[MUSIC] Learning outcomes. After watching this video you will be able to understand the concept of capital asset pricing model. [MUSIC] >> Okay, so now you understand the concept of beta. Now, how would this apply to us at pricing. I think we need to spend a couple of minutes on that before we do the strategy of betting against beta. Basically there is something called a Capital Asset Pricing Model, the formula is like this. Our expected return of a stock is RF, I'll tell you what these terms are, RM minus RF into beta. Now, expected return of a stock is, remember this, if you are holding a diversified portfolio, then your idiosyncratic risk does not matter. Any risk which is company specific, such risks don't matter at all. Right? So if you are concerned only about return, return is the only thing that comes from pricing, so your expected return is a function of your systematic risk. How risky you are compared to the market. So every investment should compensate you for taking risks. Risk-free return is something that you can make from investing in a treasury security. At least for domestic investor, a government never defaults, so technically, it is risk free. So that is why your expected return is at least this much plus the excess return that market makes, all risk free return times theta. So this is the excess return the market makes what is risk free return and this is the sensitivity. So, let's take the case, suppose the risk free return is 3% and the market return let's say at the time is 5%, risk free return is again 3%. And if our stock's beta is let's say 1.2. Now, what is the expected return of this stock? Very simple. 3%, 5 over 2. Two times 1.2, 2.4. 3% plus 2.4% equal to 5.4%. This is what? CAPM will tell you. So if you want to invest in this particular company, your average investor, or diversified investor would expect 5.4% return. Now what does this mean? Does this mean that you will always make 5.4% return by investing in this? No, not at all. This is only a benchmark. So let me tell you some downsides of this. While it sounds very beautiful and the formula is nice and it's easy to calculate and so on and so forth, in reality there is a major issue. It's very hard to calculate vita. See how did this 1.2? What you would have done is. Taken some past returns of market and past return of the stock and arrived at the sensitivity. The problem is future is never as same as the past. Future is always different. There is some unforeseen thing can happen. Nature of business can change. A lot of things can change. You don't need convincing in a dynamic world like the ones that we are living in. And that future is one way different from past. Nobody needs convincing on that. So this number, historical number that you arrive at may not be accurate. So taking this return too seriously, may be risky. While it's useful as a useful benchmark to start with but taking it too seriously is risky. All that it can help us is categorizing stocks into various buckets. Something which has a 5 beta, maybe it's safe to say that it's more risky compared to a stock with one bid offer, say. To that extent it's useful. But can you really distinguish between 1.25 and 1.24? Probably not. Or even 1.2 and 1.3? Probably not. In the next bid, the 1.2 stock may turn out to be more risky than the 1.3 stock. So you have to be carefull while interpreting this. So this is the captain model and this is how you calculate expected return. So from this expected return, we are going to talk about something called Jensen's alpha which is basically the different between actual return and expected return. I will talk about it when I talk about abstract of the paper which is beta AS beta.