Energy Market Investment Methodologies
Keywords:
Energy Market, Investment, ETF, Alternative/ Renewable
Abstract
As more and more renewable energy market investment opportunities come to the fore, investors intend to optimize their assets through risk-return diversification. In the light of Markowitz’s modern portfolio theory aimed at recognizing the potential for higher returns and lower risks, the identification of different energy market segments has become essential. In this regard, through the research of the conventional and alternative/ renewable energy market segments, as well as various international statistical models, the optimal methodology was identified. The optimal methodology allows the aggregation of different energy and alternative/ renewable energy ETFs into international investment portfolios using a variable weighing of assets and is expected to result in an adequate outcome.
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References
1. Badshah, I. U. (2018). Volatility spillover from the fear index to developed and emerging markets. Emerging Markets Finance and Trade 54 (1), 27–40.
2. Bartram, S. M., & Dufey, G. (2001). International Portfolio Investment: Theory, Evidence, and Institutional Framework’, Finance Markets Institutions and & Instruments.
3. Beber, A., & Pagano, M. (2013). Short-selling bans around the world: evidence fromthe 2007–09 crisis. Journal of Finance 68, 343–381.
4. Ben-David, I., Franzoni, F., & Moussawi, R. (2017). Exchange-Traded Funds. Annual Review of Financial Economics, 9, 169-189.
5. Bohl, M. T., Reher, G., & Wilfling, B. (2016). Short selling constraints and stock returns volatility: empirical evidence from the German stock market. Economic Modelling 58, 159–166.
6. Bollen, N. P. B., & Busse, J. A. (2001). On the timing ability of mutual fund managers. Journal of Finance 56 (3), 1075–1094 57–82
7. Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics 31 (3).
8. Brinson, G. P., Singer, B. D., & Beebower, G. L. (1991) Determinants of Portfolio Performance II: An Update. Financial Analysts Journal, 47, 40-48.
9. Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). The Econometrics of Financial Markets, Princeton University Press, Princeton, NJ, USA.
10. Cappiello, L., Engle, R. F., & Sheppard, K. (2006). Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics 4 (4), 537–572.
11. Carhart, M. M. (1996). On the persistence in mutual fund performance. Journal of Finance 52 (1)
12. Diether, K. B., Lee, J., & Werner, J. (2009). It's SHO time! Short-sale price tests and market quality. Journal of Finance 64, 37–73.
13. Efimova, O., & Serletis, A. (2014). Energy markets volatility modelling using GARCH, Energy Economics 43, 264–273.
14. Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica 50, (4).
15. Henriques, I., & Sadorsky, P. (2008). Oil prices and the stock prices of alternative energy companies, Energy Economics 30, 998–1010.
16. Ewing, B. T., & Malik, F. (2005). Re-examining the asymmetric predictability of conditional variances: the role of sudden changes in variance. Journal of Banking and Finance 29, 2655–2673.
17. Fama, E., & French, K. R. (1993). Common risk factors in the returns of stocks and bonds. Journal of Financial Economics 33 (1), 3–56.
18. Gupta, R., & Donleavy, G. D. (2009). Benefits of diversifying investments into emerging markets with time-varying correlations: an Australian perspective. Journal of Multinational Financial Management 19, 160–177.
19. Grullon, G., Michenaud, S., & Weston, J. P. (2015). The real effects of short-selling constraints. The Review of Financial Studies 28 (6), 1737–1767.
20. Huang, M. Y., & Lin, J. B. (2011). Do ETFs provide effective international diversification?. Research in International Business Finance, 25, 335–344;
21. Ibbotson, R. G., & Kaplan, P. (2000). Does Asset Allocation Policy Explain 40, 90, 100 Percent of Performance?. Financial Analysts Journal 56.
22. Inchauspe, J., Ripple, R. D., & Trück, S. (2015). The dynamics of returns on renewable energy companies: a state-space approach. Energy Economics 48, 325–335.
23. Kalotychou, E., Staikouras, S. K., & Zhao, G. (2014). The role of correlation dynamics in sector allocation Journal of Banking and Finance 48, 1–12.
24. Kyritsis, E., & Serletis, A. (2018). The zero lower bound and market spillovers: evidence from the G7 and Norway, Research in International Business Finance, 44, 100–123.
