ECON 252 Financial Markets (2011) Lecture 1 - Introduction and What this Course Will Do for You and Your Purposes [January 10, 2011] Chapter 1. Introduction to the Course [00:00:00] Professor Robert Shiller: OK. Welcome to Economics 252. This is Financial Markets, and I'm Robert Shiller. This is a course for undergraduates. It doesn't presume any prerequisites except the basic Intro Econ [Introductory Economics] prerequisite. It's about--well, the title of the course is Financial Markets. By putting "markets" in the title of the course, I'm trying to indicate that it's down to earth, it's about the real world, and, well, to me it connotes that this is about what we do with our lives. It's about our society. So, you might imagine it's a course about trading since it says "markets," but it's more general than that. Finance, I believe, is, as it says in the course description, a pillar of civilized society. It's the structure through which we do things, at least on a large scale of things. It's about allocating resources through space and time, our limited resources that we have in our world. It's about incentivizing people to do productive things. It's about sponsoring ventures that bring together a lot of people and making sure that people are fairly treated, that they contribute constructively and that they get a return for doing that. And it's about managing risks, that anything that we do in life is uncertain. Anything big or important that we do is uncertain. And to me that's what financial markets is about. To me, this is a course that will have a philosophical underpinning, but at the same time will be very focused on details. I'm fascinated by the details about how things work. It can be boring, and I hope I'm not boring in this course, but it's in the details that things happen. So, I want to talk about particular institutions, and I'm interpreting finance broadly in this course. I want to talk about banking, insurance --sometimes people don't include insurance as part of finance, but I don't see why not, so we'll include it. It's about securities, about futures markets, about derivatives markets, and it's going to be about financial crises. And it's also about the future. I like to try to think about the future, although it's hard to do so. Where are we going? This course will have a U.S. bias since we live in the United States. I know the U.S. better than any other country, but at the same time, I recognize that many of you, or even most of you, will work outside the U.S., and so it's important that we have a world perspective, which is something I will try my utmost to incorporate in this course. The world perspective also particularly matters since we have other viewers for this course besides those people in this room. This course is one of a couple dozen courses that Yale University is offering free to the world as part of Open Yale. And that means there's a cameraman back there if you've noticed. That's Dan Cody filming the course. And it will be eventually posted on the Internet and it will be available through Open Yale, and then by proliferation, you'll find it on many other websites as well. This is the second time this course has been filmed for Open Yale. The first time was in 2008, three years ago. And I'm very pleased to report that I have a lot of people in every imaginable country who have watched these lectures. And I get emails from them, so I know that they're out there. But I thought that this course needs updating, probably more than any course on Open Yale. You know, a course in physics only has to be updated for the last three years of research in physics, and it's probably not a big thing for an undergraduate course. But finance really has to be updated, I think, because it's going through such turmoil and change right now. We've had the worst financial crisis since the Great Depression, and it's been a worldwide crisis. And governments around the world are working on changing our financial institutions. We have organizations of governments, notably the G20, which is very involved in finance. It's one of the top items on their agenda for international cooperation; it's changing our financial markets. So, I think that that's another reason why I want to try to keep as international a focus as I'm good at doing in this course. But I hope that those of you who are in this room are not disturbed by the camera and feel you can ask questions. You don't have to be on camera. I think I'm just being filmed. So, that's where we are. Chapter 2. Broader Context of the Course [00:06:12] Now, I wanted to put this in a little bit broader context. The other major finance course that we have here at Yale is Economics 251 and it's taught by Professor John Geanakoplos, who is a mathematical economist and also a practitioner. He's research director for Ellington Capital. So, he's somewhat like me in that he's interested both in theory and practice. But his course is definitely more theoretical and mathematical than mine. His is entitled "Financial Theory." And I can read some of the topics that--and his course also will appear on Open Yale shortly. You can take the whole course. But I don't know--it's not up at this moment. It will be up in a matter of months. So, I encourage you, if you want to, to take Open Yale Econ 251. But the things that he talks about in that course, if you read the topics in this course you'll see that they're more mathematical and technical than mine. He talks about ''Utilities, Endowments and How It Leads to Equilibrium,'' ''Assets and Time,'' ''The Mathematical Theory of Bond Pricing,'' ''Dynamic Present Value,'' ''Social Security and the Overlapping Generations Model,'' ''Uncertainty and Hedging.'' I'm quoting his titles. ''State Pricing.'' That's kind of an abstract theory. We talk about the price of a state of nature. I won't explain that. He talks in some length about the ''Theory of Risk'' and the ''Capital Asset Pricing Model,'' and about the ''Leverage Cycle,'' which is relevant to our crises. So, I recommend you take Econ 251, but I don't expect you to take it. This course is self-contained. And I'm going to keep mathematics to the minimum in these lectures. But the idea here is that we can't avoid it completely. I personally am mathematically inclined, too, but I'm understanding that we have divided our subject matter. So, John Geanakoplos is doing the math and the theory, and I'm doing the real world. It's not a complete division like that, but it's something like that. So, I'm going to stay to that. I'm going to talk more about institutions and history than about mathematics. Since I know that most of you or many of you will not take Economics 251, what we are doing is, I'll give a little indication of the mathematical principles, more intuitive, and we have review sessions with our teaching assistants. We plan to have six of those. And those will be on a Friday in this room. And they won't be on Open Yale. Those will cover the theory, and it will be like a short form of Geanakoplos' course. And then we'll have problem sets. And there will be six problems sets, one for each of those sessions. So, there will be some math in this course. I wanted to talk about the purpose of this course, to clarify it. One thing is, what do I imagine you're going to do with this course? Well, first of all, I pride myself that I think I teach--if I might boast for a minute--I think I teach one of the most useful courses in Yale College. At least that's the way I think about it. Because this course really prepares you to do things in the world. By the way, I've been teaching this course now for 25 years. I first taught it in the fall of 1985. Now I don't know if that's depressing or not. To me, it's great. I like to be able to keep moving ahead. I wonder what my 1985 course looked like? Unfortunately, they didn't do Open Yale and I can't go back and look at it. But I think I've gotten more philosophical and maybe more real world oriented as time has gone by. But the excitement I have is when I go--I give a lot of public talks, and it's often on Wall Street. And when I do one on Wall Street, I like to ask people for a show of hands. How many of you were in my Economics 252 class? And I typically get one or two at least who raise their hand. So, that's a source of pride to me, that I was involved in the beginning of their careers. And I hope I instilled some kind of moral sense to what they do. But I should say I don't think that most of you will go into finance, because I think that most of you have other purposes. What does it mean to go into finance? Well, it sounds like that means you would be listed as someone who is very focused on finance. But I think everyone should know finance. This should be a required course, actually, at Yale College, because finance is so fundamental to what we do and the structure of our lives that I don't see how you can avoid doing finance if you want to do something big and important. Maybe you don't want to do that either, so you might want to become a hermit and then you don't need finance. But to me, I like to think that many of you have a sense of purpose in life. I should say--that