behavioral finance other noise trader models feb 3, 2015 behavioral finance economics 437
TRANSCRIPT
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Behavioral Finance Other Noise Trader Models Feb 3, 2015
Behavioral Finance
Economics 437
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Behavioral Finance Other Noise Trader Models Feb 3, 2015
US Oil Production Doubled in 5 Years
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Behavioral Finance Other Noise Trader Models Feb 3, 2015
What Does Shleifer Accomplish?
Given two assets that are “fundamentally” identical, he shows a logic where the market fails to price them identically Assumes “systematic” noise trader activity Shows conditions that lead to noise traders
actually profiting from their noise trading Shows why arbitrageurs could have trouble
(even when there is no fundamental risk)
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Behavioral Finance Other Noise Trader Models Feb 3, 2015
Are There Other Noise Trader Models? Yes Broadly, two kinds NT models
Momentum models (whatever the stock price has been, it will continue to do
Feedback models (exhibiting the effect of a higher {than efficient} stock price on economic behavior, including work effort, investment, etc.
Problem: most interesting thing is “turning points”; not really addressed well in this literature
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Behavioral Finance Other Noise Trader Models Feb 3, 2015
Choices When Alternatives are Uncertain
Lotteries Choices Among Lotteries Maximize Expected Value Maximize Expected Utility Allais Paradox
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Behavioral Finance Other Noise Trader Models Feb 3, 2015
What happens with uncertainty
Suppose you know all the relevant probabilities
Which do you prefer? 50 % chance of $ 100 or 50 % chance of $
200 25 % chance of $ 800 or 75 % chance of zero
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Behavioral Finance Other Noise Trader Models Feb 3, 2015
Lotteries
A lottery has two things: A set of (dollar) outcomes: X1, X2, X3,…..XN
A set of probabilities: p1, p2, p3,…..pN
X1 with p1
X2 with p2
Etc. p’s are all positive and sum to one (that’s
required for the p’s to be probabilities)
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Behavioral Finance Other Noise Trader Models Feb 3, 2015
For any lottery
We can define “expected value” p1X1 + p2X2 + p3X3 +……..pNXN
But “Bernoulli paradox” is a big, big weakness of using expected value to order lotteries
So, how do we order lotteries?
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Behavioral Finance Other Noise Trader Models Feb 3, 2015
For any two lotteries, calculate Expected Utility II p U(X) + (1 – p) U(Y) q U(S) + (1 – q) U(T)
U(X) is the utility of X when X is known for certain; similar with U(Y), U(S), U(T)
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Behavioral Finance Other Noise Trader Models Feb 3, 2015
Allais Paradox
Choice of lotteries Lottery A: sure $ 1 million Or, Lottery B:
89 % chance of $ 1 million 1 % chance of zero 10 % chance of $ 5 million
Which would you prefer? A or B
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Behavioral Finance Other Noise Trader Models Feb 3, 2015
Now, try this:
Choice of lotteries Lottery C
89 % chance of zero 11 % chance of $ 1 million
Or, Lottery D: 90 % chance of zero 10 % chance of $ 5 million
Which would you prefer? C or D
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Behavioral Finance Other Noise Trader Models Feb 3, 2015
Back to A and B
Choice of lotteries Lottery A: sure $ 1 million Or, Lottery B:
89 % chance of $ 1 million 1 % chance of zero 10 % chance of $ 5 million
If you prefer B to A, then .89 (U ($ 1M)) + .10 (U($ 5M)) > U($ 1 M) Or .10 *U($ 5M) > .11*U($ 1 M)
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Behavioral Finance Other Noise Trader Models Feb 3, 2015
And for C and D
Choice of lotteries Lottery C
89 % chance of zero 11 % chance of $ 1 million
Or, Lottery D: 90 % chance of zero 10 % chance of $ 5 million
If you prefer C to D: Then .10*U($ 5 M) < .11*U($ 1M)
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Behavioral Finance Other Noise Trader Models Feb 3, 2015
So, if you prefer
B to A and C to D It must be the case that:
.10 *U($ 5M) > .11*U($ 1 M)
And
.10*U($ 5 M) < .11*U($ 1M)
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Behavioral Finance Other Noise Trader Models Feb 3, 2015
The End