Alpha, Beta and Standard Deviation with Structured Positions

At the highest levels, much emphasis is placed on critical statistics of Modern Portfolio Theory, primarily alpha and beta, along with a couple of other less familiar items, such as R-squared and the Shortino ratio.  I’m not going to go into a white paper on these latter items; that’s for another day. But I want to be sure investors understand how my Structured Positions differ from standard investing, what the reasonable expectations are for statistical outcomes, and why those are still a good thing.

First of all, alpha is largely removed as a statistical tool. I use primarily indexes as the underliers, with multiples of them backed by contracts with other investors.  The main risk to getting exactly what is expected is bond performance, which may seem counter-intuitive.  But as long as the bonds produce the expected yield in an up market, we should be close to the expected outcome-–an outcome that exceeds normal market investing, in the case of a market multiple position.  It’s a simpler equation. It’s just math, for the most part. Maybe that’s why I like it so much.

As to beta, or volatility relative to the market:  be definition, if I’ve created a position that has a market multiple in its structure, the position should move more than the market index to the upside. This is a statistical reality---but a good one. It’s what the investor wants.

It’s the downside where the investor doesn’t want greater volatility (read: losses) than the market.  By using bonds and puts, we reasonably expect our positions to have lower losses (and even gains, in some scenarios), and therefore lower volatility, than a declining market.  As an example, I recently calculated a .74 beta on a market-multiple position. Statistically, the position was producing what it should:  lower average volatility overall than the market.

Standard deviation is another important measurement:  an investment that varies more in its returns (both upside and downside are part of the measurement) relative to its market can be seen as of lower value than one that varies less than the market.  But when the position is designed to produce two times the market return, by definition its upside results should be more variable than the market.  Again, a statistical reality—but a good one. 

Setting reasonable expectations for MPT statistics with Structured Positions has been a challenge for me so far, because the concepts largely are outside of “investment culture” norms. But intelligent, informed investors, for whom reasonable expectations have been set, are my favorite kind.  And I love meeting or surpassing expectations.

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