The Market Mind Hypothesis, page 38
Emotions as Portfolios of Psychurities
First, we need to make the distinction between an investment portfolio or IP (which contains securities) and an emotion portfolio or EP (which contains psychurities). Specifically, emotions can be viewed as portfolios of domain-specific psychurities. Each psychurity is a single psychological adaptation: its activation or trigger is event-dependent or, in finance terms, ‘state contingent’. As such (and just like finance’s “pure securities”), a psychurity embeds a contingent claim, or payoff. These can be held individually or can be combined. In the latter case, your EP can contain those proverbial ‘mixed emotions’. In general, each EP is structured to replicate a strategy to respond to an event. Such strategies are ultimately aimed at gaining a reward or hedging a risk, especially if the latter cannot be quantified, i.e. is more about uncertainty. Portfolioism suggests that the mind forms a multi-layered complex of EPs (a ‘fund-of-fund’ if you will) which, via allocation and dynamic rebalancing, allows it to seek or avoid exposure to a multitude of circumstances, sometimes unexpectedly. At the same time, just like the fund-of-fund leads to a stream of payoffs, the combined EPs result in a ‘stream of consciousness’ for experienced emotions.
The values of these EPs are determined across various mind markets. First, they are appraised by way of the exchanges through cortical centres, and other exchanges between the subcomponents in the individual mind. Specifically, the competition for neuronal resources in the brain between emotions and thoughts is an extension of the broader polarity between the unconscious respectively deliberate forces. Second, they are also appraised via the exchange with other minds. Here mirror neurons, for example, seem to play a physical role in the shared unconscious assessment of emotions (Gallese, Eagle and Migone, 2007). We can consequently view this as a global market of emotions. Together with the local (personal) market, emotions are valued according to their fitness to a certain situation: an emotion becomes more valuable if its payoff, implied by the strategy as a response to the situation, increases the mental (e.g. epistemic) utility of the overall complex of portfolios (see Evolutionary Rationality in Appendix 1-B4). Also, due to their ancient existence (making S1 much older than S2), the history of emotion valuation is much longer than that of, say, logic valuation. (For a financial comparison: the history of gold valuation is much longer than that of oil).
There are four arguments why the EP interpretation is useful:
1. Focus on the leading indicator of cognitions
As so much of our behaviour originates in the unconscious (S1), we are mostly interested here in clarifying the earliest phase of the emergence and impact of cognitions, in particular instinctive (or “fast”) ones. In other words, we are interested in the leading indicator of cognitions. How is this mirrored in the collective world of economics? Financial markets are generally considered the leading indicator for the real economy. As discussed, they are an economic meta-adaptation in that they solve a crucial economic problem: to allocate capital, in a reasonably efficient way, to investments which eventually find their way into physical assets, (the output) of the real economy. And like the personal unconscious, much of market cognition remains hidden which, depending on your preferences, you can view in terms of “supra-conscious” (Hayek, 1967), “macroscopic intelligence” (Sornette, 2003), “cognitive non-conscious” (Hayles, 2014), or “collective unconscious” (Jung, 1934), for example. But in both cases, of the mind and the market, emotions are the early expressions of such non-conscious activity.
Again, this interpretation is part of the general connection between the economic mind~body and the mind~body economy. That also includes the sector-specific securities in the economic mind~body which can be equated to domain-specific psychurities in the mind~body economy. Both have a risk~return profile reflecting simultaneously historic experiences and implied expectations. And whereas individual cognitions are correlated to (historic) collective cognitions (like myths, stories, and themes), individual assets are correlated to the risk factors of the broader markets (like momentum, quality, and value). In short, both IP and EP reflect historic experiences, future expectations, and intersubjectivity. This makes portfolio management so appropriate as a shared and mutually applicable concept between securities and psychurities.
2. Focus on valuation
I argued in Appendix 1 why the mind is about valuation. Like the value of a portfolio of securities, the value embedded in an emotion, as a portfolio of psychurities, is not always clear-cut and can fluctuate. In particular, it emphasises that there is always a flipside to the return of the psychurity, namely its risk, like the cost of selecting it.
This is consistent with the original meaning of responses to stimuli, for example in terms of foraging. The attractive prospect of the stimulus food may not outweigh the cost of obtaining it as it can be bad or poisonous, too risky to pursue, and/or not adding (diversification) value (because similar food is already available or stored). More importantly, as aforementioned, the value of cognitions is ‘above all’ assessed collectively. This not only concerns ‘nature’s cognitions’ which are the primordial instinctive cognitions which reflect values with a rich history that we commonly share with our ancestors. It also includes ‘nurtured cognitions’: those more social and culturally biased cognitions, such as morals, which we commonly express in our exchanges while we simultaneously experience the same situation (for instance a family mourning the death of a child). Embodied simulation via mirror neurons suggests that the capturing of an expressed emotion by the senses, e.g. via observation, unconsciously triggers a similar emotion in the observer. In short, cognitions may be experienced privately but, like portfolios, they receive their ‘objective’ appraisal collectively. On that note, a bubble is not only an excessive valuation in financial wealth terms, but also in terms of collective narrow-minded emotional values.
