Do Macroeconomic Variables Impact the Indian Stock Market?

2016 ◽  
Vol 5 (3) ◽  
Author(s):  
Khalid Ul Islam ◽  
Mohsina Habib
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Stock Returns ◽  
Causal Relationship ◽  
Granger Causality ◽  
Oil Prices ◽  
Granger Causality Test ◽  
Causality Test ◽  
Macroeconomic Variables ◽  
Indian Stock Market

This paper is intended to study the impact of various macroeconomic variables on Indian stock market. Based on the Arbitrage Pricing Theory (APT) propounded by Ross in 1976 and various other studies, a number of macroeconomic variables including, inflation, industrial production, exchange rate, money supply, interest rate, and oil price have been identified to have a significant impact on the stock market. We have applied the multivariate extension of the classical linear regression model computed on Ordinary Least Squares method and Granger Causality test to re-establish the relationship between macroeconomic variables and stock returns over a period of 10 years from 2005 to 2015 using monthly observations. The results of this study show that only exchange rate has a significant negative impact on stock returns. The other macroeconomic variables are not significantly affecting stock returns, however, their impact is in accordance with the economic theory. The Granger Causality test reveals absence of any causal relationship between stock returns and macroeconomic variables, except in case of oil prices, where we find a unidirectional causal relationship running from stock returns to oil prices. However, the Granger Causality results should not be taken in the conventional meaning of causality, but results merely identifying precedence.

scholarly journals Nexus between Stock Market Returns and Economic Variables: Evidence

2017 ◽  
Vol 4 (01) ◽  
Author(s):  
Vanitha Chawla ◽  
Shweta .
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Granger Causality ◽  
Granger Causality Test ◽  
Market Returns ◽  
Causality Test ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
Indian Stock Market ◽  
The Impact

The paper examines the impact of selected macroeconomic variables on the Indian stock market. The macroeconomic variables used in the study are interest rate, exchange rate, index of industrial production (IIP) and gold price. BSE Sensex is used as proxy for Indian stock market. We have used the monthly data for all the variables from January 2001 to December 2016. Regression analysis and Granger Causality test is used to establish the relationship between the stock market and macroeconomic variables. The results show significant impact of only exchange rate on stock returns. All the other variables have shown insignificant impact on the stock market returns. The results of Granger causality test show unidirectional relationship between exchange rate and stock prices and bi-directional relation between IIP and SENSEX.

An Econometric Analysis of Linkages between Macroeconomic Variables and Stock Markets: Evidence from Asian Emerging Markets

GIS Business ◽  
2018 ◽  
Vol 13 (5) ◽  
pp. 21-30
Author(s):  
Risha Khandelwal
Keyword(s):  
Emerging Markets ◽  
Interest Rates ◽  
Stock Returns ◽  
Granger Causality ◽  
Stock Markets ◽  
Unit Root Test ◽  
Granger Causality Test ◽  
Causality Test ◽  
Macroeconomic Variables ◽  
Study Results

The purpose of this paper is to investigate impact of macroeconomic variables on stock markets of India and Indonesia. This paper also attempts to identify linkages between markets and macroeconomic variables. The rationale behind selecting these countries for the present study is MSCI emerging markets index of Asia, which comprises emerging economies with huge return potential for prospective investors. This study will help investors and researchers to understand dynamics of linkages between markets and macroeconomic variables. Augmented Dickey-Fuller (ADF) unit root test is used to assess the stationary of time series, Johansen test co-integration is applied to examine long-term integration among variables, Granger causality test is used to examine the causality relationship between macroeconomic variables and stock returns. The monthly data are taken for the study which ranges from July 1997 to July 2017. Currency exchange rates, interest rates, money supply, and inflation are the macroeconomic variables for the current study. Results revealed that there is one co-integrating equation of long-run equilibrium between the variables for both countries. Granger causality test reveals that there exists unidirectional and bidirectional relationship between the variables.

