Impact of Oil Price Changes on Stock Returns of UK Oil and Gas Companies: A Wavelet-Based Analysis

Author(s):  
Jingzhen Liu
2018 ◽  
Vol 5 (1) ◽  
pp. 1-12
Author(s):  
Elias Randjbaran ◽  
Reza Tahmoorespour ◽  
Marjan Rezvani ◽  
Meysam Safari

This study investigates the impact of oil price variation on 14 industries in six markets, including Canada, China, France, India, the United Kingdom, and the United States. Panel weekly data were collected from June 1998 to December 2011. The results indicate that price fluctuations primarily affect the Oil and Gas as well as the Mining industries and have the least influence on the Food and Beverage industry. Furthermore, in three out of six of these countries (Canada, France, and the U.K.), oil price changes negatively affect the Pharmaceutical and Biotechnology industry. One possible reason for the negative relationship between oil price changes and the Pharmaceutical and Biotechnology industries in the above-mentioned countries is that the governments of these countries fund their healthcare systems. Portfolio managers and investors will find the results of this study useful because it enables adjusting portfolios based on knowledge of the industries that are impacted the most or the least by oil price fluctuations.


2015 ◽  
Vol 41 (9) ◽  
pp. 974-994 ◽  
Author(s):  
Andre Mollick ◽  
Khoa H Nguyen

Purpose – The purpose of this is paper is to pay a closer look at the 2008-2009 financial crisis (and its aftermath) and analyzes stock returns of nine major US oil companies as well as the oil and gas sector under daily data from January 1992 to April 2012. Design/methodology/approach – The authors adopt the arbitrage pricing theory model to examine the relationship between stock returns and their influences including oil price return, yield spreads, and US dollar index return. The authors also provide a test for structural changes in each regression model of return series to capture for multiple breaks. To examine the asymmetric effect of oil price returns on stock returns, the authors separate oil price returns series into two series: positive changes in oil price and negative changes in oil price. Findings – The authors find stock returns of oil companies as well as the oil and gas sector are positively affected by oil prices and have stronger effects in the downward direction. Interestingly, The authors find the effects of oil price movements on stock returns increase over time. The authors examine the possibility that investors wishing to hedge against a weakening USD invest in US oil companies and find that more than half of these companies benefit from a weaker USD against the JPY, while all strongly benefit from a weaker USD against major currencies. Originality/value – The authors employ daily data for two-decade period including the last global financial crisis. Due to the long-term period covered in this study, sequential Bai-Perron tests are used to detect structural breaks of stock return series. In addition, the data-dependent procedures result in good specifications throughout with white-noise processes in almost all cases.


2020 ◽  
Author(s):  
Thu Thuy Nguyen ◽  
T.N. Tran ◽  
V.C. Nguyen

This research examines the influence of world crude oil price shocks on the financial performance of Vietnamese oil- and gas-related firms. Based on copula approach and the sample data of domestic giant oil- and gas firms from 2009 to 2019, in particular in the situation of oil price steadily going up and economic depression of 2011–2012; approximately nine copulas including Gauss, Clayton, Rotated-Clayton, Plackett, Frank, Gumbel, Rotated-Gumbel, Student, Symmetrized-Joe-Clayton have been focused. A new evidence could be found that the oil price shocks have not impacted on the stock return of oil- and gas-related firms in the wave of increasing oil price, but a lagged period of time oil- and gas-related firms could receive more stock returns. The results further demonstrate that world oil price fluctuations have significantly impacted on the financial performance of some firms as PVS, PVG, and PET in the pre-depression period. In respect to the economic depression of 2011–2012, the study reveals no evidence in the relationship between world oil price fluctuations and stock returns of oil- and gas-related firms. In other words, results in the post-depression period suggest that world oil price shocks can affect stock returns of selected giant oil- and gas-related firms.


2017 ◽  
Vol 15 (3) ◽  
pp. 108-118 ◽  
Author(s):  
Olfa Belhassine ◽  
Amira Ben Bouzid

This study investigates how oil price movements impact the main Eurozone industry supersectors returns. We use a multifactor market model in which we incorporate oil price changes as an additional risk factor. In order to account for possible breaks in the relationship, we use the Bai and Perron (1998, 2003) breakpoints identification methodology. We find evidence of the presence of structural instabilities on the relationship between sector stock returns and oil price changes. Different breakpoints are identified, particularly the 2003 Iraq invasion year, the 2008 subprime crisis and the 2012 Euro debt crisis. Moreover, our results prove that stock return sensitivities to oil prices are time varying and sector dependent. Besides, the subprime financial crisis appears to induce a significantly positive effect on the oil-stock market nexus. However, the Euro debt crisis has a mostly negative effect. The other identified breakpoints do not seem to have any significant effect on the oil stock market nexus.


2016 ◽  
Vol 13 (2) ◽  
pp. 351-370 ◽  
Author(s):  
Geeta Duppati ◽  
Mengying Zhu

The paper examines the exposure of sectoral stock returns to oil price changes in Australia, China, Germany, New Zealand and Norway over the period 2000-2015 using weekly data drawn from DataStream. The issue of volatility has important implications for the theory of finance and as is well-known accurate volatility forecasts are important in a variety of settings including option and other derivatives pricing, portfolio and risk management (e.g. in the calculation of hedge ratios and Value-at-Risk measures), and trading strategies (David and Ruiz, 2009). This study adopts GARCH and EGARCH to understand the relationship between the returns and volatility. The findings using GARCH (EGARCH) models suggests that in the case of Germany eight (nine) out of ten sectors returns can be explained by the volatility of past oil price in Germany, while in the case of Australia, six (seven) out of ten sector returns are sensitive to the oil price changes with the exception of Industrials, Consumer Goods, Health care and Utilities. While in China and New Zealand five sectors are found sensitive to oil price changes and three sectors in Norway, namely Oil & Gas, Consumer Services and Financials. Secondly, this paper also investigated the exposure of the stock returns to oil price changes using market index data as a proxy using GARCH or EGARCH model. The results indicated that the stock returns are sensitive to the oil price changes and have leverage effects for all the five countries. Further, the findings also suggests that sector with more constituents is likely to have leverage effects and vice versa. The results have implications to market participants to make informed decisions about a better portfolio diversification for minimizing risk and adding value to the stocks.


2012 ◽  
Vol 11 (2) ◽  
pp. 205
Author(s):  
Michael Soucek

This study shows that the relationship between oil price changes and European stock market is significant and vary in relation to individual industry sectors. The oil price changes exhibit significant Granger causality for majority of European industry sector stock returns, but no cointegration could be determined for the price series. The results are proved to be economically exploitable for trading strategies. The trading rule based on the bivariate VAR( ) model for forecasting future stock returns significantly outperforms the buy-and-hold strategy in term of expected return and risk. It yields large Sharpe ratios and significant positive Jensen's alpha for both weekly and monthly data.


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