7.2 Robustness tests
7.2.5 Ethical rating
The Morningstar sustainability rating ranks funds by their historical sustainability score.
The funds are ranked and then assigned a group based on a normal distribution. There are 36 funds in the ethical portfolio that have a Morningstar sustainability rating of below average or low. Having a low sustainability score may suggest that these funds do not take ethical issues seriously and may be a sign of greenwashing. One issue is that 54 of the funds do not have a sustainability rating. I will only look at funds that have a sustainability score of average or above. In this sample, the average score for socially responsible funds is ”above average”, and for the conventional funds it is ”average”. The score for the conventional funds is the same as in the initial sample.
Table 22 presents the results of the pooled SRI portfolio. The results do not differ signifi-cantly and the conclusion remains the same. The results for the ESG and environmental portfolios are shown in table 23. The conclusion about performance remains the same for both the ESG and environmental portfolios. The most important difference is that the SMB factor coefficient is significant for the environmental difference portfolio. The environmental portfolio is more exposed to small stocks than the conventional portfolio.
8 Discussion
Generally, my results show that there is not a statistically significant difference in risk-adjusted performance between the socially responsible and conventional portfolios. This is in line with previous research, most of which has concluded that there is no difference in performance. In theory, one would expect socially responsible funds to have lower returns since their investment universe is narrower. In Europe, the most common strategy to incorporate ethical factors is to exclude companies or entire sectors, which should significantly limit diversification (Statista, 2018). It seems like the socially responsible funds manage to diversify, which may indicate that they still have a large enough investment universe after screening. On the other hand, socially responsible companies can be less exposed to litigation and reputational risk than other companies, which should have a positive effect on SRI fund performance.
I find that the SRI portfolio is more volatile than the market, and that there are growth and size effects when comparing the socially responsible portfolio to the benchmark. This is in line with Lean et al. (2015) who find similar results for the European market. However, they also find that the European SRI funds outperform the market, I find that there is not a statistically significant difference in performance between the SRI portfolio and the market. Further, they find that SRI funds are more exposed to contrarian stocks than the market while the momentum factor is not significant in my findings.
All robustness tests except for one confirmed my conclusion about insignificant difference in performance. The results from the Fama French three and five factor models show that the conventional portfolio outperforms the SRI and ESG portfolios. The magnitude of the coefficients is small, which means that there is not a big difference in performance.
These models do not include the widely accepted momentum factor, which means that they may be missing a risk factor. The results from the environmental portfolio shows no statistically significant difference in performance for both models.
The results on investment strategy all had the same conclusion; the socially responsible portfolio is more growth-oriented and more exposed to large stocks than their conventional counterpart. This is in line with previous research, Bauer et al. (2005) finds that ethical
are less exposed to typical value sectors such as chemicals and energy. The difference in exposure to small cap stocks may be due to how fund managers approach ESG. The best-in-class approach may affect the small cap exposure. Drempetic et al. (2019) raise concerns about the relationship between firm size and ESG scores. Sustainability measures may give an advantage to larger firms with better resources for providing ESG data. This may explain why the socially responsible portfolio is more exposed to large stocks than the conventional portfolio. Furthermore fund managers may be vary of excluding large companies as they constitute a large part of the market, and could thus affect returns greatly. The best-in-class approach does not exclude entire sectors, which means that fund managers using this approach will still be able to diversify. The other factor coefficients are not statistically significant, which indicates that there is not a difference in momentum strategy or volatility to the market.
I have applied a unconditional model, which assumes that the alpha and factor coefficients are constant over time. An alternative to this is using a conditional model, such as the method of Ferson and Schadt (1996). To be able to evaluate performance over time, I look at three sub-periods. The results from the environmental portfolio presents some interesting findings. The environmental portfolio began by underperforming their conventional counterpart between 2011 and 2014. One potential explanation for this, is that during this time period the oil sector was doing quite well and the oil price was high.
Between 2014 and 2017 there was not a statistically significant difference in performance.
The oil price crash between 2014 and 2016 could have negatively affected the conventional portfolio returns (Stocker et al., 2018). During the last period, the environmental portfolio outperformed the conventional portfolio. Coal fired power plants are a large contributor to global warming and they are a focal point for governments to reach their environmental goals. Recently, it was announced that EU member states were going to phase out coal by 2030. Coal has been declining for decades, but it accelerated in 2019. Between 2010 and 2020, coal generation in Europe has fallen by over 40 percent. There are three main reasons for the decline of coal; stagnant electricity demand, aggressive capacity build of solar and wind in the EU, and EU policies (The Economist Intelligence Unit, 2020). Environmental funds are not likely to be invested in coal companies, and would thus not be affected by the decline of coal. The move to more renewable energy may also affect the performance of environmental funds positively. Stagnant electricity demand also affects other parts
of the energy sector, which may affect conventional fund returns negatively as they have more investments in the energy sector. The phasing out of coal and the changing energy market in the EU should also affect the ESG funds to an extent. One reason why it has not lead to a higher performance may be that ESG funds are less invested in renewable energy. Another possible explanation is that ESG funds can be even less diversified than environmental funds since they also consider social and governance issues, which may counterbalance the positive effect from stagnating energy demand and phasing out of coal. Climent and Soriano (2011) also found that the performance of environmental funds compared to conventional funds changed over time in the United States. As fund managers and investors gain experience with green investments and green investment opportunities increased, the performance gap between green and conventional funds shrank.
