Monte Carlo Methods in Financial Engineering:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer New York
2003
|
| Schriftenreihe: | Stochastic Modelling and Applied Probability
53 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management. These applications have, in turn, stimulated research into new Monte Carlo methods and renewed interest in some older techniques. This book develops the use of Monte Carlo methods in finance and it also uses simulation as a vehicle for presenting models and ideas from financial engineering. It divides roughly into three parts. The first part develops the fundamentals of Monte Carlo methods, the foundations of derivatives pricing, and the implementation of several of the most important models used in financial engineering. The next part describes techniques for improving simulation accuracy and efficiency. The final third of the book addresses special topics: estimating price sensitivities, valuing American options, and measuring market risk and credit risk in financial portfolios. The most important prerequisite is familiarity with the mathematical tools used to specify and analyze continuous-time models in finance, in particular the key ideas of stochastic calculus. Prior exposure to the basic principles of option pricing is useful but not essential. The book is aimed at graduate students in financial engineering, researchers in Monte Carlo simulation, and practitioners implementing models in industry |
| Beschreibung: | 1 Online-Ressource (XIII, 596 p) |
| ISBN: | 9780387216171 9781441918222 |
| ISSN: | 0172-4568 |
| DOI: | 10.1007/978-0-387-21617-1 |
Internformat
MARC
| LEADER | 00000nmm a2200000zcb4500 | ||
|---|---|---|---|
| 001 | BV042418935 | ||
| 003 | DE-604 | ||
| 005 | 20200714 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 150317s2003 |||| o||u| ||||||eng d | ||
| 020 | |a 9780387216171 |c Online |9 978-0-387-21617-1 | ||
| 020 | |a 9781441918222 |c Print |9 978-1-4419-1822-2 | ||
| 024 | 7 | |a 10.1007/978-0-387-21617-1 |2 doi | |
| 035 | |a (OCoLC)1184501992 | ||
| 035 | |a (DE-599)BVBBV042418935 | ||
| 040 | |a DE-604 |b ger |e aacr | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-384 |a DE-703 |a DE-91 |a DE-634 | ||
| 082 | 0 | |a 519 |2 23 | |
| 084 | |a MAT 000 |2 stub | ||
| 100 | 1 | |a Glasserman, Paul |d 1962- |e Verfasser |0 (DE-588)13170852X |4 aut | |
| 245 | 1 | 0 | |a Monte Carlo Methods in Financial Engineering |c by Paul Glasserman |
| 264 | 1 | |a New York, NY |b Springer New York |c 2003 | |
| 300 | |a 1 Online-Ressource (XIII, 596 p) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a Stochastic Modelling and Applied Probability |v 53 |x 0172-4568 | |
| 500 | |a Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management. These applications have, in turn, stimulated research into new Monte Carlo methods and renewed interest in some older techniques. This book develops the use of Monte Carlo methods in finance and it also uses simulation as a vehicle for presenting models and ideas from financial engineering. It divides roughly into three parts. The first part develops the fundamentals of Monte Carlo methods, the foundations of derivatives pricing, and the implementation of several of the most important models used in financial engineering. The next part describes techniques for improving simulation accuracy and efficiency. The final third of the book addresses special topics: estimating price sensitivities, valuing American options, and measuring market risk and credit risk in financial portfolios. The most important prerequisite is familiarity with the mathematical tools used to specify and analyze continuous-time models in finance, in particular the key ideas of stochastic calculus. Prior exposure to the basic principles of option pricing is useful but not essential. The book is aimed at graduate students in financial engineering, researchers in Monte Carlo simulation, and practitioners implementing models in industry | ||
| 650 | 4 | |a Mathematics | |
| 650 | 4 | |a Finance | |
| 650 | 4 | |a Distribution (Probability theory) | |
| 650 | 4 | |a Mathematical statistics | |
| 650 | 4 | |a Economics | |
| 650 | 4 | |a Operations research | |
| 650 | 4 | |a Quantitative Finance | |
| 650 | 4 | |a Probability Theory and Stochastic Processes | |
| 650 | 4 | |a Statistical Theory and Methods | |
| 650 | 4 | |a Economic Theory | |
| 650 | 4 | |a Operation Research/Decision Theory | |
| 650 | 4 | |a Mathematik | |
| 650 | 4 | |a Wirtschaft | |
| 650 | 0 | 7 | |a Monte-Carlo-Simulation |0 (DE-588)4240945-7 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Financial Engineering |0 (DE-588)4208404-0 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Financial Engineering |0 (DE-588)4208404-0 |D s |
| 689 | 0 | 1 | |a Monte-Carlo-Simulation |0 (DE-588)4240945-7 |D s |
| 689 | 0 | |8 1\p |5 DE-604 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-0-387-21617-1 |x Verlag |3 Volltext |
| 912 | |a ZDB-2-SMA |a ZDB-2-BAE | ||
| 940 | 1 | |q ZDB-2-SMA_Archive | |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-027854352 | ||
| 883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
Datensatz im Suchindex
| _version_ | 1804153088999686145 |
