biology of financial market instability

From The New Palgrave Dictionary of Economics, Online Edition, 2016
Back to top


Research in the biology of risk taking is today helping solve a problem identified in 1981 by Robert Shiller. In an influential article criticising the efficient markets hypothesis, Shiller demonstrated that ‘measures of stock price volatility over the past century appear to be far too high – five to thirteen times too high – to be attributed to new information about future real dividends’. His paper has been debated ever since, but if it was pointing out a real phenomenon in 1981 then that point could be made even more forcefully today as the frequency and severity of market bubbles and crashes – in particular the housing bubble of 2002–07 and the credit crisis of 2008–09 – has only increased. How could biology help account for volatility of this magnitude and destructiveness?
Back to top


Back to top


Back to top

Many explanations have been proposed for the cycles of market bubble and crash – psychological herding, Minskean credit cycles etc. – but since the 2008–09 credit crisis a small number of researchers have turned their attention to a relatively under-researched phenomenon: time-varying risk aversion among the financial community. The suggestion here is that traders and investors could become more risk-seeking during a bull market, driving it into a bubble, and more risk-averse during a bear market, pushing it into a crash. In other words, risk preferences could shift pro-cyclically.
These researchers are thus taking issue with one of the most influential principles in economics, which states, in the words of George Stigler and Gary Becker, that ‘one may usefully treat tastes as stable over time’ (Stigler and Becker, 1977). The principle of stable preferences was required in models of rational choice in order to ensure that choices were transitive; and it played an important role in limiting ad hoc explanations at a time when the psychological and physiological mechanisms underpinning economic preferences were not well understood. Today this assumption underlies many influential models of the financial markets. But it may be impairing our ability to understand market cycles; and recent data suggests it may be wrong.
For example, studies based on large databases drawn from brokerage accounts have found that during the housing bubble and credit crisis investors did indeed display pro-cyclical risk preferences (Guiso et al., 2013; Smith and Whitelaw, 2009; Malmendier and Nagel, 2011). Models have also been developed in which risk preferences shift as a function of cycles in the financial markets (Campbell and Cochrane, 1999; Verdelhan, 2010). This growing literature on time-varying risk aversion in the financial community nonetheless leaves open many questions. What behavioural or neurological mechanisms could drive these variations in risk preferences? What is the magnitude of the changes? And crucially, if risk aversion varies, what conclusions can we draw regarding the market’s ability to aggregate information efficiently?
In order to account for financial behaviour that has proved anomalous for existing theory, researchers have recently begun drawing on the protocols and findings of neuroscience, physiology and behavioural medicine. They have, for example, discovered many of the neural mechanisms involved in risk processing (Bossaerts, 2009; Knutson and Bossaerts, 2007; Kuhnen and Knutson, 2005; Preuschoff et al., 2008); in attempts to second-guess competing investors (Bruguier et al., 2010); and in the distortions of judgement evident during bubbles (De Martino et al., 2013). A subset of this research has tried to identify the biological systems that shift risk preferences and thereby destabilise the markets. In what follows we review this subset of research on the biology of shifting risk preferences and financial market instability.

