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應用類神經網路於台灣加權股價指數期貨日內行為知識發現
Thesis

應用類神經網路於台灣加權股價指數期貨日內行為知識發現

鄧詠駿
Masters, 國立清華大學, 計量財務金融學系
2011

Abstract

類神經網路 日內交易 台灣加權股價指數期貨 Neutral Network Intraday Price Behavior Taiwan Weighted Stock Index Futures
This study are base on manipulating the method of Artificial Intelligence to improve the flaw when people maneuvered technical or experience analysis merely, as well as modifying the shortcomings of Eight Indicators, which considered only price and quantity. Therefore, the traditional analyses are superseded by measuring the variation among three sampling points, variety technical indicators and inverse neutral network to establish a model; with that people could forecast the closing price on the day and the opening price on the next day of Taiwan weighted stock index future. Data collection is from third of January, 2011 to 29th of November, 2011. Some consequences from experiment are drawn as following, 1. Implement of inverse neutral network to project the tendency of Taiwan weighted stock index future is workable. 2. As inputting the same variable, the overnight effect would dilute the accurate rate. 3. Exercise modificatory BIAS as a input to predict the opening and closing market model would be more accurate than use MA, RSI and KD indicators.

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