Robust Capital Asset Pricing Model Estimation through Cross-Validation

Limitations of Capital Asset Pricing Model (CAPM) continue to present inconsistent empirical results despite its rm mathematical foundations provided in recent studies. In this thesis, we examine how estimation errors of the CAPM could be minimized using the cross-validation technique, a concept th...

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Main Author: Sakouvogui, Kekoura
Format: Others
Published: North Dakota State University 2018
Subjects:
Online Access:https://hdl.handle.net/10365/29019
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spelling ndltd-ndsu.edu-oai-library.ndsu.edu-10365-290192021-09-28T17:11:08Z Robust Capital Asset Pricing Model Estimation through Cross-Validation Sakouvogui, Kekoura Capital assets pricing model. Financial risk management. Portfolio management. Machine learning. Limitations of Capital Asset Pricing Model (CAPM) continue to present inconsistent empirical results despite its rm mathematical foundations provided in recent studies. In this thesis, we examine how estimation errors of the CAPM could be minimized using the cross-validation technique, a concept that is widely applied in machine learning (CV-CAPM). We apply our approach to test the assumption of CAPM as a well-diversified portfolio model with data from S&P500 and Dow Jones Industrial Average (DJIA). Our results from the CV-CAPM validate that both S&P500 and DJIA are well-diversified market indices with statistically insignificant variation in unsystematic risks during and after the 2007 financial crisis. Furthermore, the CV-CAPM provides the smallest root mean square errors and mean absolute deviations compared to the traditional CAPM. 2018-12-03T21:49:17Z 2018-12-03T21:49:17Z 2018 text/thesis https://hdl.handle.net/10365/29019 NDSU policy 190.6.2 https://www.ndsu.edu/fileadmin/policy/190.pdf application/pdf North Dakota State University
collection NDLTD
format Others
sources NDLTD
topic Capital assets pricing model.
Financial risk management.
Portfolio management.
Machine learning.
spellingShingle Capital assets pricing model.
Financial risk management.
Portfolio management.
Machine learning.
Sakouvogui, Kekoura
Robust Capital Asset Pricing Model Estimation through Cross-Validation
description Limitations of Capital Asset Pricing Model (CAPM) continue to present inconsistent empirical results despite its rm mathematical foundations provided in recent studies. In this thesis, we examine how estimation errors of the CAPM could be minimized using the cross-validation technique, a concept that is widely applied in machine learning (CV-CAPM). We apply our approach to test the assumption of CAPM as a well-diversified portfolio model with data from S&P500 and Dow Jones Industrial Average (DJIA). Our results from the CV-CAPM validate that both S&P500 and DJIA are well-diversified market indices with statistically insignificant variation in unsystematic risks during and after the 2007 financial crisis. Furthermore, the CV-CAPM provides the smallest root mean square errors and mean absolute deviations compared to the traditional CAPM.
author Sakouvogui, Kekoura
author_facet Sakouvogui, Kekoura
author_sort Sakouvogui, Kekoura
title Robust Capital Asset Pricing Model Estimation through Cross-Validation
title_short Robust Capital Asset Pricing Model Estimation through Cross-Validation
title_full Robust Capital Asset Pricing Model Estimation through Cross-Validation
title_fullStr Robust Capital Asset Pricing Model Estimation through Cross-Validation
title_full_unstemmed Robust Capital Asset Pricing Model Estimation through Cross-Validation
title_sort robust capital asset pricing model estimation through cross-validation
publisher North Dakota State University
publishDate 2018
url https://hdl.handle.net/10365/29019
work_keys_str_mv AT sakouvoguikekoura robustcapitalassetpricingmodelestimationthroughcrossvalidation
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