3. Focus on dynamic rebalancing
Dynamic rebalancing of the weights of the constituents of a portfolio enables the replication of an unlimited array of payoffs. In other words, the concept of portfolio management includes a principle which can explain the flexibility and versatility of cognitions in terms of handling the multiple psychurities to react to changing circumstances.
4. Price dynamics in financial markets differs from those in the real economy
Price discovery in financial markets is different in nature from that in the real economy. To wit, and in the words of Jim Grant: “In almost every walk of life, people buy more at lower prices; in the stock market they seem to buy more at higher prices”. Consequently, the relationship between emotions and financial assets is different than between emotions and consumer products. Specifically, due to reflexivity, the dynamics of supply and demand in response to extreme price action in financial markets is counter-intuitive from an economic perspective. Reflecting Grant’s observation, in the build-up of a crowded trade demand, in the form of volume, frequently goes up as prices increase. This leads, among others, to the phenomenon of momentum. Another example is inflows in passive indexing funds. These funds subsequently need to immediately buy the components of an index according to market capitalisation, regardless of value, making them price insensitive. This often means that, on an annual relative basis, they then buy (sell) more of those stocks that have gone up (dropped) the most over the past year.
To summarise, portfolioism’s approach to mentality (here emotions) is consistent with and fits most of the foundations of cognitive science, including evolution (see Chapter 1). Evolution, via natural selection, has resulted in psychological functions or capabilities directed at solving specific adaptive problems, mainly those that existed among our hunter-gatherer ancestors. The problems that confronted our ancestors basically involved the questions of how to gain rewards (pleasure) and/or how to avoid penalties (pain). In other words, the evolved capabilities have economic characteristics: they enable responses to stimuli which suggest a return (profit) or a risk (loss). These capabilities are adaptations which enhance survival by assessing the risk~return profile of situations and structuring an appropriate payoff. What differs, among others, with a purely economic assessment is the role of epistemological utility.
Consequently, placed back in the settings of our contemporary ‘financial jungle’, these adaptations enhance, in principle, economic survival and value creation. However, there are two reasons why they do not always lead to optimal economic solutions or enhanced economic fitness:
Because they also contain a strong historic/primordial bias this frequently does not fit the current circumstances. In other words, the ancient ‘nature’s jungle’ of our hunter-ancestors may not always properly reflect our modern-day ‘financial jungle’. Whereas nature’s jungle led to losses of lives, the financial one leads to losses of livelihoods.
They also include adaptations which attempt to optimise an individual’s well-being, irrespective of the individual’s wealth. An example is charity which attracts volunteers from both wealthy and less wealthy backgrounds. Translated in utility terms, emotional utility maximisation is not always aligned, and in fact frequently inconsistent with, economic utility maximisation. From a statistical perspective, this is due to issues such as bounded rationality (i.e. incomplete information about the likely outcomes of a series of actions) and the “inability to use optimal algorithms when combining conditional probabilities” (Rolls, 2007, p.410).2
Although the level of specialisation of these psychological capabilities varies, each reflects its characteristics in the form of a risk~return profile and can thus be considered as psychurities. Combined they require some form of management as argued, for example, by Tooby and Cosmides (2005). Emotions are among the high-level functions which achieve this by way of portfolio management: they form portfolios (EPs) of lower-level, or domain-specific, psychurities. These portfolios, in turn, can become part of higher-level portfolios. In this case, the mind manages multi-layered emotion portfolios that consist of psychurities, each characterised by a particular risk~return profile, replicating a strategy with an implied payoff.
8.3
Valuation of Emotion Portfolios
According to the view described in the previous sections, an emotion—both its expression (as behaviour) and its impression (as experience)—is reflecting the weighted value of a portfolio of psychurities. This is dynamic in the sense that the overall mind~body portfolio is dynamically rebalanced in order to benefit from/hedge against an (emerging) situation, thus reflecting fluctuating values. It means that the various S1 and S2 portfolios are exchanging in the wider mind~body (market) portfolio.
