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Regression-based estimation of covariance matrix of stock returns
- Kim, Saejoon;
- Kim, Soong
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0초록
Covariance matrix estimation is an important problem in various fields of social science including financial economics. In this paper, we consider the estimation problem in the regression framework in order to resolve the deficiencies of the traditional methods. In particular, we establish the regression framework using support vector regression for the in-sample-based and the shrinkage-based estimation methods. Empirical results will indicate that our proposed covariance matrix estimation methods sufficiently perform superior to the two traditional estimation methods. © 2018 The authors and IOS Press. All rights reserved.
키워드
Covariance matrix estimation; In-sample-based estimation; Shrinkage-based estimation; Support vector regression; Time series regression
- 제목
- Regression-based estimation of covariance matrix of stock returns
- 저자
- Kim, Saejoon; Kim, Soong
- 발행일
- 2018
- 유형
- Conference Paper
- 저널명
- Frontiers in Artificial Intelligence and Applications
- 권
- 309
- 페이지
- 182 ~ 188