0:33

The strategy that I want to talk about right now

Â is based on a concept known as beta.

Â It's about risk.

Â So before getting into the strategy, the paper is titled as Betting Against beta.

Â But before we start the strategy, we have to have some understanding of this beta.

Â 0:53

Beta, beta, whatever, depending on which part of the world you are.

Â In some part of the world, it's known as beta,

Â some parts of the world it's known as beta, whichever, its meaning is the same.

Â 1:07

Now this whole concept of beta came from terms made by

Â financial economist to measure risk, right?

Â So an assumption made in academic finance is that since

Â investors are sufficiently diversified,

Â what really matters is the systemic risk, systematic risk,

Â not individual stock specific risk or idiosyncratic risk.

Â What do I mean by systematic risk and idiosyncratic risk?

Â Let me give you an example.

Â 1:41

The risk of, say inflation.

Â The risk of a recession.

Â Now these are risks which are systematic.

Â That means it is applicable to the entire market.

Â This is not stock specific.

Â Of course, different stocks respond differently to this.

Â I'll come to it in a while.

Â But these are not particular sector specific or

Â stocks specific risk, currency depreciation for example.

Â Whereas think of something happening to a company,

Â some company loosing court case, for example, or CEO death of a company.

Â Now, these are not risks which are applicable to the entire market.

Â These are risks a company faces.

Â These are known idiosyncratic risks.

Â Now, if you think carefully,

Â it's easy to see that idiosyncratic risk can be diversified away.

Â Now, what I do mean by diversifying away idiosyncratic risk?

Â 2:41

Some companies will have negative shocks.

Â Some companies will have positive shocks.

Â In some companies, let's take this cold case, some companies may be losing cases,

Â some companies may be winning cases right.

Â Some industries may face positive price shock,

Â some industries may face negative price shocks, right.

Â So these are shocks, if you're sufficiently diversified,

Â whenever idiosyncratic shocks hit, they cancel out each other.

Â 3:13

Therefore, these for a diversified investor,

Â an investor who holds a diversified portfolio, these do not matter as much.

Â Of course, there are some papers which show that these matter,

Â because investors are not sufficiently diversified.

Â But let's stick to this idea that for a diversified investor,

Â these idiosyncratic risks that impact a particular company or

Â a particular sector, they don't matter as much.

Â What is more important is systematic risks.

Â Now these systematic risks impact the entire market.

Â 4:29

For example, if when the market goes up by 1%,

Â if a particular company's stock goes up on an average by 1.5%,

Â then this particular company has a beta of 1.5.

Â 5:18

Now, can you think of an example?

Â Pause for a while and think.

Â Yes, utilities, utilities have very low betas.

Â 5:40

So now how do you get your betas?

Â It's very simple.

Â Most of companies list their companies' betas are publicly available.

Â You don't have to compute.

Â Anyway, we have given the formula in the slides.

Â But you need not compute.

Â You'll get it publicly.

Â So all that our strategy requires is,

Â the strategy that I'm going to talk right now requires is calculation of this beta.

Â 6:19

Like in the case of all other strategies what we are going to do is

Â first we'll read out the abstract, understand what the strategy is all about.

Â Where it works, where it will not work, and

Â then we'll actually go through the strategy in detail and

Â see what has been the return when our tests are calculated for the first time.

Â And we'll produce some more results that we have calculated ourselves, right?

Â So let's start with the paper.

Â So the paper is titled as Betting Against Beta.

Â So as I've told you, by now you are familiar with the concept of beta.

Â 6:56

This is a paper [COUGH] published,

Â I'm sorry, published in Journal of International Economics.

Â So, this is one of the top journals in finance.

Â So far, we have been talking about strategies

Â which are mostly published in accounting journals.

Â So, even the the Sloan Circular are normally are even the uglier one Perdoski.

Â I hope you guys still remember Perdoski?

Â 7:37

The title of the paper is Betting Against Beta.

Â And the authors are Andrea Frazzini and Pedersen.

Â Pedersen is from NYU.

Â Now when I say this betting again beta,

Â by now you must have some rough idea regarding what I'm going to do.

Â 7:57

So I think it's time that you pause for a while and absorb.

Â So when I say betting against beta, what is likely to come in this strategy?

Â Betting against beta, right?

Â So let me go take you through the abstract.

Â 8:11

We present a model with leverage and

Â margin constraints that vary across investors and time.

Â Now, this is for, again, purely from a trading point of view,

Â you need not worry about this.

Â All that author is saying is they have built a theoretical model as to why

Â their trading strategy works.

Â So, [COUGH] that is not essential for us.

Â Those of you who are interested

Â 8:42

We'll proceed.

Â We find evidence consistent with each of the model's five central predictions.