sounded funny, didn't it? But what I'm saying is your purpose is not to make money. And this is one thing about finance that bothers me, is that people think that it's a field for money-grubbing people who just want to go out and make money. And I don't think so. I think it's a technology for doing things, and you don't want to be mystified by it. When someone talks some financial jargon, you don't want to say, I don't have a clue what that's about, because what that's about is how we make things happen. And so, I hope that you have other purposes in life besides finance, even those of you who go into finance. But the question is whether this is a vocational course. Here at Yale College there has been a long tradition that we are not a vocational school--I suppose you know that--that Yale is a liberal arts [college]-- we teach you the arts and sciences. I actually went to look at the charter and the act of the Connecticut government in 1701 that founded this university. This university was initially mostly a training ground for the ministry. But I actually read in the Acts of the Governor and Company of the Colony of Connecticut: "Yale College is founded for the educating and instructing of youth in good literature, arts, and sciences." I think that is the motive here for this university. And so, I think it is in some level vocational, but it's not vulgar vocational. I want you to think about what we're doing and how it fits into what you do for your life. So, I think of finance as a kind of engineering in a way. But it's an engineering that works not with what we call a technical apparatus, but with people. And so, if we want to understand how to do these things, we have to get some technical apparatus under our belt. And that's what I'm going to try to do in this course. The textbook that I chose for this course is by Frank Fabozzi, who is a professor at the Yale School of Management--well, with two co-authors. We have Franco Modigliani, for whom I have some personal affection, because he was my dissertation adviser at MIT, and who unfortunately died in 2003, and Frank Jones of Guardian Life Insurance Company. I've also written joint papers with, well, two of the three authors. I've written joint papers with Fabozzi and with Modigliani--research papers. But they're similar to me in many ways. They're interested in the details. I hope you get interested in the details. I find this textbook fascinating for me. Well, I first read this book when I first started assigning it. I was going on vacation with my friend Jeremy Siegel and our families, who's a professor at the Wharton School, and I brought this book as my poolside reading. And I was sitting there with this book. Other people were reading novels and fun things. I don't know what they thought of me reading this textbook by the pool, but I thought this is great because I thought I knew most of what's in here, but there's a lot of things that I still didn't know and it was answering all kinds of questions. Things you always wanted to know about real estate securities, OK, but you never found out. Well it's all answered here. So, I hope you can take that spirit in reading the textbook. That's the only book you have to purchase for this course. And it's the main work that you have. So, I'm going to ask you about the details on exams. The kinds of municipal securities we have and how the rating agencies rate them, that's part of this course. I believe the details matter. And so I'm not going to just ask you broad generalities on the exam. I can ask you the details. It's a little bit like teaching a language, right? Learning a language is really important, and you've got to learn all the words, right? There's thousands of them. It's like that. You're going to be learning the words of finance. So, I have another book also, which is actually not done yet, but you can access it through Classes*v2, and later it will come out as a published book. But I'm working on a book called--well, I don't know what it will be called finally. When you're writing a book, one thing you learn as an author is you can never be sure what the title of the book will be. Because if somebody else uses the same title and you're done, somebody else gets to it first, you've got to change your title. But at this moment the title of my book is "Finance and the Good Society." I'm not sure when it will be out. I was hoping next year, but now I'm thinking it might take longer than that. So, you have something that's imperfect. I hope youll excuse me when you look at the chapters of this book. You don't have quite all the chapters either. But I just thought it was a good thing to put it in process for you to--maybe if you have ideas you can tell me and the book will change with your input. To me it's a good way to write a book, is to be writing a book and teaching a class at the same time on the same topic. It's more social. You know, you just sit in your office and write and you end up feeling sterile. So, this makes it more alive to me to do that at the same time. But I'll tell you what my book is about. The title that I now have, "Finance and the Good Society," may sound to some people like an oxymoron because they're kind of incompatible. People are angry about finance these days. We've had--and this is going to be an important part of this course--we've had the worst financial crisis since the Great Depression of the 1930s. And it's been a worldwide financial crisis and it isn't over yet, or it's not clear that it's over yet. And people are angry. People are angry about finance, people who seem to be getting rich often it seems at the expense of others. Or they seem to be lobbying their governments to give them breaks and bailouts, and they walk home with billions of dollars. Something seems immoral and wrong. Well, I'm sure some immoral things are happening, but I don't think that finance, as a whole, is wrong. And I think of it as a noble profession. So I wanted to try to put it in perspective. And it's especially important when talking to young people like yourselves because you're launching out on a career, and I want that to be a moral and purposeful career. And I want to put finance in the perspective. So, the theme that I want to develop in my book is that part--you know, we live in a capitalist world now and this world is increasingly built on finance. Some people call it we're living in the era of financial capitalism. We have these big multinational institutions that are owned by huge numbers, maybe millions, of shareholders dispersed all over the world. And what makes the whole thing work and click? It's the financial arrangements. The world is discovering the importance of finance. When I go to a foreign country and give a talk, I find that people--it doesn't matter what country--they're generally very interested in finance, because they think that our modern financial techniques are part of what's making so many places in the world grow at rapid rates now. We're living in a time in history when [the] developing world is exploding with growth, and these countries that are doing that are countries that are adopting modern finance. So, I want this to go right, and I want this to be developing a good society. By good society, I mean a just and fair society that allows people to develop their talents and expertise. Chapter 3. Finance as an Occupation [00:22:41] So, another thought I had was that the field of finance-- let me give you another slide. I said I view this course as one of the most important courses in Yale College, at least from a standpoint of your lives and careers. I wanted to compare finance jobs with jobs. And I don't mean to put down other departments, but at least vocationally, let's put this in perspective. I wanted to compare jobs in finance with jobs in other fields. So, this is a chart that I constructed using data from the Bureau of Labor Statistics. And what it has is the number of people in various occupations in 2008 and their projections for the same in 2018. So, the red bar is for 2018, and we'll emphasize that because you'll be just getting into your careers when that comes. So, it says, if you look at financial analysts in the United States there's almost 300,000. Financial managers, it's over half a million. Personal financial advisers, a quarter of a million, all right? These are people who specialize entirely in one form of finance or another. But compare that with economists. Look at that. What is that? About 20,000? I think they're excluding professors. But, you know, just economists out there--not very many. How about astronomers? OK. I can't even read that. I love astronomy by the way, but I think I made the right choice when I decided--well, I shouldn't say that, you never know. We all have to do something different. And you could become an astronomer, but there aren't many jobs in astronomy. Sociologists, political scientists, just not many compared to--this is just enormously bigger. Or mathematicians. I also put one oddball field on here: massage therapists, OK? The number of massage therapist jobs outnumbers any of those other fields by, what is it, 100:1. So this is the kind of