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Estimation, model selection and evaluation of regression functions in a Least-squares Monte-Carlo framework
Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
2014 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This master thesis will investigate one solution to the problem issues with nested stochastic simulation arising when the future value of a portfolio need to be calculated. The solution investigated is the Least-squares Monte-Carlo method, where regression is used to obtain a proxy function for the given portfolio value. We will further investigate how to generate an optimal regression function that minimizes the number of terms in the regression function and reduces the risk of overtting the regression.

Place, publisher, year, edition, pages
2014. , 73 p.
Keyword [en]
LSMC, Least Squares Monte-Carlo, Solvency, SCR, Regression
National Category
Economics and Business
Identifiers
URN: urn:nbn:se:liu:diva-110927ISRN: LIU-IEI-TEK-A--14/02027--SEOAI: oai:DiVA.org:liu-110927DiVA: diva2:750620
Subject / course
Production Economics
Supervisors
Examiners
Available from: 2014-09-29 Created: 2014-09-29 Last updated: 2014-09-29Bibliographically approved

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Production EconomicsThe Institute of Technology
Economics and Business

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CiteExportLink to record
Permanent link

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Citation style
  • apa
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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