#97 | Proprietary Indices – Part 1
Proprietary indices have taken the FIA market by storm and are poised to do the same in Indexed UL. These indices unquestionably show well on the illustration, but will they perform better in the real world? The only way to get exposure to a proprietary index is through options, which work like a filter in that all indices with efficient risk/return profiles will have the same expected returns over time. In order for a proprietary index to deliver value and justify its fees (sometimes higher than 0.80% annually), it must generate outsized risk-adjusted returns that can flow through the option filter to benefit the customer. This is typically accomplished within a structure that also focuses on stabilizing the price of the option and delivering good “optics” in terms of participation rates or caps through volatility control. If you’re a producer selling Indexed UL, being knowledgeable and conversational about proprietary indices is about to become table stakes. This article is the first in a series that will cover how they work, what they do (and don’t do) well and how to position them (or not) with clients.
Over the past few years, no trend in the Fixed Indexed Annuity space has been more pronounced than the proliferation of proprietary indices. Whereas FIA products even just a few years ago were predominately built with and around traditional indices such as the S&P 500 (SPX), virtually every new FIA product has one or more proprietary index and, in extreme cases, it’s fairly obvious that the entire architecture of the benefits in the product are built around the characteristics of the proprietary index. Nationwide’s wildly successful New Heights annuities are a classic example of this. It should come as no surprise that these proprietary indices are starting to migrate from the annuities to life insurance. And as a result, it’s time to get educated and opinionated.
Let’s start at the beginning. The defining characteristic of an index is that it operates according to a set of fixed rules defined at the creation of the index. This is different from a mutual fund, for example, where the fund has an investment mandate and stated goals but has some discretion over how it executes on the mandate. The rough ruleset for the S&P 500 is that it tracks the 500 largest stocks and weights them by market capitalization. The S&P 500 represents just one ruleset of an infinite universe of rulesets. In the world of finance, an infinite universe of rulesets opens the door to a stampede of MIT-educated statisticians who can create and comb through all of those rulesets to find stories that can be packaged into an index with a nice marketing name and sold to insurance companies, who will in turn sell them to advisors, who will in turn sell them to clients. That, my friends, is the basic essence of a proprietary index.
Before I move on, I think it’s worthwhile to pause and take a look at the history of proprietary indices. As with more things than we would care to admit, what the insurance industry calls “innovation” is usually a repackaged strategy that already worked in another corner of the financial services world. This is certainly true of indexed life and annuity products, which are actually just a repackaged version of Structured CD. Banks have been selling these products for decades and they are more common in Europe than French baguettes. Customers in Europe can literally buy a Structured CD from an ATM. In the States, Structured products are generally sold to very wealthy clients through the private bank arms of the big issuers like Goldman Sachs and JP Morgan. Tracing the lineage of almost every new feature introduced in the indexed insurance world will bring you back to structured products. Proprietary indices are the prime example of this. They were initially created by the banks for their own individual structured products but, once the index had been created, the banks realized that they could sell the same structure to insurance companies for use in FIAs. Voila. A new market was born.
A new market – but not in the way you think. Indices aren’t investments that you can buy. An index is a tracking mechanism for the price and yield of existing securities. It doesn’t take into account things like trading friction, liquidity constraints, discrete time or any other factors of real world trading. You can, of course, have a fund that invests exactly like the index to the best of the manager’s ability but there will always be a gap (or “tracking error”) between the fund and the index due to real world challenges with executing the strategy.
But the beauty of proprietary indices is not in their ability to spawn investible funds. In fact, that’s not the point of the types of proprietary indices found in most structured products, including indexed insurance products. The beauty of proprietary indices is that they are optionable – the bank creating the index can also write options on it. This allows for exposure to the proprietary index without actually having to own the index. Even if the index would be completely impossible to replicate in the real world, the fact that it works as an index means that the client can have exposure to the index by purchasing options on it. The tradeoff, of course, is that all exposure to the index must come through the filter of option pricing. If you want the proprietary index, you have to get it through options.