disappointment that people face. You go to the college or university--this is very much on my mind--you go to the university and you develop special skills, and you leave and then you end up driving a taxi. That doesn't mean that I want to become vocational. I mean, I don't want to just train you for a job, but I want to be relevant. And it seems to me that I can be relevant in talking about finance. And so that's the basic core that I wanted to get. I mentioned before that people think that finance is the field for people who want to get rich, who want to make a lot of money. Well, I think that's right, actually. [LAUGHTER] I don't advise you to take that as your--but I wanted to talk about that a little bit. So, one thing that you'll note, Forbes Magazine has an annual list of the 400 richest people in America. So, I looked at that list. Who do you think they are? Most of you probably have not read this list. You might think that, well, who makes a lot of money? Well, it's athletes. Football players, right? Baseball players. And who else? Oh, movie stars, right? They make a lot of money. So how many do you think of those are on the Forbes 400 of the richest people in America? Well, as I read the list I didn't see a single movie star or a single athlete. There is--it depends on how you define it. Oprah Winfrey is on the list. OK? You've heard of her. She's in the entertainment business. But you know, she's also a finance person. She runs big businesses. She's into making things happen. And I can assure you that she knows finance, at least some basic finance. You see, finance gets you to build organizations. That's how it's done. And it means raising capital to make things happen on a big scale. You know, no athlete is as powerful as one of these random guys on the Forbes 400 list. It's interesting. I looked down the list and I didn't spot a single Nobel Prize winner. Maybe I missed one. I looked for best selling authors. I found one: Bill Gates, who wrote a book called The Road Ahead. But there are not many best selling authors either. What do they have in common? Now about a third of them just inherited it from their parents, but most of them did it themselves. They just made huge sums of money. And what do they do? Well, they're typically in some boring line of business. They make something, but they're doing it on a vast scale. And so that means they're making deals, they're putting things together, they're buying companies, they're absorbing other companies into theirs. There's something powerful about an ability to do that. And I think that it's good for you to understand and appreciate that. By the way, Forbes has another list called the Forbes Celebrity 100. And to be on that list, you have to be a celebrity. It's a completely different list. Oprah is on both lists, but she's practically the only one. Steven Spielberg is on both lists, I think. He makes movies, but he has a whole company called DreamWorks, and he finances all kinds of movies, so he's a businessperson as well. So I don't think of finance as a mathematical--I mean it is mathematical, it has a core element of that. But to me, it's about making things happen and about putting together deals and getting people incentivized to do something, and getting capital, getting resources in a massive scale so that something can happen. And so that's what this course is about. Oh, Jerry Seinfeld is listed by Forbes as a possibility--he's about the only one--to make the list of the Forbes 400. But he isn't there yet. I don't mean to diminish these celebrity people, but there's something else that goes on in finance, and it's quiet. It's behind the--actually, most of the Forbes 400 you've never heard of. They're kind of behind the scenes doing things that are big and important, but they don't get on the news so much. It's one of the ironies of life. You might aspire to do this, to get on the Forbes 400. You can do it and still nobody knows who you are or cares. So that's just as well, I think, for many people. Chapter 4. Using Wealth for a Purpose [00:30:40] So then the question is: Suppose you get on the Forbes 400, what are you going to do with it? In other words, to get on the Forbes 400 you have to have made at least a billion dollars. So that means, you have in your own portfolio a thousand million dollars. That's the minimum to make the list. So what are you going to do with a thousand million? Any ideas, what would you do with it? You could buy cars, right? How many sports cars could you buy for that? What could you do? You could buy 20 houses. But that doesn't begin--you could buy 20 houses and so what? You know, you still have 900 million leftover. So what are you going to do with all that money? And that's a question. Now, some people who do that, who make all this money, try to see if they can maximize their appearance of wealth. They try to show to the world how rich they are. So, you just build the biggest mansion and you do something really spectacular. But when you got a billion dollars, there isn't a house in the country you could buy for a billion dollars. You can only stay in one at a time, right? So, what are you going to do? But there are people who do that, and I think that there's a history of disgust for those people, a long history. We don't like people who do that. It's almost like it's a big mistake. Why would you do that when people don't like people who show off their wealth? There's evidence that people feel that way in many different countries and cultures, because lots of countries in history have what are called sumptuary laws. It goes back at least to 700 BC in Ancient Greece with the Locrian code. These are laws prohibiting people from conspicuous consumption. And they've been in so many different countries that I think it's evidence that something is amiss with making wealth as the objective of your life. So, one of the themes in the beginning of our reading list is--I think there's a movement afoot today around the world of thinking about this problem, that you can get so big and powerful if you build a business and you use the financial techniques that are successful for other people, but it's meaningless unless you give it away. And so, what else can you do with all this wealth but plan to give it away. So, one thing I have on the reading list right at the beginning is a chapter from a book--well, the title of the book is The Gospel of Wealth and Other Essays and it was written by Andrew Carnegie. Actually, he wrote a short article in a magazine called "Wealth" in 1889. And in the final paragraph he used the term "gospel of wealth" and it was picked up all over the world as just outrageous. And so it became named The Gospel of Wealth. So, later in the early 20th century he came out with a book entitled The Gospel of Wealth. And that's what I have assigned. You can click on it on the reading list. And Andrew Carnegie was one of these--they didn't have Forbes 400, but he was one of the richest men in America through his Carnegie Steel Company, very much steeped in finance. But he decided when he wrote his essay, The Gospel of Wealth, in 1889 that once a person reaches middle age, like 50 or 55, and has made a lot of money, they really have to go into philanthropy. There's a moral imperative. So the theme of The Gospel of Wealth was some people are just better at what he called affairs than other people. That means business. Some people have a sense of how to make things happen. These people have a moral obligation to make this work for the benefit of humankind. And that means, while they're still young, they have to take their fortune and give it all away before they die. Because if they don't give it all away, it's nonsense. If you make a billion dollars and you leave it to your children, chances are they're not like you. They're not going to be interested in working hard and making things happen. They're just going to squander it. And so that's what the moral obligation is. You have to stop at age, let's say 55--OK, you still got time left--and then use your same talents. So, it was almost a theory of capitalism--it is a theory of capitalism. It is a theory that some people are just more practical and hardworking and business-oriented, and these people can find things to do that benefit mankind, and they should do it. So, there's a natural selection. This is Carnegie. I'm not endorsing this entirely. I think there's an element of truth to The Gospel of Wealth, but it's not exactly true. But the element of truth is right, that people like Carnegie who was a very gifted person--you know what he did? He set up the Carnegie Institute of Technology, now called Carnegie Mellon University. He set up the Carnegie Endowment for World Peace, Carnegie Hall in New York. He probably gave something to Yale, too. Anyone know? Is there a Carnegie? He gave to like every imaginable university. I know at Princeton they have a Lake Carnegie. He was visiting Princeton and someone pointed out this kind of swampy land and said we'd like to really create a lake. So he said, fine. He gave them money to create Lake Carnegie. And he also gave the money for the prize for the first