The Market Mind Hypothesis, page 62
Information asymmetries. These are situations where one party in an exchange has more information than the other party. Traditional examples include adverse selection and moral hazard, but I would also add modern manifestations like dark pools, private equity and high-frequency-trading (HFT).
To be clear, although differences in market share and information access naturally occur in markets, they do not necessarily need to lead to the extremes mentioned above. The latter are, rather, the consequences of practices that constrain “free markets”, like outright manipulation, misconceived regulation, and lobbied corporatocracy. The problem with a monopoly is not just that it prevents competition and instead maintains the status-quo.80 From a cognitive perspective it also concentrates thinking into an unhealthy narrow-mindedness.
Not surprisingly, many practitioners have always been sceptical about the EMH’s assumptions and apply fundamental, quantitative and technical analysis in an attempt to outperform their markets and/or their peers. Still, in recent years such active investing is slowly being outgrown by so-called passive investing. The latter subscribes to the EMH and suggests to simply “buy the market”. That is, passive investing involves buying an instrument, like an exchange-traded-fund (ETF), that replicates benchmark indices which represent a market, like the S&P500. Such a strategy is price insensitive and does not consider other factors, like value or quality.
How is this relevant in the MMH’s context? As indicated, a potential inefficiency of particular interest for our purposes arises from the distinction between internal and external information. First, if market trades are predominantly (let alone exclusively) based on internal information, e.g. via passive investing, the risk is that the financial economy becomes decoupled from (the reality of) the real economy. Second, most historic prices were set by conscious humans via discretionary trades (see also part C). However, in recent times prices are increasingly set by machines via automated trades whereby humans are no longer aware of those past trades or the prices at which they are executed. It means that, to the extent that prices reflect all investors’ mentality, the level of consciousness ‘in prices’ has been decreasing in relative terms as time moved on. This has implications for policies and strategies which are based on, extrapolate, or otherwise use time series. For example, it adds to arguments about why the whole notion in the REH of a known objective distribution that represents the outcomes of a stable forecasting strategy is misplaced.
Finally, there is another weakness in the EMH that the MMH addresses. Any serious market hypothesis ultimately needs to have a reasonable explanation for the link between price behaviour and brain behaviour.81 The EMH fails in that regard. In particular, the EMH underlines the random nature of prices via its popularised catch phrase of the random walk (e.g. Malkiel, 1973). Consistent with the REH, it explains that this originates from external shocks only, whereby the random arrival of news gets immediately discounted in prices. But it overlooks a likely additional, and possibly more powerful, source contributing to this process, namely the random fluctuations in investor minds. This can be inferred from noise traders and was the focus of our pilot research project, discussed in section 9.2. Beyond noise, human mentality is shaped by nature and nurture, and behavioural finance has only scratched the surface on this.
B4. Behavioural Economics and Evolutionary Rationality
In recent decades behavioural economics (including behavioural finance) has started to challenge the REH and the EMH. It studies their anomalies by investigating how people make decisions in situations where their choices deviate from REH’s rationality. This can be due to cognitive biases, heuristics, emotions, norms, etc. It assumes that people’s choices reflect their preferences and beliefs, but also recognises that those preferences and beliefs may not always be fully rational.
The best-known view in behavioural economics is so-called dual-system or dual-process thinking. This has been popularised especially by Daniel Kahneman (2011) and I discuss it in Appendix A-4. Together with his long-term collaborator, Amos Tversky, Kahneman developed prospect theory which informs much of today’s behavioural economics.
Over time dozens of biases have been identified. Among the most frequently exhibited are (in alphabetical order): anchoring, availability, confirmation, loss aversion, and overconfidence.
An example of an ‘anomalous’ behaviour relevant for our context is herd behaviour.82 This occurs when investors, often driven by uncertainty, seek the comfort of the crowd and replace their own opinions by its consensus, leading to mimicking investment strategies and positioning. Research has shown, for example, that imitation of behaviour impacts the quality (i.e. experience) of human interactions generally. In particular, it increases trust which facilitates trade. In short, imitation increases trust which compensates for uncertainty but raises vulnerability. This behaviour contributes to bubbles and crashes.
Evolutionary rationality challenges both (the rationality assumptions of) mechanical economics and (the dual-process thinking of) standard behavioural economics. It has been popularised especially by Gerd Gigerenzer. Instead of assuming rationality, respectively highlighting biases, it seeks to explain how human decision-making has evolved over time through natural selection. It is based on the idea that the ultimate goal of decision-making is not to maximize (economic) utility but to maximize evolutionary fitness, which is the ability to survive and reproduce in a given environment. Evolutionary rationality considers the fact that humans have evolved to make decisions which are not always optimal from a utility-maximizing standpoint. Humans may prefer high-calorie foods, even if they are unhealthy, because in our evolutionary past, finding high-calorie foods was critical for survival in environments where food was scarce.
