So let's get started with the recap of last time, without a major discussion of statistics and then move on to today. So what was the recap? And I just want to do it a little bit hands on. And the reason is the issues are very, very important, but they're not detailed. So remember, I always show you the snapshot. And remember, the back of our minds is Orange. Do you remember Orange? Orange is that innovative company that is trying to mimic another fruit. And that fruit is called Apple. It's trying to make you part, whatever. Whatever was with I, they want to make with you. It is not a bad strategy, if you ask me, but, okay. So, you want to evaluate Orange? You've got all the cash flows because that's your job. You use to come up with this idea, you can think like that. So you got everything, now you're looking for, You got the cash flows, you're looking for r. And whenever you think of r put an a next to it. And the reason is real assets create value. Okay, so now I know that, but I don't know what my r is. This belongs to Orange in the sense that Orange created this idea but this belongs to the market. And now you know why markets are so important, is because all valuations relative. So you say, okay, I want to value Ra, I mean Orange. So you find a company called Apple and you say, okay, let me go figure it out what Ra is. What you realize is, you look at Apple and there's no Ra to be found and the real are measured. And the reason is real assets don't trade. And you see now the beauty of markets, there is equity and there is debt. And if it's in a marketplace, equity certainly trades. Debt may be between you and the bank, you being Apple and the bank. And turns out for convenience we wanted, a situation where we didn't worry about debt. Inherent value creation should fundamentally depend on what the financing is, and that's not therefore the focus of this class. So I'm going to assume, quite realistically as we saw last time, that Apple has no debt. If that's true, if I can somehow figure out how to measure the risk of this and then go from risk to return on equity. Remember, risk of equity, return on equity. I have found Ra, you see the beauty of it? And the reason is, I do not know what the machines and ideas and people residing in Apple are and they're not trading there today. But to get to return, I need to know value over time, right? What is return? Change in value plus the dividends that are paid. So, I want to figure out Ra. So, I go catch my nose the wrong way because I can't go directly. So, I go through financial markets. You see, I tried to do that, I can't. But anyway, so you got your Ra. But in order to get Ra, what do I have to do? I have a challenge. I first have to define risk. Then, I have to relate it to Ra, the return. Turns out that's what our goal is today. But one final thought about the recap. What did we see? And I'm going to pick it up here. What did we see? No about risk. What is our attitude towards risk? We do not like it, But we like return. Do not like risk, like return. However, behavior show that we will take on more risk in a portfolio context than return. So, why did I say portfolio context? Because if you're risk overs, we will always spread our wealth around, we will never put our eggs in one basket, and that's a behavior show to be the case. So last time, we saw that large portfolios of small stocks was the Treasury bill had a huge difference. A large portfolio of S and P 500 which is more representative of stocks, still had a significantly higher average return difference, 8% of that data. So, what does that tell us? That risk goes with the return, but we are using portfolios. So, the notion of a portfolio and risk are tied very closely, and we are going to squeeze every ounce of knowledge that'd been created in the last 50 years in finance. And I remind you of one thing, the definition of risk got one Nobel prize. Harry Markowitz did a lot of work in the 50s on it, and that Bill Sharp and Black and others did work, and Bill caught the Nobel prize for coming up the relationship between risk and return. And though this is eventually you'll say, this is too simplistic, and then that's the beauty of it. Is equal empty square, don't you think that's simple to, and that's its beauty eventually. The beauty of a good model is not that it's right, especially in human behavior. The beauty of a good model is how much simplicity can capture of human behavior, okay? Okay, I showed you this graph. It is also available on the website and the earlier graph, I'm not going to talk about it because we spent a lot of time. Now stare at this one, and I asked you the following. Think of one thing that makes you pause about this. There could be many, but I'm going to think of one thing, and that one thing has to have some more hoof to it. Because there are a lot of things you could think of in this graph, right? So, come again now. What's the major difference between the top 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 entries starting with Disney, ending with Proctor and Gamble and the last one, what's the major difference? The major difference is that the 11 are stocks and S and P 500 is a portfolio. Now, it is true that those are only 11 and S and P 500 has 500. But let's assume those 11 kind of cover most industries are representative. The purpose of this is not to give you a perfect example, but the purpose is to give you an example that will be very close to reality in terms of what I'm trying to express. Okay, first question. What is the one thing you notice? And I'm going to say it now, because I'm getting desperate to let you know what that one thing is. Hopefully you agree with me. One thing, S and P 500 variance is less. Standard deviation is less than all the others. Now, as I said, I could pick some stocks if I looked hard enough, that would probably be a little bit less than this or whatever. But I'm just giving you this data to think about. There's a pattern here, and the pattern is individual securities tend to be much more risky than a portfolio that put together. And this will form our basis for the entire development of the definition of risk, and the entire development of relationship between risk and return. So literally the next slide says, what is going on? So this is what's going on. Remember, there are two major risks. Keep this at the back of your mind, very important. One is macro. Or systematic. The other is unique Or specific. [COUGH] >> So please keep this at the back of your mind. And now let's talk about what's going on. So, I'm going to call the standard