A critical review of the global minimum variance theory
(2016) STAH11 20152Department of Statistics
 Abstract
 The main purpose of this thesis is to give a basic understanding of the GMV portfolio theory and the problematics that arise when using the sample covariance matrix as the only parameter. The reason for this is the amount of estimation error that tends to increase as the sample covariance matrix goes to a higher dimension. In an attempt to reduce the amount of error, an alternative approach based on sector indices is introduced, which gives new and interesting results. This is a useful approach, since we are explaining the chosen stocks with fewer time series, a smaller dimension of covariance matrix needs to be estimated. This thesis lay the ground for this basic strategy, however, before any more profound conclusions can be drawn,... (More)
 The main purpose of this thesis is to give a basic understanding of the GMV portfolio theory and the problematics that arise when using the sample covariance matrix as the only parameter. The reason for this is the amount of estimation error that tends to increase as the sample covariance matrix goes to a higher dimension. In an attempt to reduce the amount of error, an alternative approach based on sector indices is introduced, which gives new and interesting results. This is a useful approach, since we are explaining the chosen stocks with fewer time series, a smaller dimension of covariance matrix needs to be estimated. This thesis lay the ground for this basic strategy, however, before any more profound conclusions can be drawn, further investigations have to be made. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/studentpapers/record/8884891
 author
 Claeson, Martin ^{LU}
 supervisor

 Krzysztof Podgorski ^{LU}
 organization
 course
 STAH11 20152
 year
 2016
 type
 M2  Bachelor Degree
 subject
 language
 English
 id
 8884891
 date added to LUP
 20160922 14:25:39
 date last changed
 20160922 14:25:39
@misc{8884891, abstract = {The main purpose of this thesis is to give a basic understanding of the GMV portfolio theory and the problematics that arise when using the sample covariance matrix as the only parameter. The reason for this is the amount of estimation error that tends to increase as the sample covariance matrix goes to a higher dimension. In an attempt to reduce the amount of error, an alternative approach based on sector indices is introduced, which gives new and interesting results. This is a useful approach, since we are explaining the chosen stocks with fewer time series, a smaller dimension of covariance matrix needs to be estimated. This thesis lay the ground for this basic strategy, however, before any more profound conclusions can be drawn, further investigations have to be made.}, author = {Claeson, Martin}, language = {eng}, note = {Student Paper}, title = {A critical review of the global minimum variance theory}, year = {2016}, }