Laurens Swinkels

The Performance of European Index Funds and Exchange-Traded Funds: European Index Funds and Exchange-Traded Funds

European index funds and exchange-traded funds underperform their benchmarks by 50 to 150 basis points per annum. The explanatory power of dividend withholding taxes as a determinant of this underperformance is at least on par with fund expenses. Dividend taxes also explain performance differences between funds that track different benchmarks and time variation in fund performance. Our results imply that not only fund expenses, but also dividend taxes can result in a substantial drag on mutual fund performance.

Board diversity and self-regulation in Dutch pension funds

Purpose The purpose of this paper is to examine the change in pension fund board diversity after self-regulation was introduced, and investigate which pension fund characteristics influence compliance with self-regulation. In addition, the authors analyze whether compliance might be achieved by tokenism. Design/methodology/approach The authors hand-collect pension fund and pension fund board data of the largest (by assets) 200 pension funds in the Netherlands. The authors compare descriptive statistics on board diversity, perform statistical tests on these, and perform non-linear regression techniques to investigate which pension fund characteristics influence compliance. Findings The findings are fourfold. First, over the past three years, pension fund boards have only marginally improved on gender and age diversity. In April 2014, still more than 35 percent of the funds had no women on the board, and an overwhelming 60 percent had no members below 40 years of age. This indicates that self-regulation in the pension fund industry so far has not been effective for the industry as a whole. Second, the authors find that pension funds that have larger boards are more likely to have at least one woman on the board or at least one member below 40 years of age. Third, boards of pension funds with more assets are less likely to have young board members. Fourth, boards with at least one female have a higher probability of also having at least one member below 40 years, which is suggestive of tokenism. Research limitations/implications Based on Hirschman’s (1970) theory of voice and exit, the authors expect that pension fund boards would be more diverse than corporate boards. However, the authors find that this is not the case. Second, given the importance of generational value transfers in pension fund policy decisions, the authors expect that age is a more important diversity characteristic than gender for pension fund boards in the Netherlands. Again, the data does not support this prediction. Practical implications Consistent with the literature on diversity in corporate boards, the authors find that diverse boards are on average larger. This suggests that, all other things equal, small boards might want to reconsider whether increasing their size would lead to more diversity and hence to more voice for participants that cannot exit the pension scheme. If larger funds hesitate to include young members because of their lack of relevant skills, then the authors would recommend setting up a platform to educate young candidates and prepare them for board membership. Forced independent auditor verification, as in the UK, might be a fruitful action the regulator could enforce on pension funds going forward. However, if that also does not lead to a significant improvement, compulsory diversity quota might be the only option left for policy makers. Originality/value This paper contributes to the literature in at least three ways. First, the authors analyze whether self-regulation on diversity in pension fund boards has been effective. Second, the authors determine which pension fund characteristics are associated with more board diversity. Third, the authors shed light on tokenism in pension fund board composition: Diversity might be obtained through installing diversity tokens, which are individuals who have multiple diversity characteristics.

Historical Returns of the Market Portfolio

Using a newly constructed unique dataset, this study is the first to document returns of the market portfolio for a long period and with a high level of detail. Our market portfolio basically contains all assets in which financial investors have invested. We analyze nominal, real, and excess return and risk characteristics of this global multi-asset market portfolio and the asset categories over the period 1960 to 2015. The global market portfolio realizes a compounded real return of 4.38% with a standard deviation of 11.6% from 1960 until 2015. In the inflationary period from 1960 to 1979, the compounded real return of the GMP is 2.27%, while this is 5.57% in the disinflationary period from 1980 to 2015. The reward for the average investor is a compounded return of 3.24%-points above the saver’s. We also compare the performance of an investor who holds the market portfolio with an investor who uses simple heuristics for the portfolio allocation. Our results suggest that the market portfolio is close to the mean-variance frontier, but our heuristic allocations achieve a significantly higher reward for risk.

Simulating Historical Inflation-Linked Bond Returns

Empirical research on the benefits of investing in inflation-linked bonds usually relies on a limited number of observations due to the relatively recent introduction of these assets. We estimate models for the break-even inflation rate and use these to create hypothetical inflation-linked bond returns. We compare these with the return on actual inflation-linked bond returns on a recent sample and find that surveys of professional forecasters and moving average models perform best. We confirm these findings for a sample of 19 international inflation-linked bond markets. Using surveys of professional forecasters, we create hypothetical inflation-linked bond return series for 41 countries starting in 1987 or later depending on the availability of nominal bond markets. These simulated series can be used by asset allocation researchers, but an average correlation of 0.7 means that the simulated series are at best reasonable proxies for real data on inflation-linked bond returns. This cautionary note is also relevant to appreciate existing research using simulated inflation-linked bond returns.