research-article

Simulation of Impact of COVID-19 Pandemic on Dow Jones Index Using Random Walk

Authors:

Guang WuAuthors Info & Claims

CONF-CDS 2021: The 2nd International Conference on Computing and Data Science

Article No.: 59, Pages 1 - 5

https://doi.org/10.1145/3448734.3450789

Published: 17 May 2021 Publication History

Abstract

The outbreak of pandemic of COVID-19 is a totally unexpected event, which impacts heavily on the world stock market, especially the US stock market. So far, mathematical, statistical and probabilistic models have been used in the simulation of stock markets, whereas the probabilistic models appear to be more suitable for current situation because of the unexpectedness of COVID-19 pandemic. In this study, the random walk model, which is based on random walk hypothesis of stock markets, was used to simulate the opens of Dow Jones Industrial Average Index for 7 months, 2 years and 7 months, 5 years and 7 months, 10 years and 7 months, and 20 years and 7 months, respectively. The unexpected events not only include the current COVID-19 pandemic but also the 9/11 terrorism attack on the World Trade Center. The simulations demonstrate that the random walk is still difficult to precisely describe the impact of COVID-19 pandemic on the Dow Jones Industrial Average Index although the general trends look similar.

References

[1]

Eugene F. Fama. 1965. The behaviour of stock market prices. J. Business 38, 1 (January 1965) 34–105. https://www.jstor.org/stable/2350752

[2]

Stephen J. Taylor. 2000. Stock index price dynamics in the UK and the US: New evidence from a trading rule and statistical analysis. Euro. J. Finance 6, 1 (February 2000) 39–-69. https://doi.org/10.1080/135184700336955

[3]

T. G. Gordon. 1969. Cross-impact matrices – an illustration of their use for policy analysis. Futures 2, 6 (December 1969) 527-531. https://doi.org/10.1016/S0016-3287(69)80042-X

[4]

T. G. Gordon, and H. Hayward. 1968. Initial experiments with the cross-impact matrix method of forecasting. Futures 1, 2 (December 1968,) 100-116. https://doi.org/10.1016/S0016-3287(68)80003-5

[5]

Selwyn Enzer. 1971. Delphi and cross-impact techniques: an effective combination for systematic futures analysis. Futures 3, 1 (March 1971) 48-61. https://doi.org/10.1016/S0016-3287(71)80006-X

[6]

Selwyn Enzer. 1972. Cross-impact techniques in technology assessment. Futures 4, 1 (March 1972) 30-51. https://doi.org/10.1016/0016-3287(72)90023-7

[7]

Amélie Charles, and Olivier Darné. 2009. The random walk hypothesis for Chinese stock markets: evidence from variance ratio tests. Econ. Syst. 33, 2 (June 2009) 117-126. https://doi.org/10.1016/j.ecosys.2008.09.003.

[8]

Abraham Abraham, Fazal J. Seyyed, and Sulaiman A. Alsakran. 2002. Testing the random walk behavior and efficiency of the Gulf stock markets. Finan. Rev. 37, 3 (August 2002) 469-480. https://doi.org/10.1111/0732-8516.00008

[9]

Claire G. Gilmore, and Ginette M. McManus. 2003. Random walk and efficiency tests of central European equity markets. Manag. Finan. 29, 42-61. https://doi.org/10.1108/03074350310768283

[10]

David A. Dickey, and Wayne A. Fuller. 1979. Autoregressive time series with a unit root. J. Am. Stat. Ass. 74, 366a (1979) 427-431. https://doi.org/10.1080/01621459.1979.10482531

[11]

Peter B. C. Phillips. 1987. Time series regression with a unit root. Econometrica 55, 277-301. https://doi.org/10.2307/1913237

[12]

Peter B. C. Phillips, and Pierre Perron. 1988. Testing for a unit root in time series regression. Biometrika 75, 2 (June 1988) 335-346. https://doi.org/10.1093/biomet/75.2.335

[13]

https://finance.yahoo.com/quote/%5EDJI?p=^DJI

[14]

Anany Levitin. 2003. Introduction to the Design and Analysis of Algorithms. 1st ed., New Jersey: Pearson Education.

Digital Library

[15]

Systat Software, Inc. SigmaPlot 14.0, 2016.