Back to top

The molecule of irrational exuberance

The research on the neurobiology of risk attitudes may be relatively new (Caplin and Schotter, 2008), but it is based on substantial and decades-long research paradigms developed in physiology, neuroscience and behavioural medicine. These sciences have investigated, for example, how our physiology reacts to information and uncertainty (Hennessy and Levine, 1979; Dickerson and Kemeny, 2004; Pfaff, 2006); how uncertain rewards can trigger a dopamine-mediated addiction to risk (Kuhnen and Knutson, 2005; Berridge and Robinson, 1998); how increases in anabolic hormones such as testosterone and growth hormone can increase a person’s confidence and appetite for risk, even to pathological levels (Pope et al., 2000; van Honk et al., 2004; Reavis and Overman, 2001); how chronic stress can alter our memory recall; and foster avoidance behaviour (Korte, 2001; Sapolsky, 2000; Kademian et al., 2005; Arnsten, 2009).
The models developed in this research are today being extended into the financial realm in the hope of providing a scientific explanation for many risk-taking behaviours, ones that currently prove anomalous for existing economic theory (Coates et al., 2010). Important among these is the behaviour that during the internet bubble of the late 1990s came to be known as ‘irrational exuberance’. Investors are said to be exuberant when they chase a bull market, buying more and more shares at ever more lofty evaluations, paying for price earnings multiples that cannot be justified by current earnings; and offering instead an unfounded optimism that the trend will continue indefinitely (Coates, 2012). It is difficult to explain behaviour like this with the axioms of rational choice theory. But an explanation may be found in biology, in a remarkable phenomenon known as the ‘winner effect’. It has been observed in both animals and humans that winning in a competition leads to increased risk-taking, which in turn can lead to further wins.
Biologists have found that an animal winning a competition or a fight for turf is statistically more likely to win the next agonistic encounter (Dugatkin and Druen, 2004). The winner effect has been observed in a large number of species, from fish and reptiles to primates (Chase et al., 1994; Rutte et al., 2006). Studies of the winner effect have controlled for the competing animals’ physical size (or what they term resource holding potential), motivation and aggression (Hurd, 2006; Neat et al., 1998); but even with these controls in place, a pure winner effect emerges, suggesting that winning in itself contributes to future performance (Lehner et al., 2011). Once these empirical findings were established, biologists then began inquiring into the possible mechanism driving winner effects, and many were proposed: observable physical changes in a winning animal, such as increased pheromones, which would deter opponents from escalating new encounters (Rutte et al., 2006); winners revising up their estimates of their own abilities and deciding to escalate encounters (Dugatkin, 1997; Mesterton-Gibbons, 1999); or winners investing more effort in round-robin type competitions because they are closer to an overall victory (Konrad, 2012; Konrad and Kovenock, 2009; Malueg and Yates, 2010).
However, the explanation that has received the most supporting data is one that focuses on the effects of competition on an animal’s anabolic mechanisms (ones that build up tissues such as muscle), in particular on the naturally produced androgen hormone testosterone. Testosterone in an animal rises in anticipation of a competition (Wingfield et al., 1990) and rises still more after a victory (Trainor et al., 2004; Oyegbile and Marler, 2005; Oliveira et al., 2009; Fuxjager et al., 2010, 2011), while falling after a defeat. Elevated levels of testosterone give an animal an edge in competition because it increases the animal’s lean muscle mass, its haemoglobin and hence its blood’s capacity to carry oxygen, as well as its confidence (Boissy and Boissou, 1994) and persistence (Andrew and Rogers, 1972; Archer, 1977). The winner effect may thus be driven by a physiological feedback loop in which winning leads to higher levels of testosterone, which in turn effectively increase the animal’s resources, motivation, aggression and confidence, thereby raising the likelihood of further victories. This reaction may make sense from an evolutionary point of view: the loser of a fight is encouraged to retire into the bushes and nurse his wounds while the winner prepares for new challenges to his recently acquired rank.
Findings from animal studies can be extended to humans only with caution because the effects of physiological changes on our behaviour are mediated by a larger brain. Nonetheless, similar results haves been found in experiments with humans (Gladue et al., 1989). Athletes, for example, experience the same androgenic priming before a sporting contest and a further increase in testosterone after a win, a phenomenon observed for instance in tennis (Bateup et al., 2002) and wrestling (Elias, 1981), as well as more purely cognitive contests such as chess (Mazur et al., 1992). Animals, including humans, harbour within themselves what amounts to a self-doping mechanism, giving them a shot of anabolic steroids when on a winning streak. Indeed it may be to trigger and harness the physiology of the winner effect that leads athletes, without knowing the biology involved, to ‘psych themselves up’ before matches by imagining victory or even by watching videos of previous victories (Carré and Putnam, 2010).
