0:00

[MUSIC]

Â Learning outcomes.

Â After watching this video,

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

Â Two list down various market anomalies.

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

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

Â What are anomalies?

Â Anomalies have something those are exceptions to the norm.

Â For example, there is a well known size effect.

Â What is a size effect?

Â It simply says that, portfolios of small cap stocks,

Â that is, smaller company stocks.

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

Â And this is important.

Â Even after you control for beta risk,

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

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

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

Â what we traditionally called risk which is beta, right?

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

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

Â Suppose we sort all stocks in the universe,

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

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

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

Â divided by the market value of the equity.

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

Â So you take the book value to the market value,

Â just think a bit about what this ratio means,

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

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

Â placing a lower market value on your company right?

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

Â take a high tech company for example,

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

Â Which is to say these growth stocks typically have

Â very low Book-to-Market ratios.

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

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

Â stocks in two value category and growth category.

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

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

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

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

Â And let them perform and

Â observe their performance after the portfolio has been formed.

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

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

Â And what do you see?

Â You see that 100 rupees or 100 dollars in 1973 would

Â have ended up at about $600 in growth, but

Â more than triple that, about $2200 in value.

Â Now what does that tell you?

Â It tells you that value outperforms growth handsomely,

Â at this point this is not evidence of inefficiency.

Â This is simply saying that look,

Â historically values stocks have performed better than growth stocks.

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

Â well if value outperform growth in terms of returns,

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

Â Now people have tried to measure whether value and

Â growth stocks are different betas and there is no.

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

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

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

Â the higher volatility portfolio compared to value.

Â This is bizarre for a finance

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

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

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

Â Now that can be construed as an evidence or

Â a piece of evidence against efficient market.

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

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

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

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

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

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

Â Just labels.

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

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

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

Â these winners and selling the losers, right?

Â Now if the market were efficient,

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

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

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

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

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

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

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

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

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

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

Â So 1% per month for free essentially.

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

Â Now nothing in the nature of efficient market

Â seems to be able to explain this phenomenon.

Â So, I've talked about size,

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

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

Â