true competition on Lake Carnegie. So, he just had all kinds of gifts he gave it away. I also have--it's interesting, I found this on the web. Thomas Edison, the inventor, was so impressed with Carnegie's The Gospel of Wealth that Edison was developing the sound movie, I think it was 1914, but he didn't perfect it. But he said the first sound movie should involve geniuses of our time. So, he made a sound movie of Carnegie reading from his The Gospel of Wealth. Unfortunately, the visual side of it somehow got lost. Maybe it didn't work. We only have the soundtrack from the movie. So, you can listen to Carnegie reading from this book in 1914, and it's the only recording of Carnegie's voice that survived. Since then, Bill Gates and Warren Buffett and others of the Forbes 400 have done a campaign to get billionaires around the world to commit to give most of their wealth away, while they're still alive. And I'm trying to get one of these people to speak to our class, but I haven't yet arranged that. I also have on the website a review from 1890 of Carnegie's original essay from a California newspaper, and they were so negative about it. They said, Carnegie thinks that making wealth and giving it away is a noble cause. That cannot possibly be right. These people who make money are not the most enlightened and smart people in our world. I think that the truth lies somewhere in between. But we do have a society now where people--we have an increasing concentration of wealth at the top, and I don't know what we're going to do about this. This is a trend that may continue. And so, this is the thing I want to think about in this course. I don't think finance necessarily does this. It may be a bubble, that there is currently a bubble in financial careers and that you are going to be disappointed because 20 or 30 years from now if you go into a finance-related field, you'll find that it's not as lucrative as you hoped. That kind of happens, right? When a field becomes known for having a lot of successful people, then more young people go into it and they swamp the field. On the other hand, I think that it will always be true that just because of the power of the technology the top wealthiest people in the world will be finance-related. And I think that they will have a moral obligation to give their wealth away in a productive way. Chapter 5. Outside Speakers and Teaching Assistants [00:40:30] So, I have several outside speakers, and I tried to bring in people that are connected to the world in a positive way. I'm trying to bring in inspirations for you as outside speakers. And they're people who are in finance but who are not selfish. They may be rich but they are good people. So, the first person that I'm going to bring in, as I've done in previous years, is David Swensen, who is Chief Investment Officer for Yale University. Swensen also teaches a course, Economics 450, with Dean Takahashi, which you might want to take. But I have him here just for one lecture. And what Swensen has done is turn the Yale endowment into a huge number. He came to Yale in 1985, and at that time, Yale had less than $1 billion in its endowment. Swensen is the most successful university endowment manager of the United States. He turned less than $1 billion into $22.9 in 2008. The financial crisis hit and the endowment fell, but as of June of 2010, it was still 16.7 billion. So, he has done so much to make Yale a success. But it matters. That's a lot of money. And it's all for a good cause. Now I say, I believe Swensen is a good person. I think he turned down opportunities to make much more on Wall Street, because he is known--and he's continually turning them down--as an investment genius. He can command huge salaries and bonuses if he wanted to, but he stays here with Yale. I don't think that people in finance are money-grubbers, and this is an example of someone who's not. The second speaker I have is Maurice "Hank" Greenberg, who founded AIG. It started out in 1962. In 1962, he was put in charge of North American operations of the American International Group, an insurance company, which was then failing. The head of the company, C.V. Starr, put him in this to try to turn the company around. He turned it, over many years as CEO of AIG, into the biggest insurance company in the world, and he ran it until 2005. The company--have you heard of this, AIG? You must have heard of this. In the recent financial crisis it has encountered some problems. And, in fact, it was the biggest bailout of all. It was bailed out by the U.S. government. And there's a scandal about that because the bailout was so huge. It was in the hundreds of billions. Record-setting bailout. And some people are angry with Greenberg. But I think that's completely unfair, because it all happened after he left AIG. And the problems were in a particular unit within AIG that he was not really responsible for. But Greenberg is a person who has, I think, a moral purpose that I want to illustrate for you. He's been criticized. Anyone who does business on that scale is going to be criticized for being too tough or too aggressive at times. But he's a very involved person. He's the Vice Chairman for the Council on Foreign Relations, which is a think tank that thinks about the United States and its place in the world. It's a very important think tank. He's also a major philanthropist and he's given to Yale. Notably, he gave the Greenberg Center, which is right next to the Center for Globalization. A beautiful new building. So he has agreed to come. I'm very pleased to have him. The third outside speaker that I have now is Laura Cha, although she won't be here in person. We're going to have her image up on the screen because she is in Hong Kong. And she is a non-official member of the Executive Council of Hong Kong. She's a member of the government of the People's Republic of China at the vice-ministerial rank. She's the first non-Chinese delegate to the National People's Congress representing Hong Kong, and has been vice chair of the China Securities Regulatory Commission. So she is very involved in finance. She's also been affiliated with Yale and helped some of our initiatives. She'll have to get up very late at night, I think, to be on for 9:00 in the morning for us from Hong Kong. I might get one or two other speakers, but that's where it stands right now. So, I wanted also to tell you about our teaching assistants. We have four teaching assistants now. We might get another, but at this point. The first is Oliver Bunn who is from Germany, University of Bonn, and is a PhD student in economics. He's also our head TA who coordinates the whole operation. And then we have--the second one is Elan Fuld from the United States. And he's doing an interesting study of the pizza delivery industry. It sounds funny, but it's an interesting application of economic theory to very much the real world. Bige Kahraman is from Bilkent University in Turkey, and she's interested in Behavioral Finance. That means--I should have said this. It's also an interest of this course. I've skipped by it in my notes. Behavioral Finance is the application of psychology, sociology, and other social sciences to finance. I don't know how I omitted mentioning that. It's about people in finance--well, I didn't really completely omit mentioning it. You've got the sense that I'm interested in people. But there's been a revolution in finance over the last 20 years. Twenty years ago, finance was thought of in academia as an essentially mathematical discipline, that and nothing more. Well, maybe I'm exaggerating a little bit. But what's happened since then is people think of finance as involving psychology. We have to bring people with knowledge of human beings in. And so, her dissertation topic, a major theme of it, is how mutual funds operate. Mutual funds are companies that offer investment vehicles to the general public, and she finds that the mutual fund companies have complicated fee schedules and they offer different choices to people. And what sense does this make? Why are there all these different choices? You look at the fee schedules and you think--it's just like your cell phone plan, right? It's got different choices and you don't know which one I should take. Why are they doing all this? Well, she tries to analyze what's going on and she finds that sometimes it seems like clients are steered toward a fee schedule that's really not in their interest and that the mutual fund managers are doing some things that maybe we don't want them to do. Maybe it's not ideal. They're pushed by competitive pressures into offering products that are a little bit manipulative of people. And her dissertation also brings up another theme, which I thought I perhaps should have emphasized, that all is not well in the financial world. Lots of bad things happen. Or not necessarily awful things, but, you know, not socially conscious things. And that's why we need regulators. That's another reason why I brought in Laura Cha, by the way. She's a regulator. I wanted to have a voice from that side, because I personally admire regulators and think that they have a very important