估计印度共同基金净资产价值与经济决定因素关系的自回归分布滞后方法

Sathish Pachiyappan, Ankita Shrivastava, V. J. P. Raj, Saravanan Vellaiyan
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引用次数: 0

摘要

印度的累计共同基金投资出现了惊人的增长,从2012年的7.93万亿卢比增长到2022年的40.38万亿卢比,比过去10年增长了5倍多。散户投资者现在开始意识到储蓄和系统性投资计划(SIP)在积累长期财富方面的力量。席卷印度的金融知识浪潮预计共同基金将成为这一现象的重要贡献者和受益者。印度不断变化的经济格局为投资者提供了极好的机会,通过系统地投资于共同基金等安全投资工具,从这些波动中获利。与共同基金相关的市场总是受到经济风险的影响。宏观经济变量的不稳定波动可以在很大程度上解释股票型共同基金的资产净值波动。在此背景下,本文考察了选定的宏观经济变量对印度共同基金业绩的影响。为了分析这一点,我们收集了从2013年1月到2022年11月的10年间,对选定宏观经济变量的月度观察,即大盘股、中盘股和小盘股基金的平均资产净值。描述性统计用来探测变量的特征。此外,运用相关和普通最小二乘法检验宏观经济因素对所选方案资产净值的存在关系和影响程度。最后,利用自回归分布滞后模型(ARDL)分析了短期和长期的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Autoregressive Distributed Lag Approach for Estimating the Nexus between Net Asset Value of Mutual Fund and Economic Determinants in India
India has seen a phenomenal growth in cumulative mutual fund investment from Rs 7.93 trillion in 2012 to Rs 40.38 trillion in 2022, which is more than a five-fold increase since last 10 years. Retail investors are now realizing the power of savings and Systematic Investment Plans (SIP) to build long term wealth. A financial literacy wave which is sweeping across India has projected mutual funds as a significant contributor and beneficiary of this phenomenon. The evolving economic landscape of India provides investors with excellent opportunities to capitalize on these fluctuations through systematic investment in safe investment vehicles like mutual funds. The market associated with mutual funds is always subjected to economic risks. The erratic fluctuations in macroeconomic variables can largely explain the Volatility in Net Asset Value (NAV) of equity oriented mutual fund schemes. With this background, this paper examines the impact of select macroeconomic variables on mutual funds’ performance in India. To analyse this, monthly observations of select macroeconomic variables, average NAV of large cap, mid cap, and small cap funds collected for a period of 10 years starting from January 2013 to November 2022. Descriptive statistics is used to probe the characteristics of the variable. In addition, correlation and ordinary least square method is applied to check the existing relationship and impact level of macroeconomic factors on NAV of select schemes. Lastly, short and long run relationship is analysed using Autoregressive Distributed Lag Model (ARDL).
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