Discovering profitable stocks for intraday trading

被引:11
|
作者
Baralis, Elena [1 ]
Cagliero, Luca [1 ]
Cerquitelli, Tania [1 ]
Garza, Paolo [1 ]
Pulvirenti, Fabio [1 ]
机构
[1] Politecn Torino, Dipartimento Automat & Informat, Corso Duca degli Abruzzi 24, I-10129 Turin, Italy
关键词
Stock data mining; Sequence mining; Weighted data; NETWORK;
D O I
10.1016/j.ins.2017.04.013
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Intraday traders buy and sell financial instruments in the short term, typically within the same trading day. Stocks are notable examples of financial instruments. However, since hundreds of stocks are listed on the stock exchange selecting on each trading day the most tradeable stocks is a challenging task, which is commonly addressed through manual inspection of historical stock prices and technical indicators. This paper aims at discovering tradeable stocks on a given trading day by analyzing the historical prices assumed by the same stocks or by other ones on the preceding days by means of regression and weighted sequence mining techniques. The use of regression and weighted sequence mining techniques allows traders to automatically consider a potentially large number of candidate stocks and to effectively analyze their price variations across consecutive days. The experimental results, which were achieved on data acquired from different markets and under different market conditions, show that sequence mining algorithms yield profits higher than both regression techniques and naive strategies. (C) 2017 Elsevier Inc. All rights reserved.
引用
收藏
页码:91 / 106
页数:16
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