Dynamic linkages among international crude oil, exchange rate and Norwegian stock market: evidence from ARDL bound testing approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shelly Singhal ◽  
Sangita Choudhary ◽  
Pratap Chandra Biswal
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Crude Oil ◽  
Granger Causality ◽  
Granger Causality Test ◽  
Oil Price ◽  
Causality Test ◽  
Content Type ◽  
Long Run ◽  
Integration Test

Purpose The purpose of this paper is to examine the long-run association and short-run causality among oil price, exchange rate and stock market in Norwegian context. Design/methodology/approach This work uses auto regressive distributed lag (ARDL) bound co-integration test to examine the long-run association among international crude oil, exchange rate and Norwegian stock market. Further to test the causality, Toda–Yamamoto Granger causality test is used. Daily data ranging from 1 January, 2011 to 31 December, 2018 is used in this study. Findings Findings of this study suggest the existence of long-run equilibrium relationship among oil price, exchange rate and Norwegian stock market when oil price is taken as dependent variable. Further, this study observes the bi-directional causality between Norwegian stock market and exchange rate and unidirectional causality between oil and Norwegian stock market (from oil to stock market). Originality/value To the best of the authors’ knowledge, this the first study in context of Norway to explore the long-run association and causal relationships among international crude oil price, exchange rate and stock market index. Particularly, association of exchange rate and stock market largely remains unexplored for Norwegian economy. Further, majority of studies conducted in Norwegian setup have considered the period up to year 2010 and association of these variables is found to be time varying. Finally, this study uses ARDL bound co-integration test and Toda–Yamamoto Granger causality test. These methodologies have been used in literature in context of other countries like India and Mexico but not yet applied to study the Norwegian case.

An empirical study on the dynamic relationship between oil prices and Indian stock market

2014 ◽  
Vol 40 (2) ◽  
pp. 200-215 ◽  
Author(s):  
Tarak Nath Sahu ◽  
Kalpataru Bandopadhyay ◽  
Debasish Mondal
Keyword(s):  
Stock Market ◽  
Error Correction ◽  
Oil Prices ◽  
Granger Causality Test ◽  
Oil Price ◽  
Causality Test ◽  
Content Type ◽  
Long Run ◽  
Short Run ◽  
Indian Stock Market

Purpose – This study aims to investigate the dynamic relationships between oil price shocks and Indian stock market. Design/methodology/approach – The study used daily data for the period starting from January 2001 to March 2013. In this study, Johansen's cointegration test, vector error correction model (VECM), Granger causality test, impulse response functions (IRFs) and variance decompositions (VDCs) test have been applied to exhibit the long-run and short-run relationship between them. Findings – The cointegration result indicates the existence of long-term relationship. Further, the error correction term of VECM shows a long-run causality moves from Indian stock market to oil price but not the vice versa. The results of the Granger causality test under the VECM framework confirm that no short-run causality between the variables exists. The VDCs analysis revealed that the Indian stock markets and crude oil prices are strongly exogenous. Finally, from the IRFs, analysis revealed that a positive shock in oil price has a small but persistence and growing positive impact on Indian stock markets in short run. Originality/value – The study would enhance the understandings of the interaction between oil price volatilities and emerging stock market performances. Further, the study would enable foreign investors who are interested in Indian stock market helps in understanding the conditional relationship between the variables.

scholarly journals Effect of Macroeconomic Determinants on Indian Stock Market

2019 ◽  
Vol 8 (2) ◽  
pp. 22-27
Author(s):  
Krishna Gadasandula
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Causality Analysis ◽  
Stock Market Index ◽  
Causality Test ◽  
Macroeconomic Variables ◽  
Bank Rate ◽  
Market Index ◽  
Long Run ◽  
Indian Stock Market

Stock market is one of the important forms of investment. The prices of stock markets are affected by much macro-economic factors. The study investigates the relationships between the Indian stock market index (NSE Nifty) and four macroeconomic variables, namely, GDP, Inflation, Exchange Rate and Bank Rate. The data is collected on a quarterly basis for the time period March 2000 to December 2017. The study employs the Johansen’s co-integration approach to the long-run equilibrium relationship between stock market index and macroeconomic variables. For causality analysis, the study carried out Granger and Geweke causality tests. From this paper it is observed that the Granger causality test results do not demonstrate the presence of any bidirectional causality. The results show the unidirectional causal associations running from GDP to Inflation, Bank Rate to GDP, Exchange Rate to GDP, NIFTY Index to GDP, Exchange Rate to Inflation, NIFTY Index to Inflation, and Bank Rate to NIFTY Index. Apart from that, the results also show no causal association between Inflation and Bank Rate, Bank Rate and Exchange Rate, and Exchange Rate and NIFTY Index. However, the bidirectional causal associations appear. When we look into the results of Geweke causality analysis shows that bidirectional causal associations exist between Inflation and Bank Rate, and Exchange Rate and Nifty Index.