25. Lewellen, J. (2002). Momentum and autocorrelation in stock returns, Review of Financial Studies, vol. 15, no. 2, pp. 533–564, 2002.
26. Lo, A. W., & MacKinlay, A. C. (1990). An econometric analysis of nonsynchronous trading, Journal of Econometrics, vol. 45, no. 1-2, pp. 181–211, 1990.
27. Longin, F. M., & Solnik, B. (2001). Extreme Correlation of International Equity Markets. Journal of Finance LVI (2).
28. Louhelainen, M. (2005). Weekly Predictability of Daily Returns: A Periodic Autoregressive Model Approach, ISBN 952-458-666-5, ISSN 1458-686X, no. 23.
29. Maghyereh, A. I., Awartani, B., & Tziogkidis, P. (2017). Volatility spillovers and cross-hedging between gold, oil and equities: evidence from the Gulf Cooperation Council countries. Energy Economics 68, 440–453
30. Malinda, M., & Jo-Hui, C. (2016). The Study of the Long Memory in Volatility of Renewable Energy Exchange-Traded Funds (ETFs), Journal of Economics, Business and Management 4, (4).
31. Markowitz, H. M. (1952). Portfolio selection. The Journal of Finance, Vol. 7, No. 1. 77-91.
32. Miralles-Marcelo, J. L., Miralles-Quiros, M. M., & Miralles-Quiros, J. L. (2015). Improving international diversification benefits for US investors. The North-American Journal of Economics and Finance, 32, 64–76.
33. Miralles-Marcelo, J. L., & Miralles-Quiros, M. M. (2017). The role of time-varying return forecasts for improving international diversification benefits. International Journal of Finance & Economics, 22, 201–215.
34. Miralles-Marcelo, J. L., Miralles-Quiros, M. M., & Miralles-Quiros, J. L. (2018). Are alternative energies a real alternative for investors?. Energy Economics 78.
35. Mollick, A. V., & Assefa, T. A. (2013). U.S. stock returns and oil prices: the tale from daily data and the 2008–2009 financial crisis Energy Economics 36, 1–18.
36. Odier, P., & Solnik, B. (1993). Lessons for International Asset Allocation. Financial Analysts Journal 49.
37. Omar, A. M. A., Wisniewski, T. P., & Nolte, S. (2017). Diversifying away the risk of war and cross-border political crisis. Energy Economics 64, 494–510.
38. Reboredo, J. C., Quintela, M., & Otero, L. A. (2017). Do investors pay a premium for going green? Evidence from alternative energy mutual funds. Renewable and Sustainable Energy Reviews, Rev. 73, 512–520.
39. Reboredo, J., Rivera-Castro, M. A., & Ugolini, A. (2017). Wavelet-based test of co-movement and causality between oil and renewable energy stock prices, Energy Economics 61 (C), 241-252.
40. Rezec, M., & Scholtens, B. (2017). Financing energy transformation: the role of renewable energy equity indices. International Journal of Green Energy 14 (4), 368–378.
41. Sadorsky, P. (2012) Correlations and volatility spillovers between oil prices and the stock prices of clean energy and technology companies. Energy Economics 34, 248–255.
42. Silva, F., & Cortez, M. C. (2016). The performance of US and European green funds in different market conditions. Journal of Cleaner Production 135, 558–566.
43. Solnik, B., & Noetzlin, B. (1982). Optimal international asset allocation. The Journal of Portfolio Management Fall 9 (1), 11-21.
44. Tsai, P. J., & Swanson, P. E. (2009). The comparative role of iShares and country funds in internationally diversified portfolios. Journal of Economics and Business. 61(6), 472–494.
45. Thai-Ha, L., & Chang, Y. (2011). Oil and gold: correlation or causation?. Munich Personal RePEc Archive, https://mpra.ub.uni-muenchen.de/31795/
46. Xinodas, P., Hassapis, C., & Mavrotas, G. (2018). Multiobjective portfolio optimization: bridging mathematical theory with asset management practice. Annals of Operations Research 267(3).
47. Yuan, T., Gupta, R., & Roca, E. (2016). Why not diversify into emerging equity markets via ADRs?. The Journal of Investing 25 (2), 18–27.
