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Learning outcomes.

After watching this video,

you will be able to, one, define an anomaly.

Two list down various market anomalies.

>> So is emergent at this point clearly after many, many,

years of research that, there are several what are known as anomalies.

What are anomalies?

Anomalies have something those are exceptions to the norm.

For example, there is a well known size effect.

What is a size effect?

It simply says that, portfolios of small cap stocks,

that is, smaller company stocks.

And abnormally higher returns than large company stocks, even after.

And this is important.

Even after you control for beta risk,

beta is the cap time data here I'm talking about.

All right, and the graph, which we're showing you, is basically going to exactly

illustrate the fact that small stocks beat large stocks even after accounting for

what we traditionally called risk which is beta, right?

That's one anomaly, the second anomaly, which is very striking,

is the value versus growth anomaly, here the idea is very simple.

Suppose we sort all stocks in the universe,

when I say universe all the stocks in a particular exchange let's say.

And we sort them by the so called Book to Market ratio.

That's simply the book value of equity on the balance sheet,

divided by the market value of the equity.

Which is basically the market price times the number of shares in the market, right.

So you take the book value to the market value,

just think a bit about what this ratio means,

if the book to market ratio is high, in word that the market to book ratio is low.

Which is to say for every dollar of book value the market is

placing a lower market value on your company right?

Typically for growth companies where the book value is likely to be very small,

take a high tech company for example,

the market value is likely to be several times higher than the book value.

Which is to say these growth stocks typically have

very low Book-to-Market ratios.

And value stocks typically have high Book-to-Market ratios.

So somebody did this very simple experiment of sorting every year,

stocks in two value category and growth category.

Basically taking the high book to market stocks calling them value.

Take the low book to market stocks, call them growth and basically let serve

it on a horse race between two portfolios of value and growth.

We start each of them with $100 or rupees or any currency, right?

And let them perform and

observe their performance after the portfolio has been formed.

And you keep doing this, not for one year, but for let us say in this figure of

you're seeing, 22 years of data on US value US growth.

And what do you see?

You see that 100 rupees or 100 dollars in 1973 would

have ended up at about $600 in growth, but

more than triple that, about $2200 in value.

Now what does that tell you?

It tells you that value outperforms growth handsomely,

at this point this is not evidence of inefficiency.

This is simply saying that look,

historically values stocks have performed better than growth stocks.

Now, a natural response as l said before is to say

well if value outperform growth in terms of returns,

it must be that value stocks are somehow riskier than growth stocks.

Now people have tried to measure whether value and

growth stocks are different betas and there is no.

In this diagram for example I'm showing you that in fact if you look at volatility

or the sigma or the standard deviation of the returns of value versus growth.

What you're going to see is that growth is almost certainly almost always,

the higher volatility portfolio compared to value.

This is bizarre for a finance

basically this is telling you that you've picked a bunch of stocks

which are low risk simply based on the label high book to market.

And you can earn more then, the opposite strategy of picking growth stocks.

Now that can be construed as an evidence or

a piece of evidence against efficient market.

Now the other anomaly I wanted to talk about briefly is the idea called momentum.

The basic idea of momentum here is suppose at the beginning of this year

on January 1st I sort all stocks based on the past six months returns.

Easily done, we could easily do it on a computer, very quickly,

and let us say the top decile that is the top 10% of these stocks we start

calling them winners and the bottom 10%, we start calling them losers.

Just labels.

Winners that essentially those who have performed well in the recent past, and

losers, those who have not performed well at all in the last six months.

So what I say I'm going to perform this portfolio of buying

these winners and selling the losers, right?

Now if the market were efficient,

what would we expect the result of this net portfolio over the next month,

three months, six months and one year, the answer is zero.

Because all we have done is we have sorted stocks based on their past returns.

And if markets are deficient, past returns should not help us to predict or

make trading strategies, which are going to inform us about future returns.

But if you look at the graph, what you find is,

the winners continue to outperform, over the next six months or so.

And the losers continue to underperform, over the next six months.

In other words the winner minus loser portfolio makes about 1%.

And this is not trivial number because this is 1% per month.

So 1% per month for free essentially.

So that's a 12% if you include compounding etc.

Now nothing in the nature of efficient market

seems to be able to explain this phenomenon.

So, I've talked about size,

I've talked about book to market, I've talked about momentum, all right.

So, all of these point to one direction which is that