In personal correspondence,83 Gigerenzer clarifies the following aspects of his alternative to standard behavioural economics:
The unconscious and the deliberate are assumed to rely on the same processes (that is different from what dual-systems theories assume). If the situation involves uncertainty (as opposed to a small world of risk), that requires the use of heuristics. A heuristic can be modelled as an algorithm, such as a fast-and-frugal tree. Yet the choice of a heuristic requires more, that is, a judgment about what heuristic is likely successful in what situation. This judgment can itself occur deliberately, as when one reflects about whether a condition such as a dominant cue is in place, or whether one should imitate the strategy of a successful person or that of the majority. Most important, under uncertainty, as opposed to risk, there is no optimal procedure, nor an automatic one. Bayes is about small worlds where the complete space of possible actions and their outcomes is known. Outside of small worlds, one cannot construct meaningful subjective probability distributions (Savage 1954, p. 16, said this very clearly, but his followers forget). The adaptive toolbox of heuristics and the concept of ecological rationality (which answers the question what heuristic works in what situation) is a precise model about how people adapt to situations, by trying heuristics, observing their outcomes, and learning what heuristics to use.
There is some evidence that the heuristics animals use are inborn, such as those bees use to find a new nest, or ants use to find a new cavity (e.g. Gigerenzer, 2021). That would be examples for an instinctive use of heuristics. In humans, that is probably the exception. Instead, the unconscious use of heuristics (intuition) is based on experience and learning. What is innate, but also needs to be trained, are the core capacities needed for the implementation of heuristics, such as recognition memory or the ability to imitate (possibly based on mirror neurons). In humans, the term “instinct” is restricted to reflexes (such as blinking) and similar behaviours that need not be learned.
In general, the big misunderstanding in modelling in most of economics and part of the cognitive sciences is that all situations can and should be treated as situations of Knightian risk (or Savage’s small worlds), and thus Subjective Expected Utility Theory (SEUT) and Bayesian updating would be sufficient for normative rationality. Yet most relevant situations involve some degree of Knightian uncertainty (or large worlds), where optimisation is by definition not feasible, and adaptive heuristics are the best we can do. (And can outperform complex procedures in situations of uncertainty: see the bias-variance dilemma in machine learning and the study of ecological rationality). In addition, what is presented like a general theory—SEUT plus Bayes—is actually a narrow theory limited to small worlds, and cannot deal with uncertainty, intractability, and incommensurability. Human’s adaptive toolbox evolved to deal with all these situations.
B5. Economic system
An economic system allocates resources for consumption, production and investment purposes which involves prices that are determined by exchange in markets based on demand and supply. In our case the economic system consists of the combination of the real economy and the financial economy.84 In this section I will further specify this.
In the popular media, ‘the economy’ refers to the so-called ‘real’ economy which is made up of markets in goods and services. The prefix ‘real’ signifies the actual physical production and consumption of these goods and services which involves tangible objects, or real assets—like brick-and-mortar buildings, factories, human bodies, machines, and products. Other physical manifestations of the economy include processes like the transportation and distribution of goods, and the delivery of a service by a human body. The activities in the real economy are often referred to as economic fundamentals.
The ‘financial’ economy, on the other hand, consists of the financial markets,85 including the (shadow) banking system. It determines the (allocation of) investments in the real economy via financial assets86 (or instruments) in the form of securities like bonds, and stocks. Specifically, financial markets facilitate transactions between owners of capital (investors and savers) and users of capital (companies and countries). When investors buy company stocks (sovereign bonds) they can receive money back in the form of dividends (coupons). But these payoffs are in the future and their values are uncertain. So, by buying and selling such financial instruments investors make implicit predictions about a future state of the world, an ‘imagined’ economy. Some elements of those predictions are quantified in forecasts, involving numerous variables as inputs. Regularly perception meets reality. In the case of stocks corporate profits (which fund the dividends) are the main ‘real-economy’ variable that physically (dis)proves those mental forecasts. Nevertheless, as the saying87 goes, markets can remain irrational longer than you and I can remain solvent. Other issues include potential conflicts of interest resulting from a powerful entity trading financial instruments on a commodity while physically producing (or otherwise controlling) that commodity.
Combined, regional real economies and financial markets form the global economic system. Like the human mind~body, it both predicts and acts in its engagement with the wider world. The division of (mental) knowledge, with information inputs and outputs via prices, is thereby more fungible for the coordination of collective behaviour than the division of (physical) labour. I like to say that prices AID, an acronym that stands for the important reflexive cognitive roles they play as shared object~subject of attention: they raise and attract Awareness, they consume and produce Information, and they steer and undergo Discovery. But they can only do so if allowed.
Obviously, humans, with all their bodily and mental capacities, inhabit both the real and the financial economy. They do this individually and as part of a group. This can lead to imbalances. To wit, the respective weights of participation between the real and financial economy differ, not only for each individual but also, often more extremely, between (groups of) individuals. For example, John is poor and has an income of $1,000 per month, whereas James is rich and has $100,000 to spend each month. John participates almost exclusively in the real economy (by consuming, say, 90% vs investing/saving 10%). In contrast, James participates almost fully (90%) in the financial economy, leaving him plenty for consumption. Whereas the real economy has been sluggish, the financial economy has been booming over the past decades with support from central banks. This almost exclusively benefits the wealthy. There, in a nutshell, is the problem of (manipulated) decoupling of the real and financial economies with growing inequality as a consequence, now further exacerbated by the fact that higher inflation negatively impacts lower incomes more. Such inflation can manifest in hidden mode, like ‘shrinkflation’, that consumers may not notice. For example, I took the picture shown in Figure B.1 of two packs of the same brand of toilet rolls that were equally priced in the same supermarket but bought at different times in the same year (you can guess which one was bought last).
