Impact of Macroeconomic Factors on Indian Stock Market

Garg, Keshav; Kalra, Rosy

doi:10.23862/kiit-parikalpana/2018/v14/i1/173248

Cited by 9 publications

(10 citation statements)

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“…To proxy the Indian stock market, the closing prices of the leading Indian stock index, i.e., the Sensex, have been used. With reference to macro-economic variables, based on the data availability and previous studies (Ahmad, Abdullah, Sulong, & Abdullahi, 2015;Demir, 2019;Garg & Kalra, 2018;Kotha & Bhawna, 2016;Lee & Brahmasrene, 2018;Megaravalli & Sampagnaro, 2018), five macro-economic variables have been selected.…”

Section: Methodsmentioning

confidence: 99%

“…This is why there is still a surmise about this relationship and no unanimous conclusion with reference to the impact (positive or negative) of selected variables on the stock market and also vice versa. Some researchers pronounce a positive relationship between inflation and the stock market (Kibria et al, 2014), while others discern a negative relationship (Ahuja, Makan, & Chauhan, 2012;Garg & Kalra, 2018;Ho, 2017;Romer, 2012;Venkatraja, 2014). Similarly, with reference to industrial production, one school of thought asserts that the rise in the index of industrial production leads to a bullish market because industrial growth results in increased profitability, better dividends, an increment in the demand for financial instruments, and consequently a rise in stock prices (Bekhet & Matar, 2013;Nwaolisa & Chijindu, 2016;Patel, 2012;Sahu & Bandopadhyay, 2020).…”

Section: Asian Journal Of Economic Modellingmentioning

confidence: 99%

“…The study analyzed the monthly data through Granger causality. Garg and Kalra (2018) examined the relationship of the Indian stock market with five variables: inflation, unemployment, gross domestic product (GDP), gold price, and Forex reserves. Inflation and unemployment were perceived to have a negative relationship with the Indian stock market, but other variables registered positive affluence.…”

Section: Asian Journal Of Economic Modellingmentioning

confidence: 99%

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Dynamics between macro-economic variables and the stock market: Evidence from India

Bhardwaj

Sharma

Mavi

2023

5009

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The present paper examines the dynamics between macroeconomic variables and the stock market. The index of industrial production, inflation, gold price, oil price, and return from treasury bills have been used as proxy macroeconomic variables. The Indian stock market has been typified by the Sensex. Monthly observations have been analyzed from April 1993 to October 2022 through cointegration and the Granger causality test to examine possible long-run and short-run relationships, respectively. The results proclaim the presence of cointegration among variables. Further, the analysis of normalized cointegrating coefficients reveals that in the long run, changes in inflation and the rate of return from T-bills positively affect the stock market. While changes in gold and oil prices have a negative impact on the stock market. The Granger causality test implies that in the short run, the stock market is sensitive to changes in the index of industrial production, inflation, and oil prices. The results are expected to be fruitful for investors as well as traders when designing their investment and trading strategies. Since the results indicate that volatility in the stock market can significantly affect industrial production, inflation, and gold prices, regulators should be vigilant about perturbations in the stock market to mitigate adverse effects.

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Section: Methodsmentioning

confidence: 99%

Section: Asian Journal Of Economic Modellingmentioning

confidence: 99%

Section: Asian Journal Of Economic Modellingmentioning

confidence: 99%

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Dynamics between macro-economic variables and the stock market: Evidence from India

Bhardwaj

Sharma

Mavi

2023

5009

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“…A negative relationship may threaten the stock market predictions. Garg and Kalra (2018) examined the relationship between Sensex, average inflation rate and gold price in India during 1991-2017 and found that the correlation between Sensex and gold price is 0.918, and the relation between Sensex and average inflation rate is negative. Sreenu (2018) discussed the use of the co-integration ARDL approach to determine the relationship between the Yuan rate and the Chinese stock market returns.…”

