‐Monte Carlo, including the standard method and the Brownian bridge method. To apply each method...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Fan, Chenxi [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2016 |
|---|
| Rechteinformationen: |
Nutzungsrecht: Copyright © 2016 John Wiley & Sons, Ltd. |
|---|
| Schlagwörter: |
applications to actuarial sciences and financial mathematics |
|---|
| Übergeordnetes Werk: |
Enthalten in: Mathematical methods in the applied sciences - Chichester, West Sussex : Wiley, 1979, 39(2016), 9, Seite 2182-2192 |
|---|---|
| Übergeordnetes Werk: |
volume:39 ; year:2016 ; number:9 ; pages:2182-2192 |
| Links: |
|---|
| DOI / URN: |
10.1002/mma.3632 |
|---|
| Katalog-ID: |
OLC1977811639 |
|---|
| LEADER | 01000caa a2200265 4500 | ||
|---|---|---|---|
| 001 | OLC1977811639 | ||
| 003 | DE-627 | ||
| 005 | 20220220080858.0 | ||
| 007 | tu | ||
| 008 | 160719s2016 xx ||||| 00| ||eng c | ||
| 024 | 7 | |a 10.1002/mma.3632 |2 doi | |
| 028 | 5 | 2 | |a PQ20160719 |
| 035 | |a (DE-627)OLC1977811639 | ||
| 035 | |a (DE-599)GBVOLC1977811639 | ||
| 035 | |a (PRQ)c952-a96169dd63bdb7f4d8c011f76857d2d9c888d9f6319767933a82dfb2beebc2423 | ||
| 035 | |a (KEY)0093427520160000039000902182iterativealgorithmtodeterminethenumberoftimestepsi | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 510 |q DE-600 |
| 084 | |a 31.80 |2 bkl | ||
| 100 | 1 | |a Fan, Chenxi |e verfasserin |4 aut | |
| 245 | 1 | 3 | |a An iterative algorithm to determine the number of time steps in path generation methods |
| 264 | 1 | |c 2016 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
| 338 | |a Band |b nc |2 rdacarrier | ||
| 520 | |a The construction of Brownian motion paths is the most important part of simulation methods for option pricing. Particularly, there are several commonly used path generation methods in the context of quasi‐Monte Carlo, including the standard method and the Brownian bridge method. To apply each method, an inevitable step is to decide how many points are used to discretize the time interval. This paper implements an iterative algorithm to select a suitable number of time steps by successively adding discretization nodes until a specific convergence criterion is met. Numerical results with this algorithm are presented in the valuation of Asian options. Copyright © 2016 John Wiley & Sons, Ltd. | ||
| 540 | |a Nutzungsrecht: Copyright © 2016 John Wiley & Sons, Ltd. | ||
| 650 | 4 | |a applications to actuarial sciences and financial mathematics | |
| 650 | 4 | |a quasi‐Monte Carlo methods | |
| 650 | 4 | |a option pricing | |
| 650 | 4 | |a Monte Carlo methods | |
| 650 | 4 | |a path generation methods | |
| 650 | 4 | |a Brownian bridge methods | |
| 700 | 1 | |a Wu, Qingbiao |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |t Mathematical methods in the applied sciences |d Chichester, West Sussex : Wiley, 1979 |g 39(2016), 9, Seite 2182-2192 |w (DE-627)130619051 |w (DE-600)795328-8 |w (DE-576)016125967 |x 0170-4214 |7 nnns |
| 773 | 1 | 8 | |g volume:39 |g year:2016 |g number:9 |g pages:2182-2192 |
| 856 | 4 | 1 | |u http://dx.doi.org/10.1002/mma.3632 |3 Volltext |
| 856 | 4 | 2 | |u http://onlinelibrary.wiley.com/doi/10.1002/mma.3632/abstract |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_OLC | ||
| 912 | |a SSG-OLC-MAT | ||
| 912 | |a SSG-OPC-MAT | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_4318 | ||
| 936 | b | k | |a 31.80 |q AVZ |
| 951 | |a AR | ||
| 952 | |d 39 |j 2016 |e 9 |h 2182-2192 | ||
| author_variant |
c f cf |
|---|---|
| matchkey_str |
article:01704214:2016----::ntrtvagrtmoeemnteubrfietpip |
| hierarchy_sort_str |
2016 |
| bklnumber |
31.80 |
| publishDate |
2016 |
| allfields |
10.1002/mma.3632 doi PQ20160719 (DE-627)OLC1977811639 (DE-599)GBVOLC1977811639 (PRQ)c952-a96169dd63bdb7f4d8c011f76857d2d9c888d9f6319767933a82dfb2beebc2423 (KEY)0093427520160000039000902182iterativealgorithmtodeterminethenumberoftimestepsi DE-627 ger DE-627 rakwb eng 510 DE-600 31.80 bkl Fan, Chenxi verfasserin aut An iterative algorithm to determine the number of time steps in path generation methods 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The construction of Brownian motion paths is the most important part of simulation methods for option pricing. Particularly, there are several commonly used path generation methods in the context of quasi‐Monte Carlo, including the standard method and the Brownian bridge method. To apply each method, an inevitable step is