behavioral finance and this is a term that emerged into public

consciousness around the mid-1990s;

before that it was unknown. The term "efficient markets" is

much older; I mentioned the idea goes back

to the nineteenth century and the term goes back to the 1960s.

But behavioral finance is a newer revolution in finance and

it's something that I have been very involved with.

I have been organizing workshops in behavioral finance

ever since 1991, working with Professor Richard

Thaler at University of Chicago. We've been doing that for

eighteen years; amazing, that's a long time for

you, right? When we started we were total

outcasts, we thought; nobody appreciated us.

I had tenure so I could do it but the problem is,

you don't want to do things that are too out of fashion.

Fortunately, we have a system that allows it

to happen and I'm very happy to have that.

What behavioral finance is a reaction against extreme--some

extremes--that we see in efficient markets theory or also

in mathematical finance. Mathematical finance is a

beautiful structure and I admire what the people have done and

I've worked in it myself, but it has its limits.

Eventually--you know the way a paradigm develops--it goes

through a certain phase. When mathematical finance was

new, say in the 1960s, it was the exciting thing and

nobody wanted to work on anything else;

you wanted to be doing the exciting thing.

As the '70s and '80s wore on, it got to be a little bit

overdone; people run with it too far,

they think that's all we want to do, and we don't want to

think about anything else. Then they start to get

sometimes a little crazy. Than we had to reflect that,

well, things aren't perfect. The world isn't perfect and we

have real people in the world, so that led to the behavioral

finance. Behavioral finance really

means--what does it mean? It's not like behavioral

psychology. It doesn't mean behavioral

psychology applied to finance. It really means something much

more broad than that. It means all of the other

social sciences applied to finance.

The economics department is just one of many departments in

the university that teaches us something about how people

behave, so if we want to understand how

people behave we can't rely only on the economics department.

I think that it's coming around to a unifying of our

understanding. Since then--since the

beginnings in the '90s, our behavioral finance

workshops have grown and grown and,

of course, so many people are involved in it now;

it's now very well-established. Before I get into that,

I want to give some additional reflections on the last lecture.

I have this chart, which you saw last

time--actually it's an Excel spreadsheet that--I also put it

up already on the classes V2 website so you can play with it.

I just want to reflect again--I know I'm repeating myself a

little bit, but it's very important.

What we have in this chart is the blue line,

which is the Standard & Poor Composite Stock Price

Index going back to 1871--from 1871 to 2008,

right now--so that's like 130 years of data.

That's the blue line. You can see the--do you know

what that is there? That's 1929 and that is the

Crash of 1929. Well, actually it extended to

1932 and you can see other historic movements.

There's the bull market of the 1990s--a very big upswing--and

then there's the crash from 2000 to 2003.

I don't know if you remember these things,

they were big news, not as big as the 1929 crash,

but the upswing was just as big as the 1920s upswing,

wasn't it? Here's the 1920s upswing and

here's the 1990s upswing--huge upswing in stock prices.

This is in logs, by the way, so that means that

everything--the same vertical distance refers to the same

percentage change in the price. Then I had, as I said last

period, I have a random walk shown--that's the pink line.

The random walk is generated by the random number generator.

I fixed the random number generator, so I made it truly

normal this time. It slows it down a little bit,

but if you press F9 we get another random walk,

but it's always the same stock price.

This is a random walk with a trend that matches the uptrend

of the stock price. I can press--it kind of looks

similar, doesn't it? It kind of shows that in some

basic sense the stock market and the random walk are the same.

Here we have the crash of--here we have the market peak of 1929

except it turned out in this simulation to have occurred in

1910 or thereabout. Then we have the--that's The

Depression of the '30s except it's not the '30s.

I can just push a button and we get something else.

I find this amusing. I don't know.

Unfortunately, we live through only one of

these in our lifetime. There's a TV show about

parallel universes, right?

What's the name of that show? I can't remember it.

Don't you know this show? Where they go in some kind of

time machine and they emerge in another parallel universe where

history took another course. Well anyway,

these are parallel universes that we see.

In some of these universes, Jeremy Siegel would write his

book, Stocks for the Long Run,

and in some of them he would not because–well,

this one he might not because in this case the stock market

was just declining for the better part of a century.

The thing I don't see in these charts and I think we haven't

captured it perfectly with just the standard random walk is I

don't see any crash as big as the 1929 crash.

It's hard to get them. I keep pushing F9--this just

seems to dominate, right?

There's nothing as big here--press F9 again--you can

keep pushing and pushing, maybe you'll get one but you

have--you get the idea that there's something anomalous

about that crash from the standpoint of this random walk

theory. I'm not getting one, right?

