Most importantly, Charles, David, and the remainder of the MFO gang deserve the highest commendation for accepting the challenge to organize the huge body of mutual fund data in a manner that facilitates comparisons and finally decision making. That is a daunting and Herculean task. Congratulations to them; they are making great progress.
Like an earlier Investor posting, I share a few detailed project reservations, mostly related to the preferred sorting criterion. Fundamentally, the criterion (the Martin Ratio) appears to be the Chosen One mainly because it differs from the more common criteria like the Sharpe Ratio, or more simply the return-risk (volatility, standard deviation) tradeoff. Just offering a dissimilar selection criteria should never be the determining factor. It must also provide some inherent and potentially exploitable advantages.
A few days ago, I posted a comment to an Investor submittal that referenced the Hindenburg Omen. I opined that the Omen is silly and an abuse of science-based methods.
I borrowed a speculation from a Gregory Baer book that the title of a best-seller is equally important to the book’s sales as its content, and if that’s the case, then a properly selected title is pure marketing genius.
Well, the naming of Martin’s work “The Ulcer Index”, might equally qualify as pure marketing genius. Peter Martin’s research in this arena is rather mundane. He published his work in a book that is out of print except on the Internet. If you are sufficiently motivated, here is a Link that provides a free download:http://www.tangotools.com/ui/fkbook.pdf
Chapter 6, “Return, Risk, and Performance”, introduces the Ulcer Index and the Martin Ratio. You might want to access this source. I conducted a brief Internet search and failed to identify any academic or industry studies that explored the forecasting record of either the Ulcer Index or the Martin Ratio. Regardless, these metrics are frequently quoted by investment professionals, but serious examination of their persistence or reliability as a prediction tool are missing-in-action.
My current assessment of the meager historical performance documentation is that the Ulcer Index and the Martin Ratio are entirely empirically proposed mutual fund measurements. They possess no fundamental grounding. These additional gauges are more or less perturbations from the more conventional Sharpe, Treynor, and Sortino ratios. The Martin invented measures use the same data sets arranged in a slightly modified format.
Let’s focus on the differences between the Martin formulations and the traditional Sharpe Ratio. The disparity is concentrated in the denominator of the equations. They both evaluate dispersion around a baseline.
To address this dispersion, Sharpe uses standard deviation which measures variation around an average value. Martin’s Ulcer Index measures variation below the maximum price value registered within the data collection period. In essence, this distinction is a translation of the selected anchor point within the data set. Will this impact forecasting potential? I don’t know, and I can’t locate a study that examines this critical issue. My guesstimate is that I doubt that it does.
The Sharpe Ratio offers advantages by design that are NOT embedded in the Martin formulation. The Martin approach seems to be very ad hoc (arbitrary) in its construction.
The Sharpe Ratio uses Standard Deviation which is a basic characteristic of a roughly Normally distributed statistical data set. Most investors are concerned with cumulative end wealth. To calculate end wealth, the average annual return must be reduced by a volatility factor, its standard deviation squared divided by two.
The average annual return and its standard deviation are useful to estimate the likelihood of a portfolio producing negative returns for any given year. For example, a portfolio has a 10 % chance of delivering a zero annual return when its annual expected return minus 1.28 standard deviations are calculated using a Bell curve distribution.
Because of fat-tails and Black Swan events, it is unwise to reach beyond about 1.5 standard deviations when applying these data. The Bell curve is merely a returns approximation and does not hold water when assessing rare occurrences.
Will another number, like the Ulcer Index or the Martin Ratio, enhance MFO member’s mutual fund selections? I really don’t have a definitive answer. It likely depends on each investor’s approach to constructing a portfolio. But I am not Panglossian in this arena. The behavioral researchers have concluded that too many choices can produce confusion, delay, and uncertainty in the final selection decision.
I certainty highly praise the MFO team for assembling this evolving mutual fund tool with its noble goal to enrich our fund selection process. In the end, the ultimate goal is to cobble together portfolio components that fit in a manner that keeps expected returns at an acceptable level while simultaneously minimizing portfolio volatility. It’s the combined portfolio’s interactions (correlation coefficients) that matter most.
I wish the MFO team success at completing their ambitious, self-imposed task; lots of hard work required. I know the MFO membership will find their end product useful, and I hope they find this early critique informative.
Great work team MFO.