Interdependency Between Indian and US Market Indices: A Granger Causality Approach

Sachit Paliwal, Shipra Saxena
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Abstract

The Granger causality model is used in the current study to analyze the short-run cause–effect relationship between two stock market indices between 2001 and 2021 using time series data of the daily closing prices of the BSE Sensex and S&P 500 indices listed in the Indian and US stock markets, respectively. The Granger causality model and the augmented Dickey–Fuller test for data stationarity were used in the study to examine the short-term causal link between two market indices during the time period. The outcomes demonstrated the connection between the Indian and US stock markets. The findings imply that both markets have a dynamic, bidirectional relationship. This study provides the investor’s essential inputs for investment decision-making and portfolio diversification. In the current era of globalization, the study is crucial because investors and fund managers now place a high priority on stock market integration. Through fund diversification across equity markets, this study subsequently makes it easier to reduce portfolio risk by providing useful insights on diversification strategies across the stock markets.
印度和美国市场指数之间的相互依赖关系:格兰杰因果关系方法
本研究采用格兰杰因果关系模型,分别使用印度和美国股市上市的BSE Sensex指数和标普500指数的日收盘价的时间序列数据,分析2001年至2021年两个股市指数之间的短期因果关系。本文采用格兰杰因果关系模型和增强的Dickey-Fuller数据平稳性检验来检验两个市场指数在一定时期内的短期因果关系。结果显示了印度和美国股市之间的联系。研究结果表明,这两个市场都具有动态的双向关系。本研究为投资者的投资决策和投资组合多元化提供了必要的投入。在当今全球化时代,这项研究至关重要,因为投资者和基金经理现在高度重视股市一体化。通过跨股票市场的基金多元化,本研究随后通过提供跨股票市场多元化策略的有用见解,使其更容易降低投资组合风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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