Weitere Kapitel dieses Buchs durch Wischen aufrufen
Recently clean energy firms become more attractive for the investors, this leads to the more comprehensive studies in this field. Thus the aim of this study is investigating the impact of oil price volatility on the performance of S&P500 clean energy market by contributing oil price and technology market performance. To explore this relation the Zivot-Andrews test was conducted to check the stationarity of the time series, since a structural break is found during year 2007–2008, and then Bound test co-integration is applied, because of different levels of integration among time series in order to check the probable existence of the long-run relationship in the model. The results indicate that clean energy sector performance converges to its long-run level by 1.09% speed of weekly adjustment. The most magnitude finding of this paper is that, oil price volatility has significant long-run effect on the performance of clean energy sector. However, no significant short-run impact is observable.
Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten
Sie möchten Zugang zu diesem Inhalt erhalten? Dann informieren Sie sich jetzt über unsere Produkte:
Arouri, M. E. (2011). Does crude oil move stock markets in Europe? A sector investigation. Economic Modelling, 28, 1716–1725. CrossRef
Bohl, M. T., Kaufmann, P., & Siklos, P. L. (2015). What drove the mid-2000s explosiveness in alternative energy stock prices? Evidence from U.S., European and global indices. International Review of Financial Analysis, 40, 194–206. CrossRef
Broadstock, D. C., Cao , H., & Zhang , D. (2012). Oil shocks and their impact on energy related stocks in China. China Policy Institute.
Chen, S.-S., & Chen, H.-C. (2007). Oil prices and real exchange rates. Energy Economics, 29, 390–404. CrossRef
Cong, R.-G., Wei, Y.-M., Jiao, J.-L., & Fan, Y. (2008). Relationships between oil price shocks and stock market: An empirical analysis from China. Energy Policy, 36, 3544–3553. CrossRef
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74, 427–431.
Engle, R. F., & Granger, C. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55, 251–276. CrossRef
Fan, Y., & Xu, J.-H. (2011). What has driven oil prices since 2000? A structural change perspective. Energy Economics, 33, 1082–1094. CrossRef
Ferderer, P. J. (1996). Oil price volatility and the macroeconomy. Journal of Macroeconomics, 18, 1–26. CrossRef
Hamilton, J. D. (1983). Oil and the macroeconomy since World War II. Journal of Political Economy, 91, 228–248. CrossRef
Henriques, I., & Sadorsky, P. (2008). Oil prices and the stock prices of alternative energy companies. Energy Economics, 30, 998–1010. CrossRef
Huang, R. D., Masulis, R. W., & Stoll, H. R. (1996). Energy shocks and financial markets. Journal of Futures Markets, 16, 1–27. CrossRef
Kumar, S., Managi, S., & Matsuda, A. (2012). Stock prices of clean energy firms, oil and carbon markets: A vector autoregressive analysis. Energy Economics, 34, 215–226. CrossRef
Lee, K., Ni, S., & Ratti, R. A. (1995). Oil shocks and the macroeconomy: The role of price variability. The Energy Journal, 16, 39–56. CrossRef
Managi, S., & Okimoto, T. (2013). Does the price of oil interact with clean energy prices in the stock market? Japan and the World Economy, 27, 1–9. CrossRef
Milonas, N. T., & Henker, T. (2001). Price spread and convenience yield behaviour in the international oil market. Applied Financial Economics, 11, 23–36. CrossRef
Narayan, P. K. (2005). The saving and investment nexus for China: Evidence from cointegration tests from cointegration tests. Applied Economics, 37, 1979–1990. CrossRef
Nieh, C.-C., & Wang, Y.-S. (2005). ARDL approach to the exchange rate overshooting in Taiwan. Review of Quantitative Finance and Accounting, 25, 55–71. CrossRef
Park, J., & Ratti, R. A. (2008). Oil price shocks and stock markets in the U.S. and 13 European countries. Energy Economics, 30, 2587–2608. CrossRef
Pesaran, M., Shin, Y., & Smith, R. J. (2001). Bounds tesing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16, 289–326. CrossRef
Phillips, P. C., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75, 335–346. CrossRef
Radchenko, S. (2005). Oil price volatility and the asymmetric response of gasoline prices to oil price increases and decreases. Energy Economics, 27, 708–730. CrossRef
Sadorsky, P. (1999). Oil price shocks and stock market activity. Energy Economics, 21, 449–469. CrossRef
Sadorsky, P. (2006). Modeling and forecasting petroleum futures volatility. Energy Economics, 28, 467–488. CrossRef
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. CrossRef
Yang, C. W., Hwang, M. J., & Huang, B. N. (2002). An analysis of factors affecting price volatility of the US oil market. Energy Economics, 24, 107–119. CrossRef
Zivot, E., & Andrews, D. W. (1992). Further evidence on the great crash, the oil-price shock, and the unit-root hypothesisl. Journal of Business & Economic Statistics, 10, 251–270.
- Effect of Oil Price Volatility on Clean Energy Stock Market Performance
Neuer Inhalt/© Stellmach, Neuer Inhalt/© Maturus, Pluta Logo/© Pluta, Frankfurt School