- 期刊
Improved Non-equidistant Grey Model GM(1,1) Applied to the Stock Market
並列摘要
Although grey prediction has been applied in the financial field extensively, for large change data, this prediction method is not very efficient. To solve this problem, we improve the classical non-equidistant GM (1,1). To be more specific, n-AGO transformation takes the place of the original data, which is called as mGM (n,1). Besides, we use mGM (2,1) to forecast the turnover rate of the stock price. From both the rational mathematical derivative process and the actual predicted result, we have sound reasons to believe that this modified grey model is efficient for the large change data.
延伸閱讀
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