The Profitability of Intra-Day FX Trading Using Technical Indicators

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "M. A. H. Dempster and C. M. Jones",
  title =        "The Profitability of Intra-Day {FX} Trading Using
                 Technical Indicators",
  institution =  "Judge Institute of Management Studies, University of
  year =         "2000",
  type =         "Working Paper",
  number =       "35/00",
  address =      "Trumpington Street, Cambridge, CB2 1AG",
  keywords =     "genetic algorithms, genetic programming, high
                 frequency price data, market prices",
  broken =       "",
  broken =       "",
  URL =          "",
  abstract =     "Technical analysis indicators are widely used by
                 traders to predict future price levels and hence
                 enhance trading profitability. Traders often use high
                 frequency price (ie. intra-day) data when calculating
                 such indicators, which are then used as the basis for
                 trade entry rules. Similar rules, along with standard
                 exit rules aimed at reducing downside risk, are then
                 used to exit these trades. In this paper we test a wide
                 range of well known technical indicators on a set of US
                 Dollar/British Pound Spot FX tick data from 1989-1997
                 aggregated ti various intra-day frequencies. We find
                 that few of the rules, whether based on well known and
                 tested moving average crossover or on some of the more
                 esoteric and untested indicators, are consistently
                 profitable when traded under realistic slippage
                 conditions. Furthermore, we vary the lippage regime to
                 represent differences in the efficiency of trade
                 execution eg. between a bank trader and a small 'hedge'
                 fund but still find the rules to be loss-making. When
                 the rules are reversed, losses are still found
                 indicating the losses not to be economically
                 significant - a result that supports the efficient
                 market hypothesis.",
  size =         "70 pages",

Genetic Programming entries for Michael Dempster Chris M Jones