Exact Post-selection Inference For Tracking S&P500

Farshad Noravesh and Hamid Boustanifar

Papers from arXiv.org

Abstract: The problem that is solved in this paper is known as index tracking. The method of Lasso is used to reduce the dimensions of S&P500 index which has many applications in both investment and portfolio management algorithms. The novelty of this paper is that post-selection inference is used to have better modeling and inference for Lasso approach to index tracking. Both confidence intervals and curves indicate that the performance of Lasso type method for dimension reduction of S&P500 is remarkably high. Keywords: index tracking, lasso, post-selection inference, S&P500

Date: 2021-12
New Economics Papers: this item is included in nep-ecm, nep-fmk and nep-his
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