This an excerpt from the book Hedge Fund Market Wizards. The bold font is Jack Schwager’s remarks and the non-bold font is Jamie Mai’s comments. This isn’t exactly how it appeared in the book, as certain paragraph breaks and italics were omitted as I highlighted things in batches on my Kindle. I thought it was an interesting trade that is probably still relevant today if one wanted some cheap upside exposure to the market without having to risk too much capital, though you probably need a significant amount of capital under management in order to have access to this kind of trade.
We have a trade on now that I really like. I don’t know if you read Jeremy Grantham of GMO. He is a widely respected value investor who looks across all asset classes and writes commentaries and editorials about what he is seeing. For some time now, he has been arguing that high-quality, consumer oriented franchises, particularly those that have great international brands, are cheap relative to the rest of the S&P based on both dividend yield and enterprise value to cash flow. In my view, he has laid out a fairly compelling argument that places relative valuations in the context of a cycle, wherein the low-quality names tend to outperform early in the cycle, and the high-quality names tend to outperform toward the end of the cycle. There is an index called the XLP, which is an index of U.S. consumer staple companies such as Procter & Gamble, Coca-Cola, and Johnson & Johnson. If Grantham is right, at some point we should see a revaluation of the stocks in this index.
I assume that in the current cycle since the 2009 low, the XLP has gone up less than the S&P?
It has gone up a lot less. Initially, we considered buying options on the XLP, which were relatively inexpensive. But Ben came up with a much better way to structure the same trade idea based on the XLP’s low beta of 0.5 versus the S&P500.
One observation that we found particularly striking was that despite the XLP’s low beta, since the start of the index at the end of 1998, the net percentage changes in the XLP and the S&P over the entire period were almost identical. The XLP was up less in the bull markets and down less in the bear markets, but for the period as a whole, the net change was about the same. Seeing that both indexes had approximately the same net change over a long period—a period that included both the Internet boom and bust and the credit boom and bust—makes the notion that the XLP has a beta of 0.5 versus the S&P seem counterintuitive if applied to longer periods. In addition, we thought that cash flow and dividend valuations implied the potential for a 25 percent revaluation of the XLP versus the S&P. We went to an exotic option dealer and asked them to price an outperformance option that would be based on the performance of the XLP versus the S&P. What is the single measure that the dealer is going to use to price the odds that the XLP will outperform the S&P?
Right. So with the beta equal to only 0.5, the model price for an outperformance option was very cheap. Translated into English, those inputs are saying that the XLP and S&P are likely to move in the same direction; however, the XLP will move only half as much as the S&P.
But if we had a down market, then the lower beta would imply a higher probability of outperforming—namely, it would imply that the XLP would go down less than the S&P.
That’s a great point, and it is the reason why, to get the option cheaply, we had to strike the option at the current spot price. So there was a dual condition for the option to pay off: The XLP had to outperform the S&P and the S&P had to be unchanged to higher. This was essentially a conditional long beta position. It was conditional on the XLP outperforming the S&P, and it was long beta because it could only pay off in an up market.
What made you think the timing for the trade was right?
We didn’t have any conviction that the market was going higher. We almost always want to have some long beta exposure, however, and by making the option conditional on the XLP outperforming the S&P, we were able to get beta exposure to the market extremely cheaply. When you own options, you’re always fighting against the time decay. Figuring out how to make the option premium cheaper is one way of mitigating that decay.
So the basic premise is that beta is measured based on daily relative price changes, which can be a very poor indicator of long-term relative price changes.
Right, a fact that is obvious if you look at a long-term chart comparison of the XLP versus the S&P. Volatility is a terrible proxy for measuring potential price change over longer intervals of time. For example, if an asset price changes by a constant percentage each day, its volatility will be zero. One of our strategies is called cheap sigma and is predicated on the idea that markets sometimes trend and that volatility will dramatically understate the potential price move of markets that trend.