scholarly journals To Assess the Association between Exchange Rate, Commodity Prices and Cryptocurrency in Indonesia

2020 ◽  
Vol 3 (1) ◽  
pp. 1-13
Author(s):  
Nur Hussain
Keyword(s):  
Exchange Rate ◽  
Granger Causality ◽  
Commodity Prices ◽  
Oil Prices ◽  
Granger Causality Test ◽  
Oil Price ◽  
The Other ◽  
Causality Test ◽  
Cotton Price ◽  
Crypto Currency

The paper aimed to assess the association among exchange rate, commodity prices and crypto currency in Indonesia. This study is quantitative in which the data has been gathered from the Investing.com from 2016 to 2020. The variables which were considered in the study include exchange rate, gold prices, cotton prices, oil prices, Bitcoin and Ethereum. In terms of the analysis, the vector autoregression and granger causality test has been adopted.The results of this study identified that there is no effect of exchange rate, oil price, cotton price and gold price on Bitcoin. On the other hand, there is only significant effect of gold prices on Ethereum. The results of this study are restricted to Indonesian context and the data has been considered from 2016 to 2019 due to the lack of data on crypto currency.

scholarly journals Volatility Nexus Between Stock Market and Macroeconomic Variables in Bangladesh: an Extended GARCH Approach

2017 ◽  
Vol 64 (2) ◽  
pp. 233-243 ◽  
Author(s):  
Md. Abu Hasan ◽  
Anita Zaman
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
Market Returns ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
General Index ◽  
Indian Stock Market ◽  
The Garch Model

Abstract This paper examines the volatility of the Bangladesh stock market returns in response to the volatility of the macroeconomic variables employing monthly data of general index of Dhaka Stock Exchange (DSE) and four macroeconomic variables (Call Money Rate, Crude Oil Price, Exchange Rate and SENSEX of Bombay Stock Exchange) from January 2001 to December 2015. The results of GARCHS models reveal that the volatility of DSE return is significantly guided by the volatility of macroeconomic variables, such as, exchange rate and SENSEX. Specifically, volatility of the DSE is expected to 19% increase by 1% increase of exchange rate. Moreover, the volatility of the Bangladesh stock market returns is expected to dampen down by 2% with an increase in the volatility of Indian stock market of 1%. Thus, we can comment that adding exchange rate or stock returns of India in the GARCH model provides significant knowledge about the behaviour of the DSE volatility.

scholarly journals STOCK MARKET REACTIONS ON EXCHANGE RATE VOLATILITY: AN INDIAN EXPERIENCE

2020 ◽  
Vol 8 (9) ◽  
Author(s):  
Lyn Rose ◽  
Nithin Jose
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Exchange Rates ◽  
Granger Causality ◽  
Negative Relationship ◽  
Impulse Response Function ◽  
Unit Root Test ◽  
Exchange Rate Volatility ◽  
Granger Causality Test ◽  
Causality Test

This paper looks at the relationship between Nifty returns and US Dollar - Indian Rupee Exchange Rates. The study looks into the causal relationship between Nifty returns and exchange rate using Granger Causality test. It took daily data covering the period from January, 2009 to June, 2019. In this study, it was found that both variables were non–normally distributed. With the help of Unit Root Test, it was also verified that Nifty returns as well as Exchange rate, were stationary at the first difference form. Using Granger Causality test it is proved there was a bidirectional relationship between Nifty returns and Exchange rates. From the further investigation it is evident there is a causality running from exchange rate return to stock market return. Finally, employing impulse response function it found that there is a negative relationship among the variables.

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