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Analysis of Stock Returns Volatility of Oil and Natural Gas Industry using GARCH

Vol 11 , Issue 1 , January - June 2024 | Pages: 1-19 | Research Paper  

 
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https://doi.org/10.17492/jpi.mudra.v11i1.1112401


Author Details ( * ) denotes Corresponding author

1. * Ritika Agarwal, Research Scholar, Centre for Management Studies, Dibrugarh University, Dibrugarh, Assam, India (ritikaagarwal@dibru.ac.in)
2. Pratim Barua, Professor, Centre for Management Studies, Dibrugarh University, Dibrugarh, Assam, India (pratim@dibru.ac.in)

The present study aims at analysing and comparing the volatility of stock returns of Oil and Natural Gas Corporation (ONGC) and Indian Oil Corporation Limited (IOCL) through the daily closing price of each stock for a period of 15 years. Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is adopted in the study. A few preliminary tests i.e., normality test, stationarity test and residual diagnostic test were carried out to confirm the suitability of the model used. The findings of the study revealed that volatility of stock returns is highly persistent for both the companies. Moreover, the study also reported that compared to IOCL, the volatility of stock returns of ONGC is more persistent. The study has implications for investors, policymakers and other stakeholders in the financial market. The findings of the study will help them to understand the pattern of volatility in the select stocks and to take investment decisions accordingly.

Keywords

Stock Market; Return; Volatility; GARCH; Oil and Natural Gas

  1. Agarwalla, M., Sahu, T.N. & Jana, S.S. (2021). Dynamics of oil price shocks and emerging stock market volatility: A generalized VAR approach. Vilakshan-XIMB Journal of Management, 18(2), 106-121.
  2. Anand, B. & Paul, S. (2021). Oil shocks and stock market: Revisiting the dynamics. Energy Economics, 96, 105-111.
  3. Bhowink, R. & Wang, S. (2020). Stock market volatility and return analysis: A systematic literature review. Entropy, 22(5), 1-18.
  4. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31, 307–327
  5. Cheung, Y. W. & Lai, K. S. (1995). Lag order and critical values of the augmented Dickey–Fuller Test. Journal of Business and Economic Statistics, 13(3), 277–280.
  6. Das, S. & Epi, A. (2022). Review on the Indian stock market. Recent Trends in Multi-Disciplinary Research, 1, 77-84.
  7. Dickey, D. A. & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of American Statistical Association, 74(366), 427–431.
  8. Dixit, J. K. & Agrawal, V. (2020). Foresight for stock market volatility – A study in the Indian perspective. Emerald Publishing Limited, 22(1), 1-13.
  9. Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimator of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1008.
  10. Goyal, N. & Kumar, R. (2019). Modeling volatility of Indian banking sector. European Journal of Business & Social Sciences, 7(2), 820-832.
  11. Kannan, K. (2023). A study on modelling and forecasting of stock price volatility of selected Nifty 50 companies in India. Ph.D. Thesis, Department of Management Studies, Periyar University, Tamil Nadu, India.
  12. Li, S., Wang, Y., Zhang, Z. & Zhu, Y. (2022). Research on the factors affecting stock price volatility. Advances in Economics, Business and Management Research, 648, 2884-2889.
  13. Mahajan, V., Thakan, S. & Malik, A. (2022). Modeling and forecasting the volatility of NIFTY 50 using GARCH and RNN models. Economies, 10(102), 1-20.
  14. Mamtha, D. & Srinivasan, K. S. (2016). Stock market volatility – conceptual perspective through literature survey. Mediterranean Journal of Social Sciences, 7(1), 208-212.
  15. Marobhe, M. & Pastory, D. (2020). Modeling stock market volatility using GARCH models case study of Dares Salaam stock exchange (DSE). Review of Integrative Business and Economics Research, 9(2), 138-150.
  16. Matei, M. (2009). Assessing volatility forecasting models: Why GARCH models take the lead. Romanian Journal of Economic Forecasting, 4, 42-65.
  17. Mishra, S. & Patjosji, P. K. (2021). Measurement of effect of volatility in crude oil prices on share prices of major petroleum companies in the Indian Stock Market. Natural  Volatiles & Essential Oils, 8(5), 11613-11622.
  18. Mittal, A. K. & Goyal, N. (2012). Modeling the volatility of Indian stock market. International Journal of Research in IT & Management, 2(1), 1-23.
  19. Nikhil M. N., Chakraborty, C., Lithin B. M., Ledwani, S. & Satyakam (2023). Modeling Indian bank nifty volatility using univariate GARCH models. Banks and Bank Systems, 18(1), 127-138.
  20. Phillips, P. C. B. & Perron P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346.
  21. Rajashekar, M., Murthy, S. & Reddy, T.N. (2018). Stock market volatility – A study of Indian stock exchange. Journal of Emerging Technologies and Innovative Research, 5(10), 711-718.
  22. Sahu, T.N., Bandopadhyay, K. & Mondal, D (2014). An empirical study on the dynamic relationship between oil prices and Indian stock market. Managerial Finance, 40(2), 200-215.
  23. Sahu, T. N., Bandopadhyay, K. & Mondal, D. (2015). Crude oil price, exchange rate and emerging stock market: Evidence from India. Jurnal Pengurusan, 42, 75-87.
  24. Shanavas, S. M. & Hemalatha, A. V. (2018). Comparative study on the volatility of share price of private and public sector banking companies. Journal of Emerging Technologies and Innovative Research, 5(10), 138-149.
  25. Sharma, R. P. & Sharma, A. (2019). Statistical analysis of stock prices of selected companies in construction industry. Advances in Management, 12(1), 39-47.
  26. Singhal, S. & Ghosh, S. (2016). Returns and volatility linkages between international crude oil price, metal and other stock indices in India: Evidence from VAR-DCC-GARCH Models. Resources Policy, 50, 276–288.
  27. Tejeesh, H. R. & Jeelan, V. B. (2023). Forecasting the Sensex and Nifty indices using ARIMA and GARCH Models. MUDRA: Journal of Finance and Accounting, 10(1),    57-75.
  28. Vasudevan, R.D. & Vetrivel, S.C. (2016). Forecasting stock market volatility using GARCH models: Evidence from the Indian stock market. Asian Journal of Research in Social Sciences and Humanities, 6(8), 1565-1574.
  29. Yadav, S. (2017). Stock market volatility – A study of Indian stock market. Global Journal for Research Analysis, 6(4), 629-663.
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