Better Trade Exits for Foreign Exchange Currency Trading using FXGP

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

  author =       "Alexander Loginov and Garnett Wilson and 
                 Malcolm Heywood",
  title =        "Better Trade Exits for Foreign Exchange Currency
                 Trading using FXGP",
  booktitle =    "Proceedings of 2015 IEEE Congress on Evolutionary
                 Computation (CEC 2015)",
  year =         "2015",
  editor =       "Yadahiko Murata",
  pages =        "2510--2517",
  address =      "Sendai, Japan",
  month =        "25-28 " # may,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CEC.2015.7257197",
  abstract =     "Retracement is the tendency of markets to move between
                 upper resistance and lower support price levels. Human
                 traders frequently make use of visual tools to help
                 identify these resistance and support levels so that
                 they can by used in their trading decisions. These
                 decision can be put into trading strategies composed of
                 rules designed to mitigate losses after a trade is
                 started, often called stop loss orders, or to take
                 profit at a near optimal time, often called take profit
                 orders. However, identifying such resistance and
                 support levels is notoriously difficult given market
                 volatility. Indeed, the levels need recalculating on a
                 continuous basis, and only hold to an approximate
                 degree. In this work we describe an approach for
                 evolving buy-stay-sell currency trading rules using
                 genetic programming. These rules are explicitly linked
                 to technical indicators that incorporate features
                 characterizing retracement. Benchmarking is then
                 performed using the most recent three years of data
                 from the EURUSD foreign exchange market with three
                 different methods of identifying retracement based on
                 moving average, pivot points and Fibonacci ratios.
                 Investment strategies employing Fibonacci ratios and
                 found to provide superior performance among the
                 strategies examined.",
  notes =        "1010 hrs 15174 CEC2015",

Genetic Programming entries for Alexander Loginov Garnett Carl Wilson Malcolm Heywood