Paper Info
Title
Forecasting Price Movements in Betting Exchanges Using Cartesian Genetic Programming and ANN.
Abstract
Since the introduction of betting exchanges in 2000, there has been increased interest of ways to monetize on the new technology. Betting exchange markets are fairly similar to the financial markets in terms of their operation. Due to the lower market share and newer technology, there are very few tools available for automated trading for betting exchanges. The in-depth analysis of features available in commercial software demonstrates that there is no commercial software that natively supports machine learned strategy development. Furthermore, previously published academic software products are not publicly obtainable. Hence, this work concentrates on developing a full-stack solution from data capture, back-testing to automated Strategy Agent development for betting exchanges. Moreover, work also explores ways to forecast price movements within betting exchange using new machine learned trading strategies based on Artificial Neuron Networks (ANN) and Cartesian Genetic Programming (CGP). Automatically generated strategies can then be deployed on a server and require no human interaction. Data explored in this work were captured from 1st of January 2016 to 17th of May 2016 for all GB WIN Horse Racing markets (total of 204 GB of data processing). Best found Strategy agent shows promising 83% Return on Investment (ROI) during simulated historical validation period of one month (15th of April 2016 to 16th of May 2016).
Year
DOI
Venue
2018
10.1016/j.bdr.2018.10.001
Big Data Research
Keywords
Field
DocType
Algorithmic trading,Financial series forecasting,Betting exchange
Data science,Trading strategy,Return on investment,Computer science,Operations research,Commercial software,Software,Automatic identification and data capture,Financial market,Market share,Algorithmic trading
Journal
Volume
ISSN
Citations 
14
2214-5796
0
PageRank 
References 
Authors
0.34
5
2
Name
Order
Citations
PageRank
Ivars Dzalbs100.34
Tatiana Kalganova219515.96