Researchers have imported this biological model into the financial world by testing what they call ‘the financial winner effect’, hypothesising that physiological changes occur in traders and investors when they make above-average profits (Coates and Herbert, 2008). They further extended the model by asking if at some point in the upward spiral of testosterone and victory the testosterone levels could become so elevated that they impair decision-making and risk-taking and lead to irrational exuberance. This extension of the winner effect model is based on a well-established phenomenon in pharmacology known as an inverted U-shaped dose–response curve (Fig. 1). What this means is that at very low levels of most hormones – adrenalin, cortisol, testosterone etc. – we perform badly at cognitive and physical tasks, but as the hormone increases so does our performance, leading to peak performance at the height of this curve. If, however, the hormone continues to rise then it can impair performance. By way of analogy, think, for example, of your morning cup of coffee: the first two cups may waken you and sharpen attention, but after five cups you may have difficulty focusing or even sitting still. You have gone over top of the dose–response curve.
In animals something like this has been observed with testosterone levels: that acute (i.e. moderate and short-lived) increases prove to be a powerful and effective means of empowerment, as in the winner effect; but if they continue to increase may morph effective risk-taking into dangerous behaviour. Animals with highly elevated testosterone tend to fight more, stray into the open more, neglect parenting duties, patrol areas that are too large and lose fat stores. As a result they suffer increased rates of predation and mortality (Beletsky et al., 1995; Dufty, 1989; Marler and Moore, 1988; Wingfield et al., 2001). At sufficiently high levels of testosterone, effective risk taking can morph into ill-considered and fatal risk-taking.
Does something like this mechanism occur in traders and investors? Do risk takers in the financial markets experience a surge of testosterone when they make money, causing them to increase the size of their bets? Could this be the mechanism driving increasing levels of risk-taking during bull markets? Crucially, do the rising levels of testosterone cause traders to cross over the top of the dose–response curve and start placing bets in ever-increasing size with ever worsening risk–reward trade-offs until their bets go wrong and they lose more money than they made on the winning streak that originally fostered their ‘irrational exuberance’?
Support for this hypothesis has come from a number of studies. In one study conducted on a trading floor in the City of London, hormones were sampled from 17 young male traders twice a day for a week and a half (Coates and Herbert, 2008). It was found that these traders did indeed have significantly higher testosterone levels on days when they made an above-average profit. Were the profits causing the hormone change or the hormones causing the profits? The study design featured morning and afternoon sampling so it permitted the further observation that on days of high morning testosterone, the traders enjoyed an afternoon profit that was almost a full standard deviation higher than on ‘low testosterone’ days.
Other studies also looked at androgens and financial risk taking using a different marker of androgen exposure: the ratio of the second to fourth fingers (2D:4D) (Kondo et al., 1997; Malas et al., 2006; Manning et al., 1998). This marker is one of many physical traces left on our bodies by the levels of pre-natal androgen we were exposed to, much as a high-water mark is a trace of flood levels. One study looking at a cohort of 44 traders found that 2D:4D predicted their P&L as well as years of survival in the markets (Coates et al., 2009). Such a pattern in field data is backed up by experiments in the laboratory. In a financially motivated decision-making experiment, it was found that men and women with smaller digit ratios made riskier financial choices, and the effect was identical for men and women (Garbarino et al., 2011).
The findings of these studies present anomalous data for the efficient markets hypothesis. According to strong versions of this hypothesis, the market is random, so no trait, no skill, no training of a trader, not even their IQ, can improve their returns, any more than they could make a person better at tossing dice. But these findings present preliminary data suggesting that the levels of hormones can affect traders’ P&L just as they affect performance among athletes. The question then becomes: how was the elevated testosterone affecting P&L? Was it improving the traders’ judgement? Their ability at predicting the market? Or was it increasing their risk appetite?
One study tried to answer this question (Coates and Page, 2009). The researchers asked: are the androgen levels predicting the traders’ skill as measured by their Sharpe Ratios, i.e., the ratio of their P&L to the variance of their P&L, or their risk? It was found that androgenic effects did not predict Sharpe Ratios but did predict risk, with higher levels of androgen exposure predicting higher levels of risk. Other more pharmacological studies have also found that increasing levels of testosterone increase appetite for risk (Apicella et al., 2014; Booth et al., 1999); and in still others that it encourages participants to choose the high-variance, low expected return decks of cards in the Iowa Gambling Task (Apicella et al., 2008; Pope et al., 2000; Reavis and Overman, 2001; van Honk et al., 2004).
These findings – that testosterone does increase in traders when they experience an above-average P&L, and that testosterone increases risk appetite – suggest that a financial variant of the winner effect could be shifting risk preferences among the financial community during bull markets towards more risk seeking. Testosterone may be the molecule of irrational exuberance.
Back to top