to decide how many points are used to discretize the time interval. This paper implements an iterative algorithm to select a suitable number of time steps by successively adding discretization nodes until a specific convergence criterion is met. Numerical results with this algorithm are presented in the valuation of Asian options. Copyright © 2016 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2016 John Wiley & Sons, Ltd. applications to actuarial sciences and financial mathematics quasi‐Monte Carlo methods option pricing Monte Carlo methods path generation methods Brownian bridge methods Wu, Qingbiao oth Enthalten in Mathematical methods in the applied sciences Chichester, West Sussex : Wiley, 1979 39(2016), 9, Seite 2182-2192 (DE-627)130619051 (DE-600)795328-8 (DE-576)016125967 0170-4214 nnns volume:39 year:2016 number:9 pages:2182-2192 http://dx.doi.org/10.1002/mma.3632 Volltext http://onlinelibrary.wiley.com/doi/10.1002/mma.3632/abstract GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4318 31.80 AVZ AR 39 2016 9 2182-2192 |
| spelling |
10.1002/mma.3632 doi PQ20160719 (DE-627)OLC1977811639 (DE-599)GBVOLC1977811639 (PRQ)c952-a96169dd63bdb7f4d8c011f76857d2d9c888d9f6319767933a82dfb2beebc2423 (KEY)0093427520160000039000902182iterativealgorithmtodeterminethenumberoftimestepsi DE-627 ger DE-627 rakwb eng 510 DE-600 31.80 bkl Fan, Chenxi verfasserin aut An iterative algorithm to determine the number of time steps in path generation methods 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The construction of Brownian motion paths is the most important part of simulation methods for option pricing. Particularly, there are several commonly used path generation methods in the context of quasi‐Monte Carlo, including the standard method and the Brownian bridge method. To apply each method, an inevitable step is to decide how many points are used to discretize the time interval. This paper implements an iterative algorithm to select a suitable number of time steps by successively adding discretization nodes until a specific convergence criterion is met. Numerical results with this algorithm are presented in the valuation of Asian options. Copyright © 2016 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2016 John Wiley & Sons, Ltd. applications to actuarial sciences and financial mathematics quasi‐Monte Carlo methods option pricing Monte Carlo methods path generation methods Brownian bridge methods Wu, Qingbiao oth Enthalten in Mathematical methods in the applied sciences Chichester, West Sussex : Wiley, 1979 39(2016), 9, Seite 2182-2192 (DE-627)130619051 (DE-600)795328-8 (DE-576)016125967 0170-4214 nnns volume:39 year:2016 number:9 pages:2182-2192 http://dx.doi.org/10.1002/mma.3632 Volltext http://onlinelibrary.wiley.com/doi/10.1002/mma.3632/abstract GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4318 31.80 AVZ AR 39 2016 9 2182-2192 |
| allfields_unstemmed |
10.1002/mma.3632 doi PQ20160719 (DE-627)OLC1977811639 (DE-599)GBVOLC1977811639 (PRQ)c952-a96169dd63bdb7f4d8c011f76857d2d9c888d9f6319767933a82dfb2beebc2423 (KEY)0093427520160000039000902182iterativealgorithmtodeterminethenumberoftimestepsi DE-627 ger DE-627 rakwb eng 510 DE-600 31.80 bkl Fan, Chenxi verfasserin aut An iterative algorithm to determine the number of time steps in path generation methods 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The construction of Brownian motion paths is the most important part of simulation methods for option pricing. Particularly, there are several commonly used path generation methods in the context of quasi‐Monte Carlo, including the standard method and the Brownian bridge method. To apply each method, an inevitable step is to decide how many points are used to discretize the time interval. This paper implements an iterative algorithm to select a suitable number of time steps by successively adding discretization nodes until a specific convergence criterion is met. Numerical results with this algorithm are presented in the valuation of Asian options. Copyright © 2016 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2016 John Wiley & Sons, Ltd. applications to actuarial sciences and financial mathematics quasi‐Monte Carlo methods option pricing Monte Carlo methods path generation methods Brownian bridge methods Wu, Qingbiao oth Enthalten in Mathematical methods in the applied sciences Chichester, West Sussex : Wiley, 1979 39(2016), 9, Seite 2182-2192 (DE-627)130619051 (DE-600)795328-8 (DE-576)016125967 0170-4214 nnns volume:39 year:2016 number:9 pages:2182-2192 http://dx.doi.org/10.1002/mma.3632 Volltext http://onlinelibrary.wiley.com/doi/10.1002/mma.3632/abstract GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4318 31.80 AVZ AR 39 2016 9 2182-2192 |
