The hypothesis for the possible relationship between Morningstar Sustainability Rating and fund performance 𝐻3.9: If Morningstar Sustainability Rating is high then risk-adjusted returns are high was based on findings from previous literature. The results for the rules High_Sustainability ⇒ High_Sharpe and High_sustainability ⇒ High_Alpha are summarized in Table 12.
Table 12 Results of the evaluation of the validity of rules High_sustainability ⇒ High_Sharpe and High_sustainability ⇒ High_Alpha
A: High_sustainability; B: High_sharpe A: High_sustainability; B: High_Alpha
A ⇒ B A ⇒ not B A ⇒ B A ⇒ not B
F1 consistency = 0.473 F1 consistency = 0.587 F1 consistency = 0.357 F1 consistency = 0.698 F1 coverage = 0.718 F1 coverage = 0.510 F1 coverage = 0.690 F1 coverage = 0.541 F2 consistency = 0.378 F2 consistency = 0.493 F2 consistency = 0.263 F2 consistency = 0.604 F2 coverage = 0.498 F2 coverage = 0.265 F2 coverage = 0.464 F2 coverage = 0.304 F3 consistency = 0 F3 consistency = 0.114 F3 consistency = 0 F3 consistency = 0.341 F3 coverage = 0.344 F3 coverage = 0 F3 coverage = 0.272 F3 coverage = 0.038 F4 consistency = 0.443 F4 consistency = 0.557 F4 consistency = 0.329 F4 consistency = 0.671 F4 coverage = 0.672 F4 coverage = 0.484 F4 coverage = 0.636 F4 coverage = 0.519 SUP1(A⇒B) = 0.323 DISP1(A⇒B) = 0.441 SUP1(A⇒B) = 0.203 DISP1(A⇒B) = 0.483 SUP0.9(A⇒B) = 0.340 DISP0.9(A⇒B) = 0.460 SUP0.9(A⇒B) = 0.230 DISP0.9(A⇒B) = 0.530 SUP0.8(A⇒B) = 0.357 DISP0.8(A⇒B) = 0.481 SUP0.8(A⇒B) = 0.247 DISP0.8(A⇒B) = 0.589 SUP0.7(A⇒B) = 0.390 DISP0.7(A⇒B) = 0.502 SUP0.7(A⇒B) = 0.270 DISP0.7(A⇒B) = 0.633 SUP0.6(A⇒B) = 0.418 DISP0.6(A⇒B) = 0.523 SUP0.6(A⇒B) = 0.302 DISP0.6(A⇒B) = 0.669 SUP0.5(A⇒B) = 0.456 DISP0.5(A⇒B) = 0.553 SUP0.5(A⇒B) = 0.314 DISP0.5(A⇒B) = 0.686 SUP0.4(A⇒B) = 0.477 DISP0.4(A⇒B) = 0.582 SUP0.4(A⇒B) = 0.331 DISP0.4(A⇒B) = 0.698 SUP0.3(A⇒B) = 0.498 DISP0.3(A⇒B) = 0.610 SUP0.3(A⇒B) = 0.371 DISP0.3(A⇒B) = 0.730 SUP0.2(A⇒B) = 0.519 DISP0.2(A⇒B) = 0.643 SUP0.2(A⇒B) = 0.411 DISP0.2(A⇒B) = 0.753 SUP0.1(A⇒B) = 0.540 DISP0.1(A⇒B) = 0.660 SUP0.1(A⇒B) = 0.470 DISP0.1(A⇒B) = 0.774 SUP0.0(A⇒B) = 1 DISP0.0(A⇒B) = 1 SUP0.0(A⇒B) = 1 DISP0.0(A⇒B) = 1
α-SUP = 1 α-DISP = 1 α-SUP = 1 α-DISP = 1
For the relationship High_sustainability ⇒ High_sharpe, there does not seem to be strong support in the data, and there are no significant differences in consistencies in favor and against the rule. The consistencies for High_Sustainability ⇒ notHigh_Sharpe seem to be slightly higher, and F4 consistency is over 0.5, which could indicate high sustainability ratings creating not-high values for the Sharpe Ratio.
Likewise, when focusing on the rule High_sustainability ⇒ High_Alpha, the consistencies against the rule are a little higher with an F1 consistency of 0.698 and F4 consistency of 0.671. Additionally, F3 consistency is 0 for both High_Sustainability
⇒ High_Sharpe and High_sustainability ⇒ High_Alpha.
Observing the degrees of support and disproof, both α − SUP and α − DISP equal to one in both rules, which means there is both support and disproof for the rules.
