发帖
雷达卡
摘要翻译：
利用随机矩阵理论，我们建立了BM&F-Bovespa（Bolsa de Valores,Mercadorias e Futuros de S\～Ao Paulo）股票之间的协方差矩阵，消除了由于众多股票之间的复杂相互作用和可用数据的有限性而产生的一些噪声，从而得到了BM&F-Bovespa（Bolsa de Valores,Mercadorias e Futuros de S\～Ao Paulo）股票之间的协方差矩阵。我们还使用了一个回归模型，以消除由于所有股票的共同运动而产生的市场效应。然后利用这两个过程来建立基于Markowitz理论的股票投资组合，试图根据过去的数据获得对未来风险的更好预测。从2004年到2010年，巴西股市经历了多年的低波动和高波动。结果表明，用回归方法来减去市场对收益的影响，大大提高了风险预测的准确性，尽管对相关矩阵的清理往往会得到更好地预测风险的投资组合，但在市场波动性较大的时期，这种方法可能无法做到这一点。
---
英文标题：
《Building portfolios of stocks in the S\~ao Paulo Stock Exchange using
Random Matrix Theory》
---
作者：
Leonidas Sandoval Junior, Adriana Bruscato, Maria Kelly Venezuela
---
最新提交年份：
2013
---
分类信息：
一级分类：Quantitative Finance 数量金融学
二级分类：Portfolio Management 项目组合管理
分类描述：Security selection and optimization, capital allocation, investment strategies and performance measurement
证券选择与优化、资本配置、投资策略与绩效评价
--
---
英文摘要：
By using Random Matrix Theory, we build covariance matrices between stocks of the BM&F-Bovespa (Bolsa de Valores, Mercadorias e Futuros de S\~ao Paulo) which are cleaned of some of the noise due to the complex interactions between the many stocks and the finiteness of available data. We also use a regression model in order to remove the market effect due to the common movement of all stocks. These two procedures are then used to build stock portfolios based on Markowitz's theory, trying to obtain better predictions of future risk based on past data. This is done for years of both low and high volatility of the Brazilian stock market, from 2004 to 2010. The results show that the use of regression to subtract the market effect on returns greatly increases the accuracy of the prediction of risk, and that, although the cleaning of the correlation matrix often leads to portfolios that better predict risks, in periods of high volatility of the market this procedure may fail to do so.
---
PDF链接：
https://arxiv.org/pdf/1201.0625
京公网安备 11010802022788号
