This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Forecasting Stock Market Averages to Enhance Profitable Trading Strategies

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Christian Haefke
Christian Helmenstein () (Department of Economics, Institute for Advanced Studies, Vienna)

Additional information is available for the following registered author(s):

Abstract

In this paper we design a simple trading strategy to exploit the hypothesized distinct informational content of the arithmetic and geometric mean. The rejection of cointegration between the two stock market indicators supports this conjecture. The profits generated by this cheaply replicable trading scheme cannot be expected to persist. Therefore we forecast the averages using autoregressive linear and neural network models to gain a competitive advantage relative to other investors. Refining the trading scheme using the forecasts further increases the mean return as compared to a buy and hold strategy. One of the most prominent mysteries of present day finance is the ample usage of such simple and dated concepts as the arithmetic and the geometric means as proxies for the aggregate price dynamics of leading international stock markets. While such undertakings may find their explanation, though not justification, in the inertia of the finance community to adopt more modern index concepts, it is even more astounding that during the last decade of the twentieth century some newly implemented stock market indexes are still constructed in the tradition of these principles.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.unige.ch/ce/ce96/ps/haefke.eps
File Format: application/postscript
File Function:
Download Restriction: no

Publisher Info
Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 1996 with number _023.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation:
Date of revision:
Handle: RePEc:sce:scecf6:_023

Contact details of provider:
Postal: Department of Econometrics, University of Geneva, 102 Bd Carl-Vogt, 1211 Geneva 4, Switzerland
Web page: http://www.unige.ch/ce/ce96/welcome.html
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research
Keywords:

Other versions of this item:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Granger, Clive W. J. & King, Maxwell L. & White, Halbert, 1995. "Comments on testing economic theories and the use of model selection criteria," Journal of Econometrics, Elsevier, vol. 67(1), pages 173-187, May. [Downloadable!] (restricted)
    Other versions:
Full references

Statistics
Access and download statistics

Did you know? RePEc also has a blog.

This page was last updated on 2009-12-28.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.