function in our society. So, her work fits more into that regulatory side of finance. And then, finally, our fourth teaching assistant is Bin Li from Beijing, although he went to college at University College London. And he has broad interests including Leveraged Asset Pricing and also Behavioral Finance. So, those are the teaching assistants. Chapter 6. Outline of the Lectures [00:50:26] So, let me just give a brief outline of the course. There are 20 lectures that I'm giving in this course. This is the first. Let me just go through what's the content of these lectures. So, Lecture 2, that would be on Wednesday of this week, I want to talk about the core concept of risk and also about financial crises. The one reason why I wanted to update this course with Open Yale this year is because I wanted to talk about the financial crisis that we've been through, though I thought this lecture would start with something about the theory of probability, but I'm not going to get into that very much. That will be more for a TA section that will come in later. But even so, this is not a probability course. I just want to kind of remind you of the concepts of probability. And there's a concept of independent risks. If risks are independent you can diversify away them, and you can put together a portfolio that minimizes the risks. The law of large numbers says if you have a lot of independent risks, they'll average out if you have a large number of these different risks in your portfolio and there's no risk left. That's if they're independent. But in fact, risks are not as independent as you think, and that's one reason why we had a financial crisis. And so a lot of people were making plans based on portfolio theory in finance, but the plans assumed that there won't be a crisis, that maybe one of our investments will go bad, but they can't all go bad or a large number of them can't go bad. So, that was a failure of the independence assumption in finance. That failure created the financial crisis that we've been through. It was a near miss onto another Great Depression. The financial crisis that began in 1929--I'll talk about that briefly in that lecture--started with the stock market crash of 1929 and the economy spiraled down until 1933. It just kept getting worse and worse. More and more bankruptcies, more and more layoffs. So, by 1933, 25% of the U.S. population was unemployed. And it wasn't just the U.S., it was all over the world. It was a horrible crisis. And we didn't get over that crisis until World War II. It's like we couldn't get out of it. The crisis got so bad that nobody in the world could figure out what to do. And I think that part of the reason we had World War II was because of the anxieties and animosities caused by this massive unemployment. But we got out of it because World War II created a huge stimulus program. I mean, they drafted all the unemployed and made them fight. What an awful outcome, but that's what happened. It's terrible. And so this time we saw the beginnings of a similar crisis. We saw crashes in the stock market and the real estate market, we saw bankruptcies appearing, we saw runs on banks. And this time the Government decided on a controversial bailout package. And so, Ben Bernanke and Mervyn King and other central bankers and government policymakers around the world had the idea that we can't let it happen the same way this time. So, there was massive bailouts, controversial bailouts, because they seemed to be unfair to many people. So, it's a huge and interesting story. I've written three books, by the way, about this crisis. Well, two of them with co-authors. So, it's something that fascinates me. But I don't want to dwell on it too much in this course, because I'm hopeful that it will heal itself and we can put it behind us. And the financial crisis doesn't call into question the basic principles of finance. Not in my mind. The vulnerability to a crash that we see in financial markets is like the same thing as the vulnerability to crash of airplanes. Airplanes crash from time to time. You must know that when you get on one. But that doesn't mean we shouldn't have airplanes. And I think the financial system is advancing in the world with such speed and such impressiveness that this crisis is just a blip on the screen of that, and not something I think we should worry too much about. The third lecture is about technology and invention in finance. Finance is a technology just like engineering or mechanical engineering. It has principles, it has techniques, and it involves inventing of details. That is, financial institutions are complicated. They're complicated in the same way automobiles or airplanes or nuclear power reactors are. You can see this complexity if you read some of the documents that are associated with the modern corporation. There's a lot there. And the way the cash flows are divided up among different people, involving options and derivatives and other complicated financial instruments, are part of the technology. And this technology is advancing, and it will advance a lot over the time of your career. I don't have an ability to predict the future with any accuracy, but I want to try to think about what we can say about the future. I wrote a book in 2003 called The New Financial Order, and it was my take on the future. But the problem is nobody really knows the future very well. You kind of have to just invent it or dream about what it might be like. That's what I did. I kind of thought about principles of financial theory and where they might go with the advance of information technology and the globalization of the world. So, I have just a chapter from that for that section of the course. Then, Lecture 4 is about portfolio diversification, how risks are spread. And we'll talk briefly about the Capital Asset Pricing Model. Now again, the Capital Asset Pricing Model is a mathematical theory of diversification. A very important theory, and it's something that John Geanakoplos will cover with more rigor in Econ 251 that I already mentioned. But for me, I will talk briefly about the capital asset pricing model, and one of our teaching assistants will give a section on it. But I want to also think about, since this is a course about the real world, I want to think about financial institutions, and so many of our institutions are offering diversification one way or another. And so, again, I wanted to talk about the real world component of this. The fifth lecture is about insurance. And the insurance industry developed over the centuries. It goes, actually, all the way back to Ancient Rome, but only minimally. People didn't have the concepts until the 1600s when probability theory was invented. There was an intuitive concept that, sure, I could start an insurance company, I could put together a lot of insurance policies and charge for them, and probably I won't--you just have intuitive sense about law of large number or independence of risks. Probably, I'll be OK and I can make good on the policies I wrote. But it was never clear until probability theory was developed. Since then, it's been growing and it's becoming a bigger and bigger part of our lives. And I think that insurance is actually a lifesaver. I'll give you one example. You note that in the earthquake in Haiti--what was that, about a year ago? There was a tremendous loss of life, but the earthquake in San Francisco decades earlier was of the same magnitude and had very little loss of life. Also, the loss suffered by people in terms of destruction of their homes and their office buildings was vastly higher in Haiti. Well, it turns out that Haiti, a less developed country, didn't have much of the modern insurance industry, so that people were uninsured against risk of collapse of their structure and you didn't have insurance industries going in and policing building codes. If the insurance company is liable to the risk then they go in and say, we won't insure you unless you fix this. Since it didn't happen, so many people died. I think that Haiti will come along. There is already a Caribbean insurance initiative that was starting. We want to see the developing world get these institutions. I want to try to give a sense of the reality of that, that we tend to think of Haiti as an opportunity for our charity, and a lot of us gave money to help these people. But, you know, charity doesn't work on a big enough scale. Going around to people on the street and asking them to give money to help the Haitian earthquake victims, it doesn't amount to a lot. What really becomes big and important is the insurance industry, which is doing the same thing as a business model. And that's the real world and it matters enormously. The sixth lecture is about efficient markets. This is about a theory that developed in the 1960s, that financial markets are wonderfully perfect. I'm saying I'm a little bit skeptical of this theory, although I think it has an element of truth. Efficient Markets Theory is the idea that you really can't make money by trading in financial markets because the markets are so competitive that the price is always pushed to an optimal level that incorporates