8.3.1
Quantitative Valuation
Quantitative valuation involves planning or syntactic operations. In short it manages symbols. This takes place in the linguistic centre which is part of a larger higher-order-thought system (HOTs) located in the cortical area of the brain. It enables deliberate reflections on emotions. The linguistic centre tries to quantify emotions, including those expressed by other minds, by modelling their sensitivities, their fitness, to an emerging situation. However, like the CAPM in finance, its main assumption is rational behaviour. The implication of this assumption is, in simple terms, that the variables are assumed to be linear and lead to stable relationships with predetermined outcomes. To interpret this in terms of a metaphor, think of running a regression of emotions versus a similar historic situation; the linguistic centre uses an ordinary linear (or least squares) equation for its model. In this process of symbol manipulation it translates, as it were, the pre-rational representations into rational predictors of future behaviour. In fact, Rolls argues that in order to avoid inconsistencies in behaviour, the “explicit system” processing all this has to have the belief that it is in control, even if it is an illusion:
When other brain modules are initiating actions (in the implicit [unconscious] systems) … the explicit [deliberate] system may confabulate and believe that it caused the action, or at least give an account (possibly wrong) of why the action was initiated. The fact that the [explicit system] may have the belief even in these circumstances that it initiated the action may arise as a property of it being inconsistent for a system which can take overall control … to believe that it was overridden by another system. (Rolls, 2007, p. 410)
8.3.2
Qualitative Evaluation
The qualitative dimension of valuation, on the other hand, concerns the semantic representations, or symbols, themselves and is performed by the non-analytical capabilities of the mind. The qualitative meaning of the symbol emerges in consciousness as an emotional charge or feeling-tone which influences the overall value of the cognition. This value is felt which, if rationalised, becomes a confabulation: the story to explain the emotional response. In the words of Jawaharlal Nehru “a man of action in a crisis almost always acts subconsciously and then thinks of the reasons for his action”. This emotional charge consists, firstly, of its symbolic impact due to the shared meaning recognised (‘appraised’) by all agents in the ‘cognitions market’. Back in the financial markets, cognitions are collectively expressed in price patterns, including correlations and trends. Each pattern is symbolic for the behaviour of a fictional composite investor. Physically, once subliminally recognised, it could trigger cross-brain synchronisation, perhaps involving mirror neurons, leading to contagion. This part of the emotional value is mostly uniform or non-personal because the valuation follows the same path, culminating in what Vittorio Gallese—one of the discoverers of mirror neurons—calls the “same body state”. It goes through the limbic system, containing the more archaic parts of the human brain, specifically the amygdala, which particularly deal with instincts, the most uniform cognitions. Secondly, the charge includes a personal impact in that it has subjective meaning. The evaluation at the individual’s level is influenced by the subjective perception of a pattern, biased by the accumulation of previous personal experiences concerning similar patterns.
Investment NoteValuations3
Stocks aren’t cheap and popular at the same time.
Anonymous.
Robert Shiller is a Nobel laureate and professor in economics at Yale, where he is developing his heterodox theory of “narrative economics”. He largely built his reputation by presciently predicting the bursting of the internet bubble in 2000 and the financial crisis in 2008. In both cases he identified overvaluation as a key contributing factor.
Shiller is also famous for developing the Cyclically Adjusted Price/Earnings ratio, popularly known as CAPE, a valuation tool for equities. Calculated as the price divided by the 10-year average earnings adjusted for inflation, it showed relatively high readings over the last few years. It thus came as a bit of a shock when Shiller announced in early 2021 that “sky high stock prices” actually “make sense” if using a further adjustment to his CAPE indicator. Renamed into “Excess Yield CAPE”, the adjustment consists of inverting the CAPE, which turns it into a yield, and subsequently deducting the 10-year bond yield.
This justification of high stock prices was met, to put it mildly, by surprise from many in the investment community, including Albert Edwards and Jeremy Grantham. The general criticism varied, roughly, from ‘Shiller is changing his narrative’ (pun intended) to ‘Shiller is moving the goal posts’.
So, how should we view this question of valuation? Are stocks fairly valued or in a bubble when using this measure? For clarity, what follows is a discussion of this issue under the conditions that prevailed at the time (2021) and may return in the future.
Stocks are popular …
I like the opening quote (even if we do not know who said it). It combines the issue of valuation with that of crowd psychology. Regarding the latter, seminal works, such as Kindleberger (2011) and Mackay (1841), have identified common characteristics of bubbles, hypes, and manias. Those traits, updated for our modern times (at the time of writing), include:
Central banks making credit easily available, which allows leveraged bets. That includes record volumes of traded call options, often short-dated and on highly speculative stocks.
Growing retail investor participation, now facilitated by user-friendly mobile apps created by zero-commission brokers, often colluding with HFT firms.
Lack of breadth in the market characterised by a concentration in a few stocks or sectors that move broader indices. FANG (Facebook, Amazon, Netflix, and Google) and its variations are the most recent reincarnations of this phenomenon.
A frenzy in IPOs, nowadays involving loss-making companies (including some “unicorns”). Until recently it was accompanied by a craze in Special Purpose Acquisition Companies (SPACs), which are corporate vehicles established to make acquisitions. In crypto space we had Initial Coin Offerings (or ICOs) for funding projects that mostly never materialised.
Narratives and stories whereby popularity is correlated with the level of implied ‘disruption’ or ‘transformation’, not its probability. In other words, the more outrageous the claim, the more popular the theme and the stocks playing it. AI is at risk of joining this.
Exponential price patterns without significant corrections. Examples include semiconductor stocks and Tesla. Anecdotally, the always original Jesse Felder asked rhetorically on Twitter (7 January 2021) what the Scott McNealy of 20 years ago, when he was CEO of internet darling Sun Microsystems and criticised investors for paying high multiples for his company’s stock, would think about Tesla trading at 30 times revenues. He quickly got a response from the real McNealy: “I want to be Elon Musk”.
