Development of Optimum Portfolio for Investment in Oil & Gas Sector (Investor’s View)
DOI:
https://doi.org/10.1956/jge.v15i2.586Keywords:
Portfolio, Returns, Risk, Investment, Oil and gas, Stock market, India, Energy, CorrelationAbstract
With establishment of International Solar Alliance in New Delhi and due to the push given to renewable energy by the current government India has opened new dimension for innovation, investment and industry. This government has made a significant effort to push India’s renewable energy ambition. Due to this push India is now the 4th largest wind power producer in the world only behind of China, USA & Germany. India has made record addition to the solar power capacity in last 5 years. Although the recently concluded Financial Year (FY19) has shown a dip in installation of solar power with only 6500MW installed in the year. With this trend in the country the researchers are focusing on the scenario of renewable energy in India. So, the papers which are recently made available in the public domain are concerned with the current scenario. The surge in renewable energy is a good sign for the nation as renewable is the future. Though the rising demand of the fastest growing economy of the world can’t be satisfied with this growth in renewable energy. In simply words, the growth of the renewable energy is not enough to sustain the growth of the Indian economy. This statement is supported by the growing dependence of India on imported crude oil. Dependence of imported crude oil has gone up to 83.7% in Financial Year 19 from 82% in FY18. Hence, it can be said that the oil and gas sector is not getting the required focus.
Development of an optimum portfolio to minimize risk and maximize return is required before taking any investment decision. Portfolio optimization is required when you think of investing in oil and gas sector as its one of the most volatile sectors. This study is focused on developing an optimum portfolio for investment in oil and gas sector in India. Hence, 11 companies listed on Bombay Stock Exchange is selected for the study. Risk and return of all the 11 companies are calculated. The companies are ranked according to their risk. Weightage of investment is assigned to the top 5 companies (with lowest risk).
The study has been conducted to construct an optimum portfolio of oil and gas companies using Markowitz Model. The study has been conducted on individual securities listed in Bombay Stock Exchange (BSE). The objectives of this study are:
- Risk and return analysis of individual securities of oil and gas companies in India listed with BSE.
- To identify the opportunities of investment in oil and gas companies and development of an optimum portfolio for investment in these companies.
- To construct optimal portfolio using Markowitz Model.
- To check whether Markowitz Model performs well in Oil and gas companies well in BSE or not.
References
Aloui, R. S. (2014.). Dependence and extreme dependence of crude oil and natural gas prices with applications to risk management. . Energy Econ. 42,, 332–342.
Arouri, M. N. (2010). Oil prices, stock markets and portfolio investment: evidence from sector analysis in Europe over the last decade. Energy Policy 38 (8),, 4528–4539.
Bodart, V. C. ( 2009.). Evidence of interdependence and contagion using a frequency domain framework. . Emerg. Mark. Rev. 10 (2), , 140–150.
Boldanov, R. D. ( 2016.). Time-varying correlation between oil and stock market volatilities: evidence from oil-importing and oil-exporting countries. . Int. Rev. Financ. Anal. 48, , 209–220.
Brigida, M. (2014). The switching relationship between natural gas and crude oil prices. Energy Econ. 43 (C), 48–55.
Brown, S. Y. (2008). What drives natural gas prices? . Energy J. 29 (2), 45–60.
Büyük?ahin, B. H. (2010). Commodities and equities: ever a “market of one”? J. Altern. Invest. 12 (3) , 76–95.
Chevallier, J. G. (2014). Commodity markets through the business cycle. Quant. Finan. 14 (9), 1597–1618.
Chevallier, J. I. (2013). Economic regimes and commodity markets as an asset class. The Economics of Commodity Markets. Wiley, U.K., pp. , 145–178 Chapter 4.
commodities., I. i. (2012). Index investment and financialization of commodities. . Financ. J. 68 (6), 54-74.
de Roon, F. N. (2000). Hedging pressures effects in futures markets. Variable metric method for minimization. .
Domanski, D. H. (2007). Financial investors and commodity markets. . Domanski, D., Heath, A, 53-67.
Eckaus, R. 2. (2008). The Oil Price Really is a Speculative Bubble, Working Paper 08-007WP. Massachusetts Institute of Technology, Center for Energy and Environmental Policy.
Ewing, B. M. (2016.). Volatility spillovers between oil prices and the stock market under structural breaks. . Glob. Financ. J. 29, 12–23.
Faff, R. B. (1999.). Oil price risk and the Australian stock market. J. EnergyFinanc. Dev. 4 (1), 69–87.
Falkowski, M. (2011.). Financialization of commodities. Contemp. . Econ. 5 (4), 4–17.
Filis, G. D. (2011.). Dynamic correlation between stock market and oil prices: the case of oil-importing and oil-exporting countries. Int. Rev. Financ.Anal. 20 (3), 152–164.
Financialization, c. a. (2013). Financialization, crisis and commodity correlation dynamics. J. Int. Financ. Mark. Inst. Money 24,, 42–65.
