Designing short term trading systems with artificial neural networks

Lecture Notes in Electrical Engineering

Volumn 39 LNEE, Issue , 2009, Pages 401-409

  Vanstone, Bruce ^a   Finnie, Gavin ^b   Hahn, Tobias ^b  

^a BOND UNIVERSITY   (Australia)

^b NONE

Author keywords

Artificial Neural Network; Short Term; Trading strategy; Trading System; Vanstone and Finnie methodology

Indexed keywords

ARTIFICIAL NEURAL NETWORK; SHORT-TERM; TRADING STRATEGY; TRADING SYSTEM; VANSTONE AND FINNIE METHODOLOGY;

BACKPROPAGATION; ELECTRICAL ENGINEERING; NEURAL NETWORKS;

COMMERCE;

EID: 78651562073     PISSN: 18761100     EISSN: 18761119     Source Type: Book Series    
DOI: 10.1007/978-90-481-2311-7_34     Document Type: Conference Paper

References (9)

1. Vanstone, B. and Finnie, G. (2007). "An Empirical Methodology for developing Stockmarket Trading Systems using Artificial Neural Networks."Expert Systems with Applications. In-Press (DOI: http://dx.doi.org/10.1016/j.eswa.2008.08.019).
2. Elder, A. (2006). Entries & Exits: Visits to Sixteen Trading Rooms. Hoboken, NJ: Wiley.
3. guppytraders.com. "Guppy Multiple Moving Average."Retrieved 04-05-2007, from www.guppytraders.com/gup329.shtml
4. Guppy, D. (2004). Trend Trading. Milton, QLD: Wrightbooks.
5. Vanstone, B. (2006). Trading in the Australian stockmarket using artificial neural networks, Bond University. Ph.D.
6. "Norgate Premium Data."(2004). Retrieved 01-01-2004, from www.premiumdata.net
7. Wealth-Lab."(2005) from www.wealth-lab.com
8. Tharp, V. K. (1998). Trade Your Way to Financial Freedom. New York: McGraw-Hill.
9. Sweeney, J. (1996). Maximum Adverse Excursion: Analyzing Price Fluctuations for Trading Management. New York, Wiley.