The molecule of irrational pessimism

A different biological mechanism may contribute to the risk aversion that spreads during bear markets, frequently pushing them into a crash, a behaviour that has been termed ‘irrational pessimism’. That mechanism is the stress response.
The stress response is often mistakenly taken to be a predominantly psychological phenomenon: the conscious feeling of being upset because something bad has happened or is expected to happen to you. But the stress response is more accurately understood as a physical preparation for impending movement. As such it includes changes in breathing, heart rate and blood pressure, and increasing levels of the stress hormones adrenalin and cortisol, both produced by the adrenal glands. The stress hormones suppress long-term functions of the body not needed during fight or flight, such as digestion and reproduction, and instead marshal fuel for immediate use: glucose from liver and muscles and, free fatty acids from fat cells. Adrenalin is a protein hormone with a short half-life in the blood (only a few minutes), while cortisol is a steroid hormone which, by triggering gene transcription, can exert long-term changes on almost all tissues of the body and brain.
The effects of cortisol differ dramatically between acute and chronic exposure, and they display the same inverted U-shape dose–response curve as testosterone. Acute stress is a normal part of life, and acute risks can even be enjoyable, as they are when playing sports or trading the markets. Acutely elevated cortisol in the brain interacts with dopamine, also called the pleasure, circuits. Rats will self-stimulate with cortisol. But chronic stress has very different effects, contributing to gastric ulcers, hypertension, immune disorders and blood glucose imbalances; while in the brain chronically elevated cortisol can promote anxiety, depression, learned helplessness, novelty avoidance and ambiguity aversion, and importantly it can affect memory recall, contributing to a selective attention to negative precedents (Erickson et al., 2003; Korte, 2001). A chronically stressed person could therefore become more risk-averse.
Stress hormones, as part of our early warning system of potential threat, are highly sensitive to levels of novelty and uncertainty (Hennessy and Levine, 1979). Novelty and uncertainty are endemic to financial markets. Indeed, the financial markets present a rare venue for researching stress because uncertainty can be measured objectively and accurately using the volatility of the markets. The VIX – an index of implied volatilities on US equities – is often called the Fear Index because it tracks uncertainty and stress in the financial system. In one study it was found that the stress response of traders was sensitively calibrated to levels of uncertainty and volatility in the market (Coates et al., 2008). As both historic and implied volatilities rose in the markets the traders were trading, so too did the levels of the traders’ cortisol. In this trading floor study, it was found that cortisol levels among traders rose 68% over a two-week period as volatility – and hence uncertainty – increased.
This field work raised a crucial question: does the chronic elevation in stress affect the traders’ risk aversion? In a follow-on study conducted in a research hospital, the authors used more a controlled experimental protocol to answer this question (Kandasamy et al., 2014). Using a placebo-controlled double blind crossover protocol, the authors raised pharmacologically the cortisol levels in volunteers a similar 68% over an eight-day period, to replicate the cortisol levels observed in the trader study; and through a computerised risk-taking task (implementing the Hey and Orme (1994) protocol to study risk preferences) it measured the utility and probability weighting functions underlying the participants’ risk preferences. It was found that in response to the chronic increase in cortisol the participants risk aversion increased 44%. This was a large effect; and the conclusion suggested by the study is that risk preferences in the financial community are highly sensitive to sustained increases in volatility. Similarly, Cohn et al. (2015) show that simply priming traders with a situation of financial crisis leads them to be more risk-averse. The authors interpret such changes as being driven by physiology. Indeed it may have been this very physiological mechanism that contributed to the ‘irrational pessimism’ that afflicted the markets during the credit crisis of 2008–09, a period when implied volatilities rose to historically high levels.
Research into the physiological influences on financial market instability is in its infancy, but the research surveyed here suggests a new picture of financial risk-taking which departs from the assumption of stable risk preferences (Pearson and Schipper, 2013). Risk-taking behaviour changes with alterations in our physiology; and our physiology is designed to sensitively calibrate our risk-taking to the amount of opportunity, uncertainty and threat in our environment. If the apparent opportunities of a bull market cause our endocrine systems to encourage more risk-seeking then, bull markets may segue into bubbles; and if the heightened uncertainty and losses of a bear market trigger a chronic stress response and promote risk aversion, then a bear market may spiral into a crash (Coates, 2012; Coates and Herbert, 2008).
Back to top