|---|---|
| any_adam_object | |
| author | Glasserman, Paul 1962- |
| author_GND | (DE-588)13170852X |
| author_facet | Glasserman, Paul 1962- |
| author_role | aut |
| author_sort | Glasserman, Paul 1962- |
| author_variant | p g pg |
| building | Verbundindex |
| bvnumber | BV042418935 |
| classification_tum | MAT 000 |
| collection | ZDB-2-SMA ZDB-2-BAE |
| ctrlnum | (OCoLC)1184501992 (DE-599)BVBBV042418935 |
| dewey-full | 519 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519 |
| dewey-search | 519 |
| dewey-sort | 3519 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1007/978-0-387-21617-1 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03410nmm a2200589zcb4500</leader><controlfield tag="001">BV042418935</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20200714 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">150317s2003 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780387216171</subfield><subfield code="c">Online</subfield><subfield code="9">978-0-387-21617-1</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781441918222</subfield><subfield code="c">Print</subfield><subfield code="9">978-1-4419-1822-2</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-0-387-21617-1</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1184501992</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV042418935</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">aacr</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-384</subfield><subfield code="a">DE-703</subfield><subfield code="a">DE-91</subfield><subfield code="a">DE-634</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">519</subfield><subfield code="2">23</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">MAT 000</subfield><subfield code="2">stub</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Glasserman, Paul</subfield><subfield code="d">1962-</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)13170852X</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Monte Carlo Methods in Financial Engineering</subfield><subfield code="c">by Paul Glasserman</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">New York, NY</subfield><subfield code="b">Springer New York</subfield><subfield code="c">2003</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (XIII, 596 p)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Stochastic Modelling and Applied Probability</subfield><subfield code="v">53</subfield><subfield code="x">0172-4568</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management. These applications have, in turn, stimulated research into new Monte Carlo methods and renewed interest in some older techniques. This book develops the use of Monte Carlo methods in finance and it also uses simulation as a vehicle for presenting models and ideas from financial engineering. It divides roughly into three parts. The first part develops the fundamentals of Monte Carlo methods, the foundations of derivatives pricing, and the implementation of several of the most important models used in financial engineering. The next part describes techniques for improving simulation accuracy and efficiency. The final third of the book addresses special topics: estimating price sensitivities, valuing American options, and measuring market risk and credit risk in financial portfolios. The most important prerequisite is familiarity with the mathematical tools used to specify and analyze continuous-time models in finance, in particular the key ideas of stochastic calculus. Prior exposure to the basic principles of option pricing is useful but not essential. The book is aimed at graduate students in financial engineering, researchers in Monte Carlo simulation, and practitioners implementing models in industry</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Finance</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Distribution (Probability theory)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematical statistics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Economics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Operations research</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Quantitative Finance</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Probability Theory and Stochastic Processes</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistical Theory and Methods</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Economic Theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Operation Research/Decision Theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematik</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Wirtschaft</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Monte-Carlo-Simulation</subfield><subfield code="0">(DE-588)4240945-7</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Financial Engineering</subfield><subfield code="0">(DE-588)4208404-0</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Financial Engineering</subfield><subfield code="0">(DE-588)4208404-0</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Monte-Carlo-Simulation</subfield><subfield code="0">(DE-588)4240945-7</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="8">1\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1007/978-0-387-21617-1</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-SMA</subfield><subfield code="a">ZDB-2-BAE</subfield></datafield><datafield tag="940" ind1="1" ind2=" "><subfield code="q">ZDB-2-SMA_Archive</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-027854352</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">1\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield></record></collection> |