Additionally, especially for the rule High_Sustainability ⇒ High_Sharpe, the degree of support (0.323) and degree of disproof (0.441) do not differ substantially. In conclusion, there does not seem to be a pattern pointing to funds with high Morningstar Sustainability Ratings having higher Sharpe Ratios or Alphas. The results do not show a strong relationship in favor or against high sustainability leading to high risk-adjusted returns.
To further investigate the relationship between high Morningstar Sustainability Rating and fund performance, we also tested the rules High_Sustainability ⇒ Low_Sharpe and High_sustainability ⇒ Low_Alpha. The results for these rules are summarized in Table 13. There is not much support in favor of either of these rules; overall consistencies seem low and F3 consistency is 0 for both High_Sustainability ⇒ Low_Sharpe and High_sustainability ⇒ Low_Alpha. However, when focusing on proof against the rule (𝐴 ⇒ 𝑛𝑜𝑡 𝐵), there are rather strong results. The consistencies are overall higher compared to consistencies in favor of these rules, and there is some coverage to support these consistencies as well. Consistencies for F1 (0.725 and 0.727) and F2 (0.634 and 0.616), are also moderately high. For F4, the consistencies are even considerably high (0.697 and 0.696), with coverages over 0.5. Again, it must be pointed that as α − SUP and α − DISP equal to one in both rules, the relationships might not be reliable. However, SUP1(A⇒B) is only 0.211 for High_Sustainability ⇒ Low_Sharpe and 0.173 for High_sustainability ⇒ Low_Alpha, while DISP1(A⇒B) is over 0.5 for both rules.
Table 13 Results of the evaluation of the validity of rules High_sustainability ⇒ Low_Sharpe and High_sustainability ⇒ Low_Alpha
In conclusion, the results for High_sustainability ⇒ High_Sharpe and High_sustainability ⇒ High_Alpha concluded in Table 12 did not show strong evidence in favor or against the rules. Examining the rules High_sustainability ⇒ Low_Sharpe and High_sustainability ⇒ Low_Alpha, considerably strong evidence was found against these rules indicating a relationship between high sustainability and not-low risk-adjusted returns. These results suggest that although funds with higher sustainability may not reach higher risk-adjusted returns, they might prevent the fund from having low ones.
A: High_sustainability; B: Low_sharpe A: High_sustainability; B: Low_Alpha
A ⇒ B A ⇒ not B A ⇒ B A ⇒ not B
F1 consistency = 0.331 F1 consistency = 0.725 F1 consistency = 0.335 F1 consistency = 0.727 F1 coverage = 0.507 F1 coverage = 0.627 F1 coverage = 0.543 F1 coverage = 0.609 F2 consistency = 0.240 F2 consistency = 0.634 F2 consistency = 0.225 F2 consistency = 0.616 F2 coverage = 0.283 F2 coverage = 0.387 F2 coverage = 0.289 F2 coverage = 0.381 F3 consistency = 0 F3 consistency = 0.394 F3 consistency = 0 F3 consistency = 0.392 F3 coverage = 0 F3 coverage = 0.205 F3 coverage = 0 F3 coverage = 0.166 F4 consistency = 0.303 F4 consistency = 0.697 F4 consistency = 0.304 F4 consistency = 0.696 F4 coverage = 0.464 F4 coverage = 0.603 F4 coverage = 0.493 F4 coverage = 0.583 SUP1(A⇒B) = 0.211 DISP1(A⇒B) = 0.586 SUP1(A⇒B) = 0.173 DISP1(A⇒B) = 0.521 SUP0.9(A⇒B) = 0.213 DISP0.9(A⇒B) = 0.599 SUP0.9(A⇒B) = 0.179 DISP0.9(A⇒B) = 0.559 SUP0.8(A⇒B) = 0.222 DISP0.8(A⇒B) = 0.614 SUP0.8(A⇒B) = 0.194 DISP0.8(A⇒B) = 0.589 SUP0.7(A⇒B) = 0.249 DISP0.7(A⇒B) = 0.639 SUP0.7(A⇒B) = 0.234 DISP0.7(A⇒B) = 0.639 SUP0.6(A⇒B) = 0.264 DISP0.6(A⇒B) = 0.677 SUP0.6(A⇒B) = 0.268 DISP0.6(A⇒B) = 0.688 SUP0.5(A⇒B) = 0.304 DISP0.5(A⇒B) = 0.711 SUP0.5(A⇒B) = 0.297 DISP0.5(A⇒B) = 0.703 SUP0.4(A⇒B) = 0.323 DISP0.4(A⇒B) = 0.736 SUP0.4(A⇒B) = 0.312 DISP0.4(A⇒B) = 0.732 SUP0.3(A⇒B) = 0.361 DISP0.3(A⇒B) = 0.751 SUP0.3(A⇒B) = 0.365 DISP0.3(A⇒B) = 0.766 SUP0.2(A⇒B) = 0.386 DISP0.2(A⇒B) = 0.778 SUP0.2(A⇒B) = 0.411 DISP0.2(A⇒B) = 0.806 SUP0.1(A⇒B) = 0.401 DISP0.1(A⇒B) = 0.787 SUP0.1(A⇒B) = 0.441 DISP0.1(A⇒B) = 0.821 SUP0.0(A⇒B) = 1 DISP0.0(A⇒B) = 1 SUP0.0(A⇒B) = 1 DISP0.0(A⇒B) = 1
α-SUP = 1 α-DISP = 1 α-SUP = 1 α-DISP = 1
6 CONCLUSIONS
This thesis investigated if there exists a relationship between mutual fund characteristics manager tenure, fund size and sustainability, and mutual fund performance measured with Jensen’s Alpha and Sharpe Ratio. Methodologically, a novel approach to mutual fund performance evaluation was made by using fuzzy set qualitative comparative analysis (fsQCA) by Ragin (2008), with its enhancements developed by Stoklasa et al. (2017, 2018). The objective of this thesis was to examine the possible relationships between the Morningstar Sustainability Rating, fund size, manager tenure, and mutual fund performance. While these relationships have been studied several times, the evidence in the area is inconclusive. A collective literature review presented a range of results and suggestions for the relationships mentioned above, and these specific characteristics were chosen for the evaluation. Mutual fund performance was measured with three-year average Sharpe Ratios and Jensen’s Alphas. The examined sample included 429 mutual growth funds registered in Europe and the studied period was from March 2018 to March 2021.