The best analogy I can come up with for the practical implications of accessing a proprietary index through options comes from a YouTube video that I saw recently where two guys decided to put a whole host of liquids through a countertop Brita water filter to see what they looked and tasted like afterwards. No matter what liquids went into the filter, everything from Mountain Dew to mouthwash, they all came out more or less looking and sometimes even tasting like water. That’s what options do. Options are priced like a filter. No matter what asset class you dump into the filter of the option price, they all pretty much come out with the same expected payoff profile.
Forgive the digression, but I can’t really explain proprietary indices without making a slight detour into the theory behind option pricing. The simplest way to understand why option pricing works like a filter is to imagine that you are the one selling the option. When you are selling something, you want the sale price to equal the value of the thing minus your fee for selling it. The same goes for options. So what’s the value of an option? The net present value of its expected payoff distribution. To get that value, you just need to know a few things. First, when will the option pay off (or, what is its “tenor”)? Second, what rate should I use to discount the cash flows to determine the net present value? These first two ingredients will get you to the expected payoff of the option, but not the payoff distribution.
For that, you need the third and trickiest ingredient – volatility. How volatile is the underlying asset? The more volatile it is, the bigger the potential distribution of returns and the greater the spread of potential future values. Volatility is the insurance component of the option price because, like insurance, it puts a price on the uncertainty of outcomes. But the important piece here is that uncertainty only cuts one way for the option seller because the risk of selling options is asymmetrical. The seller receives a limited gain (the premium) in exchange for an unlimited liability (the payoff), so increasing uncertainty always increases the liability for the seller. As a result, the price of the option goes up with increasing volatility.
So why does option pricing work like a filter? In financial markets, risk is return and return is risk. There is no such thing as an asset class that delivers risk-free returns above the risk-free rate. Any return above the risk-free rate is evidence of capital being put at risk. The simple quantification of risk in a liquid financial market like equities is volatility. Volatility is explicitly priced into the option over the discrete tenor of the option. Over the long run, therefore, all asset classes with the same risk adjusted returns will deliver the same average returns after going through the option filter. Why? Because increased returns mean increased volatility which increases the price of the option. However, these factors are not static. Returns to risk bounce around constantly. As a result, different options strategies always perform differently than others over discrete periods of time, even if the expected return for all of the options is identical. That’s why options have always and forever been referred to as instruments for speculation or hedging, not an investment. You buy an option to either gain from or protect against a specific outcome over a specific period of time. Buying options as an “investment” would imply that risk, and therefore return, is being systematically underpriced in the underlying asset class. Otherwise, in an efficient market, the pricing for volatility in the option is sucking out the market return to risk.
I say all this not because I think you particularly enjoy reading about option pricing theory but because it has a direct impact on the mandates that proprietary indices attempt to fill. As I’ll discuss in future posts, proprietary indices already start at a disadvantage to broadly adopted indexes with liquid options markets like the S&P 500. For starters, they have embedded fees that can easily top 0.75% annually – so it’s no surprise why banks are falling all over themselves to offer these indices when their margins on asset management are being compressed everywhere else. These proprietary indices are also sometimes different enough from the broad indices that the bank offering the index is the sole provider of options on the index, which ensures some degree of pricing power and profitability for the bank, which is no small feat in the hyper-competitive market of equity derivatives where bank profits often run something like 2-5bps on option trade notional.
As a result, proprietary indices have to do something so markedly different, so value-added, that they more than recoup their (arguably) prodigious fees in performance. As discussed above, that does not mean picking a new spot on the risk/return efficient frontier because that washes out through the option filter. In order for a proprietary index to work, it has to do one or preferably both of two things. First, it has to prove that the index itself delivers superior return for level of volatility. Second, it has to present and price volatility in such a way that the optics of the trade appear to be superior to broadly traded index options by looking at things like interest caps, participation rates, hypothetical historical performance and the like. To reach way back to the Brita analogy, the proprietary index has to find a flavor and color so strong that they make it through the filter – even if the final content is still 99.99% water.
With that in our back pocket, the next few posts will cover the market for proprietary indices, the myriad of different strategies employed by index creators to get the flavor past the filter and, finally, how to talk about these indices with your clients.