In his address to the 2015 American Economic Association meeting, Olivier Blanchard pointed out that one of the key insights from the credit crisis was the existence of ‘dark corners’ where feedback loops lead traditional linear macro models to fail. He encouraged researchers to investigate macro-finance models which accommodate such feedback loops. A key feature of the research on the biology of risk-taking is that it indeed supports self-reinforcing market dynamics (Fig. 2).
Recognising that biologically mediated shifts in risk preference can destabilise markets permits us to suggest novel policies for stabilising them. Market stability is served by having a diversity of opinions; and it may be served as well by having biological diversity among the traders and investors managing the world’s wealth. How is this achieved? Androgens such as testosterone are higher in men than women (about five to ten times higher); and testosterone follows a pattern over the course of a man’s life, rising to a peak in his 20s and falling thereafter, quite rapidly after the age of 50. If bull markets segue into bubbles partly due to rising androgen levels among the financial community, then perhaps bubbles are a young male phenomenon. And if so, then perhaps bull markets could be tamed if we had more women and older men managing money, because they may be less susceptible to the winner effect. Markets during crises could similarly benefit from having more women because their stress response differs from men. Women have stress hormones as high and as volatile as men, but research has found that their cortisol levels are less reactive to stressors stemming from a competitive situation (Stroud et al., 2002). They may thus be less susceptible to the spikes in risk aversion that help drive a bear market into a crash.
Keynes long ago invoked the notion of animal spirits to explain what we now call irrational exuberance and pessimism. Akerlof and Shiller (2010) have pointed out that the study of these animal spirits has been wrongly expelled from the study of economic phenomena. With the tools of biology and neuroscience, economists are now able to open the black box of these animal spirits, taking a first step towards taming them.
Back to top


Akerlof, G. A. and Shiller, R. J. 2010. Animal Spirits: How Human Psycholsogy Drives the Economy, and Why it Matters for Global Capitalism. Princeton University Press, Princeton.

Andrew, R. and Rogers, L. 1972. Testosterone, search behaviour and persistence. Nature, 237, 343–6.

Apicella, C. L., Dreber, A., Campbell, B., Gray, P. B., Hoffman, M. and Little, A. 2008. Testosterone and financial risk preferences. Evolution and Human Behavior, 29(6), 384–90.

Apicella, C. L., Dreber, A. and Mollerstrom, J. 2014. Salivary testosterone change following monetary wins and losses predicts future financial risk-taking. Psychoneuroendocrinology, 39, 58–64.

Archer, J. 1977. Testosterone and persistence in mice. Animal Behaviour, 25(2), 479–88.

Arnsten, A. F. T. 2009. Stress signalling pathways that impair prefrontal cortex structure and function. Nature Reviews Neuroscience, 10(6), 410–22.

Bateup, H. S., Booth, A., Shirtcliff, E. A. and Granger, D. A. 2002. Testosterone, cortisol, and women's competition. Evolution and Human Behavior, 23(3), 181–92.

Beletsky, L. D., Gori, D. F., Freeman, S. and Wingfield, J. C. 1995. Testosterone and polygyny in birds. Current Ornithology, 12, 1–41.

Berridge, K. C. and Robinson, T. E. 1998. What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience? Brain Research Reviews, 28(3), 309–69.