| allfieldsGer |
10.1002/mma.3632 doi PQ20160719 (DE-627)OLC1977811639 (DE-599)GBVOLC1977811639 (PRQ)c952-a96169dd63bdb7f4d8c011f76857d2d9c888d9f6319767933a82dfb2beebc2423 (KEY)0093427520160000039000902182iterativealgorithmtodeterminethenumberoftimestepsi DE-627 ger DE-627 rakwb eng 510 DE-600 31.80 bkl Fan, Chenxi verfasserin aut An iterative algorithm to determine the number of time steps in path generation methods 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The construction of Brownian motion paths is the most important part of simulation methods for option pricing. Particularly, there are several commonly used path generation methods in the context of quasi‐Monte Carlo, including the standard method and the Brownian bridge method. To apply each method, an inevitable step is to decide how many points are used to discretize the time interval. This paper implements an iterative algorithm to select a suitable number of time steps by successively adding discretization nodes until a specific convergence criterion is met. Numerical results with this algorithm are presented in the valuation of Asian options. Copyright © 2016 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2016 John Wiley & Sons, Ltd. applications to actuarial sciences and financial mathematics quasi‐Monte Carlo methods option pricing Monte Carlo methods path generation methods Brownian bridge methods Wu, Qingbiao oth Enthalten in Mathematical methods in the applied sciences Chichester, West Sussex : Wiley, 1979 39(2016), 9, Seite 2182-2192 (DE-627)130619051 (DE-600)795328-8 (DE-576)016125967 0170-4214 nnns volume:39 year:2016 number:9 pages:2182-2192 http://dx.doi.org/10.1002/mma.3632 Volltext http://onlinelibrary.wiley.com/doi/10.1002/mma.3632/abstract GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4318 31.80 AVZ AR 39 2016 9 2182-2192 |
| allfieldsSound |
10.1002/mma.3632 doi PQ20160719 (DE-627)OLC1977811639 (DE-599)GBVOLC1977811639 (PRQ)c952-a96169dd63bdb7f4d8c011f76857d2d9c888d9f6319767933a82dfb2beebc2423 (KEY)0093427520160000039000902182iterativealgorithmtodeterminethenumberoftimestepsi DE-627 ger DE-627 rakwb eng 510 DE-600 31.80 bkl Fan, Chenxi verfasserin aut An iterative algorithm to determine the number of time steps in path generation methods 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The construction of Brownian motion paths is the most important part of simulation methods for option pricing. Particularly, there are several commonly used path generation methods in the context of quasi‐Monte Carlo, including the standard method and the Brownian bridge method. To apply each method, an inevitable step is to decide how many points are used to discretize the time interval. This paper implements an iterative algorithm to select a suitable number of time steps by successively adding discretization nodes until a specific convergence criterion is met. Numerical results with this algorithm are presented in the valuation of Asian options. Copyright © 2016 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2016 John Wiley & Sons, Ltd. applications to actuarial sciences and financial mathematics quasi‐Monte Carlo methods option pricing Monte Carlo methods path generation methods Brownian bridge methods Wu, Qingbiao oth Enthalten in Mathematical methods in the applied sciences Chichester, West Sussex : Wiley, 1979 39(2016), 9, Seite 2182-2192 (DE-627)130619051 (DE-600)795328-8 (DE-576)016125967 0170-4214 nnns volume:39 year:2016 number:9 pages:2182-2192 http://dx.doi.org/10.1002/mma.3632 Volltext http://onlinelibrary.wiley.com/doi/10.1002/mma.3632/abstract GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4318 31.80 AVZ AR 39 2016 9 2182-2192 |
| language |
English |
| source |
Enthalten in Mathematical methods in the applied sciences 39(2016), 9, Seite 2182-2192 volume:39 year:2016 number:9 pages:2182-2192 |
| sourceStr |
Enthalten in Mathematical methods in the applied sciences 39(2016), 9, Seite 2182-2192 volume:39 year:2016 number:9 pages:2182-2192 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
applications to actuarial sciences and financial mathematics quasi‐Monte Carlo methods option pricing Monte Carlo methods path generation methods Brownian bridge methods |
