文档介绍：Q UANTITATIVE F INANCE V OLUME 1 (2001) 397–413 RESEARCH PAPER
I NSTITUTE OF P HYSICS P UBLISHING quant.
A real-time adaptive trading system
using ic programming
M A H Dempster andCMJones1
Centre for Financial Research2, Judge Institute of Management, University of
Cambridge, Trumpington Street, Cambridge, CB2 1AG, UK
E-mail: ******@ and ******@
Received 15 October 2000
Abstract
Technical analysis indicators are widely used by traders in financial and
commodity markets to predict future price levels and enhance trading
profitability. We have previously shown a number of popular indicator-based
trading rules to be loss-making when applied individually in a systematic
manner. However, technical traders typically binations of a broad
range of technical indicators. Moreover, essful traders tend to adapt to
market conditions by ‘dropping’ trading rules as soon as they e
loss-making or when more profitable rules are found. In this paper we try to
emulate such traders by developing a trading system consisting of rules based
binations of different indicators at different frequencies and lags. An
initial portfolio of such rules is selected by a ic algorithm applied to a
number of indicators calculated on a set of US Dollar/British Pound spot
foreign exchange tick data from 1994 to 1997 aggregated to various intraday
frequencies. The ic algorithm is subsequently used at regular intervals
on out-of-sample data to provide new rules and a feedback system is utilized
to rebalance the rule portfolio, thus creating two levels of adaptivity. Despite
the individual indicators being generally loss-making over the data period,
the best rule found by the developed system is found to be modestly, but
significantly, profitable in the presence of realistic transaction costs.
1. Introduction as systematically as possible without automation while others
use technical analysis as the basis for constructing systems
Some financial modity market trad