division of a portfolio sigma B. Sigma stands for standard deviation, you know this from last week, just a symbol. And when you estimate it many times people use small s, and that is to differentiate between a concept and the data measurement. I'm not going to worry about it, many times they put a hat on it to show that it's nice to meet. Turns out this is sigma B, and let me call sigma I the standard deviation of a particular security I. So this is a security, say for example, Exxon. And this is in our case, SNP 500. What do you notice? You noticed that in our example each one of these is greater, Right? And how much was this? I believe 15% Turns out, if I took 1 over n average of all the standard deviation in the sap500. So what do I have on the right hand side? I'm averaging all the standard deviations of sap in the 500. And I'm assuming just what I showed you. I didn't show you all 500 [LAUGH] because that's all we would do, right? So I showed you a representative sample. What's true is, this is true. Any time you do this analysis, this will have to be true. And this is called diversification ie, and this is what we're going to talk about at length. What ie that is, diversification is the phenomena where the average standard deviation of risk, of the things within their portfolio if you average them, is much higher than the standard deviation of the combined. And quick question. We're going to go into this. Just keep this at back of mind, we'll take a break. It's a good time to pause before we pick up. However, keep one thing in mind. Always ask why. So let me leave you with one question, which will pick up next time and you'll see in detail, is which of these two risks that are present in each i, do you agree? Each security has some macro risk, some unique risk. And macro risk again, is what? Interest rates, oil shocks these days. If the web Internet stops, it's probably a huge risk [LAUGH]. Didn't used to be there, 40 years ago, right? What is a unique risk to a company, something specific to it? Industry specific could be one thing, in input peculiar to it could be another thing. And remember, these risks change over time, right? So something that was unique risk to a while ago is now a permanent risk. I give you two examples right there, all shocks. And more recently technology has become macro risk, however, one unique risk common to all companies is management investment decisions. So those can't be macro risks. So compare to, for example, the president of a country. So compare say Obama's policies versus the policies of even the best seeming CEO of all time, Jack Welch, when he was in charge of General Electric, whose unique? That one, right? Because he affect G, and G may be the most awesomest company, probably the biggest company if you are equity and debt. It still cannot have that macro effect that, say, a public policy move of a president can happen. So think like that. So which of these two get removed? Remember as use the forming the portfolio, what's happening to the average risk? It's going down. Think about it. Which of these two risks is tending to quote and quote cancel with each other? Leave that thought, think about it. We're going to come back, pick up, give a intuitive answer, and move on to the details and some of the most profound work done in finance. So let's get started with the recap of last time without a major discussion of statistics and then move on to today. So what was the recap? And I just want to do it a little bit hands on. And the reason is the issues are very, very important, but they're not detailed. So remember, I always show you the snapshot. And remember, the back of our minds is orange. Do you remember orange? Orange is that innovative company that is trying to mimic another fruit. And that fruit is called apple. It's trying to make you part whatever was with i they want to make with you. Which is not a bad strategy if you ask me, but okay. So you want to evaluate orange. You've got all the cash flows because that's your job. You have to come up to this idea. You can think like that. So you got everything, now you're looking for You got the cash flow you're looking for r. And whenever you think of r put an a next to it, and the reason is real assets create value, okay? So now I know that, but I don't know what my r is. This belongs to orange in the sense that orange created this idea. But this belongs to the market. And now you know why markets are so important, is because all valuations are relative. So you say, okay, I want to value Orange. So you find a company called Apple and you say, okay, let me go figure it out, what Ra is. What you realize is you look at Apple and there's no Ra to be found or measured. And the reason is real assets don't trade. And you see now the beauty of markets, there is equity and there is debt. And if it's in a marketplace, equity certainly trades, debt may be between you and the bank, you being Apple, and the bank. And it turns out, for convenience, we wanted a situation where we didn't worry about debt, inherent value creation. It shouldn't fundamentally depend on what the financing is, and that's not therefore the focus of this class. So I'm going to assume, quite realistically, as we saw last time, that Apple has no debt. If that's true, if I can somehow figure out how to measure the risk of this and then go from risk to return on equity, remember risk of equity, return on equity, I have found Ra. You see the beauty of it? And the reason is I do not know what the machines and ideas and people residing in Apple are, and they're not trading day to day. But to get to return, I need to know value over time, right? What is return? Change in value plus the dividends that are paid. So I want to figure out Ra. So I go catch my nose the wrong way, because I can't go direct route, so I go through financial markets. You see, I tried to do that, I can't. But anyway, so you got your Ra, but in order to get Re, what do I have to do? I have a challenge, I first have to define risk. Then I have to relate it to Re, the return. It turns out that's what our goal is today. But one final thought about the recap, what did we see? And I'm going to pick it up here. What did we know about risk? What is our attitude towards risk? We do not like it. But we like return. Do not like risk but like return. However, behaviors show that we will take on more risk in a portfolio context than return. So why did I say portfolio context? Because if we are risk averse, we will always spread our wealth around, we will never put our eggs in one basket. And that's the behavior