Boissy, A. and Bouissou, M. 1994. Effects of androgen treatment on behavioral and physiological responses of heifers to fear-eliciting situations. Hormones and Behavior, 28(1), 66–83.

Booth, A., Johnson, D. R. and Granger, D. A. 1999. Testosterone and men's health. Journal of Behavioral Medicine, 22(1), 1–19.

Bossaerts, P. 2009. What decision neuroscience teaches us about financial decision making. Annual Review of Finance and Economics, 1(1), 383–404.

Bruguier, A. J., Quartz, S. R. and Bossaerts, P. 2010. Exploring the nature of ‘trader intuition’. Journal of Finance, 65(5), 1703–23.

Campbell, J. Y. and Cochrane, J. H. 1999. By force of habit: a consumption-based explanation of aggregate stock market behavior. Journal of Political Economy, 107(2), 205–51.

Caplin, A. and Schotter, A. 2008. The Foundations of Positive and Normative Economics: a Handbook. Oxford University Press, Oxford.

Carré, J. M. and Putnam, S. K. 2010. Watching a previous victory produces an increase in testosterone among elite hockey players. Psychoneuroendocrinology, 35(3), 475–9.

Chase, I. D., Bartolomeo, C. and Dugatkin, L. A. 1994. Aggressive interactions and inter-contest interval: how long do winners keep winning? Animal Behaviour, 48(2), 393–400.

Coates, J. M. 2012. The Hour Between Dog and Wolf: How Risk-Taking Transforms Us, Body and Mind. Penguin-Random House, New York.

Coates, J. M. and Herbert, J. 2008. Endogenous steroids and financial risk taking on a London trading floor. Proceedings of the National Academy of Sciences, 105(16), 6167–72.

Coates, J. M. and Page, L. 2009. A note on trader Sharpe Ratios. PloS one, 4(11), e8036.

Coates, J. M., Gurnell, M. and Rustichini, A. 2009. Second-to-fourth digit ratio predicts success among high-frequency financial traders. Proceedings of the National Academy of Sciences, 106(2), 623–8.

Coates, J. M., Gurnell, M. and Sarnyai, Z. 2010. From molecule to market: steroid hormones and financial risk-taking. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 365(1538), 331–43.

Cohn, A., Engelmann, J., Fehr, E. and Maréchal, M. A. 2015. Evidence for countercyclical risk aversion: an experiment with financial professionals. American Economic Review, 105(2), 860–85.

De Martino, B., O’Doherty, J. P., Ray, D., Bossaerts, P. and Camerer, C. 2013. In the mind of the market: theory of mind biases value computation during financial bubbles. Neuron, 79(6), 1222–31.

Dickerson, S. S. and Kemeny, M. E. 2004. Acute stressors and cortisol responses: a theoretical integration and synthesis of laboratory research. Psychological Bulletin, 130(3), 355–91.

Dufty, A. M. 1989. Testosterone and survival: a cost of aggressiveness? Hormones and Behavior, 23(2), 185–93.

Dugatkin, L. A. 1997. Winner and loser effects and the structure of dominance hierarchies. Behavioral Ecology, 8(6), 583–7.

Dugatkin, L. A. and Druen, M. 2004. The social implications of winner and loser effects.Proceedings of the Royal Society of London. Series B: Biological Sciences, 271(Suppl 6), S488–S489.

Elias, M. 1981. Serum cortisol, testosterone, and testosterone-binding globulin responses to competitive fighting in human males. Aggressive Behavior, 7(3), 215–24.

Erickson, K., Drevets, W. and Schulkin, J. 2003. Glucocorticoid regulation of diverse cognitive functions in normal and pathological emotional states. Neuroscience & Biobehavioral Reviews, 27(3), 233–46.

Fuxjager, M. J., Forbes-Lorman, R. M., Coss, D. J., Auger, C. J., Auger. A. P. and Marler, C. A. 2010. Winning territorial disputes selectively enhances androgen sensitivity in neural pathways related to motivation and social aggression. Proceedings of the National Academy of Sciences, 107(27), 12393–8.

