标题: 运用自组织映射图神经网路于股票型基金市场行为发现
Applying Self-Organizing Map for Discovery Market Behavior of Equity Fund
作者: 陈振华
Chen, Jen-Hua
陈安斌
Chen, An-Pin
管理学院资讯管理学程
关键字: 自组织映射图神经网路;股票型基金;Self-Organizing Map;Equity Fund
公开日期: 2008
摘要: 投资理财是一门重要的学问,也是门不太容易的学问,必须敏锐地趋利避险,才能提高获利的机会。共同基金也被一般人称为“懒人投资法”。基金投资门槛极低,像是国内的共同基金单笔申购仅需新台币一万元,定期定额投资最低更只要三千元,不论您是大富翁或是小散户,都可以藉由投资基金敲开累积财富之门,是一种“共聚资金、共担风险、共同分享投资利润”的投资方法。

然而投资是存在风险的,投资者在进行基金投资时,总希望趋吉避凶,在多头时,能够买入报酬率最佳的基金,在空头时,能够不持有基金而避免损失,甚至是用期货做反向获利;本研究从国内众多的基金市场中挑选189档股票型基金,以及13个总体经济指标,经过适当的资料处理后,做为自组织映射图神经网路的输入值,从中建构基金市场行为趋势发现模型,并依此模型进行投资交易模拟。

实证结果发现于2002年1月至2008年12月期间,采用本模型模拟交易策略3,进行基金市场模拟交易,总报酬率可达122%,而同时期的加权指数为 -22%,随机交易策略平均报酬率为 -25%,明显说明运用本研究模型进行基金投资,将可有效击败大盘及随机交易;实验过程中亦发现依据模型的买卖讯号可对大盘的多空趋势进行掌握,并且也提供投资人进行基金标的物选择时的参考依据。
Investment strategy is something that is important to the general public though at the same time is difficult to be formulated. Mutual fund, as one implementation of the investment strategy, may be a good fit to people without much time or willingness to track their investment portfolio on a frequent basis. The threshold for the mutual fund investment is relatively low. For example, to make single mutual fund investment locally may only cost ten thousands (10,000) NTD. And when people choose to investment their money on a monthly basis only three thousands (3,000) NTD may be enough. Regardless of the investor’s financial status, the mutual fund creates an opportunity for people to properly manage their fortunes by pooling their investment money, sharing the risks associated with the investment, and enjoying the profit together.
However, any investment comes with the risks. Any investor including the mutual fund investor desires to maximize the profit of his/her investment portfolio while minimizing the loss. Any investor desires to purchase the mutual fund with a superior investment return ratio in the bull market. The investor may not want to be in possession of any mutual fund during the downturn of economy in order to avoid the loss, and even likes to reap certain profits by investment in futures. The present research picks and processes one hundred and eighty nine (189) domestic equity mutual funds and thirteen (13) macroeconomics indices to serve as inputs for self-organizing map neural networks so as to formulate a model for mutual fund market behavior and trend discovery. With such model in place, the present research further simulates investment transactions to verify its efficiency.
Our verification shows the investment strategy formulated on the basis of the established model the overall investment return could be as high as one hundred and twenty two (122) percents of the investment while the Taiwan weighted stock index was down by twenty two (22) percents during the period from Jan., 2002 to Dec., 2008. That the average ratio of investment return stands at minus twenty-five (25) percents during the same period further suggests utilizing the model proposed by the present research for the mutual fund investment could outperform the random investment and stock transactions. The present research might also predict the trend of the stock market through buy/sell signals according to the established model, which further provides the investors with a valuable reference when it comes to selecting a target for the mutual fund investment.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT079664529
http://hdl.handle.net/11536/43732
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