Dynamic linkages between the monetary policy variables and stock market in the presence of structural breaks: evidence from India

Abdul Moizz, S.M. Jawed Akhtar
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Abstract

PurposeThe study aims to determine the long and short-term causal relationships between the variables associated with the adjustment of monetary policy and the stock market in India in the presence of structural breaks.Design/methodology/approachThe study employed the autoregressive distributed lag (ARDL) bounds test and the Error Correction Model to assess long- and short-term causal relationships. The study also used non-frequentist Bayesian inferences for the validity of estimation robustness. The Bai–Perron test is used to identify breakpoint dates for the Indian stock market index, and the Granger Causality test is employed to ascertain the direction of causality.FindingsThe F-bounds test reveals cointegration among the variables throughout the examined period. Specifically, the weighted average call money rate (WACR), inflation (WPI), currency exchange rate (EXE), and broad money supply (M3) exhibit statistical significance with precise signs. Furthermore, the study identifies the negative impact of the COVID-19 outbreak in March 2020 on the Indian stock market.Research limitations/implicationsAlthough the study provides significant insights, it is not exempt from constraints. A significant limitation is selecting a relatively limited time period, specifically from April 2008 to September 2023. The limited time frame of this study may restrict the applicability of the results to more comprehensive economic settings, as dynamics between the monetary policy and the stock market can be influenced by multiple factors over varying time periods. Furthermore, the utilisation of the Weighted Average Call Money Rate (WACR) rather than policy rates such as the Repo rate presents an additional constraint as it may not comprehensively account for the impacts of particular policy initiatives, thereby disregarding essential complexities in the connection between monetary policy variables and financial markets.Practical implicationsThe findings of the study suggest that investors and portfolio managers should consider economic issues while developing long-term investing plans. Reserve Bank of India should exercise prudence to prevent any discretionary measures that may lead to a rise in interest rates since this adversely affects the stock market. To mitigate risk, investors should closely monitor the adjustment of monetary policy variables.Social implicationsThe study has important social implications, especially regarding the lower levels of financial literacy among investors in India. Considering the complex nature of the study’s emphasis on monetary policy adjustments and their impact on the stock market. Investors face the risk of significant losses due to unexpected adjustments in monetary policy. Many individuals may need help understanding how policy changes impact their investments. Therefore, RBI must consider both price and financial stability when formulating monetary policies. Furthermore, market participants should consider the potential impact of fluctuating monetary policy variables when devising their long-term investment strategies. Given that adjustments in interest rates can markedly affect stock market dynamics, investors must carefully assess the implications of monetary policy decisions on their portfolios.Originality/valueThe study uses dummy variables in the ARDL model to represent structural breaks that emerged from the COVID-19 pandemic (as determined by the Bai–Perron multiple breakpoint test). The study also used the Perron unit root test to find out the stationary of the series in the presence of structural breaks. Additionally, the study also employed Bayesian inferences to affirm the robustness of the estimates.
存在结构性中断时货币政策变量与股票市场之间的动态联系:来自印度的证据
目的本研究旨在确定在存在结构性中断的情况下,与货币政策调整相关的变量与印度股市之间的长期和短期因果关系。研究还使用了非频率贝叶斯推论来验证估计的稳健性。使用 Bai-Perron 检验来确定印度股市指数的断点日期,并使用格兰杰因果检验来确定因果关系的方向。具体而言,加权平均活期存款利率(WACR)、通货膨胀率(WPI)、货币汇率(EXE)和广义货币供应量(M3)在统计意义上具有精确的符号。此外,该研究还确定了 2020 年 3 月爆发的 COVID-19 对印度股市的负面影响。一个重要的限制因素是选择了一个相对有限的时间段,特别是从 2008 年 4 月到 2023 年 9 月。由于货币政策与股票市场之间的动态关系在不同的时间段内可能受到多种因素的影响,因此本研究的有限时间段可能会限制研究结果在更全面的经济环境中的适用性。此外,使用加权平均活期存款利率(WACR)而非回购利率等政策利率也带来了额外的限制,因为它可能无法全面考虑特定政策措施的影响,从而忽略了货币政策变量与金融市场之间联系的基本复杂性。印度储备银行应谨慎行事,防止采取任何可能导致利率上升的酌情措施,因为这会对股市产生不利影响。为降低风险,投资者应密切关注货币政策变量的调整。社会影响本研究具有重要的社会影响,尤其是对印度投资者较低的金融知识水平而言。考虑到该研究强调货币政策调整及其对股市影响的复杂性。投资者面临着因货币政策的意外调整而遭受重大损失的风险。许多人可能需要帮助才能理解政策变化如何影响他们的投资。因此,RBI 在制定货币政策时必须同时考虑价格和金融的稳定性。此外,市场参与者在制定长期投资战略时,应考虑货币政策变量波动的潜在影响。鉴于利率调整会显著影响股市动态,投资者必须仔细评估货币政策决策对其投资组合的影响。原创性/价值该研究在 ARDL 模型中使用虚拟变量来代表 COVID-19 大流行病中出现的结构断裂(由 Bai-Perron 多重断点测试确定)。研究还使用了 Perron 单位根检验,以找出存在结构性中断时序列的静态性。此外,研究还采用了贝叶斯推论来确认估计值的稳健性。
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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