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Please use this identifier to cite or link to this item: http://hdl.handle.net/10692/420

Title: Trend recalling algorithm for automated online trading in stock market
Authors: Fong, Simon
Tai, Jackie
Pichappan, Pit
Issue Date: Aug-2012
Publisher: ACADEMY PUBLISHER
Citation: Journal of Emerging Technologies in Web Intelligence, Aug. 2012, vol. 4, no. 3, p. 240-251
Abstract: Unlike financial forecasting, a type of mechanical trading technique called Trend Following (TF) doesn’t predict any market movement; instead it identifies a trend at early time of the day, and trades automatically afterwards by a pre-defined strategy regardless of the moving market directions during run time. Trend following trading has a long and successful history among speculators. The traditional TF trading method is by human judgment in setting the rules (aka the strategy). Subsequently the TF strategy is executed in pure objective operational manner. Finding the correct strategy at the beginning is crucial in TF. This usually involves human intervention in first identifying a trend, and configuring when to place an order and close it out, when certain conditions are met. In this paper, we presented a new type of TF, namely Trend Recalling algorithm that operates in a totally automated manner. It works by partially matching the current trend with one of the proven successful patterns from the past. Our experiments based on real stock market data show that this algorithm has an edge over the other trend following methods in profitability. The new algorithm is also compared to time-series forecasting type of stock trading, and it can even outperform the best forecasting type in a simulation.
URI: http://hdl.handle.net/10692/420
Other links: http://dx.doi.org/10.4304/jetwi.4.3.240-251
ISSN: 1798-0461
Keyword(s): Trend following algorithm
Automated stock market trading
Appears in Collections:CIS Journal Articles

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