| id | DE-604.BV042418935 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:21:03Z |
| institution | BVB |
| isbn | 9780387216171 9781441918222 |
| issn | 0172-4568 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027854352 |
| oclc_num | 1184501992 |
| open_access_boolean | |
| owner | DE-384 DE-703 DE-91 DE-BY-TUM DE-634 |
| owner_facet | DE-384 DE-703 DE-91 DE-BY-TUM DE-634 |
| physical | 1 Online-Ressource (XIII, 596 p) |
| psigel | ZDB-2-SMA ZDB-2-BAE ZDB-2-SMA_Archive |
| publishDate | 2003 |
| publishDateSearch | 2003 |
| publishDateSort | 2003 |
| publisher | Springer New York |
| record_format | marc |
| series2 | Stochastic Modelling and Applied Probability |
| spelling | Glasserman, Paul 1962- Verfasser (DE-588)13170852X aut Monte Carlo Methods in Financial Engineering by Paul Glasserman New York, NY Springer New York 2003 1 Online-Ressource (XIII, 596 p) txt rdacontent c rdamedia cr rdacarrier Stochastic Modelling and Applied Probability 53 0172-4568 Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management. These applications have, in turn, stimulated research into new Monte Carlo methods and renewed interest in some older techniques. This book develops the use of Monte Carlo methods in finance and it also uses simulation as a vehicle for presenting models and ideas from financial engineering. It divides roughly into three parts. The first part develops the fundamentals of Monte Carlo methods, the foundations of derivatives pricing, and the implementation of several of the most important models used in financial engineering. The next part describes techniques for improving simulation accuracy and efficiency. The final third of the book addresses special topics: estimating price sensitivities, valuing American options, and measuring market risk and credit risk in financial portfolios. The most important prerequisite is familiarity with the mathematical tools used to specify and analyze continuous-time models in finance, in particular the key ideas of stochastic calculus. Prior exposure to the basic principles of option pricing is useful but not essential. The book is aimed at graduate students in financial engineering, researchers in Monte Carlo simulation, and practitioners implementing models in industry Mathematics Finance Distribution (Probability theory) Mathematical statistics Economics Operations research Quantitative Finance Probability Theory and Stochastic Processes Statistical Theory and Methods Economic Theory Operation Research/Decision Theory Mathematik Wirtschaft Monte-Carlo-Simulation (DE-588)4240945-7 gnd rswk-swf Financial Engineering (DE-588)4208404-0 gnd rswk-swf Financial Engineering (DE-588)4208404-0 s Monte-Carlo-Simulation (DE-588)4240945-7 s 1\p DE-604 https://doi.org/10.1007/978-0-387-21617-1 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Glasserman, Paul 1962- Monte Carlo Methods in Financial Engineering Mathematics Finance Distribution (Probability theory) Mathematical statistics Economics Operations research Quantitative Finance Probability Theory and Stochastic Processes Statistical Theory and Methods Economic Theory Operation Research/Decision Theory Mathematik Wirtschaft Monte-Carlo-Simulation (DE-588)4240945-7 gnd Financial Engineering (DE-588)4208404-0 gnd |
| subject_GND | (DE-588)4240945-7 (DE-588)4208404-0 |
| title | Monte Carlo Methods in Financial Engineering |
| title_auth | Monte Carlo Methods in Financial Engineering |
| title_exact_search | Monte Carlo Methods in Financial Engineering |
| title_full | Monte Carlo Methods in Financial Engineering by Paul Glasserman |
| title_fullStr | Monte Carlo Methods in Financial Engineering by Paul Glasserman |
| title_full_unstemmed | Monte Carlo Methods in Financial Engineering by Paul Glasserman |
| title_short | Monte Carlo Methods in Financial Engineering |
| title_sort | monte carlo methods in financial engineering |
| topic | Mathematics Finance Distribution (Probability theory) Mathematical statistics Economics Operations research Quantitative Finance Probability Theory and Stochastic Processes Statistical Theory and Methods Economic Theory Operation Research/Decision Theory Mathematik Wirtschaft Monte-Carlo-Simulation (DE-588)4240945-7 gnd Financial Engineering (DE-588)4208404-0 gnd |
| topic_facet | Mathematics Finance Distribution (Probability theory) Mathematical statistics Economics Operations research Quantitative Finance Probability Theory and Stochastic Processes Statistical Theory and Methods Economic Theory Operation Research/Decision Theory Mathematik Wirtschaft Monte-Carlo-Simulation Financial Engineering |
| url | https://doi.org/10.1007/978-0-387-21617-1 |
| work_keys_str_mv | AT glassermanpaul montecarlomethodsinfinancialengineering |