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How Neurobiology Can Inform Decision Science: The Case of Trading Skill PROF PETER BOSSAERTS AND DR CARSTEN MURAWSKI THE UNIVERSITY OF MELBOURNE AND THE FLOREY INSTITUTE OF NEUROSCIENCE AND MENTAL HEALTH HTTP://FBE.UNIMELB.EDU.AU/FINANCE/BMMLAB

How Neurobiology can Inform Decision Science: The Case of

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How Neurobiology Can Inform Decision Science: The Case of Trading Skill PROF PETER BOSSAERTS AND DR CARSTEN MURAWSKI THE UNIVERSITY OF MELBOURNE AND THE FLOREY INSTITUTE OF NEUROSCIENCE AND MENTAL HEALTH

HTTP://FBE.UNIMELB.EDU.AU/FINANCE/BMMLAB

NEUROBIOLOGY ALLOWS ONE…

! To make sense of observed behaviour and behavioural heterogeneity

! To understand behaviour beyond AS IF “mental models” (psychology) or “preference models” (economics)

! To identify aspects of behaviour missed in a behaviour-oriented approach

! To formulate more effective interventions, including pharmacological

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Today’s Example

A sensational article about the relation between ability to sense one’s heartbeat and… trading success

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The findings 4

Why does this make sense?

Neurobiology (decision neuroscience/neuroeconomics) provides answers

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Heartbeat detection ability depends on size of a crucial cortical structure, anterior insula

Critchley ea, Nat Neuro 2004.

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Anterior insula is involved in risk prediction

Preuschoff ea, Neuron 2006; J Neurosci 2008

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Professional traders’ heartbeat correlates with risk (volatility)

Lo-Repin, J Cog Neuro 2002

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Anterior insula activates in response to leptokurtic noise

LEPTOKURTOSIS is typical for financial market risk:! Frequent outliers! Many outliers revert >> noise

“It’s all about tail risk” (Morgan Stanley CBOT trader)

D’Acremont ea, Cerebral Cortex 2016

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Leptokurtosis

! Relative to Gaussian distribution, returns are more peaked and have “fat tails”

Under the Gaussian distribution, a daily return of +/–4% is expected to occur only once every 128 years. Over the 25 years displayed here, there were forty-one such outliers!

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(Q Learning)

A robot trained on leptokurtic noise using Q learning/SARSA exhibits same biases as humans! Q learning/SARSA is consistent with neural activation during learning! There is a “flaw” in the algorithm that makes it harder to learn under

leptokurtic noiseHuang ea, in prep.

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Anterior insula activation predicts who will get out of bubble in time

Smith ea, PNAS 2014(Insula Activation based onPreuschoff ea, J Neuro 2008)

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(Who rides bubble? Those with superior Theory of Mind skills)

De Martino ea, Neuron 2013

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Insula shows enhanced activation when there are insiders

Bruguier ea, J Finance 2010

INSULA

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Emotions are necessary for sound financial decision-making

Here: Skin conductance (>> transpiration); NOT heartbeat

Bechara ea, Science 1997

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Do these neurobiological insights help policy?1. The link between heartbeat and trading success is not a fluke

! But effective intervention should not be based on modulating heartbeat!! (Hiring is based on Theory of Mind skills – Bloomberg etc.)

2. Attempts at eliminating emotions could be counter-productive! People on mood stabilisers should be warned that they may make bad financial decisions

! … or, if professional, they should not be allowed to trade

! There is a much under-appreciated link between mental and financial health!

3. Medication aiming at controlling insula activation (e.g., chronic pain) could have detrimental effects on financial decision-making! Likewise: deep brain stimulation

4. Trading biases that seem to be caused by maladaptive emotional responses may emerge because of the way learning is implemented in the brain ! Smart drugs may actually have a beneficial effect because they interfere with those neural

learning processes!

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