Â So what they do is that, let me spend [COUGH] spend a few seconds here.

Â They build a model where investors are leveraged, and

Â they have very high constraints.

Â So this model yields five predictions, so we are interested, as trainers,

Â as students of training, we are interested in two of those five predictions.

Â I'll just read out all the five.

Â 9:14

Again, as I've said, if you are interested you can go through them in detail, but

Â we are interested in two of them.

Â So what is the first?

Â First, because constrained investors bid up high-beta assets.

Â So their model says constrained investors bid up high-beta assets.

Â Now why do they do it?

Â I'll talk about the model a little bit because as I've said,

Â here we are not going to mechanically implement reading strategies.

Â This is not a data mining exercise.

Â We are going to tell you economic rational behind strategies,

Â I've been telling this repeatedly.

Â In this paper, in this strategy,

Â we will tell you, in reasonable detail, why this strategy works.

Â So, he gives a hint here.

Â Because constraint investors bid up high beta stock prices.

Â Now, why they bid up is something that we'll see when we see the theory of this.

Â But they bid up for time being assume that

Â high constraint investors bid high beta stock prices up.

Â High beta is associated with low alpha.

Â Now, another term you should know is alpha.

Â I should have told you about this when I described beta.

Â So, alpha is nothing but the extraordinary return that you make.

Â So, there is an expected return, right.

Â So, suppose, let me give you an example.

Â 10:35

Suppose a stock has a beta of say two, right?

Â Expected beta of two, in the past, using past data.

Â Now the market return let's say is 5% for a period.

Â And the risk-free return is, say, 3%.

Â 10:53

Just to give an example, we have already given you the formula,

Â if you remember the formula what is that?

Â Alpha plus, alpha is risk-free return plus market return minus

Â risk free-return into beta, right, that's expected return.

Â Suppose let;s take this example of four marks and

Â expected return For 5%, risk free rate is 3%.

Â So the excess return is 2%, beta is 2,

Â that means you have 4% plus the risk free rate of 2%.

Â So total expected return will be 6%.

Â Now this is expected return but if the stock actually gives

Â a return of 8% then the balance 2% is known as alpha.

Â 11:40

So, that is the alpha that they're talking about.

Â So what they say that because constrained investors bid up stock prices

Â significantly, high beta stocks have lower refund, that's the point.

Â By now you should get hints of what is the trading strategy going to be.

Â 12:17

Now, let's proceed.

Â So they say that because constrained investors bid up high beta assets,

Â high beta is associated with low alpha, as we find empirically for US equities,

Â 20 international equity markets, treasury bonds, corporate bonds, and futures.

Â See they test this strategy or

Â they test this point that high beta stocks are excessively bid up,

Â and hence they have low alphas on not just one asset class,

Â they're tested on many asset class, they're tested on US equities,

Â they're tested on bonds, they're tested on treasury bonds,

Â corporate bonds and also futures, derivative instruments.

Â So therefore, a betting against beta, BAB factor,

Â which is long leveraged low beta assets and short high-beta assets,

Â produces significantly positive risk-adjusted returns.

Â This is the most important thing,

Â entire strategy now is explaining these two lines.

Â They create something known as BAB factor, betting-against-beta factor.

Â What is this?

Â Very simple.

Â Long, low beta stocks, and short high beta stocks.

Â Let me read this once again.

Â Long leverage low beta assets, and short high beta assets.

Â So they go long on low beta assets, and short high beta assets.

Â Why? Because high beta assets had bid up,

Â by these constraining investors and hence their future

Â returns are expected to be low, or alphas are expected to be low.

Â So long, high beta and short low beta.

Â 14:13

When funding constraints tighten, the return of the BAB factor is low.

Â Now when does this strategy work?

Â I've been telling you repeatedly that we are also going to tell you when does each

Â of this strategy work.

Â Here is the answer for this particular strategy.

Â They say that when funding becomes very tight, when constraint tighten,

Â then this strategy does not work.

Â 14:39

More constrained investors hold riskier assets.

Â So this are their predictions from their reference.

Â So we're going to see in detail, when we go further, why this strategy works.

Â And we are also going to implement this strategy and

Â tell you what has been the return in the past.

Â Now, remember, the strategy is very simple.

Â The idea is very simple, that levered investors,

Â constrained investors bid up the stock price of high beta

Â stocks beyond the expected stock price based on fundamentals.

Â And therefore, the expected future returns, abnormal returns,

Â alpha of these stocks are likely to be low.

Â Now, as a trader, as a trader who is there to explore anomalies out there,

Â what one should do is sell such stocks and buys stocks which are low beta.

Â That's all the strategy's all about.

Â We'll get into nuts and bolts of this strategy very soon.

Â