My lectures on Behavioural Finance

I’ve just completed second year of my subject Behavioural Finance at the University of Western Sydney. This is of course a non-traditional subject–meaning non-Efficient-Markets-Hypothesis–but even here I take a non-standard approach. While I have great respect for the work of Kahneman and Tversky on behavioural economics, I argue that much of the subsequent work is mis-directed, because of a crucial misinterpretation of the original work on expected utility by von Neumann and Morgenstern.

Much of the standard behavioural finance literature shows that individual behaviour violates the precepts of expected utility theory when faced with a choice between two hypothetical options, and then develops some modified utility function that fits the actual behaviour. The options are normally presented in this manner:

1. Choose between
- A.$1000 with certainty; OR
- B. 90% odds of $2000 & 10% odds of -$1000
2. Choose between
- A. $0 with certainty; OR
- B. 50% odds of $150 and 50% odds of -$100
3. Choose between
- A. -$100 with certainty; OR
- B. 50% odds of $50; 50% odds of -$200

It is alleged that a rational person according to expected utility theory would choose B in all 3 cases, since the expected value of B exceeds A every time. The expected value is calculated simply by multiplying the value of each outcome by the probabilities. Thus the values above are

1. Choose between
- A: $1000
- B. .9 times $2000 + .1 times -$1000 = 1800 — 100 = 1700
2. Choose between
- A. $0
- B. .5 times $150 — .5 times $100 = $75 — 50 = 25
3. Choose between
- A. -$100
- B. .5 times $50 — .5 times $200 = $25 — 100 = -$75

However, when experiments are conducted, the majority of people choose option A in choices 1 and 2, but B in number 3: they are “irrational” twice and rational once. This sets up all sorts of conundrums, leading to a range of interesting problems, and a voluminous literature on irrationality, bounded rationality, risk aversion, preference reversal, and so on. The Wikipedia entry (as at November 11 2010) encapsulates this perspective:

The expected utility hypothesis, as applied to economics, has limited predictive accuracy, simply because in practice, humans do not always behave VNM-rationally. This can be interpreted as evidence that

humans are not always rational, or
VNM-rationality is not an appropriate characterization of rationality, or
some combination of both.

Had von Neumann lived to see the development of this theory, I expect he’d be questioning, not human rationality in general, but the rationality of his interpreters–because his concept of expected utility was very different to how it is now portrayed in the literature. The crucial difference is that the literature uses a subjective vision of probability, when this was explicitly rejected by von Neumann and Morgenstern:

“Probability has often been visualized as a subjective concept more or less inthe nature of estimation. Since we propose to use it in constructing anindividual, numerical estimation of utility, the above view of probability wouldnot serve our purpose. The simplest procedure is, therefore, to insist uponthe alternative, perfectly well founded interpretation of probability as frequency in long runs.” (von Neumann & Morgenstern 1944: 19)

What difference does that make? A lot! Try it with the above three examples: consider exactly the same choices, but with the proviso that whichever option you choose you must repeat 100 times:

1. Choose between
- A. Receiving $1000 with certainty 100 times; OR
- B. 100 gambles with 90% odds of $2000 & 10% odds of -$1000
2. Choose between
- A. Receving $0 with certainty 100 times; OR
- B. 100 gambles with 50% odds of $150 and 50% odds of -$100
3. Choose between
- A. Losing -$100 with certainty 100 times; OR
- B. 100 gambles with 50% odds of $50; 50% odds of -$200

Now there’s no doubt that option B is the rational one. The total values of the options are now:

1.
- A. $100,000
- B. 100 times (.9 times $2000 — .1 times -$1000) = 100 times ($1,800 — $100) = $180,000 — $10,000 = $170,000
2.
- A. $0
- B. 100 times (.5 times $150 — .5 times $100) = 100 times ($75 — $50) = $2,500

A. -$10,000
B. 100 times (.5 times $50 — .5 times -$200) = 100 times ($25 — $100) = -$7,500

Do the sums and you’d have to be irrational (or very bad at arithmetic) to choose A over B.

The difference between the way the literature has interpreted von Neumann and Morgenstern and the way they intended their work to be used is that, in their model, the consumer actually gets the Expected Value of the gamble, because if you take a gamble 100 times, the outcome is very likely to be close to the predicted odds. If on the other hand you undertake a gamble only once, you don’t get the Expected Value: you get either one option or the other, and probability can tell you which is more likely, but it can’t tell you which one you’ll actually get.

Consequently I see much of the behavioural economics & finance literature as interesting, but wrong-headed–and is so often the case in economics, using a definition of “rational” that is seriously irrational. My subject therefore devotes a modicum of time to the standard literature before moving into what I see as a more realistic approach, of considering what the macro behaviour of the finance sector actually is. This leads ultimately to Minsky’s Financial Instability Hypothesis and the “Great Recession”.

All my lectures (in powerpoint format) are linked below, as well as MP3 recordings of the lectures and, in some cases, FLV recordings of my presentation. I had some hardware and software hassles while doing all this; hopefully I’ll be able to post a more complete set of these next year.