Dynamic Stock Trading Strategy Based on Various Moving Average with Meta-heuristic Algorithm

Autor: CHEN, CHIH-CHI, 陳智琦
Rok vydání: 2016
Druh dokumentu: 學位論文 ; thesis
Popis: 104
In our research proposed a trading system with dynamic analysis ability. Nowadays people are facing inflation and low interest in bank savings, lots of people try to gain some profit in making investments. By comparison, stock market becomes a hot financial product because of the low threshold and the transparent information. But the stock market is changeable, how to gain stable profit without losing money is a difficult problem. Previous literatures observe the change of price and volume to make trading decision, which knows as technical analysis. Recently, computation intelligence is imported into financial market to assist making investment strategy. The research propose a novel dynamic trading system. We utilize simple but enduring technical indicator, Moving Average (MA). Our method applies the MA with released traditional restriction. Also, a modified evolutionary algorithm, Globe Best-guide Quantum-Inspired Tabu Search Algorithm (GQTS), is invented to search the optimal MA parameter quickly and stably. Furthermore, combining sliding window with the conception of 2-phase is applied to the rapidly changeable stock trading problem. The experimental environment is Taiwan stock market. The experiment result reveals that our method has greatly improved ability of MA, and get some exceptional discover with MA. Moreover, our method shows well profitability than the previous method.
Databáze: Networked Digital Library of Theses & Dissertations