all information that anyone could ever have about the security. And the theory has been that it's hopeless to try to invest and beat the market. Well, I think there's an element of truth to that but it's not quite true, and people like David Swensen are counterexamples, that it is possible for professional money managers to beat the market. And that's something I want to think about and talk about in that lecture. Lecture 7 is about debt markets. We have a lot of money that's lent. The Federal Reserve manages these markets. It tries to coordinate the markets through open market operations and through what now is called Quantitative Easing. But the markets are huge and international. They involve errors that people make. A lot of people get overly indebted and make mistakes over their lives. But they also offer opportunities, that debt markets are fundamental to the things we want to do in our lives. For example, when you are a little bit older, many of you will want to buy a house, right? But you won't be in that point in the life cycle when you have the money to buy a house, most of you, so you'll be borrowing. It's elementary. You take out a mortgage. That seems obvious. But still today in many countries of the world, the mortgage market is not very developed, and you can't do that. So, there's a good side to borrowing as well as a bad side. I want to put it in perspective. We've got our review session. We'll talk a little bit, somewhat, with one of our teaching assistants about the mathematics of debt. Lecture 8 will be about the stock market. Again, I think of the stock market not as something that we're going to beat. I think it's something that is an invention to motivate people to get people working together. So, the basic idea of a stock investment: You and your friends want to set up a company, OK? How do you do that? Well, the company needs money to start. So, somebody's got to contribute capital. Well, some of you have more money to contribute than others, so you should have a bigger share in the company. Some of you have no money at all to contribute, but you're going to contribute your time and energy. So, you want to give a share in the company to these other people as well in order to incentivize them. So, you devise a whole scheme to set up a company that involves the creation of stock. And then you start trading the stock and then it gets all the more interesting. And then there are options on these stock certificates. But it's all for a purpose. The purpose is to make some enterprise happen. And it really is important that we have these institutions, and if you don't have them, your little group trying to do something is going to fall apart. Someone's going to get angry and leave. It's just not going to work. And so I think of the stock market as doing these functions. Now I know Karl Marx said he thought it was a big casino, but we're not communists here. This is about modern finance. Lecture 9 is about real estate--another fascination for me. I've been working for years about real estate. And, in fact, with my colleague Karl Case, we have our own home price indices called the Standard and Poor Case-Shiller Home Price Indices. We'll talk about those. But it's really important for this crisis that we've just seen, because the financial crisis was caused substantially by a bubble in home prices, I believe, a psychologically induced excitement or euphoria about home prices in the United States and in other countries that collapsed around 2006. These bubbles are restarting in other parts of the world more recently. And the real estate market is getting very speculative and psychological, I believe. And the outlook right now for the economy hinges on how these markets behave. So, that will be, I think, an important lecture for this course. Lecture 10 is about Behavioral Finance. It's about psychology in finance. I talked about that. It's another long-standing interest of mine to try to incorporate psychology into our theory. So, lecture 12 is about banking, multiple expansion of credit, the money multiplier, and bank regulation, which is something that is a fascinating topic because we almost lost our banking system. We had to bail them out massively. We have international accords now. Notably, a new one just came out called Basel III from Basel, which is the city in Switzerland, and it was endorsed by the G-20 countries at their Korean meeting in Seoul. So, we're seeing a change in bank regulation that will, we hope, prevent another crisis like the one we just went through. Lecture 13 is about forwards and futures markets. Forward markets are markets for contracts that deliver in the future. Over-the-counter contracts, they're called, that are done one-on-one between parties with the help of an investment bank. Or futures contracts, which are traded on organized futures exchanges, like the Chicago Mercantile Exchange. I have some involvement with this because we worked with the Chicago Mercantile Exchange to create a futures market for single-family homes using the S&P Case-Shiller Index. So, I'm involved in this. And we have that market functioning at a rather low level, but it is functioning and it seems to be growing lately. I'm hopeful for that market. Lecture 14 is about options markets. These are most typically stock options, which are contracts that allow you to purchase a share of a stock or to sell a share at a pre-specified price. These are traded on options exchanges. They have a price that goes up and down. This is an example of a derivative contract that injects a lot of complexity into financial theory. Lecture 15 is about monetary policy. It's about the central banks of the world. For example, our central bank, called the Federal Reserve in the United States. And it's about what they do and how they help prevent crises like the one we've just seen. They did help prevent it. I think they staved off disaster. Lecture 16 is about investment banking. I know this is of great interest because we place a lot of students in good jobs in investment banking. Companies like Goldman Sachs, the most talked about one. Investment bankers help companies raise capital, issue securities, retire securities. And we're going to talk about how they're regulated. And I didn't mention Dodd-Frank, by the way, but we have a new bill that just passed in July in the United States that changes the regulatory structure for investment banks and a whole array of financial institutions. And I want to talk about that. The European Parliament has created a number of new laws and organizations that somewhat resemble Dodd-Frank. And other countries have also done financial regulation reform that affects investment banking and other aspects of finance. It's extremely complicated. I don't want to give you too many details but I want to give you some sense of the revolution that we're seeing. Lecture 17 is about professional money managers like David Swensen, people who manage portfolios. You don't have to be a billionaire to manage a billion-dollar portfolio. In fact, some of you may be doing it sooner than you realize if you get the right kind of job. Managing a portfolio means managing the risks, putting them in the right places. You think of institutional investors, big money managers, as just trying to make money. But when you get into that field you realize that you have power as an institutional investor. When you own a big share of some company, you can go to the board meeting and talk to these people, or the stockholders' meeting, and you will get heard if you own 10% of the shares of a company. Then you suddenly realize that you are a steward of the public interest. And I think institutional investors are recognizing that more and more. Lecture 18 is about exchanges, brokers, dealers, clearinghouses, like the New York Stock Exchange or the London Stock Exchange. They are proliferating around the world. Whereas there were just a few 30 years ago, now almost every country has a stock exchange and a complicated list of exchanges. They're increasingly electronic; they have interesting new features, like microsecond trading that's going on, computers trading with other computers. We'll talk about where this is going. Lecture 19 is about public and nonprofit finance. So, I think this is very important. Nonprofit finance would include organizations like Yale University, or churches and charities and other things like that. But I'm also including in this lecture public finance. And that means governments financing projects. So, for example, you take it for granted that our city here of New Haven has roads, it has schools, it has sewers, it has water. All this kind of comes without you even asking. But all of these things had to be financed. And the City of New Haven, like other cities, is issuing debt and it's a complicated business. I want to get you into some of the details because it matters, because this is how you make things happen. You can go to your city government and you can propose that they issue revenue bonds to start some new product. You would know--that's what I want you to do, is to know how these things are done so that it's not just