Transparent structured products for retail investors

• Prior critique of the complexity of structured investment products (SPs) is revisited. • Simple-to-understand, transparent SPs (TSPs) are introduced and conceptualized. • TSPs are studied with both theoretical & empirical approaches of operations research. • Results show that both rational and behavioral investor demand exists for TSPs. • Moderately priced TSPs are competitive even compared to index fund products. Structured investment products (SPs) are derivative securities whose return is contingent on the return of their underlying assets, such as a certain stock market index. SPs have been criticized for being complex and costly on the inside, while attracting retail investors with emotionally appealing promises, on the surface, to provide tempting yields and protection for the capital invested. To circumvent such criticism, we consider transparent SPs (TSPs), which simply offer a lower and upper limit on annual return (after costs and fees) as well a transparent rule defining the return based on the return of the underlying asset. We study TSPs using both empirical and theoretical approaches. An empirical survey of real investors with best-worst scaling as well as theoretical analyses based on utility theory and multi-stage stochastic programming (MSSP) show that moderately priced TSPs are competitive in comparison with other investment products, such as index funds. Furthermore, retail investors actually exhibit substantial preference for TSPs with partial capital guarantees, over and above SPs with the superficially tempting, full capital guarantees. A theoretical, MSSP-based analysis similarly confirms that including TSPs in an investment portfolio can yield substantial gains in certainty equivalent annual return. The results further indicate that perceived gains from TSPs are sensitive to costs, market imperfections, and interest rates, as well as private preferences and stock market expectations of retail investors. This demonstrates how MSSP can be applied to financial engineering for successful implementation of TSPs in future financial markets.