OIL PRICE AND STOCK RETURNS IN EUROPE

. In this paper we examine the relationship between oil price changes and of European oil and gas companies. We use all the widely known equilibrium models and extend them with the oil price factor as well. We classify the companies according to their location into Western European (WE), Central and Eastern European (CEE) and South Eastern European region (SE). Our results show that oil is a significant factor for most of the Western European, but less than the half of the CEE and SE companies. These results suggest that Western European oil and gas companies have high exposure to oil price changes, while the returns of their CEE and SE counterparts are less influenced by the oil price. When we incorporate oil price changes the explaining power of the models increases substantially for Western European companies but we can detect only a slight change for CEE and South Eastern European oil and gas companies. We also detect regional differences in the sign of the HML factor, which is usually negative for Western European and positive for CEE and South Eastern European companies.


Introduction
The relationship between oil price changes and stock returns has been investigated thoroughly (e.g., Chen, Roll and Ross 1986, Basher and Sadorsky 2006, Nandha and Hammoudeh 2007, Fang and You 2014;Masood et al., 2019;Šubová et al., 2021).The results were highly dependent on countries, regions, industries and even periods examined.Aloui et al. (2013) show positive (however varying) dependence between oil price changes and returns of Central and Eastern European stock market indexes.Asteriou and Bashmakova (2013) find that the reaction of CEE stock returns to oil price changes is more significant when oil prices are low.Articles examining stock returns on sectoral level find that oil and gas industry of Australia (Faff and Brailsford, 1999), Canada (Boyer and Filion, 2007), Europe (Arouri and Nguyen, 2010;Mura et al., 2015) and the UK (El-Sharif et al., 2005) has all significant sensitivity to oil price changes.Nandha and Faff (2008) detect a negative impact of oil price increases on returns for all of the examined 35 global sectors except mining, and oil and gas industries.Ramos and Veiga (2011) show that oil price has a positive impact on global oil and gas industry returns, however oil price is a more important factor in developed countries than in emerging markets.Nandha and Brooks (2009) also document substantial differences in the role of oil price changes in determining transport sector returns between developed and emerging countries.Oberndorfer (2009) shows that oil price changes positively related to returns of oil and gas stock returns in the Eurozone.Mohanty et al. (2010) find no significant relation between oil prices and returns of CEE oil and gas companies.Narayan and Sharma (2011) report positive relation between oil price changes and returns of US energy and transportation companies.
We examine the effects of oil price changes on returns of shares of European oil and gas companies.We use the constituents of EUROPE-DS Integrated Oil & Gas and EMERGING EUROPE-DS Integrated Oil & Gas indexes, provided by Reuters.We use monthly total returns measured in US dollars for the period January 2002 and April 2022.For the oil price changes we use the total return of Crude Oil-WTI Spot Cushing measured in US dollars.

Methodology and Data
We apply different equilibrium models to capture the excess returns of the examined shares and to calculate the explanatory power of the different models.We run ordinary least squares regressions with different set of explanatory variables.
The first equilibrium model we use is the standard Capital Asset Pricing Model (CAPM) proposed by Sharpe (1964), Treynor (1961), Lintner (1965), andMossin (1966), and is in the following form, where ri represents the return of the index; α represents the constant term of the regression, i.e., the abnormal return; represents β a relevant risk parameter that is estimated as the independent variable of the regression; rM represents the market return; and ε represents the error term of the regression: (1) The second equilibrium model is the Fama and French (1992, 1993, 1996) three-factor model.The authors extend the explanatory variable using the SMB (small minus big) and HML (high minus low) factors respectively, to capture the size premium and the value over growth premium.The model is written as follows, where the β variables represent the regression coefficients and rM, SMB and HML are the market, size, and value premiums, respectively: (2) Carhart (1997) extends the three-factor model using a momentum (MOM) parameter that measures the tendency for the share price to continue increasing if it was previously increasing and its tendency to continue decreasing if it was previously decreasing.Therefore, the model can be written in the following form, where βMOM captures the excess return gained by the persistency of the previous month's return and MOM stands for the momentum factor: (3) Pastor and Stambaugh (2003) used liquidity measure as a new factor and extended the model used by Carhart (1997) using market, size, value and momentum factors: (4) We also use Fama and French (2015) five-factor model, they extend their three-factor model with profitability (robust minus weak) and investment style (conservative minus aggressive) factors.
We extend all aforementioned capital market equilibrium models by the oil price factor.
We use monthly total return data (in USD) of the examined shares for the period January 2002 and April 2022.The descriptive statistics of the monthly returns are summarized in Table 1.
The oil price is represented by the WTI USD per barrel price (from Reuters).The market, size, value, profitability, investment style and momentum factors are the European factors from Kenneth R. French's data library while as the liquidity factor we use traded liquidity from the website of Pastor Stambaugh.

