The Low Volatility Anomaly and the Failures of Your Asset Manager

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John Henry Smith
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According to John Henry Smith, fund managers are too much focused on bench-marking their performance to a market index, over-emphasizing the importance of “alpha”. But asset managers should abstract from alpha and construct portfolios that have lower risk and higher return than the market. Impossible?

This post is the second part of The Fallacies of Portfolio Volatility Measurements.

The Market Return

For reasons of consistency, fund managers are primarily focused on benchmarking their performance to a broad market index and ignore attempts at profit maximization.  This is because of the mistaken belief that portfolio diversification diminishes approximately two thirds of all specific stock risks, leaving only the market return as the basis of reward. Thus the removal of these risks explains why index funds dominate all other types of equity investing, but not the rationale for over-diluting the Alpha element. As a consequence, the pursuit of merely achieving the market return for consistency’s sake requires the construction of portfolios with low Alphas, which by default require the selection of stocks with mediocre growth prospects. This convention is reinforced by the obsolete theory that you cannot beat the market all of the time; a hypothesis which attempts to justify index-linked investing, but in the face of its self-fulfilling prophesy is an approach that absolute return investors categorically reject, and correctly so!

One reason for nurturing these old beliefs of the 1970s is the upfront management fee structure, which acts as a disincentive for change from a market return approach to an absolute return oriented fee structure.

Volatility’s Payoffs in the three phases of a trading cycle

The following extracts from the Omega portfolio show the influence of investor sentiment under three different market conditions. The first example is the overall result, made up of the other three phases.

Note that in example 3 sigma declined by -34% but the portfolio still delivered a strong return of 18%.

1. The complete trading cycle, this covers the bullish, range-bound and bearish phases.

2. Bullish behaviour generates higher volatility and higher accumulation.

3. Range-bound behaviour is usually accompanied by declining volatility and either increasing or decreasing accumulation or distribution. Here it is increasing distribution.

4. Bearish behaviour causes declining volatility with a corresponding loss in the portfolio’s value.

Professor Malcom Baker of Harvard University and Messrs. Bradly and Wurgler, wrote in 2010 a seminal paper entitled ‘Benchmarks as Limits to Arbitrage: Understanding the Low Volatility Anomaly’. Their research paper covered 41 years of data and provided conclusive evidence that portfolios of low volatility are able to generate high returns and not what is conventionally accepted as requiring higher volatility, and thus risk. In spite of this irrefutable evidence, the finance world nevertheless still stubbornly holds on to the out-of-date concept of the normal distribution as the basis for calculating risk metrics.

This inability to change continues to generate an ever increasing plethora of Index Funds, EFTs and portfolios with only the minimal addition of Alpha, just sufficient to marginally outperform the Market Risk Premium of a broad index.

The Low Risk Anomaly means that high returns can be achieved with equal or even less risk than the S&P 500; an observation rejected by standard finance theory. Grail research confirmed that Betas are asymmetric by showing in these calculations that down- and upside Betas have different values and are not the uniform values forecasted by normal distribution theory.

Behavioural Economics provides the explanation

Behavioural economics proves why the bell curve of a normal distribution is incorrect. It is because it rejects the theoretical concept of a wholly abstract rational homo economicus in terms of computational capacity and memory used in decision-making, but now accepted as being economically unrealistic. Instead, even the most rational of us are constrained by our own personal experiences, or bounded realities. These mental shortcuts, or heuristics, help us to operate intuitively, especially under severe time constraints and limited information. Thus a group-think response is invariably created by equity traders reading the same breaking news. In this sense, when prolonged, this concerted group behaviour, whether human or computerized, tends to shift the market in a given asymmetric direction, giving rise to different mean, median and mode values, as well as creating leptokurtic or platykurtic distributions. These dimensions are of course in a constant state of flux, dependent on the flow and ebb of investor sentiment.

We all tend to overestimate our skills and knowledge as well as under-estimating the impact of uncertainty. We view the world from within the boundaries of our comfort zones, hardly daring to risk expanding our actions to gain a greater insight into the problems that face us. At the edge of our self-created reality is the Platonic Fold, where the gap between what we know and what we think we know creates regular crises by calling into question the very heuristics and biases we use to solve our day-to-day problems. By avoiding such confrontations, we risk the greatest risk of all: by opting for the safe decision we deny ourselves the opportunity of challenging new experiences, gaining new knowledge and thereby reaping the prospect of achievement and growth, not to mention gaining a strong and sustainable advantage vis-à-vis complacent, change-resistant competitors.

At any rate, the current view of volatility remains deeply-rooted, invalid through its approximation of reality, in spite of the visionary words of The Low Volatility co-authors:

“We believe the long-term outperformance of low risk portfolios is perhaps the greatest anomaly in finance. It is large in economic magnitude and practical relevance and challenges the basic notion of a risk-return trade off.”