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Technical analysis and central bank intervention

  • Christopher Neely
  • Paul Weller

This paper extends the genetic programming techniques developed in Neely, Weller and Dittmar (1997) to show that technical trading rules can make use of information about U.S. foreign exchange intervention to improve their out-of-sample profitability for two of four exchange rates. Rules tend to take positions contrary to official intervention and are unusually profitable on days prior to intervention, indicating that intervention is intended to check or reverse predictable trends. Intervention seems to be more successful in checking predictable trends in the out-of-sample (1981-1996) period than in the in-sample (1975-1980) period. We conjecture that this instability in the intervention process prevents more consistent improvement in the excess returns to rules. We find that the improvement in performance results solely from more efficient use of the information in the past exchange rate series rather than from information about contemporaneous intervention.

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Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 1997-002.

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Date of creation: 2000
Date of revision:
Publication status: Published in Journal of International Money and Finance, December 2001, 20(7), pp. 949-70
Handle: RePEc:fip:fedlwp:1997-002
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  1. LeBaron, Blake, 1999. "Technical trading rule profitability and foreign exchange intervention," Journal of International Economics, Elsevier, vol. 49(1), pages 125-143, October.
  2. Klein, Michael W., 1993. "The accuracy of reports of foreign exchange intervention," Journal of International Money and Finance, Elsevier, vol. 12(6), pages 644-653, December.
  3. Neely, Christopher J. & Weller, Paul A., 1999. "Technical trading rules in the European Monetary System," Journal of International Money and Finance, Elsevier, vol. 18(3), pages 429-458.
  4. Levich, Richard M. & Thomas, Lee III, 1993. "The significance of technical trading-rule profits in the foreign exchange market: a bootstrap approach," Journal of International Money and Finance, Elsevier, vol. 12(5), pages 451-474, October.
  5. repec:fth:pennfi:70 is not listed on IDEAS
  6. Neely, Christopher & Weller, Paul & Dittmar, Rob, 1997. "Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(04), pages 405-426, December.
  7. Franklin Allen & Risto Karjalainen, . "Using Genetic Algorithms to Find Technical Trading Rules (Revised: 20-95)," Rodney L. White Center for Financial Research Working Papers 20-93, Wharton School Rodney L. White Center for Financial Research.
  8. Sweeney, Richard J, 1986. " Beating the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 41(1), pages 163-82, March.
  9. Christopher J. Neely, 1998. "Technical analysis and the profitability of U.S. foreign exchange intervention," Review, Federal Reserve Bank of St. Louis, issue Jul, pages 3-17.
  10. Szakmary, Andrew C. & Mathur, Ike, 1997. "Central bank intervention and trading rule profits in foreign exchange markets," Journal of International Money and Finance, Elsevier, vol. 16(4), pages 513-535, August.
  11. Christopher J. Neely, 2002. "The temporal pattern of trading rule returns and central bank intervention: intervention does not generate technical trading rule profits," Working Papers 2000-018, Federal Reserve Bank of St. Louis.
  12. Bhattacharya, Utpal & Weller, Paul, 1992. "The Advantage to Hiding One's Hand: Speculation and Central Bank Intervention in the Foreign Exchange Market," CEPR Discussion Papers 737, C.E.P.R. Discussion Papers.
  13. Peiers, Bettina, 1997. " Informed Traders, Intervention, and Price Leadership: A Deeper View of the Microstructure of the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 52(4), pages 1589-1614, September.
  14. Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules," Journal of Financial Economics, Elsevier, vol. 51(2), pages 245-271, February.
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