Figure B.1: Shrinkflation in toilet rolls.
Talking about central banks, they are among the other entities that exchange with markets. Depending on their mandate, central banks aim to achieve goals related to the real economy (like low unemployment and low but stable inflation) as well as goals related to the financial markets (financial stability). The former are targeted via monetary policies, whereas the latter are targeted via macroprudential policies. The main monetary policy is setting the official interest rate. In many countries the level of these rates came down significantly, sometimes to zero (zero-interest-rate-policy, a.k.a. ZIRP) or even below it (negative-interest-rate-policy, a.k.a. NIRP). Other policies have recently been used, most famously quantitative easing or QE. QE is an asset-purchase program whereby a central bank buys bonds (aimed at lowering longer-term interest rates) and other assets to stimulate the real economy and improve liquidity in the financial economy. Another policy that has become popular is forward guidance whereby the central bank communicates its intentions regarding future interest rate setting to influence expectations. An example of macroprudential policies is the requirement for commercial banks to set aside extra capital as a buffer against risks.
The main tool used in the exchanges that take place in markets (of goods and services, respectively securities) is money. Money is a social construct that performs three functions: a store of value, a measure of value, and a medium of value exchange. Those functions explain what money does, not what it is or what it means. Money has been studied widely, including in philosophy (e.g. Simmel, 1907) and psychology (e.g. Furnham and Argyle, 1998). In today’s modern (fiat) currency system money is credit and has symbolic, but no intrinsic value. It differs from physically based money, like gold. For our purposes, money refers to fiat currencies. Despite legal enforcement it ultimately remains faith/trust-based which makes it vulnerable. As Bagehot (1873, p. 151) pointed out: “The peculiar essence of our financial system is an unprecedented trust between man and man; and when that trust is much weakened by hidden causes, a small accident may greatly hurt it, and a great accident for a moment may almost destroy it”. In fact, there is scant evidence to support the lingering belief that the earliest trade was purely based on barter (see Humphrey, 1985). Rather, gifts and promises to pay for goods and services ‘later’ facilitated such trade (see Davies, 1994; Graeber, 2011; Douglas, 2016, Part III). It was largely a consequence of the so-called “double coincidence of wants”, which creates a gap between demand and supply. This underlines the ancient use of credit/IOU, including letters of exchange, as money. Since the word credit derives from credo, or “I believe”, belief and trust (e.g. ‘creditworthiness’) became the early psychological foundations of trade. The social and symbolic nature of money puts it thus squarely into the domain of complex collective dynamics which emerge over and above that of the individual. Crucially, it plays a central role in closing the explanatory gap of the economic system, as discussed elsewhere in this book. There are various forms of money, the main ones being cash (e.g. coins) and deposits. A recent addition are cryptocurrencies which supposedly offer, in the (in)famous words of bitcoin creator Satoshi Nakamoto, “transactions without relying on trust”.88
Price discovery is the process of finding the price of an asset in a market through exchanges, in all their forms, of buyers and sellers. When a market ‘clears’ at a price it suggests a temporary balance between demand and supply during which an exchange or trade takes place. The topic of (fundamental) value is important but also vast, and I cannot discuss it in too much detail here. Although the EMH argues that the price almost constantly equals the value of an asset, this is not a generally accepted assumption. Value in general is in the eye of the beholder. Appropriately for this book, Carl Menger argued that “value does not exist outside the consciousness of men”. Warren Buffett89 defined it as “the discounted value of the cash that can be taken out of a business during its remaining life”. Furthermore he emphasised that “regardless of price, we have no interest at all in selling any good businesses that Berkshire owns”. Combining these statements leads us to translate the value of a “good” business as the price an investor is willing to pay for its stock with the intention to hold it forever. It also means that the ability to trade, with related issues like liquidity and mood, is crucial as far as the relativity (or elusiveness) of value is concerned.
As mentioned, in financial markets assets are mostly traded on exchanges in the form of financial instruments called securities.90 Securities are contracts embedding rights of ownership to assets, including their cash flows. The funding of such cash flows comes from different sources, depending on the entity that issued the security. A treasury bond is issued by a government and the coupons, as well as the repayment of the principle, are funded, in most cases, by taxes. A stock, on the other hand, is issued by a private company and the related dividends are funded by the earnings the company generates. Most common securities, like bonds and stocks, are so-called cash securities. Another type of securities is called derivatives. These give the holder the obligation (in case of a future) or the right (in case of an option) to buy or sell a cash security or other asset for a pre-determined price at or before a certain date. As their name implies, derivatives subsequently ‘derive’ their value from the value of their underlying securities or assets. Investors buy specific securities because they have beliefs and expectations about their values in the context of (future) states of the world. In other words, their expected pay-offs benefit, respectively offer protection from such states.