imagination, you can make it happen. And also nonprofits. I want you to understand that you can set up your own nonprofits, and there's a lot of advantages to doing that. That's an organization that has a financial structure but no shareholders. Nobody takes home the money. It all goes to some cause. And, finally, my last lecture, Lecture 20, I'm calling it ''Finding your Purpose in Finance.'' I just want to come back in the last lecture to the idea that this is a course not about making money. I don't want you to give a billion dollars to your children and grandchildren, which they will then squander in conspicuous consumption. The idea is a moral purpose. And that's one thing I wanted to try to convey, partly with outside speakers, maybe with other examples that I can give, that I think that many people who are wealthy and who have succeeded in finance really don't care about spending the money on themselves. They really do have a purpose. And even if that's not true of many of them. There's an interesting book by Robert Frank, I don't have it on the reading list, called Richistan, who talks about what wealthy people are like these days. And if you read his book sometimes they are disgustingly rich and spending the money on silly things. But there is an idea among many of them that they are going to do their good things for the world. I think many of you will do these things; I want to think about the purpose that you'll find in finance. So, that's just the closing thought. I'll see you again on Wednesday. But the closing thought is that this is about making your purposes happen. OK. [end of transcript] ECON 252 Financial Markets (2011) Lecture 2 - Risk and Financial Crises [January 14, 2011] Chapter 1. Financial Crisis of 2007-2008 and Its Connection to Probability Theory [00:00:00] Professor Robert Shiller:So, what I want to do this time is talk about probability. I don't think many of you have taken a course in probability theory. I don't take that as a prerequisite for this course, but I think that actually Probability theory is fundamental to the way we think about finance. So, I wanted to talk about that a little bit today. And I'm going to put it in a concrete context, namely, the crisis that the world has been through since 2007, and which we're still in at this point. It's a financial crisis that's bigger than any since the Great Depression of the 1930's. There's many different ways of thinking about a crisis like this. And I wanted to focus on one way that people think about it in terms of probability models. So, that's not the only way, it's not necessarily my favorite way of thinking about it. That's, I think, a good way of introducing our discussion of probability as it relates to finance. Excuse my cold. I am managing to talk. I didn't bring any water. I hope I make it through this lecture. It's a little bit iffy. So, let's just think about the crisis. Most people, when they talk about financial crises, they talk in terms of narrative, of a historical narrative. So, I'll give you a quick and easy historical narrative about the crisis. The crisis began with bubbles in the stock market, and the housing market, and also in the commodities market. Bubbles are--I will talk about these later, but bubbles are events, in which people get very excited about something, and they drive the prices up really high, and it's got to break eventually. And there was a pre-break around 2000 when the stock market collapsed around the world. All over the world, the stock markets collapsed in 2000. But then they came back again after 2003 and they were on another boom, like a roller coaster ride. And then they collapsed again. That's the narrative story. And then, both the housing market [and the] stock market collapsed. And then, what happened is, we see a bunch of institutional collapses. So, we see, in 2007, failures in companies that had invested in home mortgages. And we see a run on a bank in the United Kingdom, Northern Rock. It was arrested, but it looked like 1930's all over again with the bank failure. We saw bank failures in the United States. And then, we saw international cooperation to prevent this from spreading like a disease. And then, we had governments all over the world bailing out their banks and other companies. So, a disaster was averted, and then we had a nice rebound. That's the narrative story, OK. And it makes it sound--and I'm going to come back to it, because I like the narrative story of the collapse. But I want to today focus on something that's more in keeping with probability, with the way financial theorists think about it. And what financial theorists will think about is that actually it's not just those few big events. The crisis we got into was the accumulation of a lot of little events. And sometimes they accumulate according to the laws of probability into big events. And you are just telling stories around these accumulation of shocks that affected the economy. And the stories are not, by some accounts, not that helpful. We want to understand the underlying probabilities. And so that's--thank you, a good assistant. He knows what I need. I just announced what I need, he got it. A bottle of water. Tomorrow I may have absolutely no voice. You're lucky. I'm going to talk today about probability, and variance, and covariance, and regression, and idiosyncratic risk, and systematic risk. Things like that which are core concepts in finance. But I'm also going to, in the context of the crisis, emphasize in this lecture, breakdowns of some of the most popular assumptions that underlie financial theory. And I'm thinking particularly of two breakdowns. And we'll emphasize these as other interpretations of the crisis. One is the failure of independence. I'll come back and redefine that. And another one is a tendency for outliers or fat-tailed distributions. So, I'll have to explain what all that means. Chapter 2. Introduction to Probability Theory [00:05:51] But basically, let me just try to elaborate on--probability theory is a conceptual framework that mathematicians invented. And it's become a very important way of thinking, but it doesn't go back that far in time. The word probability in its present meaning wasn't even coined until the 1600's. So, you if you talk to someone before the year 1600, and say, this has a probability of 0.5, they would have no idea what you're talking about. So, it's a major advance in human understanding to think in terms of probabilities. Now we do. And now it's routine, but it wasn't routine at all. And part of what I'm thinking about is, what probability theorists do, or in particular finance theorists like to do, is they think that the world is, well, let me just say, it's kind of a realization that the world is very complex, and that the outcomes that we see are the results of millions of little things. And the stories we tell are just stories. So, how do we deal with the complexity of the world? Well, we do it by dealing with all of these little incremental shocks that affect our lives in a mathematical way. And we think of them as millions of shocks. How do they accumulate? We have mathematical laws of how they accumulate. And once we understand those laws, we can we can build mathematical models of the outcomes. And then we can ask whether we should be surprised by the financial events that we've seen. It's a little bit like science, real hard science. So, for example, weather forecasters. They build models that--you know, you see these weather forecasts. They have computer models that are built on the theory of fluid dynamics. And there is a theory of all those little atoms moving around in the air. And there's too many atoms to count, but there's some laws about their cumulative movement that we understand. And it actually allows us to forecast the weather. And so, people who are steeped in this tradition in finance think that what we're doing when we're doing financial forecast is very much like what we do when we do weather forecasts. We have a statistical model, we see all of the shocks coming in, and of course there will be hurricanes. And we can only forecast them--you know there's a limit to how far out we can forecast them. So, all hurricanes are a surprise two weeks before they happen. Weather forecasters can't do that. Same thing with financial crises. This would be the model. We understand the probability laws, there's only a certain time horizon before which we can forecast the financial crisis. That isn't exactly my view of the situation. I'm presenting a view this time which is very mathematical and probability theory oriented. So, let me get into some of the details. And again, these are going to be re-covered in the review session that Elan Fuld, one of our teaching assistants, will do. I have just slides with some graphs and equations. But, that's not Elan Fuld. Chapter 3. Financial Return and Basic Statistical Concepts [00:09:58] I want to start out with just the concept of return. Which is, in finance, the basic, the most basic concept that -- [SIDE CONVERSATION] Professor Robert Shiller:When you invest in something, you have to do it for a time interval. And I'm writing