In this section, we discuss the obtained estimates and describe the main findings and results.
4.1. ESG Ratings and Implied Moments
Table 2 shows the number of months where the implied moments of companies in either the high or low ESG rating groups are lower. If this number exceeds half of the total number of months, the implied moments of this group are fewer than those of the comparable group. We also provide the results of the related
t-test. In the second, sixth, and tenth columns, the results for implied volatility (IV), implied skewness (IS), and implied kurtosis (IK) are shown, respectively. The total number of months is 118, as shown in the denominator of the provided ratios. The other columns show the mean value, statistics, and
p value of the related
t-test in the same order.
Columns 2, 6, and 10 in
Table 2 show the following.
There are 118 months in which the average value of implied volatility in the high ESG rating group is lower than that in the low ESG rating group, which means that the high ESG rating group has a lower average implied common risk than the low ESG rating group. A similar finding also holds for individual E, S, and G ratings.
There are only 12 months in which the average value of implied skewness in the high ESG rating group is less negative than that in the low ESG ratings. Since 12 months do not exceed half of the total number of months, this shows that the high ESG rating group has a higher implied tail risk than the low ESG rating group. A similar finding also holds for individual E and G ratings.
There are 0 months in which the average value of implied kurtosis in the high ESG rating group is lower than that in the low ESG rating group. Hence, we draw the similar results as above, namely, that the high ESG rating group has a higher implied tail risk than the low ESG rating group. A similar finding also holds for individual E, S, and G ratings.
Columns 3–5 show the results of the t-test, which is tested on equal means. The null hypothesis of equal means is typically rejected with a very small p value. Hence, these first statistics show that, in terms of implied moments of companies, there are statistically significant differences between the high and low ESG rating groups. Thus, companies with a high ESG, E, S, and G rating tend to have lower implied volatility.
Columns 7–9 and 11–13 provide similar statistics for implied skewness and implied kurtosis, respectively. The t-test results are not significant for implied skewness and implied kurtosis in the G category, and the t-test results are significant for implied skewness and implied kurtosis in the E, S, and ESG categories.
Figure 1 provides a time-varying view on these implied moments of companies in the high and low ESG rating groups. We use the exponential weighted moving average smoothing procedure for smoothing the time series. The first column shows that companies with a high ESG rating tend to always have low implied volatility during the whole period. However, the difference in implied volatility between the high and low G rated groups is much smaller than that in other cases. This could indicate that the influence of the G rating on implied volatility is rather weak. Differences in the G rating tend to be larger after 2016. The last two columns of
Figure 1 show that companies with a high E, S, and ESG composite rating always tend to have more negative implied skewness and higher implied kurtosis than those for companies with a low E, S, and ESG composite rating. Although the difference in implied skewness and implied kurtosis of companies between the high and low G rating groups is very small, companies in the high G rating group exhibit less negative average implied skewness after 2015 than companies in the low G rating group.
Company size is a proven risk factor, and most empirical research sets company size as a control variable when examining the relation between ESG investment and financial risk to exclude its endogenous effect [
17,
18]. We divide companies into large and small company groups according to quantile to examine whether company size influences the relation between ESG rating and implied moments in our data set.
Figure 2 shows the ESG composite rating and implied moments of large and small companies. We categorize a company as large if its market capitalization is larger than the third quantile of the corresponding data set, and categorize it as small if its market capitalization is smaller than the first quantile of the corresponding data set. The figure shows that large companies tend to have a higher ESG rating, but also more negative implied skewness. Hence, to decrease the potential influence of company size, we remove companies that have more market capitalization than the third quantile, or less than the first quantile of the whole data set.
Table 3 shows the comparison of implied moments of companies in the corresponding high ESG rating groups and companies in the low ESG rating groups. Columns 2–5 show that there are 114 months in which the high ESG rating group has lower average implied volatility than the low ESG rating group. This result also holds for E, S, and G pillar ratings. However, the corresponding
t-test results of the E rating groups are no longer significant, indicating that there is not really a statistical difference in terms of implied volatility between high and low E rated companies. A similar observation holds for the difference between high G and low G rated companies. Columns 6–9 show that, after excluding large and small companies, there are 89 months in which the high ESG rating group has less negative skewness than the low ESG rating group. This result is similar with those of E and G ratings. This is, however, not the case for the S rating; the
t-test result of the S rating category is no longer statistically significant. No conclusion can, therefore, be made on whether mid-sized companies in a low S rating have less negative skewness or not. The
t-test results of the E, G, and composite ESG rating, on the other hand, are significant, which means that there are statistical differences in the implied skewness of companies in the two groups. Column 10 shows that there are 56 months in which the high ESG rating group has lower average implied kurtosis than the low ESG rating group; however, the results of the corresponding
t-test is not significant, as is not the E rating. There are 89 months in which the high G rating group has lower average implied kurtosis than the low G rating group. Moreover, the
t-test result of the G rating category is statistically significant, which shows that the high G rating group tends to have a lower implied tail risk than the low G rating group.
Figure 3 shows the implied moments of mid-sized companies in the high and low ESG rating groups. Although the difference in the implied volatility of mid-sized companies in the high and low ESG rating groups in
Figure 3 is not obvious from the first column, companies in the high ESG rating group always appear to have low implied volatility. Moreover,
Figure 3 shows that mid-sized companies in the high ESG rating groups tend to have less negative skewness, and this trend is more pronounced after 2016. After 2016, companies with a high E, G, and ESG composite rating tend to have less negative implied skewness and lower implied kurtosis. Moreover, companies with a high G rating always have less implied skewness and lower implied kurtosis after 2010. For the mid-sized company sample, the difference in implied skewness and implied kurtosis is more pronounced than that for the full sample.
