![]() Simon Gervais & Ron Kaniel & Dan Mingelgrin, "undated". ![]() A short discussion concerning the system improvements regarding to the application of GPLAB is also included. At the end of this paper also revealed the strength and weakness of GPLAB as a financial forecasting tool. This paper also further indicates the credibility of different technical and fundamental factors regarding to the prediction of future price movement in four different market situations including non-specific, static, bull and bear market period. This empirical evidence suggests the market efficiency in TWSE is a semi-strong form market that stock price movement could be predicted with the analysis of historical data. The empirical results of this inter-discipline study has revealed this bio-financial hybrid system successfully predicted the stock price movement in a one-month forecasting range by 23% and 22% lower than the appointed benchmark during a random chosen period and a bear market period respectively. This concept has been applied on the field of finance to build up forecasting models predicting future price movement within one day, one month and one season. GPLAB was built on biological evolutionary concept to realize fittest surviving rules in the natural selection process. This paper intends to demonstrate the application of an artificial intelligence system named GPLAB on the prediction of stock price movement in TWSE. The establishment of the Stock Movement Forecasting System has become an important issue. Now, TAIEX has exceeded the level before the financial crisis. It has been even dramatically losing 60%. Taiwanese economy exhibited a negative growth of 7.53%, and the fluctuation is manifest in Taiwan stock index. It broke out in the United States, and then spread to the whole world. The financial tsunami is a crisis that happened in 2007.
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