What are Investors Willing to Pay to Customize Their Investment Product?

Vrecko Dennis, Langer Thomas

Abstract
Even though buy-and-hold (B&H) investment strategies can take the risk tolerance of an investor into account by specifying a suitable stock proportion, the outcome profiles of B&H strategies are restricted to a specific class of return distributions. For investors with particular risk preferences, further customization should thus provide additional value. The objective of this paper is to investigate the strength of preference for such customized distributions and to draw conclusions about the demand for personalized investment products. In two experimental studies, 256 participants could adjust the return distribution of an initially chosen B&H investment by using an interactive software program. Our main finding is that most investors make extensive use of the customization option and many are willing to pay a substantial fee for this additional flexibility. We further find that the willingness to pay for customization is lower if the fee is integrated into the display of the return distribution, making its impact on final returns more obvious. We also observe that investors can be clustered into distinct subgroups via their adjustment patterns, but individually elicited prospect theory parameters are barely able to explain and predict these adjustments. As a robustness check, we also survey real investors at an investors fair to compare their preferences with those of our main pool of student subjects. We find that the willingness to pay for customization is slightly lower for these real investors and the main effect of fee integration is also less pronounced. In summary, we observe a strong willingness to pay for additional flexibility even though the actual benefits of customization vary markedly according to the individual. In many cases the accepted fees are so high that standard B&H strategies stochastically dominate the customized distributions after fee integration.

Keywords
behavioral economics; investment behavior; customization; distribution builder; decision support; experimental economics; prospect theory