運用模糊倒傳遞類神經網路在箱型理論股票市場漲跌預測之應用

The Application of Price Fluctuation of Stock Market Based on Box Theory in Fuzzy Back-propagation Neural Network

陳勤達(Chen Chin-Da)

指導教授 ： 蘇慶隆

長榮大學/資訊暨工程學院/資訊管理研究所/碩士(2007年)

https://doi.org/10.6833/CJCU.2007.00079

摘要

本研究以股價波動理論中由達拉斯提出的箱型理論和股價循環趨勢測量學中的黃金螺旋測量原理為基礎，分析股價在支撐和壓力之間震盪的往返重覆性運動；將箱型理論、黃金螺旋測量原理和多重技術指標作為模糊規則庫的建立後，導入多階層倒傳遞類神經網路，最後結合模糊規則庫和倒傳遞類神經網路，完成模糊倒傳遞類神經網路訓練，以對股價波動進行預測和未來走勢。

關鍵字

箱型理論 ； 黃金螺旋測量原理 ； 模糊理論 ； 倒傳遞類神經網路

並列摘要

The study is based on box theory by Nicolas Darvas and golden spiral of measurement by the recurrent trend of the stock to analyze the stock of upside and downside repeatedly. Using the box theory, golden spiral of measurement and multiple indexes to establish the knowledge base of fuzzy rules, we construct a three layers back-propagation neural network to integrate the knowledge base of fuzzy rules. When completing training fuzzy back-propagation neural network, we are capable of forecasting the price fluctuation and trend of the stock.

並列關鍵字

Box Theory ； Golden Spiral of Measurement Principle ； Fuzzy Theory ； Back-propagation Neural Network

參考文獻

[16] Yoshinori Kawasaki, Seisho Sato, Shigeru Tachiki (2000), “Vector-Valued Multiple Regression Model with Time Varying Coefficients and its Application to Predict Excess Stock Returns”, Computational Intelligence for Financial Engineering, 162-165.

[17] Harrald Paul G.., Mark Kamstra, (1997), “Evolving artificial neural networks to combine financial forecasts”, IEEE Transactions on Evolutionary Computation,Vvol. 1, 40-52.

[18] Michael Negnevitsky (2004), “Artificial Intelligence: A Guide to Intelligent Systems”, 2/e, Addison Wesley.

一、中文部分

[1] 胡為善（2001），外資買賣超交易資訊對股價波動影響之研究，中原大學企業管理研究所碩士論文。