The ESG indice seems to explain both SRI and conventional performance well. This is in contrast to Cort´ez et al. (2009) and Bauer et al. (2005), who found that ethical indices did a worse job in explaining ethical returns. I did test the results with different SRI benchmarks and some of them did in fact perform worse. The results are not shown in this thesis.
9 Conclusion
By applying the Carhart four factor model, I investigate whether there is a difference in performance between socially responsible and conventional funds. The main results show no statistically significant difference in risk-adjusted returns between the socially responsible and conventional portfolio. This result implies that fund managers do not have to give up on financial performance to incorporate ethical considerations into their investment decisions. The same conclusion can be drawn from all except for one robustness check.
The robustness check using the Fama French three and five factor models show that the conventional portfolio outperforms the socially responsible and the ESG portfolios. I do not find a statistically significant difference in performance between environmental and conventional funds between 2010 and 2020. However, when looking at sub-periods, I find that environmental funds went through a catching-up phase. At the beginning of the period, the environmental portfolio underperformed their conventional counterpart.
Between 2014 and 2017, there was no statistically significant difference in performance.
During the last period, between 2017 and 2020, I found that the environmental portfolio outperformed the conventional portfolio.
Furthermore, my results show that the SRI and conventional portfolios differ in exposure to size and value factors. The SRI and ESG portfolios are more tilted toward growth and large stocks than their matched conventional portfolios. The environmental portfolio is more growth-oriented than their conventional counterpart. The robustness tests confirm my results regarding differences in investment strategies.
The results are limited to my sample, time period and the European market. As we have seen, performance can change over time and past returns do not necessarily predict future returns. Furthermore, it is possible to apply a conditional model to test the robustness of the results.
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10 Appendix
10.1 Diagnostics tests
From the correlation matrix in table 4, we see that we do not have perfect collinearity since none of the correlations are equal to -1 or 1. There is moderate correlation between some of the factor portfolios, but this should not be an issue. These results do not indicate multicollinearity, which I will also test using VIF.
Table 4: Cross-correlation table
I use the Variance Inflation Factor test, VIF, to test for multicollinearity. A rule of thumb is that if VIF is higher than 10 or 1/VIF is smaller than 0.10, there may be a multicollinearity problem. As we can see from table 5, the VIF’s are under 10 and 1/VIF is smaller than 0.10. There may still be a problem if the average VIF is much larger than 1.00 as well (Acock, 2014). The mean VIF is 1.29, which means that this is not an issue.
Next, I test for heteroskedasticity using the White test and the Breusch-Pagan test. From table 6, we see that we can reject the null-hypothesis of homoskedasticity for a significance of 10 percent for all portfolios. However, we can only reject it for a significance level of 5 percent for the conventional and difference portfolios.
Table 6: White test for heteroskedasticity SRI Conventional Difference
chi2(14) 23.03 39.47 30.77
Prob > chi2 0.060 0.000 0.006
Table 7 shows the results of the Breusch-Pagan test for heteroskedasticity. The null hypothesis of constant variance, i.e. homoskedasticity, is rejected for the conventional portfolio. We cannot reject the null hypothesis that the SRI or difference portfolio as the p-values are high (Cameron and Trivedi, 2009).
Table 7: Breusch-Pagan / Cook-Weisberg test for heteroskedasticity SRI Conventional Difference
chi2(1) 1.25 7.32 1.84
Prob > chi2 0.264 0.007 0.175
I test for serial correlation using Durbin Watson and Breusch-Godfrey, and find that I have issues for some of the portfolios. I can not reject the null-hypothesis of no serial correlation for the pooled portfolios. I use Newey West standard-errors with four lags in all my regressions to correct for heteroskedasticity and serial correlation. There are different rule of thumbs for choosing the lag, one of them is T1/4. Generally the rule of thumbs say that for a sample of 121, I should use 4 lags.
Table 8: Breusch-Godfrey LM test for autocorrelation Ethical Conventional Difference
chi2 1.010 1.878 1.600
df 1 1 1
Prob >chi2 0.315 0.171 0.206
To test normality, I use the Jarque-Bera and the Shapiro Wilk tests. We cannot reject the null-hypothesis of normality for the SRI and conventional portfolios. We can however reject the null hypothesis of normality of the difference portfolio. The results indicate that
Table 9: Jarque-Bera
SRI Conventional Difference Test statistic 0.672 0.9072 13.33
Chi(2) 0.7146 0.6354 0.0013
The results from the Shapiro Wilk test confirms the results from the Jarque-Bera test. We cannot reject the null hypothesis of normality for the SRI and conventional portfolios, but we can reject it for the difference portfolio.
Table 10: Shapiro Wilk W test for normal data SRI Conventional Difference
W 0.993 0.990 0.977
V 0.687 0.931 2.198
z -0.843 -0.161 1.766
Prob >z 0.880 0.564 0.039