The Electric Kool-Aid Market Test
“Everybody, everybody everywhere, has his own movie going, his own scenario, and everybody is acting his movie out like mad, only most people don’t know that is what they’re trapped by, their little script.”
I must confess that Tom Wolfe is one of my favorite authors. And I am sure that he would have loved to write something about what is currently going on capital markets. Maybe Michael Lewis plans to work on such a book?
Everyone will agree that the past five weeks have been extremely violent. Thus, the million-dollar question is, has the market bottomed or not? To try to answer this question, it is necessary to provide an accurate definition of financial cycles, using insights from behavioral finance and econophysics. If you are mainly interested in pure chart analysis, I suggest you take a look at Sven Henrich’s work on Northmantrader.com.
History has always been very helpful for economic analysis. For instance, you would learn that money printing was massively used during the French Revolution in response to a severe debt problem. Unfortunately, that experiment failed, leading to a political mess and the rise to power of Napoleon.
Understanding past markets routs enables to properly analyze current financial cycles. Great work has been achieved by people like John Kenneth Galbraith to inform on iconic events such as the Wall Street crash of 1929. So, what is a so-called bull market? And what is a bear market?
Forget the media headlines about equity indices entering bull or bear market, they are totally meaningless! What History and behavioral analysis have taught us is that both bull and bear markets are processes.
A bull market is a pretty long-term process that starts when almost all investors have capitulated, meaning that they feel desperate about the state of the economy and about their portfolios. In other words, excess has been wiped off and the market has just become vulnerable to upside risks. Therefore, risky asset prices are likely to rise at a moderated pace, even if most people might not have faith in that new trend.
Localized bubbles and bursts are always possible on a few sectors or thematics. Moreover, short-term corrections are likely to occur. But if the market succeeds on recovering after each stress, then bears will slowly capitulate, and the market will head toward the ‘irrational exuberance’ phase.
In his book Why Stock Markets Crash: Critical Events in Complex Financial Systems, Didier Sornette wrote that markets exhibit a macro-behavior during bubbles. Said differently, they self-organize as a fractal object and asset returns display log-periodicity. The period from October 2019 to February 2020 was a typical example.
Euphoria means that most investors have become highly vulnerable to downside risks. There might be a specific trigger for the transition towards a bear market (e.g. an external black swan event), but sudden psychological shifts among participants can also occur without any obvious reason (e.g. the 1929 crash). Volatility is likely to spike significantly, displaying fat-tailed amplitudes. Like at the beginning of a bull market but in the opposite direction, most people will deny the possibility of sustainable downward trend and will bet on a fast return to normal.
Of course, a bear market is not a straightforward process, and powerful counter rally episodes are likely to occur. Actually, the process will last until all investors capitulate and forget about returning to previous highs. I have never read papers on that, but I have the intuition that after a huge sell-off, the market also becomes a fractal object, but characterized by extreme risk-aversion instead of excessive risk-appetite. In a sense, bull and bear markets could be regarded as symmetric processes.
So, where do we stand now? The most relevant question to ask yourself is, do you believe that investors have capitulated or not? To answer this question, I think it’s relevant to capture real sentiment trends using social platforms such Seeking Alpha, Twitter, etc. I have no opinion on the quality of existing machine learning algorithms doing that, and it’s clearly a long and exhaustive job if you do it by yourself, but I can assure you that it is worth it!
This article was originally published on LinkedIn March 27, 2020.