Previously in this series, we have looked at the guiding philosophy of legendary investor George Soros (Trades, Portfolio), as told through his own words. We have discussed the concept of reflexivity, which states that the price of a security is not just a reflection of its underlying fundamentals, it can also affect the asset itself. This is the driving force behind the creation of bubbles. For instance, in real estate bubbles, increases in the price of property creates the (false) impression that homeowners are becoming more creditworthy. Now let’s look at the types of conditions that create bubbles.
Near equilibrium vs. far from equilibrium conditions
Price distortions can result from "near equilibrium" conditions or "far from equilibrium" conditions. The former applies to the majority of days in the stock market, where prices oscillate randomly around a mean in accordance to some knowable statistical model. In this case, the distortions are relatively minor. The latter applies in cases where bubbles dominate.
What is the practical implication of this? Most conventional risk management is based on the idea that near-equilibrium conditions predominate and that non-equilibrium conditions are vanishingly rare. In reality, this is not the case, as was evidenced in 2008:
“The recent financial crisis is a case in point. All the risk management tools and synthetic financial products that were based on the assumption that price deviations from a putative equilibrium occur in a random fashion broke down. And people who relied on mathematical models which had served them well in near-equilibrium conditions got badly hurt.
[During the financial crisis] as a participant, I had to act under immense time pressure and I couldn’t gather all the information that would have been available, and the same applied to the regulatory authorities in charge. That’s how far from equilibrium situations can spin out of control."
This insight that the actions of market participants is time-bound, rather than timeless, is missing from many investing discussions. When we look at how a certain event affected a stock in the past, we have the luxury of time and the ability to synthesize all the data available. However, this does not mean someone would have had the ability to access all that information in the moment. Efficient market theory (sometimes) falls down precisely because it assumes all information is being processed by all participants. In reality, this is clearly not so.
Never underestimate just how uncertain uncertainty can be
Even though he clearly has a good grasp of these concepts, Soros himself freely admits that he sometimes does not implement them perfectly. In 2008, for instance, he underestimated the volatility of the market, which limited his upside:
“I was aware of the uncertainty associated with reflexivity, but even I was taken by surprise by the extent of the uncertainty in 2008. It cost me dearly. I got the general direction of the markets right, but I didn’t allow for the volatility. As a consequence, I took on positions that were too big to withstand the swings caused by volatility and several times, I was forced to reduce my positions at the wrong time in order to limit my risk. I would have done much better if I had taken smaller positions and stuck with them. I learned the hard way that the range of uncertainty is also uncertain and at times it can become practically infinite.”
So what does this mean for the average investor? We often talk about having strong convictions and being willing to double down on a good opportunity, but while that can be important, having a good risk management is even more important. Never risk more than you can afford to lose, and always be mentally prepared for the possibility that you may be wrong, no matter how strong your thesis seems.
Read more here:
- George Soros’ Investment Philosophy, Part 2
- George Soros’ Investment Philosophy, Part 1
- The WeWork IPO Looks Finished
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