Fuxjager, M. J., Oyegbile, T. O. and Marler, C. A. 2011. Independent and additive contributions of postvictory testosterone and social experience to the development of the winner effect. Endocrinology, 152(9), 3422–9.

Garbarino, E., Slonim, R. and Sydnor, J. 2011. Digit ratios (2D:4D) as predictors of risky decision making for both sexes. Journal of Risk and Uncertainty, 42(1), 1–26.

Gladue, B. A., Boechler, M. and McCaul, K. D. 1989. Hormonal response to competition in human males. Aggressive Behavior, 15(6), 409–22.

Guiso, L., Sapienza, P. and Zingales, L. 2013. Time Varying Risk Aversion. National Bureau of Economic Research, Cambridge MA.

Hennessy, J. W. and Levine, S. 1979. Stress, arousal, and the pituitary-adrenal system: a psychoendocrine hypothesis. Progress in Psychobiology and Physiological Psychology, 8, 133–78.

Hey, J. D. and Orme, C. 1994. Investigating generalizations of expected utility theory using experimental data. Econometrica, 62(6), 1291–326.

Hurd, P. L. 2006. Resource holding potential, subjective resource value, and game theoretical models of aggressiveness signalling. Journal of Theoretical Biology, 241(3), 639–48.

Kademian, S. M., Bignante, A. E., Lardone, P., McEwen, B. S. and Volosin, M. 2005. Biphasic effects of adrenal steroids on learned helplessness behavior induced by inescapable shock. Neuropsychopharmacology, 30(1), 58–66.

Kandasamy, N., Hardy, B., Page, L., Schaffner, M., Graggaber, J., Powlson, A. S., Fletcher, P. C., Gurnell, M. and Coates, J. 2014. Cortisol shifts financial risk preferences. Proceedings of the National Academy of Sciences, 111(9), 3608–13.

Knutson, B. and Bossaerts, P. 2007. Neural antecedents of financial decisions. Journal of Neuroscience, 27(31), 8174–7.

Kondo, T., Zákány, J., Innis, J. W. and Duboule, D. 1997. Of fingers, toes and penises. Nature, 390(6655), 29.

Konrad, K. A. 2012. Dynamic contests and the discouragement effect. Revue d'Économie Politique, 122(2), 233–56.

Konrad, K. A. and Kovenock, D. 2009. Multi-battle contests. Games and Economic Behavior, 66(1), 256–74.

Korte, S. M. 2001. Corticosteroids in relation to fear, anxiety and psychopathology. Neuroscience and Biobehavioral Reviews, 25(2), 117–42.

Kuhnen, C. M. and Knutson, B. 2005. The neural basis of financial risk taking. Neuron, 47(5), 763–70.

Lehner, S. R., Rutte, C. and Taborsky, M. 2011. Rats benefit from winner and loser effects. Ethology, 117(11), 949–60.

Malas, M. A., Dogan, S., Evcil, E. H. and Desdicioglu, K. 2006. Fetal development of the hand, digits and digit ratio (2D: 4D). Early Human Development, 82(7), 469–75.

Malmendier, U. and Nagel, S. 2011. Depression babies: do macroeconomic experiences affect risk taking? Quarterly Journal of Economics, 126(1), 373–416.

Malueg, D. A. and Yates, A. J. 2010. Testing contest theory: evidence from best-of-three tennis matches. Review of Economics and Statistics, 92(3), 689–92.

Manning, J. T., Scutt, D., Wilson, J. and Lewis-Jones, D. I. 1998. The ratio of 2nd to 4th digit length: a predictor of sperm numbers and concentrations of testosterone, luteinizing hormone and oestrogen. Human Reproduction, 13(11), 3000–4.

Marler, C. and Moore, M. 1988. Evolutionary costs of aggression revealed by testosterone manipulations in free-living male lizards. Behavioral Ecology and Sociobiology, 23(1), 21–6.

Mazur, A., Booth, A. and Dabbs, J. M. Jr, 1992. Testosterone and chess competition. Social Psychology Quarterly, 55, 70–7.