Results
We run the equilibrium linear regression models for the monthly returns of the sample period of January 2002 and April 2022.We use different equilibrium models extended by the oil factor.We divide the examined companies into three different geographic regions: Western (or developed) Europe (Austria, Finland, France, Italy, Norway, Portugal, Spain, United Kingdom); South-East Europe (Cyprus, Greece and Turkey) and Central and Eastern Europe (Croatia, Hungary, Poland, Romania, Slovenia).
If we use CAPM the average determination coefficient (adjusted R 2 ) for Western European companies is 0.3876, for CEE companies 0.3425 and for South-East European companies 0.2919, while the market factor is significant for all the shares except one company from Turkey.If we extend the standard CAPM by the oil factor we receive average adjusted R 2 s of 0.4358, 0.3506 and 0.2940 respectively, while the oil factor is significant for 9 (out of 11) Western European, for 3 (out of 8) CEE and 2 (out of 5) SE companies.The average determination coefficients of the Fama-French 3 factor model are 0.4357, 0.3678 and 0.3076 for Western European, CEE and SE shares, when we involve the oil price change as well we receive 0.4751, 0.3703 and 0.3061 average adjusted R 2 s respectively.In the latter case oil factor is significant for 9 (out of 11) Western European, for 3 (out of 8) CEE and 0 SE shares (see Table 1, 2, 3, 4).So, the return of oil price is relevant for most of the Western European companies, while the return of shares of CEE and SE oil companies is not sensitive to oil price.
In FF3+oil model market is a significant factor for 11 Western, 8 CEE and 4 SE European companies.SMB factor is significant for 6 WE, 4 CEE and 2 SE companies, it is significantly positive for only 1 WE and 4 CEE and 2 SE companies.HML is a significant factor for 9 WE, 2 CEE and 3 SE companies, and it is positive in all the aforementioned cases.
The average determination coefficients of Fama-French 5 factor model are 0.4520, 0.3778 and 0.3075, when the oil factor is taken into consideration the average adjusted R 2 s are 0.4830, 0.3783 and 0.3063 for Western, CEE and SE companies.Oil is a significant factor for 9 Western European, 2 CEE and 0 SE oil companies.
In FF5+oil model SMB factor is significant for 6 WE (for 5 of them negatively), 4 CEE and 2 SE companies (all positively).HML factor is significant for 8 WE, 4 CEE and 1 SE, while RMW factor is significant for 6 WE, 4 CEE and 0 SE companies.Both HML and RMW factors are positively significant in all the previous cases.CMA factor is significant only for 3 Western European and 2 CEE companies, and it is not significant for any SE companies, but while in case of WE companies it is positively for CEE companies it is negatively significant.
The average adjusted R 2 s of the model that involves market, size, value, profitability, investment style, momentum and liquidity factors and the oil factor as well are 0.5123 for Western European, 0.3831 for CEE and 0.3144 for South Eastern European companies.In this setting oil factor is significant for 8 out of 11 Western European oil companies and none CEE and SE companies.
Market factor is significant and positive for all but one (SE, Turkey) companies.SMB factor is significant for 6 Western European, 3 CEE and 2 SE companies, but while for most of the cases (5 out of 6) it is significantly negative for Western European companies it is significantly positive for all 3 CEE and 2 SE companies.HML factor is significant for 8 Western European, 4 CEE and 1 SE companies and all in these cases it is significantly positive (see Table 5,6,7).RMW factor is significant (and positive) for 7 Western European, 4 CEE shares and it is not significant for any SE companies.CMA factor is significant for 4 Western and 3 Central Eastern European companies, but while it is significantly positive for all the former it is significantly negative for all the latter cases.
Momentum (WML) factor is significant only for 2 Western European and 1 SE companies, while traded liquidity is significant for 4 Western European, 2 CEE and 1 SE shares, and it is positive for all the 4 Western European and for the 1 SE companies it is negative for the 2 CEE companies.

Conclusions
The regression results for the standard CAPM-model and its extended version with the oil price factor show that for Western European oil and gas companies the explanatory power significantly increases when the oil price is taken into consideration, while for CEE and SE companies there is only a slight difference in the R 2 s.Oil is a significant factor for most of the Western European, but less than the half of the CEE and SE companies.These results suggest that Western European oil and gas companies have high exposure to oil price changes, while the returns of their CEE and SE counterparts are less influenced by the oil price.
Other model settings give the same result, when we extend the equilibrium model with the oil price factor the average adjusted R2 increases substantially for Western European companies but we can detect only a slight change for CEE and South East European oil and gas companies, Our results also show that HML factor influences differently the examined Western European oil and gas companies and their CEE and SE counterparts, for WE companies when it is significant it is usually negative, while for CEE and SE companies it is positive (in all the significant cases).We can not detect such differences for other factors.

Table 1 .
R 2 in Western Europe

Table 2 .
R 2 in Central and Eastern Europe

Table 4 .
Average R 2 in three Regions

Table 5 .
Parameter Estimation for Western European Oil Companies in Different Model Settings

Table 6 .
Parameter Estimation for Central and Eastern European Oil Companies in Different Model Settings

Table 7 .
Parameter Estimation for South-Eastern European Oil Companies in Different Model Settings