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  • 标题:Portfolio Selection via Shrinkage by Cross Validation
  • 本地全文:下载
  • 作者:Xiaochun Liu
  • 期刊名称:Journal of Finance and Accounting
  • 印刷版ISSN:2333-8849
  • 电子版ISSN:2333-8857
  • 出版年度:2014
  • 卷号:2
  • 期号:4
  • 页码:74-81
  • DOI:10.12691/jfa-2-4-1
  • 语种:English
  • 出版社:Science and Education Publishing
  • 摘要:Given the importance of the loss function choice [Christoffersen, P. and K. Jacobs (2004) The importance of the loss function in option valuation. J. Financial Economics 72: 291-318], this paper proposes the nonparametric technique of cross validation, to tuning the shrinkage intensity estimation of Ledoit and Wolf [Ledoit, O. and W. Michael (2003) Improved estimation of the covariance matrix of stock returns with an application to portfolio selection. J. Empirical Finance 10: 603-621; Ledoit, O. and W. Michael (2004) Honey, I Shrunk the Sample Covariance Matrix. J. Portfolio Management 30: 110-119; Ledoit, O. and W. Michael (2004) A well-conditioned estimator for large-dimensional covariance matrices. J. Multivariate Analysis 88: 365-411]. By aligning the loss function of out-of-sample forecast identical to the one used for the shrinkage intensity estimation, the proposed cross validation approach shows the significant gains in terms of both the variance reduction and information ratio improvement to various portfolios of the U.S. firms.
  • 关键词:cross validation; shrinkage targeting; portfolio choice; shrinkage intensity; loss function
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