Orthogonal Alpha, from what I can gather, is excess return generated by a portfolio manager that is statistically independent from other factors. When I say “from what I can gather”, this should be a tell to the fact that I just did a quick google search to figure out on a broad stroke basis what this term means. Even in that first sentence there is quite a bit to unpack for virtually every casual investor like myself; “orthogonal alpha”, “excess return”, “statistically independent”, “factors”, these are all terms that I either don’t understand or only somewhat understand, and in either case I want to learn more about them.
I believe this desire to push further and learn more in the face of incomplete understanding perfectly encapsulates what I envision for this blog. To be more specific, I plan on using this space to first lay out a brief summary of a key project I am working on followed by a real-time documentation/memoir of my journey in pursuing the end result of this project. The path is long, and there are many concepts foreign to me that I need to try to wrap my head around (such as orthogonal alpha) in getting there.
The project specifically is an investment strategy I’ve built that seems to produce consistently high returns over and above that of the North American Equity Market. The numbers look good, over the past 18 years (December 1999 - July 2018), the strategy produced a total return of 1,035.6% compared to the market return of 194.7%. This return was achieved by a portfolio consisting of only 20-30 securities pulled from the S&P 500 with trades happening only once per year. There is nothing exotic about the strategy; no shorting, no leverage. With all this in mind, the strategy showed a market *beta of 0.92 and correlation to the S&P 500 of 0.87.
The question that remains is whether or not this return profile is a result from chance, or is this strategy genuinely a better alternative to just holding an index fund that tracks the market? One quick and dirty way to get a gauge for this is to consider SPIVA’s Scorecard report which mentions that 84.23% of Large Cap Domestic Equity managers failed to outperform the S&P 500 for the five-year period 2012-2017. Extend the time period to 15 years and we are told that 92.33% of the same category of managers failed to outperform the S&P 500. This strategy outperformed the S&P 500 over every five year period from 1999-2017.
I mentioned that comparison was quick and dirty, as it doesn’t provide the detail I’m looking for. Specifically, I want to know what types of risks this strategy is exposed to in pursuing these returns; how much of the strategy’s returns are explained by the market and these risks it is exposed to? Is this strategy actually unique, or is it just a repackaged version of an already prominent strategy? These questions and more are what I will tackle and comment on throughout this blog, and maybe, just maybe, we’ll find out what orthogonal alpha really means.
*As a quick aside, “beta” is the sensitivity of an asset to some benchmark, in this case equity markets (think S&P 500). Just to show you how it works, the market would have a market beta of 1, because for every 1% the market goes up/down, the market also goes up/down 1% (duh, cause they are the same thing). Great, now let’s talk about a portfolio having a market beta of 0.92. This means that for every 1% the market goes up/down, the portfolio will also go up/down 0.92%. Technically this means the portfolio is moving slightly less than the market, which implies it’s slightly less risky than the market (this isn’t as cut and dry as it seems, but this post isn’t about getting too far into the weeds.)