A method for automatic stock trading combining technical analysis and nearest neighbor classification

被引:103
作者
Teixeira, Lamartine Almeida [2 ]
Inacio de Oliveira, Adriano Lorena [1 ]
机构
[1] Univ Fed Pernambuco, Informat Ctr, Recife, PE, Brazil
[2] Univ Fed Pernambuco, Dept Comp Syst, Recife, PE, Brazil
关键词
Stock trend prediction; Financial forecasting; Machine learning; Nearest neighbor prediction; MARKETS; MACHINE;
D O I
10.1016/j.eswa.2010.03.033
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper we propose and analyze a novel method for automatic stock trading which combines technical analysis and the nearest neighbor classification. Our first and foremost objective is to study the feasibility of the practical use of an intelligent prediction system exclusively based on the history of daily stock closing prices and volumes. To this end we propose a technique that consists of a combination of a nearest neighbor classifier and some well known tools of technical analysis, namely, stop loss, stop gain and RSI filter. For assessing the potential use of the proposed method in practice we compared the results obtained to the results that would be obtained by adopting a buy-and-hold strategy. The key performance measure in this comparison was profitability. The proposed method was shown to generate considerable higher profits than buy-and-hold for most of the companies, with few buy operations generated and, consequently, minimizing the risk of market exposure. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:6885 / 6890
页数:6
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