Gallegati, M. (2012.). A wavelet-based approach to test for financial market contagion. Comput. Stat. Data Anal. 56 (11), , 3491–3497.
Gatfaoui, H. (2016). Linking the gas and oil markets with the stock market: investigating the US relationship. Energy Economics, Paris, 5-16.
Gogineni, S. (2010). Oil and the stock market: an industry level analysis. . Financ. Rev. 45 (4), 995-1010.
Gorton, G. R. (2006). Facts and fantasies about commodity futures. Financ.Anal. J. 62 (2) , 47–68.
Greer, R. (2006 ). Commodity indexes for real return. In: Greer, R.J. (Ed.) . The Handbook of Inflation Hedging Investments. McGraw Hill, U.S.A., pp. , 105–126 Chapter 5.
Hamilton, J. ( 2009a). Causes and consequences of the oil shock of 2007–08. Brook. . Pap. Econ. Act. 40 (1), 215–283.
Hamilton, J. ( 2009b). Understanding crude oil prices. . Energy J. 30 (2), , 179–206.
Hartley, P. M. (2014). The relationship between crude oil and natural gas prices: the role of the exchange rate. Energy J. 35 (2),, 25–44.
Hensel, C. A. (1993). Commodities in asset allocation: a real-asset alternative to real estate? . Financ. Anal. J.49 (3),, 20–29.
Husain, A. A. (2015.). Global Implications of Lower Oil Prices. . International Monetary Fund.
(2015). IMF, 2015. Spillover Report. International Monetary Fund.
Jammazi, R. (2012b.). Cross dynamics of oil-stock interactions: a redundant wavelet analysis. Energy 44 (1), , 750–777.
Jammazi, R. A. (2010.). Wavelet decomposition and regime shifts: assessing the effects of crude oil shocks on stock market returns. Energy Policy 38 (3),, 1415–1435.
Jiménez-Rodríguez, R. S. (2005.). Oil price shocks and real GDP growth: empirical evidence for some OECD countries. . Appl. Econ. 37 (2),, 201–228.
Karolyi, G. L.-H. (2012). Understanding commonality in liquidity around the world. J. Financ. Econ. 105 (1), , 82–112.
Khalfaoui, R. B. ( 2015.). Analyzing volatility spillovers and hedging between oil and stock markets: evidence from wavelet analysis. Energy Econ. 49 (C), 540–549.
Kilian, L. (2009). Not all oil price shocks are alike: disentangling demand and supply shocks in the crude oil market. . Am. Econ. Rev. 99 (3), , 1053–1069.
Lippi, F. N. ( 2012). Oil and the macroeconomy: a quantitative structural analysis. J. Eur. Econ. Assoc. 10 (5), 1059–1083.
Maghyereh, A. A. (2016.). The directional volatility connectedness between crude oil and equity markets: new evidence from implied volatility indexes. Energy Econ. 57,, 78–93.
Maghyereh, A. A. (2017.). Volatility spillovers and cross-hedging between gold, oil and equities: evidence from the Gulf Cooperation Council countries. Energy Econ.
Malik, F. E. (2009.). Volatility transmission between oil prices and equity sector Gulf equity markets. Int. Rev. Econ. Financ. 16 (3), 357–368.
Martín-Barragán, B. R. (2015.). Correlations between oil and stock markets: a wavelet-based approach. . Econ. Model. 50, 212–227.
Mensi, W. H. ( 2017b). Modeling systemic risk and dependence structure between oil and stock markets using a variational mode decomposition-based copula method. J. Bank. Financ. 75,, 258–279.
Mensi, W. H.-J. ( 2017a). Dynamic risk spillovers between gold, oil prices and conventional, sustainability and Islamic equity aggregates and sectors with portfolio implications. . Energy Econ. 67,, 454–475.
Miller, J. R. (2009). Crude oil and stock markets: stability, instability, and bubbles. Energy Econ. 31 (4), 559–568.
Nikolaos Antonakakis a, b. J. (2018). Oil volatility, oil and gas firms and portfolio diversification. Energy Economics 70 (2018) , 499–515.
Park, J. R. (2008.). Oil price shocks and stock markets in the U.S. and 13 European countries. Energy Econ. 30 (5), 2587–2608.
Phan, D. S. (2016.). Intraday volatility interaction between the crude oil and equity markets. . J. Int. Financ. Mark. Inst. Money 40 (C),, 1–13.
Sadorsky, P. (1999.). Oil price shocks and stock market activity. Energy Econ. 21 (5),, 449-469.
Sadorsky, P. (2012). Correlations and volatility spillovers between oil prices and the stock prices of clean energy and technology companies. Energy Econ. 34 (1), 248-255,.
Singhal, S. G. (2016.). Returns and volatility linkages between international crude oil price, metal and other stock indices in India: evidence from VAR-DCC-GARCH models. . Resour. Policy 50, 276–288.
(February 6, 2016.). The Economist, 2016. Oil Companies: In the Dark Ages. The Economist.
Zvi, B. R. (1980). Risk and return in commodity futures. Financ. Anal. J. 36 (3), 27-39.