48. Zhou, J., & Nicholson, J. R. (2015). Economic value of modeling covariance asymmetry for mixed-asset portfolio diversifications. Economic Modelling 45, 14–21.
2. Bartram, S. M., & Dufey, G. (2001). International Portfolio Investment: Theory, Evidence, and Institutional Framework’, Finance Markets Institutions and & Instruments.
3. Beber, A., & Pagano, M. (2013). Short-selling bans around the world: evidence fromthe 2007–09 crisis. Journal of Finance 68, 343–381.
4. Ben-David, I., Franzoni, F., & Moussawi, R. (2017). Exchange-Traded Funds. Annual Review of Financial Economics, 9, 169-189.
5. Bohl, M. T., Reher, G., & Wilfling, B. (2016). Short selling constraints and stock returns volatility: empirical evidence from the German stock market. Economic Modelling 58, 159–166.
6. Bollen, N. P. B., & Busse, J. A. (2001). On the timing ability of mutual fund managers. Journal of Finance 56 (3), 1075–1094 57–82
7. Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics 31 (3).
8. Brinson, G. P., Singer, B. D., & Beebower, G. L. (1991) Determinants of Portfolio Performance II: An Update. Financial Analysts Journal, 47, 40-48.
9. Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). The Econometrics of Financial Markets, Princeton University Press, Princeton, NJ, USA.
10. Cappiello, L., Engle, R. F., & Sheppard, K. (2006). Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics 4 (4), 537–572.
11. Carhart, M. M. (1996). On the persistence in mutual fund performance. Journal of Finance 52 (1)
12. Diether, K. B., Lee, J., & Werner, J. (2009). It's SHO time! Short-sale price tests and market quality. Journal of Finance 64, 37–73.
13. Efimova, O., & Serletis, A. (2014). Energy markets volatility modelling using GARCH, Energy Economics 43, 264–273.
14. Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica 50, (4).
15. Henriques, I., & Sadorsky, P. (2008). Oil prices and the stock prices of alternative energy companies, Energy Economics 30, 998–1010.
16. Ewing, B. T., & Malik, F. (2005). Re-examining the asymmetric predictability of conditional variances: the role of sudden changes in variance. Journal of Banking and Finance 29, 2655–2673.
17. Fama, E., & French, K. R. (1993). Common risk factors in the returns of stocks and bonds. Journal of Financial Economics 33 (1), 3–56.
18. Gupta, R., & Donleavy, G. D. (2009). Benefits of diversifying investments into emerging markets with time-varying correlations: an Australian perspective. Journal of Multinational Financial Management 19, 160–177.
19. Grullon, G., Michenaud, S., & Weston, J. P. (2015). The real effects of short-selling constraints. The Review of Financial Studies 28 (6), 1737–1767.
20. Huang, M. Y., & Lin, J. B. (2011). Do ETFs provide effective international diversification?. Research in International Business Finance, 25, 335–344;
21. Ibbotson, R. G., & Kaplan, P. (2000). Does Asset Allocation Policy Explain 40, 90, 100 Percent of Performance?. Financial Analysts Journal 56.
22. Inchauspe, J., Ripple, R. D., & Trück, S. (2015). The dynamics of returns on renewable energy companies: a state-space approach. Energy Economics 48, 325–335.
23. Kalotychou, E., Staikouras, S. K., & Zhao, G. (2014). The role of correlation dynamics in sector allocation Journal of Banking and Finance 48, 1–12.
24. Kyritsis, E., & Serletis, A. (2018). The zero lower bound and market spillovers: evidence from the G7 and Norway, Research in International Business Finance, 44, 100–123.
25. Lewellen, J. (2002). Momentum and autocorrelation in stock returns, Review of Financial Studies, vol. 15, no. 2, pp. 533–564, 2002.
26. Lo, A. W., & MacKinlay, A. C. (1990). An econometric analysis of nonsynchronous trading, Journal of Econometrics, vol. 45, no. 1-2, pp. 181–211, 1990.