That's something that we'll talk about.

I would--I'm not--I can push for a long time and I don't

see--well there's a pretty big one.

Isn't that just about as--not quite as sharp as the 1929

crash, but it's hard to get them.

I think that one thing–there are a couple

of things that we'll come back to.

One is--I think I've already mentioned it--fat tales.

Stock price movements have a tendency to show some extreme

outliers that are not represented by the normal

distribution. But also, there are variations

in the variance. So, in this period here--in the

'20s and '30s--the stock market was extremely variable on a

day-to-day basis; it was way beyond anything

we've observed since. So, that's why it seems to be

more volatile in that period because the accumulation of

bigger random shocks. Anyway, we can play this game

for a while but now I want to go and talk about--remember that

the random walk that we see in stock prices is not the behavior

of a drunk, even though you can describe a

random walk as drunken behavior. The idea in the theory is that

these movements only appear random because they're news and

news is always unpredictable. If the market is doing the best

job--this is efficient markets--in predicting the

future, that means then that any time

the stock market moves it's because something surprising

happened. Like there might be a new

breakthrough in science or there could be war or something

outside--this is the story--outside of the economic

system that disrupts things. The next question

then–now, I've added something--it's on

this little tab here--I've added something, which is a plot of

present values. This is something that I

published in 1981. That's a long time ago,

isn't it? It was my first big success.

Not everyone liked this article, but what I had--I got

into a lot of trouble for it. I learned some people react

with hostility when you offend their cherished beliefs,

so I was on the outs for a while with this article.

I said, it's kind of interesting to think that all

these apparently random movements are really resulting

in news about something that is fundamental--that's the

efficient markets. Every time the stock market

moves it's because there was some news about what?

Well, it's about present value. The efficient markets theory,

in its simplest incarnation, says that the price is the

expected present value of future dividends.

What I did, in a paper that I published in 1981,

is I said, well let's just plot the present value of dividends

through time. That's how I constructed this

long time series back to 1871; nobody else was looking at it.

Typically, researchers want the best data, the high quality

data, and so they would look at recent data,

which was the best data, and they would think going back

to 1871 is crazy because that's so long ago.

We have daily or minute-by-minute data by now,

but we can't get it for that remote period.

On the one hand, as I argued,

the stock market is pricing things that occur over long

periods of time. The present value formula is

pricing dividends into the future, decades into the

future--well, actually to the infinite

future, but most of the weight is on the next few decades.

So, we can't evaluate the theory by just looking at ten

years of data we've got to get a lot of data.

What I did then in that paper was I computed the actual

present value of subsequent dividends for each year--that's

on this tab--and compared it with the stock price;

so that's what I did. This is an update of a plot

that I showed in my 1981 American Economic Review paper.

The blue line--because when I published it I was right here.

It's amazing how time goes by; it was 1979, I was right here.

We had just come off from the big stock market drop of the--it

was the '73-'75 drop and it was a couple of years later,

so we were kind of bumbling around down here.

We didn't have any idea whether this was coming at the time.

What I did was I just, for each year,

computed the present value of the dividend.

I have a dividend series for every year.

In fact, it's right over here. I have to--this is the data,

so I have the--this is the S&P Price Index monthly,

back to 1871, and here are the dividends they

paid per share every year since 1871.

I just, for each year, I took all subsequent dividends

and I priced them out at the present value formula and I used

the constant discount rate of 6% a year.

So, you see how we get what the present value was.

Of course, there's a problem because we don't know dividends

after 2007 because we don't have data on dividends past then.

But, I just made some assumptions, so the value at the

end is maybe a little bit arbitrary.

It could be dragged up or down if I made a different assumption

about dividends at the end. More or less,

this is going to be what actually the present value of

dividends was over this whole period.

Here's the dilemma--this is what I said in my 1981

article--this is the thing that is supposed to be forecasted.

That's the present value and the blue line is the forecast of

that thing. Then you ask,

does this look like a good forecast?

Were people doing a good job of forecasting the red line with

the blue line? Now, that may be a loaded

question; but, I think that you get the

impression that there's something possibly wrong here

with efficient markets because the red line is just a smooth

growth path like nothing happens to it and yet the stock market

is going up and down all over the place.

It's a little bit like if you had a weather forecaster and

this morning he says, I predict today that the low

today will be -100º and then two days later he

says, I predict that the low today

will be +150º. You would eventually start

concluding that this weather forecaster can't be trusted

because we never get to those temperatures.