Section: Some Relevant Researchmentioning

confidence: 99%

Relation Between Inflation and Capital Market in India

Bhowmik

2023

FMIR

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Capital market has significant influence on the inflationary situation in an economy both in the short run and in the long run. The general determinants which affect capital market are share indices, stock prices, prices of gold and silver, interest rate, exchange rate and even money supply can be treated as influencing variable when money is treated as capital. In this paper the author examined the impact of capital market on inflation in India during 1980-2022 taking CPI and WPI as the indicators of inflation and gold price, silver price, BSE index, BSE market capitalization, money supply and rupee dollar nominal exchange rate are considered as the indicators of capital market. Augmented Dickey-Fuller test was applied to verify unit root for all variables including break unit roots and the author calculated growth rates during 1980 – 2022 using the simple semi-log linear trend model. Author applied Johansen cointegration test and vector error correction models among the variables in both the cases of CPI and WPI and calculated short run causality through Wald test and long run causality through cointegrating equation. In VECM, the paper found one significant cointegrating equation in case of CPI and found three significant cointegrating equations in WPI. The paper found that CPI has long run causal relationships with BSE index, BSE market capitalisation, money supply and rupee dollar exchange rate and WPI has long run cointegrating relationships with BSE market capitalisation, money supply and rupee dollar exchange rate respectively. Rupee dollar exchange rate has short run causal relationships with CPI and again CPI and BSE index has bidirectional short run causality. According to impulse response functions, the responses of CPI to gold price, BSE market capitalization and money supply have been approaching towards equilibrium but finally diverged away from equilibrium. There are significant short run causalities from BSE index and money supply to WPI. The impulse response of WPI to gold price, silver price, BSE index, BSE market capitalisation and exchange rate of rupee have been converging towards equilibrium many times although diverged finally. The model can be modified by including interest rate, share prices, bond prices under monthly data analysis.

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“…Garg and Kalra [24] studied the effect of six macroeconomic indicators, namely, GDP, gold prices, exchange rate, foreign exchange rate, average inflation, and unemployment rate on the Indian stock market. They found that GDP, gold prices, exchange rate, and foreign exchange rate have a positive impact, and average inflation and unemployment rate have a negative influence on the Indian stock market.…”

Section: Literature Reviewmentioning

confidence: 99%

Identifying Significant Macroeconomic Indicators for Indian Stock Markets

2019

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The macroeconomic indicators play a major role in all the stock markets, and they vary from nation to nation. This paper identifies the influence of macroeconomic indicators on the National Stock Exchange (NSE) and the Bombay Stock Exchange (BSE) of India. Total of forty-four macroeconomic indicators for eight years from the year 2011 to 2018 are considered in this study. The macroeconomic factors are aggregated and considered in average monthly form. The proposed method finds the correlation matrix of all considered macroeconomic indicators. The need for dimensionality reduction and the existence of multicollinearity are proven using validation techniques such as the Kaiser-Meyer-Olkin and Bartlett tests. The Principal Component Analysis (PCA) method is used to reduce the dimensionality to seven factors and then PCA with the varimax rotation method is applied to find factors with maximum variation. In addition, the influence of these seven factors on the NSE Nifty and BSE SENSEX indices are analyzed using regression. Finally, an Artificial Neural Network is used to predict stock market movement with the help of macroeconomic indicators. Accuracy of 92% and 87% are obtained on NSE NIFTY and BSE SENSEX respectively.INDEX TERMS Decision support systems, knowledge discovery, macroeconomic indicators, principal component analysis, artificial neural network, data mining.

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Impact of Macroeconomic Factors on Indian Stock Market

Cited by 9 publications

References 0 publications

Dynamics between macro-economic variables and the stock market: Evidence from India

Dynamics between macro-economic variables and the stock market: Evidence from India

Relation Between Inflation and Capital Market in India

Identifying Significant Macroeconomic Indicators for Indian Stock Markets

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