Findings in past research suggested a negative relationship between large fund size and fund performance. The results did not find a strong pattern of large fund sizes creating low risk-adjusted returns. On the contrary, there was no strong evidence of large fund size leading to high risk-adjusted returns either. Results did not support a positive relationship between long manager tenure and fund performance, but they could implicate that the long tenure of a manager could prevent the fund from having low risk-adjusted returns. On the other hand, results showed more evidence for a long tenure of a manager creating not-high performance. The results for either fund size or manager tenure did not show strong proof of relationships.
Results on the effect of high Morningstar Sustainability Ratings did produce interesting findings. There seems to be some support for high sustainability creating high risk-adjusted returns, but the support for high sustainability creating not-high risk-risk-adjusted returns is stronger. However, when examining a rule if sustainability is high then performance is low, the evidence against it is stronger. Based on the results, there seems to be a considerably strong relationship between high Morningstar Sustainability rating and not-low risk-adjusted returns implicating that the high
sustainability of a fund could avoid it from having low risk-adjusted returns. In other words, investing in funds with high Morningstar Sustainability ratings may not create abnormal financial performance, but it can help avoid poor financial performance.
The current COVID19 pandemic could partially emphasize these results as it has caused the studied period to be economically unstable. Early in the pandemic, sustainable market actors Bloomberg, Morningstar and MSCI reported ESG funds and indices outperforming conventional funds as they were losing less value than their conventional indices (Boffo and Patalano (2020). In support of this, Nofsinger and Varma (2014) found socially responsible funds outperforming during times of market crisis and underperforming during times of non-crisis. Our results outline these observations since high sustainability helped funds avoid low risk-adjusted returns during the studied period. However, as this study examined only three-year values of the whole period, and thus did not consider economically more stable periods, these results do not offer proof of the results being affected by recent market turmoil.
The limitations of this study occurred mostly from the survivorship bias in the data sample. As Morningstar Mutual Fund Screener does not hold data for dead funds, all funds that did not survive over the period (March 2018 – March 2021) were eliminated.
Furthermore, look-ahead bias may have occurred in the sample since values for fund size (net assets), manager tenure, and the Morningstar Sustainability Rating were current values, while risk-adjusted returns were three-year averages. Also, the computed fuzzy numbers were mostly created arbitrarily and not based on theoretical information, which can weaken the results. This thesis did not study other mutual fund types than equity funds due to the low amount of available data for funds from other categories, such as bond or income funds.
Future research could extend these findings by studying the role of sustainability during periods of market crisis and periods of non-crisis. By doing this, the overall impact of sustainable investing on financial performance could be observed. In addition, a bias-free data sample should be used to validate these findings. The lack of long-term data for the Morningstar Sustainability Ratings published in 2016 propose avenues for future research to explore the effects of the rating on long-term mutual fund performance. Methodologically, there is much room for applying fsQCA and its
enhancements developed by Stoklasa et al. (2017, 2018) in future mutual fund research and performance evaluation. Based on this study, the methodology works well for mutual fund performance research and succeeded in identifying patterns in the sample.
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