Interest Rate Sensitivity of Non-banking Financial Sector in India

Abstract

Executive Summary Before financial liberalization, interest rates were administered and exhibited near-zero volatility. The easing of financial repression in the 1990s generated experiences with interest rate volatility in India. Administrative restrictions on interest rates in India have been steadily eased since 1993. This has led to increased interest rate risk for financial firms. Most research studies have almost exclusively focused on the developed countries especially the banking sector of the United States. The present study attempts to examine the interest rate risk of non-banking financial institutions in India by using the methodology of panel regression and generalized autoregressive conditional heteroscedasticity (GARCH) (1, 1) model for the period from 1 April 1996 to 30 August 2014. The sample used in the study consists of all non-banking financial companies (NBFCs) listed in the S&P CNX 500 index which has continuous availability of share prices over the study period. The study also examines the impact of unanticipated changes in interest rate on stock returns of NBFCs. The Box–Jenkins methodology is applied to calculate unanticipated changes in interest rate variable, autoregressive integrated moving average (ARIMA) (24, 1, 0) model. The time series used in the present study is found to be stationary at the first logarithmic difference. Stock returns exhibit significant exposure with both market returns and interest rate changes. The interest rate sensitivity of large, medium, and small financial institutions is also found to be different. Estimation results for the variance equation in GARCH (1, 1) model suggest that the volatility for individual firm stock returns is time-variant. The ARCH and GARCH coefficients are found to be significant, providing evidence against using traditional model (ordinary least square (OLS)) that assumes time-invariant volatility. This implies that the market has a memory longer than one period and volatility is more sensitive to its own lagged values than it is to new surprises in the market. This study also investigates the possible determinants that account for cross-sectional variation in the interest rate sensitivity of NBFCs. It is found that the size of the firm is the preferred determinant that accounts for cross-sectional variation in the interest rate sensitivity of finance companies. When unanticipated changes in interest rate are used in lieu of actual interest rate changes, not much difference is observed in the significance coefficients. The only significant difference observed is in the magnitude. The impact of actual interest rate changes is more than the impact of unanticipated interest rate changes in absolute terms. This difference in the magnitude of impact arises because actual data incorporate movement in both anticipated and unanticipated components of interest rate. Hence, NBFCs managers and regulators should adopt policies and strategies to avoid the transmission of interest rate risk in their stock returns.

Analisis Pengaruh Interest Rate, Exchange Rate, Inflation, Covid-19 Terhadap Lq-45

“…Berdasarkan rumusan masalah yang ada dalam penelitian ini, maka dari sini dapat disimpulkan tujuan dari penelitian ini, yakni: a. Untuk mengerti apakah tingkat suku bunga memiliki efek dengan harga saham yang terdaftar di dalam Indeks LQ45. 2017), Haque & Sarwar (2012), Linck & Decourt (2016), Oshaibat (2017), Ghosh et al (2018), Sutrisno (2017), Balagobei (2017), Barakat et al (2015), Iqmal & Putra (2020), Tangjitprom (2012), membuktikan suku bunga dan return indeks saham memiliki ikatan yang bersifat negatif yang signifikan. Ketika suku bunga naik, investor dapat mengalokasikan uang mereka untuk investasi sekuritas.…”

A Review Paper on Shadow Banking in India

“…Corporate Governance Insight, Volume-3, Issue-1, eISSN: 2582-0834 Ghosh et al (2018) examined the interest rate sensitivity of NBFCs in India by using the techniques of panel regression and generalized autoregressive conditional heteroscedasticity (GARCH) (1,1). The relevant time period for the study was taken as 1 April 1996 to 30 August 2014.…”

The Influence of Specific Indicators on the Volatility of Shares on the Bucharest Stock Exchange During the Covid-19 Pandemic

“…The literature includes the influence of macroeconomic indicators and factors specific to listed companies on the share prices of listed companies. Studies, older or more recent, show the influence of an indicator or group of indicators on the stock market price (Aveh & Awunyo-Vitor, 2017;Ghosh et al, 2018;Shaikh et al, 2017;Aliu et al, 2021;Pelcher, 2019;Modigliani & Miller, 1958;Erasmus, 2013;Hooi et al, 2015). The values of the stock market indicators on January 1, 2020, for each company included in the research were collected from the BSE platform.…”