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Risk Parity is Too 'Extreme' – MIT's Lo Presents His Third Way

Andrew Lo, MIT Sloan Professor of Finance, calls for a happy medium between risk parity and mean variance optimisation.

(June 7, 2013) - Risk parity ignores the fact markets adapt across changing conditions, and a third way between this and traditional asset allocation theories must be adopted by investors, according to a renowned academic.

Andrew Lo, a professor of Finance at MIT Sloan and director of MIT's Laboratory for Financial Engineering, believes investors should use analysis of human behaviour-both in times of market stress and during calmer markets-when thinking about their portfolio strategy.

Writing in RBC's latest Perspectives report, called Realities of Risk, Lo said he was using his analysis of hedge fund behaviour to find ways of more dynamically managing volatility, and rethinking risk parity was key.

"Today, investors are thinking about risk parity, but risk parity is the opposite extreme from strategic asset allocation and portfolio theory. In the past, we would allocate across asset classes based on mean variance optimisation," he wrote.

"Risk parity says forget about the mean and instead allocate to equity risk buckets. There is a more sensible alternative that lies somewhere between these two extremes. That is what I am currently working on."

Lo argues that you don't want to throw away all the information contained in active returns across asset classes, but investors should recognise that markets adapt across changing conditions.

"Investors need to move with changing conditions and manage volatility exposure so they get a consistent amount of risk. Investors are willing to take risk, but they want to know that the risk they agreed to take is the one they are actually getting," he continued.

"In the last five years, however, volatility has become much too high and has bounced around more than ever. I am now trying to develop specific allocations for hedge funds and institutional investors based on the Adaptive Markets Hypothesis that can help them manage volatility on a day-to-day basis."

Lo's Adaptive Markets Hypothesis has been around for some time: it looks to take existing efficient markets hypotheses and add an understanding that analysing human behaviour can help investors realise how markets move at different times, helping to create better portfolio constructions.

Economists have overly focussed on rational human behaviour, Lo argued, but while humans can be supremely rational when it comes to certain kinds of decisions, they can be very irrational under certain market conditions.

"It's easy to point fingers at the types of mistakes investors make, but I would argue the kind of behaviour that occurs during periods of market distress or booms is not necessarily irrational. It's maladapted," Lo explained.

"It's clear that "business as usual" is no longer working - there have been fundamental changes in the global economy. Behaviour plays a large role and rational expectations and market efficiency have very little to say that would explain the kind of market behaviour we have observed. In that respect, behavioural economists have provided a number of counter examples.

"But they haven't presented a framework investors can use. The challenge today is to come up with a unified investment theory based on all this information, which is where the Adaptive Markets Hypothesis comes in."

The full report can be read here.

Related News: Why Risk Parity is Like Goldilocks and Has Risk Parity Jumped the Shark? 

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