Figure 4 shows the monthly difference in implied moments between mid-sized companies in the high and low ESG rating groups from August 2009 to May 2019. For implied volatility and implied kurtosis, a negative value means that companies in the high ESG rating group have lower implied volatility or lower implied kurtosis than companies in the low ESG rating group. For implied skewness, a positive value means companies in the high ESG rating group have less negative implied skewness than companies in the low ESG rating group. For the ESG composite rating, in most months, the difference in implied volatility is negative, and the difference in implied skewness is positive. This trend is also present for the E and G pillar ratings. However, for the influence of the S rating on implied skewness, in most months, the difference in implied skewness is negative. Moreover, for the E pillar rating, the difference in implied skewness increases, and the difference in implied kurtosis decreases as time goes by. This could indicate that the E rating has played an increasingly important role in decreasing the tail risk in recent years.
4.2. ESG Ratings and Implied Moments Divided by Sector
To further explore the relationship between ESG ratings and implied moments, we divide the data set by sector according to the GICS categorization. To exclude the influence of company size, we only use the mid-sized company data set in the following study.
Table 4 shows the number of months during which companies in the high ESG rating group have fewer implied moments than companies in the low ESG rating group. Column 4 in
Table 4 of the ESG composite rating indicates that, in all sectors, the number of months during which companies in the high ESG rating group have lower implied volatility is larger than the number of months during which companies in the low ESG group have lower implied volatility, except for the industrial, information technology, and real estate sectors. A similar trend also holds for the E and S pillar ratings; however, for high G rating, companies in the materials and utilities sectors tend to have fewer months with lower implied volatility.
Compared with implied volatility, the ESG composite rating has a much more pronounced influence on implied skewness in the industrial, information technology, and real estate sectors. Companies with a negative relation between ESG rating and implied skewness are mainly in the materials, healthcare, and communication sectors. The influence of ESG ratings on implied kurtosis is not as obvious as that on implied volatility and implied skewness. However, in the consumer staples, communication services, and real estate sectors, they still play an important role. In addition, for companies in the consumer discretionary sector, E, S, and G pillar ratings are all important for decreasing common risk and tail risk, while for companies in the energy and financial sectors, E and G ratings are both important for decreasing common risk and tail risk.
Table 5 shows the number of months during which companies in the high ESG rating group have fewer moments than companies in the low ESG rating group. The thresholds to divide the high and low ESG rating groups are the 0.4 and 0.6 percentiles of ESG ratings, respectively.
Table 5 shows that the trend in
Table 4 is still present, and that the number of months during which companies in the high ESG rating group have fewer implied moments than companies in the low ESG rating group increases. Moreover, this phenomenon indicates that the relation between ESG ratings and implied moments is most likely nonlinear.
4.3. Discussion
In this subsection, we further discuss the results of this study. Companies with a higher ESG rating would typically have a lower implied volatility, as shown in
Table 2 and
Table 3. This holds not only for mid-sized companies, but for the full sample; such effects become weaker for mid-sized companies. Several studies already examined the relationships between ESG rating and company volatility, and found that better ESG rated companies tend to yield a lower volatility [
4]. However, the effect that high E and G ratings lead to lower implied common risk becomes statistically insignificant after excluding the effect of company size, which indicates that company size plays an important role in the relation between implied common risk and E and G behaviors.
Companies with a higher ESG rating typically have lower tail risk for mid-sized companies. Since company size is an important risk factor, using the data set that only includes mid-sized companies, companies with a higher ESG rating tend to have lower tail risk, which is measured by implied skewness and implied kurtosis. It is in line with findings that a better ESG rating leads to lower expected tail risk [
4,
17]. The reason for this empirical result is that ESG behavior would burden small companies, and would not become a decision factor to large companies when decreasing their tail risk. Hence, ESG behaviors play a role in decreasing the volatility and implied tail risk of mid-sized companies. This result also provides some insight to explain the ambiguous and contradictory influence of ESG behavior on companies’ performance and risk. In addition, a higher S rating leads to higher tail risk, which is cohesive with the findings of Diemont et al. [
19]; nevertheless, they used historical methods, while we use a forward-looking method to measure tail risk. However,
Figure 3 and
Figure 4 show that the difference in implied tail risk between the two groups became smaller after 2015, and a higher S rating gradually led to a lower tail risk after 2017.
Furthermore, the proposition that a positive ESG standing decreases tail risk appears especially obvious before 2012 and after 2016. Before 2012, the economy was recovering from the 2008 financial crisis; thus, positive ESG behavior was able to decrease the tail risk of companies. In 2016, the Paris Agreement was legally signed, and more companies began to pay attention to their corporate ESG behaviors. Since then, there has been a large difference in tail risk between the high and low ESG rating groups. G rating apparently always plays a significant role in determining the volatility and tail risk of a company. For tail risk, this is even more pronounced for mid-sized companies.
Lastly, we did not find a strong correlation between ESG ratings and implied moments for all sectors. ESG composite rating is, to some extent, correlated to lower implied volatility or lower implied tail risk over all sectors. In other words, if companies with a higher ESG composite rating have, on average, higher implied volatility, they have lower tail risk, and vice versa. Moreover, companies with a higher ESG composite rating in the consumer discretionary and financial sectors (companies with a higher E and G rating in the energy, consumer discretionary, and financial sectors; companies with a higher G rating in the consumer discretionary sector) have on average both lower implied volatility and implied tail risk.