27. Longin, F. M., & Solnik, B. (2001). Extreme Correlation of International Equity Markets. Journal of Finance LVI (2).
28. Louhelainen, M. (2005). Weekly Predictability of Daily Returns: A Periodic Autoregressive Model Approach, ISBN 952-458-666-5, ISSN 1458-686X, no. 23.
29. Maghyereh, A. I., Awartani, B., & Tziogkidis, P. (2017). Volatility spillovers and cross-hedging between gold, oil and equities: evidence from the Gulf Cooperation Council countries. Energy Economics 68, 440–453
30. Malinda, M., & Jo-Hui, C. (2016). The Study of the Long Memory in Volatility of Renewable Energy Exchange-Traded Funds (ETFs), Journal of Economics, Business and Management 4, (4).
31. Markowitz, H. M. (1952). Portfolio selection. The Journal of Finance, Vol. 7, No. 1. 77-91.
32. Miralles-Marcelo, J. L., Miralles-Quiros, M. M., & Miralles-Quiros, J. L. (2015). Improving international diversification benefits for US investors. The North-American Journal of Economics and Finance, 32, 64–76.
33. Miralles-Marcelo, J. L., & Miralles-Quiros, M. M. (2017). The role of time-varying return forecasts for improving international diversification benefits. International Journal of Finance & Economics, 22, 201–215.
34. Miralles-Marcelo, J. L., Miralles-Quiros, M. M., & Miralles-Quiros, J. L. (2018). Are alternative energies a real alternative for investors?. Energy Economics 78.
35. Mollick, A. V., & Assefa, T. A. (2013). U.S. stock returns and oil prices: the tale from daily data and the 2008–2009 financial crisis Energy Economics 36, 1–18.
36. Odier, P., & Solnik, B. (1993). Lessons for International Asset Allocation. Financial Analysts Journal 49.
37. Omar, A. M. A., Wisniewski, T. P., & Nolte, S. (2017). Diversifying away the risk of war and cross-border political crisis. Energy Economics 64, 494–510.
38. Reboredo, J. C., Quintela, M., & Otero, L. A. (2017). Do investors pay a premium for going green? Evidence from alternative energy mutual funds. Renewable and Sustainable Energy Reviews, Rev. 73, 512–520.
39. Reboredo, J., Rivera-Castro, M. A., & Ugolini, A. (2017). Wavelet-based test of co-movement and causality between oil and renewable energy stock prices, Energy Economics 61 (C), 241-252.
40. Rezec, M., & Scholtens, B. (2017). Financing energy transformation: the role of renewable energy equity indices. International Journal of Green Energy 14 (4), 368–378.
41. Sadorsky, P. (2012) Correlations and volatility spillovers between oil prices and the stock prices of clean energy and technology companies. Energy Economics 34, 248–255.
42. Silva, F., & Cortez, M. C. (2016). The performance of US and European green funds in different market conditions. Journal of Cleaner Production 135, 558–566.
43. Solnik, B., & Noetzlin, B. (1982). Optimal international asset allocation. The Journal of Portfolio Management Fall 9 (1), 11-21.
44. Tsai, P. J., & Swanson, P. E. (2009). The comparative role of iShares and country funds in internationally diversified portfolios. Journal of Economics and Business. 61(6), 472–494.
45. Thai-Ha, L., & Chang, Y. (2011). Oil and gold: correlation or causation?. Munich Personal RePEc Archive, https://mpra.ub.uni-muenchen.de/31795/
46. Xinodas, P., Hassapis, C., & Mavrotas, G. (2018). Multiobjective portfolio optimization: bridging mathematical theory with asset management practice. Annals of Operations Research 267(3).
47. Yuan, T., Gupta, R., & Roca, E. (2016). Why not diversify into emerging equity markets via ADRs?. The Journal of Investing 25 (2), 18–27.
48. Zhou, J., & Nicholson, J. R. (2015). Economic value of modeling covariance asymmetry for mixed-asset portfolio diversifications. Economic Modelling 45, 14–21.
Published
2022-05-31
How to Cite
Bernadett, M. T. (2022). Energy Market Investment Methodologies. European Scientific Journal, ESJ, 18(15), 22. https://doi.org/10.19044/esj.2022.v18n15p22
Section
ESJ Social Sciences
Copyright (c) 2022 Matyas Tímea Bernadett
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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