| dewey-raw |
510 |
| isfreeaccess_bool |
false |
| container_title |
Mathematical methods in the applied sciences |
| authorswithroles_txt_mv |
Fan, Chenxi @@aut@@ Wu, Qingbiao @@oth@@ |
| publishDateDaySort_date |
2016-01-01T00:00:00Z |
| hierarchy_top_id |
130619051 |
| dewey-sort |
3510 |
| id |
OLC1977811639 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1977811639</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220220080858.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">160719s2016 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1002/mma.3632</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20160719</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1977811639</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1977811639</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)c952-a96169dd63bdb7f4d8c011f76857d2d9c888d9f6319767933a82dfb2beebc2423</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0093427520160000039000902182iterativealgorithmtodeterminethenumberoftimestepsi</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">510</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">31.80</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Fan, Chenxi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="3"><subfield code="a">An iterative algorithm to determine the number of time steps in path generation methods</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The construction of Brownian motion paths is the most important part of simulation methods for option pricing. Particularly, there are several commonly used path generation methods in the context of quasi‐Monte Carlo, including the standard method and the Brownian bridge method. To apply each method, an inevitable step is to decide how many points are used to discretize the time interval. This paper implements an iterative algorithm to select a suitable number of time steps by successively adding discretization nodes until a specific convergence criterion is met. Numerical results with this algorithm are presented in the valuation of Asian options. Copyright © 2016 John Wiley & Sons, Ltd.</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="a">Nutzungsrecht: Copyright © 2016 John Wiley & Sons, Ltd.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">applications to actuarial sciences and financial mathematics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">quasi‐Monte Carlo methods</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">option pricing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Monte Carlo methods</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">path generation methods</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Brownian bridge methods</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wu, Qingbiao</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Mathematical methods in the applied sciences</subfield><subfield code="d">Chichester, West Sussex : Wiley, 1979</subfield><subfield code="g">39(2016), 9, Seite 2182-2192</subfield><subfield code="w">(DE-627)130619051</subfield><subfield code="w">(DE-600)795328-8</subfield><subfield code="w">(DE-576)016125967</subfield><subfield code="x">0170-4214</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:39</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:9</subfield><subfield code="g">pages:2182-2192</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1002/mma.3632</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://onlinelibrary.wiley.com/doi/10.1002/mma.3632/abstract</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4318</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">31.80</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">39</subfield><subfield code="j">2016</subfield><subfield code="e">9</subfield><subfield code="h">2182-2192</subfield></datafield></record></collection>
|
| author |
Fan, Chenxi |
| spellingShingle |
Fan, Chenxi ddc 510 bkl 31.80 misc applications to actuarial sciences and financial mathematics misc quasi‐Monte Carlo methods misc option pricing misc Monte Carlo methods misc path generation methods misc Brownian bridge methods An iterative algorithm to determine the number of time steps in path generation methods |
| authorStr |
Fan, Chenxi |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)130619051 |
| format |
Article |
| dewey-ones |
510 - Mathematics |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
OLC |
| remote_str |
false |
