The emotional core of our brain, the Amygdala, has the primary role of triggering fear responses. Information that passes through the Amygdala is tagged with emotional significance. If the market continues to decline, an investor could be under the influence of what is referred to as the “red-effect” by Elliot et al. (2007). Further research shows that even a two second glimpse of color red can have an important influence on our cognition, and behavior, and processing this color can undermine our intellectual performance – this phenomenon is called the “semantic red effect” [Lichtenfeld, Elliot et.al. (2009)]. Going beyond traditional finance, new research now combines neuroscience, psychology, economics and behavioral science in an attempt to explain how people make economic and portfolio decisions under uncertainty.
In an earlier blog on Trader induced Volatility and Market Correction, we defined excess market volatility, a concept that some academicians termed as “animal spirits”. The behavior of volatility during an environment when fundamentals are weak could be different from volatility-clustering – the tendency of volatility to persist in clusters, as a natural result of price formation process with heterogeneous beliefs across traders. Long term investors naturally focus on long-term behavior of prices, whereas traders aim to exploit short-term fluctuations. Although CBOE VIX® Index, the Fear Gauge of the market may have spiked, the absolute level is still low compared to the previous markers in 2018, let alone in 2008. Asness of AQR indicated in his recent post, this just ain’t a big number compared to the historical levels.
However, when an investor engages in “short-term thinking with long-term capital”, it becomes the classic “Fight or Flight” scenario with the Amygdala. An investor becomes impulsive and sells his or her investments in order to avoid further losses, does excessive trading, or attempts to recoup losses by investing in high-risk investing strategies.
In the scholarly paper by Brinson et.al (1986), the authors argued the importance of asset allocation and concluded that asset allocation explained an average 93.6% of the variation of returns, whereas timing and security selection explained the reminder of 6.4%. In addition, the contributions from timing and security selection to active returns, were in fact, negative, which suggested that investors who tried to time the market were not rewarded on an average. Despite the empirical debate on the importance of asset allocation over market timing or security selection, the conclusion is pretty clear that sidestepping from a disciplined investment strategy e.g. Strategic Asset Allocation, Tactical Asset Allocation or a Target Date Solution won’t bring an extraordinary reward. When investors, under the influence of “fear”, decide to engage in an active, or an impulsive investment decision, they must assess the costs, skills and informational efficiency associated with those decisions. It is important to remember the goals associated with an investment strategy rather than an attempt to time the market, which is more considered gambling than a legitimate investment strategy.
Seasoned portfolio managers stick to their guns because of their conviction, and it is important to ensure that the investment process is “disciplined” and “repeatable”. In social parties, I often hear the excitements of a few who boastfully declare their smartness by indicating their success of selling out of a position before it declined by x%. I would buy these geniuses at any cost if they can prove this outcome repeatedly. As seasoned financial market professionals, we all know the infamous Efficient Market Hypothesis (EMH), which suggests that stock prices incorporate all relevant information making it impossible to predict and consistently earn excess returns over a long period of time.
It’s a very common psychology to derive conclusions from examining history. This results in people engaging in Confirmation Bias – looking for data that confirms past beliefs and ignoring new information that contradicts existing perceptions. One could look at the historical data and come to the conclusion that we should see a decent rally ensuing from very oversold levels and highly bearish sentiment at the indication of the first leg of a bear market, or we are already in a bear market that preludes to full-blown recessions, which is expected in 2019.
Currently, we may have a case of what we indicated in our previous blog that this December may prove to be the worst December in the history of 44 years. This could suggest that you better sell your portfolio positions now, and claim your brilliance in social parties next year if the history repeats itself, i,e. if 2019 repeats the history of 2008, or something worse. Or, one can believe in the Fed hypothesis, as it released from its December 19th meeting, “consistent with sustained expansion of economic activity, strong labor market conditions, and inflation near the Committee’s symmetric 2 percent objective over the medium term. The Committee judges that risks to the economic outlook are roughly balanced…” Although the Fed reduced its forecast for 2019 rate increases, from three quarter point rises to two, given rising risks across the global economy, from U.S. , Europe to Asia, it noted that the federal funds rate target range is only touching the lower bound of neutral.
Which one is true?
In my mind, this is a classic case of running into Type I (“false positive”) and Type II (“false negative”) errors in statistical hypothesis. Type I error occurs when you incorrectly reject a true null hypothesis or a Type II error: failing to reject a false null hypothesis.
Type I error – selling out of the positions now and going to cash because of the “red” alert (Rejecting the “Fed” hypothesis when it is correct, i.e, economic growth is on course and risk is roughly balanced.)
Type II error – staying put with your portfolio (Rejecting the “red” alert that it is an indication of a serious, long-lasting declines in stock markets and believing the Financial Media that the “worst is yet to come“)
One could argue the cost of a Type II-error as it defines the probability of making the wrong decision when the specific hypothesis is true, but again, it depends on what you are testing from a behavioral standpoint. You would find enough evidence of proving a hypothesis one way or the other that you believe in, and prove to be right, or wrong. The common mistake is confusing a statistical significance with practical significance. As I mentioned in a recent blog post, the decision making in financial markets is seldom rational as human beings have informational, intellectual and computational limitations.
You could decide to “Flight” from this market now or “Fight”, by sticking to your guns. The media and prominent headlines can trigger the Amygdala for many investors, and it can cause severe stress. Advisors can be inundated with questions from their clients about what they are doing in the circumstances.By putting the brain on alert by this market, the Amygdala can cause a series of changes in your brain chemicals and hormones that can put you in a serious anxiety mode. This can bring more downside to your body and mind than the result from making instinctive portfolio decisions over the fear response.
If you are stressed, take this an opportunity to evaluate your investments and better deal with the risks by adjusting your asset allocation to account for your goals. By doing so, you would feel much better by kicking your conscious mind and rationality into gear. This can help you rationalize whether these signals really require an active response, and if they do, let a well thought out portfolio decision work for you.
At Convex, we offer a suite of Behaviorally Adapted Portfolios (BAM), which incorporates practical use of behavioral finance in asset management. BAM attempts to reduce your anxiety and stress with financial markets and it also makes an advisor’s life easier with Convex OCIO solution. We believe risks are time-varying and in our opinion, better managed as they ebb and flow. An efficient allocation of capital should adapt with evolving fundamentals and level of risks in capital markets.
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