Ever since Jevons and the marginal revolution in economics in the late nineteenth century there have been enormous benefits from quantitative techniques in economics and finance. Critics have warned, though, of the associated tendency to over-emphasise the importance of the measurable as compared to what is immeasurable or simply not measured.
A high degree of reliance on quantitative techniques to calculate risk and optimise asset allocations has made sense for individual decision-makers and investors, and over short periods, yet collectively and over time has led to huge market inefficiencies and distortions. Moreover, when it comes to what is not measured, the bigger the scale of the information gap, the bigger the problem.
Two investment areas stand out more than most as being discriminated against for lack of easy measurement are emerging markets and private markets. This is precisely why New Sparta Asset Management (NSAM) is focussed on sector specific opportunities in private markets across EM.
However, errors of omission are not restricted to certain types of investments which are difficult to asses or value, but also affect markets which have some measurable elements but also unmeasured ones. The consequence is that prudent investment does not necessarily equate with restricting investment to asset classes and investments widely assumed to be safe. Such allocations may nurture major hidden risks. This is all the more likely, depending on investor base structure and perceptions, where there are similar and shared broad misperceptions, and consequently potentially highly-correlated risks under crisis conditions across many asset classes. Conservative investment strategies (highly risk-averse according to widespread and conventional definitions of risk) can be demonstrably highly imprudent.
In the length of a blog, it is difficult to give comprehensive treatment to every logical category of problem. Suffice it to say, though, that there is a long history of confusion over probability, risk, and uncertainty. Almost a hundred years ago Keynes in his 1919 Treatise on Probability charted the logical categories for which past recorded correlations can not be, but are often assumed to be, indicative of future likelihoods. Yet many investment professionals today, let alone the wider public, consistently fail to understand even basic distinctions between correlation and causality.
Keynes went on to write his General Theory of Employment, Interest and Money which, like the Treatise on Probability, amounted to a brilliant hatchet job on the standard academic thinking of the time. His insight that investment is almost impossible to predict and a result of “animal spirits” has not been much improved upon since (Akerlof and Shiller’s aptly-named 2009 book “Animal Spirits” and much of behavioural finance besides, testifies to the difficulty of quantifying emotions and actual decisions).
Keynes’s observation that in the face of significant uncertainty firms will not invest in new capital, and that such behaviour, en masse, can create more uncertainty for all firms and so lead to depression, has ever since guided governments and central banks in stimulating investment and at least trying to manage expectations. In assessing investment and asset allocations it is a long-held understanding, as in many walks of life, that precision is not the same thing as accuracy.
That economic and financial theory often informs policy and investment decisions also creates feedback patterns, often for long periods. They can create self-fulfilling prophesies and bubbles, as well as the not uncommon phenomenon of theories based on empirically-observed phenomena which evaporate once investors or policy-makers try to exploit them. Such feedback can make otherwise spurious theory believable and, it would seem, empirically validated.
Such feedback can be further bolstered. Leverage, sophisticated financial derivatives, shared thinking and approaches to investing, can all reinforce both the widespread sense that particular observed market relationships are stable, as well as our sense of what is and is not risky, and hence our perceptions of the ways in which past data can help us understand the future.
One consequence, for example, is that financial market “technical analysis”, which is used to draw conclusions about the future from patterns in past price movements but is agnostic about other factors, can be of practical use. Technical analysis in a particular market often yields useful results mainly or even solely because enough market participants behave as if it is going to do so. Indeed, market behaviour is often driven by short-term beliefs bearing little relevance to broad factors of supply and demand. This creates arbitrage and other market inefficiencies which are inconsistent with standard economic assumptions about market efficiency. Bubbles and crashes, according to The Efficient Market Hypothesis, are a result of new information being processed by market participants, not the result of collectively irrational mass behaviour.
If something as banal as technical analysis can move markets, just imagine what more respectable financial theory can do.
It is a consequence of the potential financial benefits which can accrue from predictive power in financial markets which makes it so difficult for finance theory to be objective. The theorist often cannot both get acclaim for his or her theory and for the theory not to impact behaviour and so impact its own validity – either by negating its insight or over-estimating it. Genius theories which suddenly fail can result, as can the real misery and impact on people’s lives resulting from huge bubbles followed by systemic crises. LTCM comes to mind but there are many examples.
Lots of investors already know all of the above, so what is new? Arguably not enough, insofar as investors and policy-makers, collectively, have not acted sufficiently on what they do know – which is as follows. Firstly, the biggest macroeconomic risks are in the developed world. Secondly, developed markets have demonstrated that in crisis they can all go down together in a highly correlated way. We have seen in the 2008 crisis the failure of the inter-bank market, and massive falls in liquidity across many markets considered highly diverse and previously uncorrelated – including markets considered low risk and “risk free”.
Thirdly, where markets are more in bubble territory, as they are much more in developed than emerging markets, they can be expected to stay down should there be another major global financial crisis. The argument that new bubbles in developed markets would simply reappear is a dangerous one to rely on. The status quo has been sustained post-2008, but a repeat crisis can be expected to result in much more focussed political pressure to radically restructure global finance, and with it the leverage to create new bubbles.
Fourthly, despite this knowledge, there has been no widespread rejection of the financial models and theories which helped create and then grow the imbalances leading to the 2008 crisis. Hence a repeat is possible – maybe one with even more adverse consequences.
Fifthly, and crucially, there is still a huge potential for investors to reduce the likelihood of large permanent losses from a 2008 re-run – albeit investments fairly immune to large permanent loss may still be vulnerable to short term mark-to-market losses, volatility and illiquidity. The best way to insure against this – indeed the prudent risk-reducing course – is to invest significant assets into emerging markets and real assets, indeed into real assets in emerging markets.
By Jerome Booth