...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>African Journal of Business Management >A newly application of the random matrix theory on the exploration of the efficiency of investment portfolios in the Taiwan Stock Market
【24h】

A newly application of the random matrix theory on the exploration of the efficiency of investment portfolios in the Taiwan Stock Market

机译：随机矩阵理论在台湾股票市场投资组合效率探索中的新应用

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In the past, the investment portfolio theory regarding stock price deviation was considered to be individual risk that occurred in the market at random. However, the outcome efficiency of portfolios could be influenced by other factors that were found to be interrelated. In this study, we attempted to filter out those random parts of correlation matrix by the walk forward approach (WFA), and applied the Random matrix theory (RMT) that was developed from nuclear physics. We constructed a portfolio and then estimate the accumulation returns and Sharpe ratio. Based on the daily trading records from the Taiwan Stock Exchange (TWSE), the component indexes were grouped into 19 categories from Jan. 2, 2007 to Jan. 29, 2010, and there were a total of 767 data set entries as input information to this study. We employed variance tests, ANOVA,?and least squares mean (LSM) to test the results. This study finds that, in general, the random part of stock return increases the portfolio risk, and consequently decreases the efficiency of the portfolio. In addition, this study adapted the concept of?principal component analysis to?analyze the information eigenvectors, which provided the information sequence for detecting the presence of unusual information that might affect the portfolio. As a result, the new approach could be helpful in forecasting the direction of price fluctuation.
机译：过去，关于股票价格偏差的投资组合理论被认为是随机出现在市场中的个人风险。但是，投资组合的结果效率可能会受到其他相互关联的因素的影响。在这项研究中，我们尝试通过前向方法（WFA）过滤掉相关矩阵的那些随机部分，并应用了从核物理发展而来的随机矩阵理论（RMT）。我们构建了一个投资组合，然后估计累积收益和夏普比率。根据台湾证券交易所（TWSE）的每日交易记录，从2007年1月2日到2010年1月29日，成分指数分为19类，共有767个数据集条目作为输入信息，这项研究。我们采用方差检验，ANOVA和最小二乘均方（LSM）来检验结果。这项研究发现，总的来说，股票收益的随机部分会增加投资组合的风险，从而降低投资组合的效率。此外，本研究采用“主要成分分析”的概念来分析信息特征向量，从而为检测可能影响投资组合的异常信息提供了信息序列。因此，新方法可能有助于预测价格波动的方向。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号