Fischer Black famously stated that “noisy trading puts noise into the prices" (1986, p. 532). Our pilot project links the topic of noise trading in finance to the topic of neural noise in cognitive science. Specifically, using high-frequency data we look for an alternative explanation for the origin of excess volatility, derived from a phenomenon that can be observed in brain research called the readiness potential (RP).
Active investors and behavioural academics question the Efficient Market Hypothesis (EMH), in particular its emphasis on the randomness in prices. However, what all critics of EMH have overlooked is, ironically, something EMH itself also has ignored: the possible link between accumulating randomness in traders’ brains and accumulating randomness in prices, as well as the (anomalous) patterns it may result in.
Although all investors experience build-up of noisy neuronal activity within their decision-making to some extent, this phenomenon is particularly applicable to noise traders. It is due to their focus on non-fundamental/intra-market data and extrapolation tendencies which makes them especially susceptible to the build-up of neural noise.
RP refers to a build-up of brain activity ahead of an event, e.g. a movement or decision. The decades-long consensus interpretation of RP, the so-called Libet interpretation, was recently challenged. In particular, rather than some preconscious preparation and planning ahead of a decision, the precise moment at which the decision threshold is crossed leading to movement is largely determined by spontaneous subthreshold fluctuations in neuronal activity. Not only does a gradual increase in neural activity preceding spontaneous movements occur in both vertebrates and invertebrates. Also, the general pattern of noisy build-up ahead of events seems to be a common phenomenon that can be observed in other domains, like weather.
Our intention is to follow-up the pilot project by more extensive projects, one of which involves real traders who will be monitored via eye-scanners, and possibly EEG, in their live trading environment.
For this pilot project the key question is how noisy prices relate to noisy neurons. In a broader context, and inspired by Hayek, Soros, and others, our research is driven by the following question: how are markets and minds related?
The individual human mind is a complex adaptive system and its interaction with similar systems can give rise to a collective consciousness. The latter is manifested in capital markets, the composite of which investors call “the market” or “Mr. Market”. In simple terms, the Market Mind Hypothesis (MMH) tries to formalise what investors casually refer to as “the market’s mind”. That includes its relationship to the real (‘physical’) economy which showed a dangerous tail-wagging-the-dog dynamic during the global financial crisis. In more technical terms it states that the market, embodying numerous interacting investors and their technologies, intersubjectively extends their minds, thereby manifesting collective consciousness. A particularly vivid manifestation of this is market mood which can have a profound impact on investors. In the words of George Soros, “markets are not supposed to have moods . . . Yet, they do” (2009).
The market facilitates the most efficient allocation of society’s resources, a problem which cannot be solved by any central planner. In other words, like the mind there is no place for a omniscient homunculus (nor demon, for that matter) in markets. Price discovery, the self-organizing process in capital markets aimed at value creation, is society’s psychophysical bridging. Although it forms a reflexive loop, viewed in one direction society’s chain of discovery starts with insights in individual minds. Sometimes involving an interim step (e.g. inventions), they are then shared and turn into innovation (e.g. technology) in the real economy. Finally, this culminates in their valuation via price discovery in markets. Prices are discovered symbols which capture the information that is realised both physically and phenomenally.
Overall, MMH challenges mainstream economics. Its broader context involves ontology, epistemology, metaphysics, and the general mind-matter issues involved in economics. In particular, we view the economic system from a cognitive (‘mind-body’) perspective, rather than the dominant, but flawed, mechanical (‘machine’) perspective. We build on support (and look for insights) from major cognitive theories, including the Extended Mind Theory, the Global Workspace Theory, the Integrated Information Theory, and Predictive Processing.
Our research is relevant because the key lesson from the collapse of Lehman Brothers in 2008, namely that it was a reality check, has unfortunately not been learned. Specifically, although some (e.g. Akerlof and Shiller, 2009) correctly identified the key issue of mental causation, economics is largely ignorant about such cognitive complexity. Also, limited progress has been made in understanding market mood, as recently admitted by the Chairman of the Federal Reserve, Jerome Powell: “The linkages among monetary policy, asset prices, and the mood of global financial markets are not fully understood” (2018).
More than a decade ago we came close to financial Armageddon. Signs that some dangerous pre-crisis behaviour is reappearing speak to the urgency to seek explanations, including for spontaneous, particularly volatile, market moves. Among others, the insights from our research can potentially guide practitioners, policy makers and regulators to take precautionary measures to prevent such events.
This pilot project is supported by Eidyn/PPLS and a pilot grant from the Edinburgh Futures Institute. Ths project is also a collaboration with the Centre for Cognitive Science (COGS), University of Sussex.
- Prof Ron Chrisley (cognitive science; Director of Centre for Cognitive Science (COGS), University of Sussex).
- Prof Andy Clark (philosophy, cognitive science, University of Sussex).
- Dr. Marian Gatzweiler (management, business; University of Edinburgh).
- Dr. Robin Hill (cognitive science, informatics; University of Edinburgh).
- Prof. Duncan Pritchard (philosophy, cognitive science; Director of Eidyn Research Centre, University of Edinburgh).
- Dr. Patrick Schotanus (finance, investment, cognitive science).
- Dr. Aaron Schurger (neuroscience; INSERM, France).
- Dr. Dave Ward (philosophy, cognitive science; University of Edinburgh).