[16]

Andrew W. Lo, and Craig A. MacKinlay. 1988. Stock market prices do not follow random walks: Evidence from a simple specification test. Rev. Finan. Studies 1, 41–66. https://doi.org/10.3386/w2168

[17]

Maira R. Borges. 2011. Random walk tests for the Lisbon stock market. Appl. Econ. 43, 5 (2011) 631–639. https://doi.org/10.1080/00036840802584935

[18]

Per Frennberg, and Bjorn Hansson. 1993. Testing the random walk hypothesis on Swedish stock prices:1919–1990. J. Bank. Finan. 17, 175–191. https://doi.org/10.1016/0378-4266(93)90087-T

[19]

Terrance Greib, and Mario G. Reyes. 1999. Random walk tests for Latin American equity indices and individual firms. J. Finan. Res. 22, 4 (Winter 1999) 371–383. https://doi.org/10.1111/j.1475-6803.1999.tb00701.x

[20]

Hafiz A. A. B. Hoque, Jae. H. Kim, and Chong S. Pyun. 2007. A comparison of variance ratio tests of random walk: a case of Asian emerging stock markets. Int. Rev. Econ. Finan. 16, 4 (2007) 488–502. https://doi.org/10.1016/j.iref.2006.01.001

[21]

Bwo-Nung Huang. 1995. Do Asian stock market prices follow random walk? Evidence from the variance ratio test. Appl. Finan. Econ. 5, 4 (1995) 251–256. https://doi.org/10.1080/758536875

[22]

Peter L. Jennergren, and Paul E. Korsvold. 1974. Price formation in the Norwegian and Swedish stockmarkets: some random walk tests. Swed. J. Econ. 76, 171–185.

[23]

Eduardo J. A. Lima, and Benjamin M. Tabak. 2004. Tests of the random walk hypothesis for equity markets: evidence from China, Hong Kong and Singapore. Appl. Econ. Lett. 11, 255–258. https://doi.org/13504850410001674911

[24]

Andrew W. Lo, and A. Craig MacKinlay. 1997. Market Efficiency: Stock Market Behavior in Theory and Practice. Edward Elgar Publishing. MA.

[25]

Sunil Poshakwale. 2002. The random walk hypothesis in the emerging Indian stock market. J. Bus. Finan. Account. 29, 9-10 (November/December 2002) 1275–1299. https://doi.org/10.1111/1468-5957.00469

[26]

Graham Smith. 2007. Random walks in Middle Eastern stock markets. Appl. Finan. Econ. 17, 7 (July 2007) 587–596. https://doi.org/10.1080/09603100600911200

[27]

Graham Smith, Keith Jefferis, and Hyun-Jung Ryoo. 2002. African stock markets: multiple variance ratio tests ofrandom walks. Appl. Finan. Econ. 12, 7 (July 2002) 475–484. https://doi.org/10.1080/09603100010009957

[28]

Bruno H. Solnik. 1973. Note on the validity of the random walk for European stock prices. J. Finan. 28, 5 (December 1973) 1151–1159. https://doi.org/10.1111/j.1540-6261.1973.tb01447.x

Cited By

Yan SWu G(2022)Fitting of Russell 2000 Index for the First 20 Years in the 21st Century with Random Walk – Application in Big Data and Digital EconomyProceedings of the 2022 International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2022)10.2991/978-94-6463-010-7_25(238-247)Online publication date: 2-Dec-2022
https://doi.org/10.2991/978-94-6463-010-7_25

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Simulation of Impact of COVID-19 Pandemic on Dow Jones Index Using Random Walk

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CONF-CDS 2021: The 2nd International Conference on Computing and Data Science

January 2021

1142 pages

ISBN:9781450389570

DOI:10.1145/3448734

Copyright © 2021 ACM.

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Published: 17 May 2021

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CONF-CDS 2021

CONF-CDS 2021: The 2nd International Conference on Computing and Data Science

January 28 - 30, 2021

CA, Stanford, USA

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Cited By

Yan SWu G(2022)Fitting of Russell 2000 Index for the First 20 Years in the 21st Century with Random Walk – Application in Big Data and Digital EconomyProceedings of the 2022 International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2022)10.2991/978-94-6463-010-7_25(238-247)Online publication date: 2-Dec-2022
https://doi.org/10.2991/978-94-6463-010-7_25

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