- author = "R. G. Bates and M. A. H. Dempster and Y. S. Romahi",
- title = "Evolutionary reinforcement learning in {FX} order book and order flow analysis",
- booktitle = "IEEE International Conference on Computational Intelligence for Financial Engineering",
- year = "2003",
- pages = "355--362",
- address = "Hong Kong",
- month = "20-23 " # mar,
- keywords = "genetic algorithms, genetic programming",
-
URL = "
http://mahd-pc.jbs.cam.ac.uk/archive/PAPERS/2003/WP06.pdf",
-
DOI = "
doi:10.1109/CIFER.2003.1196282",
-
abstract = "As macroeconomic fundamentals based modelling of FX
time series have been shown not to fit the empirical
evidence at horizons of less than one year, interest
has moved towards microstructure-based approaches.
Order flow data has recently been receiving an
increasing amount of attention in equity market
analyses and thus increasingly in foreign exchange as
well.
In this paper, order flow data is coupled with order book derived indicators and we explore whether pattern recognition techniques derived from computational learning can be applied to successfully infer trading strategies on the underlying timeseries.
Due to the limited amount of data available the results are preliminary. However, the approach demonstrates promise and it is shown that using order flow and order book data is usually superior to trading on technical signals alone.",
-
notes = "Final report to HSBC Investment Bank, November (2002).
Location: Technical report WP06/2003
",
