Fitting of Russell 2000 Index for the First 20 Years in the 21^st Century with Random Walk – Application in Big Data and Digital Economy

DOI

10.2991/978-94-6463-010-7_25How to use a DOI?

Keywords

Big Data; Digital Economy; Russell 2000 Index; Random Walk; Stock Market

Abstract

Without any question, the stock markets are the engine to generate the big data, which become an active part of digital economy. The big data provide rich opportunities through internet to combine various technologies with the issues raised in the economic developments in modern society. Whether a stock index can be described by the random walk is an important approval to the efficient market hypothesis (EMH). Of well-known stock indices, the Russell 2000 index, which includes 2000 small-cap companies, has a smaller capitalization compared with other well-known indices. It therefore draws less attention from investors and is less subject to manipulations. Hence, it potentially behaves more randomly than other heavily manipulated indices. As a result, it might be more suitable for the random walk statistical tests and simulation/fitting. In this study, the Russell 2000 index from 2001to 2020 was fitted by the random walk method in five segments of time. In general, the results showed that the random walk method can fit the Russell 2000 index for different periods of time. Thus, the results add a piece of evidence to support EMH. However, how to reconcile the random walk fitting with the random walk statistical tests still requires more studies in the future. More importantly how to apply the artificial intelligence (AI) to the random walk model to fit the stock index in order to decide whether EMH is valid demands many new studies.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Shaomin Yan
AU  - Guang Wu
PY  - 2022
DA  - 2022/12/02
TI  - Fitting of Russell 2000 Index for the First 20 Years in the 21st Century with Random Walk – Application in Big Data and Digital Economy
BT  - Proceedings of the 2022 International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2022)
PB  - Atlantis Press
SP  - 238
EP  - 247
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-010-7_25
DO  - 10.2991/978-94-6463-010-7_25
ID  - Yan2022
ER  -