Alphabet Soup

Note: this posting originally appeared in IPE (Investment & Pensions Europe) on January 4, 2010.  This version differs only in that I converted spellings to standard American English.

04 Jan 2010

W, U, V, L? It’s all a symptom of the misleading ‘patternicity’ that dogs traditional macroeconomic thinking, argues Damian Handzy

Much has been written about the shape of the recovery. Will it be ‘V-shaped’, implying as swift a return as we had a drop? Will it be ‘U’-shaped, implying a period of low economic activity before a swift return? Will it be ‘W’-shaped, implying a second crash before an eventual recovery? Perhaps it will be €-, £-, ¥-, or $- shaped, implying that some lucky country will lead the way and benefit handsomely while it does so. If I am forced to pick some symbol for the shape of the recover, then my choice is the Chinese characters 不 and 複, the first of several that together represent ‘uncertainty’ and ‘complexity.’

The very process of reducing the crises and subsequent recovery to a recognizable shape is an example of what behavioral economists call ‘patternicity’, the tendency humans have to find patterns just about everywhere, whether they are real or not. The term was coined by Michael Shermer, author of ‘Mind of the Market’, in which he explores many aspects of how we humans interpret and misinterpret information about markets. The overarching field, behavioral economics, incorporates a very important component into our understanding of markets that is missing from traditional approaches: the real ways in which the human market participants actually act and make financial decisions. Without including some aspects of real human behavior, economic models are doomed to describe only an idealized world that has little to do with the one in which real people live, trade and make and lose money.

Unfortunately, the economics that was taught to most policy makers – including central and Federal Reserve bankers – was based upon the unrealistic tenets of the efficient markets hypothesis (EMH). Driven by a desire to do for economics what Newton’s laws of motion did for science, its authors succumbed to a common yet devastating flaw – oversimplification. According to MIT’s Andrew Lo, “We wish that 99% of economic behavior could be captured by three simple laws of nature. In fact, economists have 99 laws that capture 3% of behavior.”

Incorporating real human behavior into the models does not just lead to a better understanding of economics – it has practical applications, including advancements in risk management that have relevance for pension funds. Work that was originally intended to demonstrate the flaws in one of the key assumptions of the EMH was then adapted into a tool to help detect signs of illiquidity in managers returns and has even been used to help identify possible signs of smoothing and fraud.

The problems with traditional economic and market theories do not just have to do with ignoring how humans behave – they also have to do with oversimplifying how such systems work on a macro scale. Unlike systems of billiard balls and planets that obey relatively simple rules of motion, economies and financial markets are in a very different category of phenomena that have recently become known as complex adaptive systems. Our natural desire to come up with simple explanations for observed market phenomena flies in the face of what is being discovered about how incredibly non-linear these systems really are. Feedback loops are a staple of these complex/non-linear systems and exemplify how quickly things can spiral out of control – just think of the last time someone put a microphone too close to a speaker! Financial markets have many sources of feedback, with capital itself as the most obvious example – one person’s expenses are another’s revenue, which is in turn used to pay employees so they can pay their expenses. And so it goes, feeding back upon itself. Market behavior isn’t simple. It can’t be ‘broken down’ into simpler parts and then added back together to understand the whole.

When our political and financial leaders decide to act by reducing interest rates and injecting liquidity (and hopefully trust) back into the markets, they do so because they learned the hard way back in the 1930s what it means to do otherwise. But they can’t know the myriad ways in which people will react, nor can they follow the many possible feedback loops that will result – not because it is too hard, but because their models don’t know about difficult things like non-linearities, feedback loops, behavioral biases and complexity. But one thing they do have right is their call for increased transparency. This is echoed by the boards of leading pension funds and other institutional investors. Increased risk transparency will be the mantra of 2010. This does not mean access to mounds of data no one knows what to do with. Rather, it means using appropriate risk aggregation tools to better understand the sources of risk generated by managers individually and, even more importantly, in concert.

Where does that leave us? For those with long-term investment horizons and passive investment style, the shape of the recovery doesn’t really matter as long as in the end the markets are back up and gains can be made through indexing. For those with shorter investment horizons or managed investments, the path doesn’t seem as clear.

When you consider the dynamics and the quickly changing nature of the markets as we emerge from the crisis, however, one thing is clear: managers who are nimble and flexible enough to adapt by rapidly changing investments have the best chances of earning returns. The only group of managers that have consistently demonstrated the nimbleness to make money in such turbulent markets is hedge funds. Commodities traders who have been around longer than a few years have especially good practice at making money in sideways markets.

In 2009, we saw convertible arbitrage and long equities as winning strategies. In 2010, it will likely be some other alternative strategy. For the institutional investor, trying to predict which strategy will win is not as effective as betting that the group of them will: by maintaining a significant investment in diverse alternative strategies, where the managers are paid to be nimble while simultaneously managing their risk, an investor is likely to materially increase his chance of benefiting from whatever shape the recovery takes. When you examine real returns, hedge funds, on average, lost the smallest amount of capital for their investors in 2008, and as a group have made more money for their investors since the recovery began than any other strategy or investment style. Those firms that are not significantly invested with alternative managers today are precisely those who are likely to ‘wait and watch’ while they deliver higher returns over the next few years – only to finally invest near the peak of whatever bubble comes next.

One Response to Alphabet Soup

  1. I am glad you took the time and said this 🙂

    Sincere regards
    Letitia

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