Using equity premium survey data to estimate future wealth

We present the first systematic methods for combining different experts' responses to equity premium surveys. These techniques are based on the observation that the survey data are approximately gamma distributed. This distribution has convenient analytical properties that enable us to address three important problems that investment managers must face. First, we construct probability density functions for the future values of equity index tracker funds. Second, we calculate unbiased and minimum least square error estimators of the future value of these funds. Third, we derive optimal asset allocation weights between equities and the risk-free asset for risk-averse investors. Our analysis allows for both herding and biasedness in expert responses. We show that, unless investors are highly uncertain about expert biases or forecasts are very highly correlated, many investment decisions can be based solely on the mean of the survey data minus any expected bias. We also make recommendations for the design of future equity premium surveys

Is Ethical Money Sensitive to Past Returns? The Case of Portfolio Constraints and Persistence in Islamic Funds

In this paper, we analyze the performance persistence and survivorship bias of Islamic funds. The remarkable growth of these types of ethical funds raises the question of how non-financial attributes, including beliefs and value systems, influence performance and its persistence. A procedure commonly used in prior literature to assess persistence is the measuring of the performance of investment strategies based on past performance. In this context, we propose a refined version of this methodology that controls the cross-sectional significance of the performance of these strategies. This procedure correctly identifies whether abnormal performance is due to a dynamic investment strategy based on past performance, or whether it is obtained by investing in a particular set of mutual funds. The significance of the persistence varies depending on the time horizon (yearly/half-yearly), survivorship, or the tail of the distribution. In particular, we find that persistence only exists for the best funds, whereas for the worst funds, the results are not significant