英文标题:
《Random walks and market efficiency in Chinese and Indian equity markets》
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作者:
Oleg Malafeyev, Achal Awasthi, Kaustubh S. Kambekar
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最新提交年份:
2017
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英文摘要:
Hypothesis of Market Efficiency is an important concept for the investors across the globe holding diversified portfolios. With the world economy getting more integrated day by day, more people are investing in global emerging markets. This means that it is pertinent to understand the efficiency of these markets. This paper tests for market efficiency by studying the impact of global financial crisis of 2008 and the recent Chinese crisis of 2015 on stock market efficiency in emerging stock markets of China and India. The data for last 20 years was collected from both Bombay Stock Exchange (BSE200) and the Shanghai Stock Exchange Composite Index and divided into four sub-periods, i.e. before financial crisis period (period-I), during recession (period-II), after recession and before Chinese Crisis (periodIII) and from the start of Chinese crisis till date (period- IV). Daily returns for the SSE and BSE were examined and tested for randomness using a combination of auto correlation tests, runs tests and unit root tests (Augmented Dickey-Fuller) for the entire sample period and the four sub-periods. The evidence from all these tests supports that both the Indian and Chinese stock markets do not exhibit weak form of market efficiency. They do not follow random walk overall and in the first three periods (1996 till the 2015) implying that recession did not impact the markets to a great extent, although the efficiency in percentage terms seems to be increasing after the global financial crisis of 2008.
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中文摘要:
市场效率假说是全球持有多元化投资组合的投资者的一个重要概念。随着世界经济日益一体化,越来越多的人投资于全球新兴市场。这意味着了解这些市场的效率是相关的。本文通过研究2008年全球金融危机和2015年中国金融危机对中国和印度新兴股票市场效率的影响来检验市场效率。过去20年的数据收集自孟买证券交易所(BSE200)和上海证券交易所综合指数,并分为四个分阶段,即金融危机前(第一阶段)、衰退期间(第二阶段)、衰退后和中国危机前(第三阶段)以及从中国危机开始到日期(第四阶段)。在整个样本期和四个子期内,采用自相关检验、运行检验和单位根检验(增强Dickey-Fuller)相结合的方法,对苏格兰和苏格兰证券交易所(SSE)和疯牛病(BSE)的每日收益进行随机性检验和测试。所有这些测试的证据都支持印度和中国股市都没有表现出弱的市场效率。总体而言,它们并没有遵循随机游走原则,在前三个时期(1996年至2015年),这意味着经济衰退并没有对市场造成很大影响,尽管2008年全球金融危机之后,从百分比来看,效率似乎在提高。
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分类信息:
一级分类:Quantitative Finance 数量金融学
二级分类:Computational Finance 计算金融学
分类描述:Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法,包括蒙特卡罗,偏微分方程,格子和其他数值方法,并应用于金融建模
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一级分类:Quantitative Finance 数量金融学
二级分类:Statistical Finance 统计金融
分类描述:Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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