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Missing Data in Value-at-Risk Analysis: Conditional Imputation in Optimal Portfolios Using Regression
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2013 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

A regression-based method is presented in order toregenerate missing data points in stock return time series. The method usesonly complete time series of assets in optimal portfolios, in which the returnsof the underlying tend to correlate inadequately with each other. The studyshows that the method is able to replicate empirical VaR-backtesting resultswhere all data are available, even when up to 90% of the time series in half ofthe assets in the portfolios have been removed.

Place, publisher, year, edition, pages
2013. , 52 p.
TRITA-MAT-E, 2013:18
National Category
Probability Theory and Statistics
URN: urn:nbn:se:kth:diva-122276OAI: diva2:624029
Subject / course
Mathematical Statistics
Educational program
Master of Science in Engineering - Industrial Engineering and Management
Physics, Chemistry, Mathematics
Available from: 2013-05-29 Created: 2013-05-16 Last updated: 2013-05-29Bibliographically approved

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