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Correlation and volatility in an Indian stock market: A random matrix approach

机译:印度股票市场的相关性和波动性:随机矩阵方法

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We examine the volatility of an Indian stock market in terms of correlation of stocks and quantify the volatility using the random matrix approach. First we discuss trends observed in the pattern of stock prices in the Bombay Stock Exchange for the three-year period 2000-2002. Random matrix analysis is then applied to study the relationship between the coupling of stocks and volatility. The study uses daily returns of 70 stocks for successive time windows of length 85 days for the year 2001. We compare the properties of matrix C of correlations between price fluctuations in time regimes characterized by different volatilities. Our analyses reveal that (i) the largest (deviating) eigenvalue of C correlates highly with the volatility of the index, (ii) there is a shift in the distribution of the components of the eigenvector corresponding to the largest eigenvalue across regimes of different volatilities, (iii) the inverse participation ratio for this eigenvector anti-correlates significantly with the market fluctuations and finally, (iv) this eigenvector of C can be used to set up a Correlation Index, CI whose temporal evolution is significantly correlated with the volatility of the overall market index.
机译:我们根据股票的相关性检查印度股市的波动性,并使用随机矩阵方法量化波动性。首先,我们讨论孟买股票交易所在2000年至2002年的三年期间股票价格走势中观察到的趋势。然后应用随机矩阵分析来研究股票耦合与波动之间的关系。该研究使用2001年的连续85天的连续时间窗中的70只股票的日收益率。我们比较了以不同波动率为特征的时间范围内价格波动之间的相关性矩阵C的性质。我们的分析表明,(i)C的最大(有偏差)特征值与指数的波动性高度相关,(ii)与不同波动率范围内的最大特征值相对应的特征向量分量分布发生了变化,(iii)该特征向量的逆参与比与市场波动显着相关,最后,(iv)C的这个特征向量可用于建立一个相关指数CI,其时间演化与该指数的波动性显着相关整体市场指数。

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