Auke Plantinga

Socially Responsible Investing and Management Style of Mutual Funds in the Euronext Stock Markets

This paper analyses fund management styles on the Euronext stock exchanges. Especially, we investigate how social responsibility is accounted for. We use style analysis to assess fund performance in Belgium, France, and the Netherlands for over 800 investment funds during the 1990s. We find remarkable and significant differences in performance characteristics among these markets. Furthermore, we find that funds that to some extent mirror well known social responsibility indices tend to perform better than funds that bear no relationship with social responsible investment strategies.

Fundamental Indexing: An Analysis of the Returns, Risks and Costs of Applying the Strategy

We study the risk-adjusted performance of strategies based on fundamental indexation in Europe. Fundamental indexes are formed on the basis of book value of the assets, gross dividends, revenue, operating income and a composite of these values. Previous research in the US has shown that fundamental indexation provides positive risk-adjusted returns. We analyze whether the fundamental indexing strategy generates a positive alpha after correcting for risk factors and costs of managing the index portfolios. We use the three factor model of Fama and French to correct for risk. We find that fundamental indexation has a higher factor loading on the risk factors based on book-to-market (HML) and size (SMB). We also find that the strategy generates significant alpha after correcting for the three risk factors.

Preference functions and risk-adjusted performance measures

Publisher Summary This chapter explores the relation between risk preference functions and risk-adjusted performance measures. Both private and institutional investors delegate a considerable part of the management of their asset portfolios to external fund managers. Investors face the problem of selecting the best from a large set of potential portfolio managers. This selection process involves the evaluation of the return distribution generated by the portfolio manager. An important aspect of this evaluation is the risk attitude of the investor. There are at least two general approaches for the evaluation of the attractiveness of return distribution. The first approach is to choose a preference model, such as a utility function, and use the expected value of this preference model as the decision criterion. This approach allows the user to model explicitly the risk preferences of the investor. The second approach is to use a risk-adjusted performance measure to select the portfolio manager with the highest score. Usually, with this approach it is not possible to explicitly model the risk preferences of the investor. The chapter also describes the preference functions that best correspond to the risk-adjusted performance measures.

Private Acquisition Gains: A Contingent Claims Explanation

This paper studies announcement returns of Western European acquisitions of private and public targets. It uses a contingent claims perspective to offer a new explanation for the difference in abnormal returns between acquirers of private and public targets. In this context, an acquisition is analogous to buying a call option and the value of the acquirer increases with uncertainty about its growth prospects (options). We test this idea by studying the relation between announcement returns and acquirers characteristics that proxy for the existence of growth options. Consistent with the contingent claims hypothesis, the private acquisition gains are associated with the combined effects of growth options (having higher runup before the acquisition announcement) with low level of leverage (near-all equity capital) and with uncertainty (measured by age and analyst coverage of acquirers).

Sharing downside risk in defined benefit pension funds

This chapter aims to develop a measurement model that provides information on how risks are allocated across pension fund participants. It calculates the total risk of the portfolio, and determines how risk can be attributed to the individual groups of participants. In order to do this, it uses a simulation model and a set of loss allocation rules. Based on the simulation results, it attributes the risk to individual groups of beneficiaries. Furthermore, it uses downside risk as a measure of risk, and uses the decomposition of downside risk. Thereafter, it decomposes downside risk along the risky assets to see where the risk originates and over the groups of participants in the pension fund. This information is important, as it provides the input for evaluating whether the risks are shared in a responsible way. This presentation format is based on decomposing downside risk over the participants involved in a pension fund. Next to the formal rules, there are informal rules that are dictated by negotiations and the willingness of participants to share losses. The decomposition of downside risk allows the group of participants to evaluate their relative share in the losses. This may facilitate the discussion between sponsor and beneficiaries on strategies in times of underfunding.

Beyond the Sortino Ratio

The investment objective requires the calculation of the return needed to achieve the goal, which is the Desired Target Return ™ (DTR). Thus, the upside potential ratio is a measure of the inherent risk the manager is taking of not achieving the investors DTR relative to the potential of exceeding that desired return. It is not measuring what the manager has done but is an estimate of what he is statistically capable of achieving. It is one thing to have a better concept of measuring performance. It is quite another to obtain reliable estimates of the risk and return measures. Many people are now measuring downside risk as deviations below some number other than the DTR. Also, almost all of them use the managers returns instead of using returns from the managers style blend. At least value at risk (VAR) assumes investors are risk neutral and their utility function is linear below the DTR. Risk-neutral investors believe losing all their money is only twice as painful as losing half of it. Most firms that use Monte Carlo simulation focus on the average return and standard deviation when evaluating managers or determining the asset allocation. Sortino Investment Advisors (SIA) focuses on upside potential and downside risk.

Performance Attribution and the Accuracy of Detecting Timing and Selection Skills

In this study we investigate the accuracy of the popular Brinson, Hood, and Beebower [1986] attribution model in identifying investors with forecasting abilities. The purpose of the Brinson, Hood, and Beebower model is to classify the forecasting abilities of a portfolio manager into timing and selection skills. In our study, we performed two simulation experiments, one with managers having only timing skills and one with managers having only selection skills. Furthermore, we model two different types of portfolio managers. The first manager is able to forecast the direction of the future stock returns relative to a benchmark, whereas the second manager is also able to predict a part of the magnitude of the future performance. Our results suggest that the measurements of timing ability are associated with a lot of uncertainty. This is rather surprising, since the model uses also direct observations of the portfolio composition in the estimation of the timing ability. On the other hand, selection ability can be detected with far better accuracy. Furthermore, we conclude that the nature of the forecasting ability has an impact on the reliability of the evaluations.