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中国管理科学 ›› 2008, Vol. 16 ›› Issue (5): 9-16.

• 论文 • 上一篇    下一篇

STAR与ANN模型:证券价格非线性动态特征及可预测性研究

苏治1, 方明2, 李志刚3   

  1. 1. 清华大学经济管理学院, 北京100084;
    2. 吉林大学数学研究所, 吉林长春130012;
    3. 吉林大学商学院, 吉林长春130012
  • 收稿日期:2008-01-23 修回日期:2008-09-30 出版日期:2008-10-31 发布日期:2008-10-31
  • 作者简介:苏治(1977- ),男(汉族),吉林长春人,清华大学经济管理学院金融系博士后,研究方向:金融市场投资与公司金融.
  • 基金资助:

    中国博士后科学基金资助项目(20070410539);国家自然科学基金资助项目(70573040);国家社会科学基金项目(06CJL006)

STAR & ANN Model: Study on Nonlinear Dynamic Characteristics of Securities Price and Its Forecast

SU Zhi1, FANG Ming2, LI Zhi-gang3   

  1. 1. School of Economics and Management, Tsinghua University, Beijing 100084, China;
    2. Mathematical Research Institute, Jilin University, Jilin Changchun 130012, China;
    3. Business School, Jilin University, Jilin Changchun 130012, China
  • Received:2008-01-23 Revised:2008-09-30 Online:2008-10-31 Published:2008-10-31

摘要: 证券价格的可预测性一直是现代金融学的研究焦点。近年来,以平滑迁移(STAR)模型和神经网络(ANN)模型为代表,国外学者将许多非线性模型应用于证券价格非线性动态特征及可预测性的研究。本文采用多种线性、非线性股价预测模型对上证180指数短期和中长期可预测性进行研究,并基于统计指标和投资策略指标比较了不同模型的预测能力。结果表明:我国证券价格具有非线性特征,在短期和中长期水平上具有一定的可预测性,这对有效市场假说提出了质疑;ANN模型的预测能力多数情况下优于RW模型、线性AR模型和STAR模型,基于ANN模型的"盯市"投资策略能获得比"买入持有"投资策略更高的平均净收益。

关键词: 有效市场, 可预测性, 非线性模型, 投资策略

Abstract: In finance,scholars applied no nlinear models to describe and predict securities price movement in recent years,especially using Smooth Transition Auto Regression(STAR)model and Artificial Neural Network(ANN)model.In this paper,we examine the out-of-sample fo recasts performance of several linear and no nlinear models for ShangZheng 180 index in short term,middle term and relatively long term as well.We compare their forecast precision by statistical and investment criteria.The results indicate that securities price has nonlinear characteristics in our country,and is able to be predicted in some extent, which put the Efficient Markets Hypothesis(EMH)into question.Furthermore,ANN models mostly produce better forecasts than the RW,AR model as well as STAR model.Nevertheless,on average,investors can obtain a higher net return according to a market-timing strategy based on the forecasts fro m ANN models than a risk-adjusted buy and hold strategy.

Key words: efficient market, predictable, nonlinear model, investment strategy

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