The authors compare four methods of valuing structured products, which tend to be sold at a substantial premium, and evaluate the effectiveness and efficiency of each of those methods in valuing a range of structured products. Depending on the particular product and its characteristics, one approach may be more suitable than another. The authors focus on the implications of how each method incorporates credit risk.

Structured products constitute a significant market, making up nearly $500 billion in issuances globally between 2010 and 2013. They also played a critical role in the development of the 2008–09 financial crisis. Many of these products consist of complex combinations of features that can be challenging to value accurately. Previous researchers have demonstrated the existence of issue-date mispricing in the market for structured products. The ability to identify accurately the components of a particular structured product and to evaluate each component appropriately can help investors make more prudent decisions when purchasing these products.

The authors identify credit risk as a potentially underappreciated aspect of structured product valuation and specify the way each method of valuation incorporates default risk and the effect that risk has on pricing. Investors who fail to fully appreciate the magnitude of default risk may habitually misprice structured products.

The authors describe typical characteristics inherent in structured products—for example, the underlying assets, principal protection, call features, and use of leverage. They then discuss four approaches to structured product valuation: (1) the simulation approach, which relies on computing power to perform Monte Carlo simulations; (2) the numerical integration approach, which integrates the return distribution and the payoff rule; (3) the decomposition approach, which can be used on products for which the payoff can be expressed as a combination of conventional debt instruments and options; and (4) the partial differential equation (PDE) approach, which models the relationship between product values and the underlying asset prices.

The authors explain each approach step by step and assess its advantages and disadvantages, including simplicity, computational intensity, versatility, and flexibility. Not all of the methods can be used on the full range of structured products available in the market; the numerical integration and decomposition approaches can be used for only a subset of structured products, whereas the PDE and simulation approaches can be used for a wider variety of products. Each method has its benefits and limitations, as described by the authors, who have valued more than 20,000 US structured products in the course of their work.

After describing in detail each of the four methods, the authors demonstrate how each of the methods would be used to evaluate a sample product, a Buffered PLUS (Performance Leveraged Upside Security) issued by Morgan Stanley on 31 December 2008. The PLUS is a structured product that offers partial downside protection and upside benefit, based on the future value of the S&P 500 Index.

To highlight the importance of adequately acknowledging default risk, the authors also identify two products that were priced identically but whose value differed notably when calculated using their pricing algorithms.

Given the size and importance of the market for structured products and the depth of the authors’ experience in valuing these products, this research is useful in summarizing the advantages and disadvantages of the existing methods of structured product valuation. As the authors observe, these valuation methods will undoubtedly continue to evolve with further research and with such improvements as increased computational efficiency.