Evolving Technical Trading Strategies Using Genetic Algorithms: A Case About Pakistan Stock Exchange

被引：0

作者：

Khan, Basit Tanvir ^{[1
]}

Javed, Noman ^{[1
]}

Hanif, Ambreen ^{[1
]}

Raja, Muhammad Adil ^{[1
]}

机构：

[1] Namal Coll, Mianwali, Pakistan

来源：

INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2017 | 2017年 / 10585卷

关键词：

EFFICIENT CAPITAL-MARKETS;

D O I：

10.1007/978-3-319-68935-7_37

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Finding optimum trading strategies that maximize profit has been a human desire since the inception of the first stock market. Many techniques have been employed ever since to accomplish this goal without sacrificing much computational power and time. In this paper, Genetic Algorithms (GAs) are used to achieve the aforementioned objectives. The performances of trading strategies devised by the GA are compared with the performance of the infamous Buy and Hold (B&H) Strategy. The stocks on which the performances are compared belong to Pakistan Stock Exchange (PSX). The strategies generated by GA outperform the B&H strategies on these stocks.

引用

页码：335 / 344

页数：10

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