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...
Main Author: | |
---|---|
Format: | Others |
Published: |
North Dakota State University
2018
|
Subjects: | |
Online Access: | https://hdl.handle.net/10365/29019 |
id |
ndltd-ndsu.edu-oai-library.ndsu.edu-10365-29019 |
---|---|
record_format |
oai_dc |
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 |
_version_ |
1719485731719610368 |