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BEHAVIOURAL RESEARCH Trust, News and the Efficient Markets Hypothesis Fairness, Trust and Emotions 1 July 2010 Behavioural Finance Working Group Cass Business.

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Presentation on theme: "BEHAVIOURAL RESEARCH Trust, News and the Efficient Markets Hypothesis Fairness, Trust and Emotions 1 July 2010 Behavioural Finance Working Group Cass Business."— Presentation transcript:

1 BEHAVIOURAL RESEARCH Trust, News and the Efficient Markets Hypothesis Fairness, Trust and Emotions 1 July 2010 Behavioural Finance Working Group Cass Business School

2 Efficient markets hypothesis Bachelier (1900), Samuelson (1965), Fama (1970) Prices in an efficient market reflect all publicly available information In strong form, prices reflect all information So what is information?

3 What is information? Is this information? – “IBM profits in 2011 will be $15.1 billion” How about this: – “General Electric’s profits in 2006 were $20.9 billion” That was “information” until profits were restated It depends on the source...

4 An extended model of information We model beliefs instead of information A belief: – is held by an agent – has a source – expresses the relative value of two goods (typically money and a financial instrument) – has a confidence level

5 For instance Jim Cramer told me that Intel stock is worth $28 I place a confidence level of 5% in this belief

6 On the other hand... Google Finance tells me that Intel stock is worth $21.22 I place a confidence level of 70% in this belief

7 How do I integrate these beliefs? I could just weight the confidence levels and produce an average valuation Or I could go with the most trusted source Other integration functions are available

8 Confidence-weighted integration Leads to smooth behaviour Small changes in trust or value result in small changes in price

9 Most-trusted integration Leads to volatility A small change in trust can result in a big jump in valuation

10 Simulation 1 Integration by weighted probability

11 Simulation 2 Integration by most trusted source

12 Manipulation test We specified one agent as a “promoter” of a higher price We give them a one-off boost of 0.05 to trust, representing an investment in their reputation Average price of stock is increased by 16% In many plausible scenarios it is more worthwhile to invest in reputation than in fundamentals

13 Other variations in model Trust in some agents depends on trust in other agents – Leads to extreme volatility Merged integration functions – Leads to more realistic medium volatility

14 So what? Regulators ought to be aware of the value of manipulating trust Model implies that agents will overinvest in the structures of the market itself compared with investment in productive assets Future research directions: – Multi-good markets – Inference of beliefs from market prices


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