Mesterton-Gibbons, M. 1999. On the evolution of pure winner and loser effects: a game-theoretic model. Bulletin of Mathematical Biology, 61(6), 1151–86.

Neat, F. C., Huntingford, F. A. and Beveridge, M. M. C. 1998. Fighting and assessment in male cichlid fish: the effects of asymmetries in gonadal state and body size. Animal Behaviour, 55(4), 883–91.

Oliveira, R. F., Silva, A. and Canário, A. V. 2009. Why do winners keep winning? Androgen mediation of winner but not loser effects in cichlid fish. Proceedings of the Royal Society B: Biological Sciences, 276(1665), 2249–56.

Oyegbile, T. O. and Marler, C. A. 2005. Winning fights elevates testosterone levels in California mice and enhances future ability to win fights. Hormones and Behavior, 48(3), 259–67.

Pearson, M. and Schipper, B. C. 2013. Menstrual cycle and competitive bidding. Games and Economic Behavior, 78, 1–20.

Pfaff, D. W. 2006. Brain Arousal and Information Theory. Harvard University Press, Harvard.

Pope, H. G., Kouri, E. M. and Hudson, J. I. 2000. Effects of supraphysiologic doses of testosterone on mood and aggression in normal men: a randomized controlled trial. Archives of General Psychiatry, 57(2), 133–40.

Preuschoff, K., Quartz, S. R. and Bossaerts, P. 2008. Human insula activation reflects risk prediction errors as well as risk. Journal of Neuroscience, 28(11), 2745–52.

Reavis, R. and Overman, W. H. 2001. Adult sex differences on a decision-making task previously shown to depend on the orbital prefrontal cortex. Behavioral Neuroscience, 115(1), 196–206.

Rutte, C., Taborsky, M. and Brinkhof, M. W. 2006. What sets the odds of winning and losing? Trends in Ecology & Evolution, 21(1), 16–21.

Sapolsky, R. M. 2000. Glucocorticoids and hippocampal atrophy in neuropsychiatric disorders. Archives of General Psychiatry, 57(10), 925–35.

Smith, D. R. and Whitelaw, R. F. 2009. Time-Varying Risk Aversion and the Risk–Return Relation. NYU Stern School of Business Working Paper.

Stigler, G. J. and Becker, G. S. 1977. De gustibus non est disputandum. American Economic Review, 67(2), 76–90.

Stroud, L. R., Salovey, P. and Epel, E. S. 2002. Sex differences in stress responses: social rejection versus achievement stress. Biological Psychiatry, 52(4), 318–27.

Trainor, B. C., Bird, I. M. and Marler, C. A. 2004. Opposing hormonal mechanisms of aggression revealed through short-lived testosterone manipulations and multiple winning experiences. Hormones and Behavior, 45(2), 115–21.

van Honk, J., Schutter, D. J. L. G., Hermans, E. J., Putman, P., Tuiten, A. and Koppeschaar, H. 2004. Testosterone shifts the balance between sensitivity for punishment and reward in healthy young women. Psychoneuroendocrinology, 29(7), 937–43.

Verdelhan, A. 2010. A habit‐based explanation of the exchange rate risk premium. Journal of Finance, 65(1), 123–46.

Wingfield, J., Hegner, R., Dufty, A. M. and Ball, G. F. 1990. The ‘challenge hypothesis’: theoretical implications for patterns of testosterone secretion, mating systems, and breeding strategies. American Naturalist, 136, 829–46.

Wingfield, J. C., Lynn, S. and Soma, K. K. 2001. Avoiding the ‘costs’ of testosterone: ecological bases of hormone-behavior interactions. Brain, Behavior and Evolution, 57(5), 239–51.

Back to top

How to cite this article

Coates, John and Lionel Page. "biology of financial market instability." The New Palgrave Dictionary of Economics. Online Edition. Eds. Steven N. Durlauf and Lawrence E. Blume. Palgrave Macmillan, 2016. The New Palgrave Dictionary of Economics Online. Palgrave Macmillan. 30 April 2016 <> doi:10.1057/9780230226203.3957

Download Citation:

as RIS | as text | as CSV | as BibTex