Financial Markets

  • William S. Mallios


The modeling objective is to forecast a currency’s short term direction based on past, publicly available data. (“Short term” will be limited to a month or less.) Successful modeling—defined in terms of predictive validity—would invalidate the efficient market hypothesis (EMH) under which a current exchange rate fully and instantaneously reflects all relevant information. “Whatever information is received that alters the market’s view of the likely future of an asset, the current price of that asset immediately reflects that alteration.” 1 Successful modeling based solely on public information would also rule out the need for insider information.a,b


Exchange Rate Stock Issue Wall Street Journal Statistical Shock Closing Price 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References: Part VII

  1. 1.
    Brooks S, Cuthbertson K, Mayes DG. The Exchange Rate Environment. Croom Helm: London, 1986. (Quotation, p. 83)Google Scholar
  2. 2.
    Ibid. (Quotation, p. 280–81)Google Scholar
  3. 3.
    Meese RA, Rogoff K. Empitical exchange rate models of the seventies: Do they fit out of sample? Journal of International Economics, 1983; 14: 3–24.CrossRefGoogle Scholar
  4. 4.
    Meese RA, Rogoff K. The out of sample failure of empitical exchange rate models: Sampling error or misspecification? In Exchange rates and International Economics, J. Frenkel, ed. University of Chicago Press: Chicago, 1983.Google Scholar
  5. 5.
    Diebold FX. Empirical Modeling of Exchange Rate Dynamics. Springer Verlag: NY, 1988.CrossRefGoogle Scholar
  6. 6.
    Mallet V. The Trouble with Tigers. Harper Collins: NY, 1999.Google Scholar
  7. 7.
    Lingle C. The Rise and Decline of the Asian Century. Tauris: NY, 1999.Google Scholar
  8. 8.
    Peikoff L. Ominous Parallels. Stein Day: NY,1982. (Quotation, p. 187)Google Scholar
  9. Dominguez K, Frankel J. Does foreign Intervention Work? Institute for International economics: Washington DC, 1993.Google Scholar
  10. 10.
    Ibid. (Quotation, p. 46–47)Google Scholar
  11. 11.
    Granger CWJ, Morgenstern O. Predictability of Stock Market Prices. Heath Lexington: Lexington, MA, 1970. (Quotation, p. 282)Google Scholar
  12. 12.
    Bachellier L. “Theory of Speculation.” In Random Character of Stock Market Prices, P.H. Cootner, ed. MIT Press: Cambridge, 1964.Google Scholar
  13. 13.
    Soros G. Soros on Soros. Wiley: NY, 1995.Google Scholar
  14. 14.
    Malkiel BG. A Random Walk Down Wall Street. Norton: NY, 1985.Google Scholar
  15. 15.
    Mussa M. “Theory of Exchange rate Determination.” In Exchange Rate Theory and Practice,R.C. Marston and J.F. Bilson eds. University of Chicago Press: Chicago, 1988. (Quotation, p15)Google Scholar
  16. 16.
    Ridley M. Frontiers of fame. The Economist, Oct. 9, 1993: 3–22.Google Scholar
  17. 17.
    The Economist, January 13, 1996: 69–70.Google Scholar
  18. 18.
    Taylor S. Efficiency of the Yen Futures Market at the Chicago Mercantile Exchange.“ In Rational Expectations and Efficiency in Futures Markets,Routledge: London, 1992.Google Scholar
  19. 19.
    Fama EF. Foundations of Finance. Basil Blackwell: Oxford. 1976.Google Scholar
  20. 20.
    Jensen MC. Some anomalous evidence regarding market efficiency. Journal of Financial Economics, 1978; 6: 95–101.CrossRefGoogle Scholar
  21. 21.
    Box GEP, Cox DR. “An analysis of transformations.” Journal of the Royal Statistical Society, 1964; Series B (26); 211–43.Google Scholar
  22. 22.
    Reference 1. (Quotation, p. 27)Google Scholar
  23. 23.
    Reference 1. (Quotation, p.7)Google Scholar
  24. 24.
    Nison S. Japanese Candlestick Charting Techniques. NY Institute of Finance: NY, 1991.Google Scholar
  25. 25.
    Reference 6 of Part 6.Google Scholar
  26. 26.
    Fisher RA. The use of multiple measurements in taxonomic problems. Annals of Eugenics, 1936; VII (Pt. II); 179–88.CrossRefGoogle Scholar
  27. 27.
    Reference 1 of Part 3.Google Scholar
  28. 28.
    Cox DR, Snell EJ. Analysis of Binary Data. Chapman Hall: NY, 1989.Google Scholar

Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • William S. Mallios
    • 1
  1. 1.Craig School of BusinessCalifornia State UniversityFresnoUSA

Personalised recommendations