Better Not Forget: On the Memory of S&P 500 Survivor Stock Companies

Author:

Grobys Klaus1,Han Yao2ORCID,Kolari James W.3

Affiliation:

1. Finance Research Group, School of Accounting and Finance, University of Vaasa, Wolffintie 34, 65200 Vaasa, Finland

2. College of Finance, Jiangxi University of Finance and Economics, 169 Shuanggang East Avenue, Nanchang 330013, China

3. Department of Finance, Mays Business School, Texas A&M University, College Station, TX 77843-4218, USA

Abstract

This study explores the dependency structure of S&P 500 survivor stocks. Using a hand-collected sample of stocks that survived in the S&P 500 since March 1957, we employ rescaled/range analysis to investigate survivors. First, we find nonlinearities in the return processes of survivor stocks due to Paretian tails. Second, the return processes of very long-lived outliers exhibit long-term memories with Hurst exponents that significantly exceed one half on average. Third, sample-split tests reveal that the memory on average has virtually not changed over time—that is, survivor stocks do not forget. Fourth, and last, the long-term memory of survivor stocks appears to be unrelated to their exposures to traditional asset pricing risk factors.

Publisher

MDPI AG

Subject

Finance,Economics and Econometrics,Accounting,Business, Management and Accounting (miscellaneous)

Reference39 articles.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Python Module for Selecting the Number of Assets in Optimal Portfolios via Two Alternative Techniques;2023 9th International Conference on Optimization and Applications (ICOA);2023-10-05

2. A Fractal and Comparative View of the Memory of Bitcoin and S&P 500 Returns;Research in International Business and Finance;2023-10

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