shown to be the case. So last time we saw that large portfolios of small stocks versus the tragic bill had a huge difference. A large portfolio of S&MP 500, which is more representative of stocks, still had a significantly higher average return difference, 8% in that data. So what does that tell us? That risk goes with the return, but we are using portfolios. So the notion of a portfolio and risk are tied very closely. And we are going to squeeze every ounce of knowledge that have been created in the last 50 years in finance. And I remind you of one thing, the definition of risk got one Nobel prize. Harry Markowitz did a lot of work in the 50s on it, and that Bill Sharp and Black and others did work, and Bill got the Nobel Prize for coming up with the relationship between risk and return. And though this is, eventually you'll say, this is too simplistic, and then that's the beauty of it. E=Mc squared, don't you think that's simple too? And that's its beauty, eventually, it's the beauty of a good model is not that it's right, especially in human behavior, the beauty of a good model is how much simplicity it can capture of human behavior, okay? Okay, I showed you this graph, it is also available on the website. And the earlier graph I'm not going to talk about because we spent a lot of time. Now stare at this one, and I asked you the following. Think of one thing that makes you pause about this. There could be many, but I'm going to think of one thing, and that one thing has to have some more oomf to it. Because there are a lot of things you could think of in this graph, right? So come again now, what's the major difference between the top 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 entries, starting with Disney ending with Procter & Gamble, and the last one? What's the major difference? The major difference is that the 11 are stocks and S&P 500 is a portfolio. Now it is true that those are only 11 and S&P 500 has 500. But let's assume those 11 cover most industries, are representative of them. The purpose of this is not to give you a perfect example, but the purpose is to give you an example that will be very close to reality in terms of what I'm trying to express. Okay, first question. What is the one thing you notice? And I'm going to say it now, because I'm getting desperate to let you know what that one thing is. Hopefully, you agree with me. One thing, S&P 500 variance is less, standard deviation is less than all the others. Now, as I said, I could pick some stocks, if I looked hard enough, that would probably be a little bit less than this or whatever. But I'm just giving you this data to think about. There's a pattern here, and the pattern is individual securities tend to be much more risky than a portfolio of them put together. And this will form our basis for the entire development of the definition of risk and the entire development of relationship between risk and return. So literally the next slide says what is going on? So this is what's going on. Remember, there are two major risks. Keep this at the back of your mind, very important. One is macro, or systematic. The other is unique, or specific. Please keep this at the back of your mind. And now let's talk about what's going on. So I'm going to call the standard division of a portfolio sigma B. Sigma stands for standard deviation, you know this from last week. Just a symbol. And when you estimate it, many times people use small s, and that is to differentiate between the concept and the data measurement. I'm not going to worry about it, many times they put a hat on it to show that it's an estimate. Turns out this is sigma B and let me call sigma I the standard deviation of a particular security I. So this is a security say, for example, Exxon. And this is in our case, S and P 500. What do you notice? He noticed that in our example each one of these is greater, right? And how much was this? I believe 15%. Turns out, if I took 1 over n average of all the standard deviation in the S and P 500. So what do I have on the right hand side? I'm averaging all the standard deviations of S and P in the 500. And I'm assuming just what I showed you. I didn't show you all 500 [LAUGH] because that's all we would do, right? So surely a representative sample,. What's true is this is true. Any time you do this analysis, this will have to be true. And this is called Diversification, ie, and this is what we're going to talk about at length. What i e that is diversification is the phenomena where the average standard deviation. Or risk of the things within their portfolio if you average them. Is much higher than the standard division of the combined and quick question. We're going to go into this. Just keep the settle back of mind. We'll take a break. It's a good time to pause before we pick up. However, keep one thing in mind. Always ask why. So let me leave you with one question, which will pick up next time. And you'll see in detail is which of these two risks that are present in each i. Do you agree each security has some macro risk? Some unique risk and macro risk again, is what interest rates oil shocks these days. If the Web Internet stops, it's probably a huge [LAUGH] risk. India is to be there 40 years ago, right? What is a unique risk to accompany something specific to it? Industry specific could be one thing in input peculiar to it could be another thing. And remember, these risks change over time, right? So something that was unique risk to a while ago is now a permanent risk. I give you two examples right there. All shocks and more recently, technology has become macro risk. However, one unique risk common to all companies as management investment decisions. So those can't be macro risk. So compared to, for example, the president of a country. So compared to Obama's policies versus the policies of even a the best seeming CEO of all time. Jack Welch, when he was in charge of General Electric, whose unique that book, right? Because he affect G, and G may be the most awesome company. Probably the biggest company. If you had equity and debt, it still cannot have that macro effect that, say. A public policy move of a president can happen. So think like that. So which of these two get removed? Remember, as is forming the portfolio, what's happening to the average risk? It's going down. Think about it. Which of these two risks is tending to court and court cancel with each other? Leave that thought. Think about it. We're going to come back, pick up, give us kind of intuitive answer. And move on to the details and some of the most profound work done in finance
