Financial models are no excuse for resting your brain

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Diversification is a matter of judgment not statistics. A model will tell you only what you have already told the model and can never replace, though it can enhance, an understanding of market psychology and the factors that make for successful business.

US universities have been widely admired in the past two decades for their investment performance. They were early supporters of private equity and hedge funds and the Yale model has attracted interest among sophisticated investors. But Yale reported in December that its endowment had lost a quarter of its value in the preceding six months. Other institutions are in worse straits.

The model seems to be in question. But the idea behind it – that careful diversification can combine good returns with low risk – is as valid as ever. The problem is that some supporters of that approach put too much blame on sophisticated modelling techniques at the expense of their own knowledge and judgment. Banks made the same error in their risk assessments: their value-at-risk models had similar structure and origins to those in portfolio planning.

Quantitative portfolio management relies on measures of correlations between asset classes. These historical correlations are not universal constants but the products of particular economic conditions. Unless you understand the behaviour that produced them, you cannot assess their durability. In 2007-08, assets that had been uncorrelated were strongly correlated and many portfolio managers were surprised when the diversification they sought proved illusory.

Underlying causal relations had changed, as they frequently do in business. In the new economy bubble of the 1990s, equities roared ahead while property languished. But during 2003-2008, the availability of underpriced credit, followed by its abrupt withdrawal, affected property and shares in similar ways. Anyone in the financial world knew these things: but computers, churning through reams of data, did not.

Asset classifications change their meaning. The alternative asset classes that yielded strong returns in the 1990s for Harvard and Yale were hedge funds and private equity. But the increase in the number of hedge funds and the volume of their assets meant that an investment in the sector – once a bet on an individual’s idiosyncratic skills – became more similar to a general investment fund. Hedge fund returns were therefore increasingly correlated with those of other investments.

Private equity was once a punt on small entrepreneurs. A manager with good judgment could make money from a few hits in a diversified portfolio. But by 2006 the sheer size of private-equity funds led them to focus on well established businesses. Such investments were a geared play on the stock market. They no longer spread risk: they concentrated it. Worse, many uncorrelated assets appeared uncorrelated in the past only because they were thinly traded and infrequently valued. Pressures to “mark to market” revealed the underlying correlations.

But, during the credit crunch, traditional forms of diversification have done what they are supposed to do. Gold, trading at about $650 per ounce before the credit crunch, is nearing $850. UK government stocks show a total return of 23 per cent from conventional bonds and 15 per cent from indexed bonds from July 2007 to December 2008: for global sovereign bonds, the sterling returns are 75 per cent and 41 per cent.

Diversification is a matter of judgment not statistics. A model will tell you only what you have already told the model and can never replace, though it can enhance, an understanding of market psychology and the factors that make for successful business. As a student of finance, I never expected to see the efficient risk-return frontiers I drew on the blackboard feature in PowerPoint presentations to meetings of trustees: or that these trustees would view the numbers that emerged as statements of fact rather than illustrations of possibilities.

People who were persuaded by these analyses have been badly hurt. Some will never pay heed to quantitative investment analysis again. Others will place equally blind faith in some new and fanciful construction. Both reactions are mistakes. Financial models are indispensable. So is scepticism in their application.

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