| illustrated |
Not Illustrated |
| issn |
0170-4214 |
| topic_title |
510 DE-600 31.80 bkl An iterative algorithm to determine the number of time steps in path generation methods applications to actuarial sciences and financial mathematics quasi‐Monte Carlo methods option pricing Monte Carlo methods path generation methods Brownian bridge methods |
| topic |
ddc 510 bkl 31.80 misc applications to actuarial sciences and financial mathematics misc quasi‐Monte Carlo methods misc option pricing misc Monte Carlo methods misc path generation methods misc Brownian bridge methods |
| topic_unstemmed |
ddc 510 bkl 31.80 misc applications to actuarial sciences and financial mathematics misc quasi‐Monte Carlo methods misc option pricing misc Monte Carlo methods misc path generation methods misc Brownian bridge methods |
| topic_browse |
ddc 510 bkl 31.80 misc applications to actuarial sciences and financial mathematics misc quasi‐Monte Carlo methods misc option pricing misc Monte Carlo methods misc path generation methods misc Brownian bridge methods |
| format_facet |
Aufsätze Gedruckte Aufsätze |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
nc |
| author2_variant |
q w qw |
| hierarchy_parent_title |
Mathematical methods in the applied sciences |
| hierarchy_parent_id |
130619051 |
| dewey-tens |
510 - Mathematics |
| hierarchy_top_title |
Mathematical methods in the applied sciences |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)130619051 (DE-600)795328-8 (DE-576)016125967 |
| title |
An iterative algorithm to determine the number of time steps in path generation methods |
| ctrlnum |
(DE-627)OLC1977811639 (DE-599)GBVOLC1977811639 (PRQ)c952-a96169dd63bdb7f4d8c011f76857d2d9c888d9f6319767933a82dfb2beebc2423 (KEY)0093427520160000039000902182iterativealgorithmtodeterminethenumberoftimestepsi |
| title_full |
An iterative algorithm to determine the number of time steps in path generation methods |
| author_sort |
Fan, Chenxi |
| journal |
Mathematical methods in the applied sciences |
| journalStr |
Mathematical methods in the applied sciences |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
500 - Science |
| recordtype |
marc |
| publishDateSort |
2016 |
| contenttype_str_mv |
txt |
| container_start_page |
2182 |
| author_browse |
Fan, Chenxi |
| container_volume |
39 |
| class |
510 DE-600 31.80 bkl |
| format_se |
Aufsätze |
| author-letter |
Fan, Chenxi |
| doi_str_mv |
10.1002/mma.3632 |
| dewey-full |
510 |
| title_sort |
iterative algorithm to determine the number of time steps in path generation methods |
| title_auth |
An iterative algorithm to determine the number of time steps in path generation methods |
| abstract |
The construction of Brownian motion paths is the most important part of simulation methods for option pricing. Particularly, there are several commonly used path generation methods in the context of quasi‐Monte Carlo, including the standard method and the Brownian bridge method. To apply each method, an inevitable step is to decide how many points are used to discretize the time interval. This paper implements an iterative algorithm to select a suitable number of time steps by successively adding discretization nodes until a specific convergence criterion is met. Numerical results with this algorithm are presented in the valuation of Asian options. Copyright © 2016 John Wiley & Sons, Ltd. |
| abstractGer |
The construction of Brownian motion paths is the most important part of simulation methods for option pricing. Particularly, there are several commonly used path generation methods in the context of quasi‐Monte Carlo, including the standard method and the Brownian bridge method. To apply each method, an inevitable step is to decide how many points are used to discretize the time interval. This paper implements an iterative algorithm to select a suitable number of time steps by successively adding discretization nodes until a specific convergence criterion is met. Numerical results with this algorithm are presented in the valuation of Asian options. Copyright © 2016 John Wiley & Sons, Ltd. |
| abstract_unstemmed |
