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題名:螞蟻理論在臺灣股市投資決策的應用
書刊名:創新研發學刊
作者:方閔正譚百齡
作者(外文):Fang, Min-jengTan, Bai-lin
出版日期:2009
卷期:5:2
頁次:頁17-31
主題關鍵詞:螞蟻理論技術分析投資決策風險中立Ant colony optimizationTechnical analysisRisk avoiderRisk takerRisk neutral
原始連結:連回原系統網址new window
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  • 點閱點閱:19
本研究結合ACO的特性並利用技術分析中的股票成交量與報酬率等指標,建構投資決策資金分配數學模式。針對台灣股票市場分別隨機選擇六支電子業股票(三大盤三小盤),作為本系統提供每天六個標的的投資組合;而外另加人銀行作為本研究之避險功用,當投資股票市場之時機不適當時,投資者則可將資本投資銀行,所以可視銀行為避險之作用。本研究投資者以日為投資單位,作為各股票在進出場時點的依據。所以,本研究在當日開盤時為進行進場投資時機,而在每日收盤時為進行賣出動作。 本研究以2005年1月1日至2008年12月31日的台灣上市公司證券每日交易紀錄(股價、交易量、報酬率)作為系統的累積資料,經模擬實驗綜合結論得知:本研究所提出之模型在台灣牛市、熊市及全時期市場比標準系統表現佳且具獲利能力。當蒸發係數低其表現獲利能力佳;當蒸發係數高其表現越為保守但為持有獲利能力,所以本模型具有風險規避及獲利能力。
This research combines the characteristics of ACO with stock trading volume and return rate indicators in technological analysis to construct the capital allocation mathematics model of the investment strategy. Randomly choose six electronic industry stocks in Taiwanese stock markets. It will be the investment combination of six targets in this system; and add bank as hedging function in this research. Investors could invest bank when there are inappropriate opportunities in stock market. So, it could regard bank as hedging function. In this research, investor regards day as the investing unit, an basis checked while buy and sell points each stock. So, this research determines the opening quotation of stock market as buy investment opportunity every day, and the closing price as sell action every day. This research is based on daily stock trading records of listed companies in Taiwan, which includes stock prices, trading volume, and the rate of return from January 1(superscript st), 2005 to December 31st, 2008. The comprehensive conclusions after simulation are as following: The model of this research has better performance and profit making ability than the standard system in bull, bear and whole period of Taiwan stock markets. Finally, the profit making ability is better when the evaporating coefficient is lower. The performance becomes conservative but it still holds profit-making ability when the evaporating coefficient is high. So, this model has hedge and profit making ability.
期刊論文
1.譚百齡(200707)。利用螞蟻系統對公司股票的投資分析--以臺灣上市公司股票為例。蘇州大學學報,4。  延伸查詢new window
2.Botee, H. M.(1998)。Evolving Ant Colony Optimization。Adv. Complex Systems,1,149-159。  new window
3.James, F. E. Jr.(1968)。Monthly Moving Averages: An Effective Investment Tool?。The Journal of Financial and Quantitative Analysis,3(3),315-326。  new window
4.Dorigo, Marco、Gambardella, Luca Maria(1997)。Ant Colony System: A cooperative learning approach to the traveling salesman problem。IEEE Transactions on Evolutionary Computation,1(1),53-66。  new window
5.Dorigo, M.、Gambardella, L. M.(1997)。Ant Colonies for the Traveling Salesman Problem。BioSystems,43(2),73-81。  new window
6.Dorigo, M.、Di Caro, G.、Gambardella, L. M.(1999)。Ant Algorithms for Discrete Optimization。Artificial Life,5(2),137-172。  new window
7.Gunasekarage, Abeyratna、Power, David M.(2001)。The profitability of moving average trading rules in South Asian stock markets。Emerging Markets Review,2(1),17-33。  new window
8.Banerjee, Abhijit V.(1992)。A simple model of herd behavior。The Quarterly Journal of Economics,107(3),797-817。  new window
9.Bessembinder, Hendrik、Chan, Kalok(1995)。The Profitability of Technical Trading Rules in the Asian Stock Markets。Pacific-Basin Finance Journal,3(2/3),257-284。  new window
10.Fama, Eugene F.(1970)。Efficient Capital Markets: A Review of Theory and Empirical Work。The Journal of Finance,25(2),383-417。  new window
學位論文
1.宋威夷(2008)。羊群行為對中國房地產市場的影響(碩士論文)。大連理工大學。  延伸查詢new window
2.於沛欣(2008)。一種混合蟻群演算法在JSP問題中的應用研究(碩士論文)。中國海洋大學。  延伸查詢new window
3.徐俊傑(2007)。元啟發式優化演算法理論與應用研究(碩士論文)。北京郵電大學。  延伸查詢new window
4.裴文(2005)。利用螞蟻族群最佳化及股市技術分析建立股市的投資模型(博士論文)。蘇州大學。  延伸查詢new window
5.熊應(2008)。施工專案資源優化配置理論和方法(博士論文)。北京交通大學。  延伸查詢new window
6.阮國賢(2001)。價值投資與投資報酬間相關性之探討(碩士論文)。銘傳大學。  延伸查詢new window
7.林天中(1998)。臺灣股票市場三因數:系統風險、公司規模及淨值市價比實證研究(碩士論文)。清華大學。  延伸查詢new window
8.許維真(1996)。何種益本比資料有助於選股?--臺灣股市橫斷面報酬率影響因素之研究(碩士論文)。國立台灣大學。  延伸查詢new window
9.陳建良(1994)。我國股票市場異常現象之實證研究(碩士論文)。國立交通大學。  延伸查詢new window
 
 
 
 
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