1. I have a question about the decrement indices. These indices are decremented by a certain amount per year, i.e. 4%. How do we model the volatility for these structured products?
When modelling any equity structured product, the first tool that many traders and quantitative strategists reach for is a Monte Carlo implementation of a local volatility model. This type of model is covered in some depth in the LFS course Volatility: Trading and Managing Risk. It is this Monte Carlo type approach that I usually recommend for these types of products. For both decrement indices and for volatility controlled indices, my preferred approach is to model the underlying index with its full volatility surface and then simulate the performance of the more exotic index and the complex payoff based on that exotic index. For some of the simpler indices and simpler payoffs, there are approximations that can be made to gain a faster calculation of the price, but in general, these have to be used with great caution.
It is interesting to note that decrement indices are often introduced to give an underlying with a lower forward. Similarly, volatility controlled indices are often introduced to give an underlying with lower volatility. Both a lower forward and a lower volatility will allow higher participation in capital protected products. In the era of higher interest rates, such added complexities may not be required. The higher interest rates mean that zero coupon bonds are cheaper, leaving a greater amount available to spend on optionality. Full 100% participation may be achievable in many products using regular indices without having to resort to a decrement index.
Structured products have a great deal of relevance in many emerging markets. Investors recognise the great opportunities in these markets but are frequently put off by what they perceive as large downside risks. Capital protected products are one way in which investors can gain from the upside from emerging markets while still having capital protection. For capital protected products in a domestic market, high interest rates can be an advantage allowing greater participation in the products. However, it should be noted that many overseas investors will look for equity participation in an emerging market but without taking FX risk. They want the structure to be in USD, or EUR with the underlying equity participation “quantoed” into the currency of the structured product. The high interest rates in both USD and EUR give plenty of opportunities here for interesting structures.
One of the key problems of structuring products in emerging markets is the lack of a developed options market for the issuer to hedge out the volatility exposure within the product. One way people solve this problem is to use a volatility controlled index. This subject is explored in some depth in the LFS course Equity Derivatives 2: Exotics and Structures.
The problem with correlation exposure is that in many situations it is an exposure that can only be warehoused. By that, I mean that it is very difficult to hedge and is priced with almost an actuarial approach. Correlations are marked above historic levels to give the issuers of structured products a P&L margin to withstand changing levels of correlation and the associated changes in mark to market. The problem is that during periods of stress, correlations can move widely. For this reason, the mark to market P&L on correlation products can be volatile, and concentration risk can lead to large losses in times of extreme stress (such as pandemics, or the Lehman’s crisis). Hedging correlation may have a cost, but it will remove the concentration risk and reduce P&L volatility. In this way, hedging correlation can potentially increase risk-adjusted returns for an issuer, as well as protect the business during extreme events.
4. Do you see any major changes in the way structured products will be priced and risk-managed?
To be honest, I don’t really see many changes in the models used to price and risk manage structured products. Rising interest rates mean that products are likely to get simpler, rather than more complex. For the majority of products, a well-implemented local volatility model will suffice. Some people may prefer a Heston type approach, but within equity markets, these tend to be in the minority. The local volatility model has many flaws which are explored in the LFS course Volatility: Trading and Risk Management but it has the great advantage of being relatively simple to implement for multiple underlyings.
Trying to guess the future is always difficult, but I think one thing that has perhaps been underestimated is the potential of the return of cliquet style products. Although I would still only give the return of cliquets a small probability, it is by no means zero. A structured cliquet product can be a good way of generating a product with capital protection and a “coupon at risk”, which may become more attractive to investors in a higher rate environment. These products are notorious for having a very large amount of model risk. If cliquet products do return, then this will re-invigorate the exploration of more complex pricing models such as Bergomi-style models and stochastic local volatility models.
One thing I do anticipate for sure, regardless of the product mix we see in the future, is a continued focus on reducing operational costs. I expect to see issuers focusing on automating the process of issuing a new structured product, as well as automating much of the hedge. Firm-wide risk management issues such as the introduction of FRTB will also have an impact on structured products. Investment banks, which can jump through the considerable hurdles of implementing an internal model, will have a significant capital advantage when issuing these products.
Related Courses
Equity Derivatives
Volatility: Trading and Managing Risk
Equity Derivatives 2: Exotics and Structures
