Mathematical Sciences: Faculty Publications
Randomly Walking Through Wall Street
Document Type
Article
Publication Date
9-1999
Publication Title
Mathematics and Computers in Simulation
DOI
10.1016/S0378-4754(99)00040-3
ISSN
0378-4754
Abstract
The daily closing values of the S&P 500 Index from January 1, 1926 through June 11, 1993, a total of 17,610 values, were entered into Mathematica, and the day-to-day percent changes were calculated. Using the Standard Mathematica Package Statistics ‵ContinuousDistributions‵ and the built-in function NonLinearFit, procedures were developed to find the probability distribution that best models these daily changes. Although the log-normal distribution has been used traditionally, we found that a logistic distribution provides the best model, having a coefficient of determination 0.998. Using this model and Mathematica to simulate stock market performance we have found that, although the short-term changes in the stock market can often be explained by world events, longer-term behavior of the market can be modeled with accuracy. Simulations for time periods between 6 months and 10 years show that, although dollar-cost average investing has less volatility, the long-term investor can expect a higher return from a lump-sum investment.
Recommended Citation
Braselton, James P., John Rafter, Patricia B. Humphrey, Martha L. Abell.
1999.
"Randomly Walking Through Wall Street."
Mathematics and Computers in Simulation, 49 (4-5): 297-318.
doi: 10.1016/S0378-4754(99)00040-3
https://digitalcommons.georgiasouthern.edu/math-sci-facpubs/434
Copyright
This work is archived and distributed under the repository's Standard Copyright and Reuse License (opens in new tab). End users may copy, store, and distribute this work without restriction. For all other uses, permission must be obtained from the copyright owners or their authorized agents.