The construction of Brownian motion paths is the most important part of simulation methods for option pricing. Particularly, there are several commonly used path generation methods in the context of quasi‐Monte Carlo, including the standard method and the Brownian bridge method. To apply each method, an inevitable step is to decide how many points are used to discretize the time interval. This paper implements an iterative algorithm to select a suitable number of time steps by successively adding discretization nodes until a specific convergence criterion is met. Numerical results with this algorithm are presented in the valuation of Asian options. Copyright © 2016 John Wiley & Sons, Ltd. |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4318 |
| container_issue |
9 |
| title_short |
An iterative algorithm to determine the number of time steps in path generation methods |
| url |
http://dx.doi.org/10.1002/mma.3632 http://onlinelibrary.wiley.com/doi/10.1002/mma.3632/abstract |
| remote_bool |
false |
| author2 |
Wu, Qingbiao |
| author2Str |
Wu, Qingbiao |
| ppnlink |
130619051 |
| mediatype_str_mv |
n |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth |
| doi_str |
10.1002/mma.3632 |
| up_date |
2024-07-03T19:36:39.299Z |
| _version_ |
1803587838859542528 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1977811639</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220220080858.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">160719s2016 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1002/mma.3632</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20160719</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1977811639</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1977811639</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)c952-a96169dd63bdb7f4d8c011f76857d2d9c888d9f6319767933a82dfb2beebc2423</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0093427520160000039000902182iterativealgorithmtodeterminethenumberoftimestepsi</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">510</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">31.80</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Fan, Chenxi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="3"><subfield code="a">An iterative algorithm to determine the number of time steps in path generation methods</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The construction of Brownian motion paths is the most important part of simulation methods for option pricing. Particularly, there are several commonly used path generation methods in the context of quasi‐Monte Carlo, including the standard method and the Brownian bridge method. To apply each method, an inevitable step is to decide how many points are used to discretize the time interval. This paper implements an iterative algorithm to select a suitable number of time steps by successively adding discretization nodes until a specific convergence criterion is met. Numerical results with this algorithm are presented in the valuation of Asian options. Copyright © 2016 John Wiley & Sons, Ltd.</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="a">Nutzungsrecht: Copyright © 2016 John Wiley & Sons, Ltd.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">applications to actuarial sciences and financial mathematics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">quasi‐Monte Carlo methods</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">option pricing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Monte Carlo methods</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">path generation methods</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Brownian bridge methods</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wu, Qingbiao</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Mathematical methods in the applied sciences</subfield><subfield code="d">Chichester, West Sussex : Wiley, 1979</subfield><subfield code="g">39(2016), 9, Seite 2182-2192</subfield><subfield code="w">(DE-627)130619051</subfield><subfield code="w">(DE-600)795328-8</subfield><subfield code="w">(DE-576)016125967</subfield><subfield code="x">0170-4214</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:39</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:9</subfield><subfield code="g">pages:2182-2192</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1002/mma.3632</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://onlinelibrary.wiley.com/doi/10.1002/mma.3632/abstract</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4318</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">31.80</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">39</subfield><subfield code="j">2016</subfield><subfield code="e">9</subfield><subfield code="h">2182-2192</subfield></datafield></record></collection>
|
| score |
7.3998547 |