Today, his quantitative methodology is becoming increasingly accepted by the post-crisis global investment community. We invited leading portfolio management thinkers to a debate with the Professor to determine the current state and future of quantitative investment strategies. Yuri Bender directs the discussion.
Emerging markets roundtable, 21 June 2010,
Click here to watch the video version
Roundtable participants:
- James Bevan, Head of Investments, CCLA
- Matteo Campi, Head of Quantitative Management, AllianzGI Investment Group
- Professor Robert Haugen, CEO Haugen Custom Financial Systems and Academic Adviser to Alfred Berg
- Ben Palmer, Head of Portfolio Construction, Schroders Private Bank
- Professor Amin Rajan, CEO, Create Research Consultancy
- John Ventre, Portfolio Manager, Skandia Investment Group
- Adam Wethered, Co-founder, Lord North Street - Private Investment Office
- Yuri Bender, Editor in Chief, Professional Wealth Management
Yuri Bender: Professor Haugen, you are widely credited as being the man who cast a dark shadow over Eugene Fama’s efficient market hypothesis. But your discovery of a market abnormality in 1967 appeared to fall on deaf ears. Can you simply explain the Minimum Variance concept you discovered together with Jim Heinz, and why your discovery was ignored for at least 25 years and in some ways still flies in the face of conventional portfolio theory taught in US and European business schools?
Robert Haugen: I was trained under the “old finance” of the early 1960s in the legal ramifications of bankruptcy, mergers, and consolidations, to understand accounting numbers, standardise them across different kinds of companies and value the companies.
At graduate school, I heard rumours about something stirring at the University of Chicago, leading to a paradigm shift in the finance field. Gene Fama, a graduate student around 1963, came up with the idea that markets are efficient, with the price of every stock at all times reflecting a company’s true value. This rendered obsolete everything I was trained to do, because if that were true, the market peered through the veil of accounting numbers, standardised everything already and what we were doing was redundant.
My professors became obsolete. They were slowly replaced by professors trained under the new paradigm of efficient markets and eventually I went to the University of Wisconsin and accepted the new paradigm at first, but over the years began assessing the evidence, which appeared highly inconsistent.
With economics professor Jim Heinz at the University of Illinois, we looked at the performance of randomly constructed, equally weighted stock portfolios going back to 1926 and found in most periods the lowest risk portfolios had the highest realised returns. This seemed to be consistent all the way through the middle 1960s. Since then, I’ve done studies that follow this up and it continues to be true to this day. Low risk portfolios of stocks tend to produce higher returns.
Finance departments in business schools across the world are trained to theorise on the basis of rational economic behaviour and if they’re confronted with evidence totally inconsistent with the way markets perform, they become obsolete, just as my old professors became obsolete. It wasn’t a pleasant experience for them, it’s not going to be a pleasant experience for the professors of the paradigm of modern finance either and they’re going to resist this with all their might; and they’re doing that.
John Ventre: Does the research stand up using arithmetic average returns rather than compound returns, ie if portfolio managers rebalance frequently to overcome the geometry effect, does it still work or are you effectively arguing ‘buy and hold’?
And if beta is a negative predictor, perhaps there’s more than just one beta and once you move to a multi-factor model, what you’re actually seeing is other betas drowning the effect of the main market beta?
Robert Haugen: Arithmetic mean return versus geometric mean return was initially brought up by Michael Jensen in his PhD dissertation around 1968, published in the early 1970s, and has to do with ‘volatility drain’.
If you have two portfolios with identical expected return, but one has higher volatility, and you look at multiple periods of time into the future, they have the same expected return over multiple periods, but the distribution for the high volatility portfolio gets skewed in the sense that the expected return become increasingly dominated by very high returns that are very unlikely.
So if you look at the median average return on a high volatility portfolio, against a low volatility portfolio, the median average for the low volatility portfolio begins climbing relative to the median average for the high volatility portfolio and this is one possible explanation as to why we see low volatility portfolios outperforming.
In terms of multiple betas, I have a paper that I recently wrote called Case Closed, where we re-iterate that high expected return portfolios have a very interesting characteristic. They tend to be relatively large companies, low risk in terms of all the measures of market risk, but going beyond market risk and looking at fundamentals, they tend to be profitable companies on the uptrend in terms of profitability, selling at cheap prices, with positive momentum. So in terms of aggregate characteristics, they look absolutely spectacular in terms of everything.