the return as one time period. T is time. And so, it could be [a] year, or it could be months, or it could be [a] day. We're going to number these months, let's say it's monthly return, we're going to number these months, so that the first month is number one, second month is number two. And so, return at time t, if t is equal to 3, that would be the return at month three. And we'll do price at the beginning of the month. And so, what is your return to investing in something? It's the increase in the price. That's pt+1 pt. I'm spelling it out here. Price--I spelled it out in the numerator, I guess I didn't do it in the denominator. It's price at time t+1 minus the price at time t, which is called the capital gain, plus the dividend, which is a check you receive, if you do, from the company that you're investing in. That's the return. We have something else called gross return. Which is just 1 plus the return. Returns can be positive or negative. They can never be more than--never be less than minus 100%. In a limited liability economy that we live in, the law says that you cannot lose more than the money you put in, and that's going to be our assumption. So, return is between minus 100% and plus infinity. And gross return is always positive. It's between zero and infinity. Now what we're going to do--this is the primary thing that we want to study, because we are interested in investing and in making a return. So, we want to do some evaluations of the success of an investment. So, I want to now talk about some basic statistical concepts that we can apply to returns and to other random variables as well. These on this slide are mostly concepts that you've already heard. This is expected value. This is the mathematical expectation of a random variable x, which could be the return, or the gross return, or something else, but we're going to substitute something else. We're going to substitute in what they are. So, the expectation of x, or the mean of x, x is another term for it, is the weighted sum of all possible values of x weighted by their probabilities. And the probabilities have to sum to 1. They're positive numbers, or zero or positive numbers, reflecting the likelihood of that random variable occurring, that value of the random variable occurring. So, I have here--there's an infinite number of possible values for x, and we have a probability for each one, and the expectation of x is that weighted sum of those, weighted by probabilities, of those possible values. This is for a discrete random variable that takes on only a finite, only a countable number of values. If it's a continuous random variable, if x is continuous, then the expectation of x is an integral of the probability density of x, times x dx. I'm just writing that down for you now for completeness. But I'm not going to explain or elaborate that. These two formulas here are measures of the central tendency of x, OK. It's essentially the average of x in the probability metric that we have up here. But this formula is something we use to estimate the expected value of x. This is called the mean or average, which you've learned long ago. If you have n observations on a random variable x, you can take the sum of the x observations, summation [over] i equals 1 to n, and then divide that by n. That's called the average. So, what I want to say is that this is the average, or the mean, or sample mean when you have a sample of n observations, which is an estimate of the expected value of x. So, for example, if we're evaluating an investor who has invested money, you could get n observations, say annual returns, and you can take an average of them. And that's the first and most obvious metric representing the success of the investments if x is the return, OK. People are always wanting to know, they're looking at someone who invests money, is this person a success or not? Well this is the first and most obvious measure. Let's see what that person did on average. You were investing for, let's say n equals 10, ten years, let's take the returns you made each year, add them up and divide by 10. And that gives us an average. I put this formula down as an alternative, because it's another--this is called the geometric mean. This is the arithmetic mean. This is the geometric mean and you're probably not so familiar with that, because it's a different concept. The geometric mean, instead of adding your n observations, you multiply them together. You form a product of them. And then, instead of dividing by n, you take the nth root of the product. And so, that's a formula that's used to estimate the average return of a portfolio of investments, where we use gross return for x, not just the simple return. This geometric mean makes sense only when all the x's are non-negative. If you put in a negative value, you might get a negative product, and then, if you took the nth root of that, it could be an imaginary number, so let's forget that. We're not going to apply this formula if there are any negative numbers. But it's often used, and I recommend its use, in evaluating investments. Because if you use gross return, it gives a better measure of the outcome of the investments. So, think of it this way. Suppose you invested money with some investment manager, and the guy said, I've done a wonderful job investing your money. I made 50% one year, I made 30% another year, oh, and by the way, I had one bad year with minus 100%, OK. So, what do you think of this investor? Well, you think about it, if he made 50% one year, and then 30% another year, and then he lost everything. That dominates everything, right? If you have a minus 100% simple return, your gross return is 0, OK? So, if I plug in, if I put in a 0 here to any of the x's, right, this product will be 0. Anything times 0 is 0. And I take the nth root of zero, and what's that? It's 0. So, if there's ever a year in which the return is minus 100%, then the geometric mean is 0. That's a good discipline. This obviously doesn't make sense as a way to evaluate investment success. Are you with me on this? Because you care a lot, if the guy wipes you out. Whatever else is done after that doesn't matter. So, that's why we want to use the geometric return. These are all measures of central tendency. That is, what is the central result? Sometimes the investor had a good year, sometimes the investor had a bad year, but what was the typical or central value? So, these are a couple of measures of them. But we care more than just about central tendency when evaluating risk. We have to do other things as well. And so, you want to talk about--and this is very fundamental to finance. We have to talk about risk. What could be more fundamental than risk for finance? So, what we have here now is a measure of variability. And the upper equation here is something called variance. And it's equal to the weighted average of the x random variables [correction: realizations of the x random variables] squared deviation from the mean, weighted by probabilities. OK? All it is, is the expectation of the square of the deviation from the mean. The mean is the center value, and the deviations from the mean are--whether they're positive or negative, if you square them they become positive numbers. And so, that's called variance. So, for example, if x tends to be--if the return tends to be plus or minus 1% from the mean return. . . say the mean return for an investor is 8% a year, and it's plus or minus 1%, then you would see a lot of 1's when you squared the deviation from the mean. And the variance would probably be 1. And the standard deviation, which is--the standard deviation is the square root of the variance. And it would also be 1. OK. This is a very simple concept. It's just the average squared deviation from the mean. The estimate of the variance, or the sample variance, is given by this equation. And it's s squared of x. It's just the sample mean. Take deviations of the variable from its sample mean. You have n observations, say someone has invested money for ten years, you take the average return for the ten years and that's x bar, and then you take all 10 deviations from the mean and square them, and then divide by n. Some people divide by n-1, but I'm just trying to be very basic and simple here, so I'm not going to get into these ideas. The next thing is covariance. We're getting through these concepts. They're very basic concepts. Covariance is a measure of how two different random variables move together. So, I have two different random variables, x and y. So, x is the return on, let's say, the IBM Corporation, and y is the return on General Motors Corporation. And I want to know, when IBM goes up, does General Motors go up or not? So, a measure of the co-movement of the two would be to take the deviation of x from its mean times the deviation of y from it's mean, and take the average product of those. And that's called covariance. It's a positive number if, when x is high relative to it's mean, y is high relative to its mean also. And it's a negative number if they tend to go in opposite directions. If GM tends to do well when IBM does poorly, then we have a negative covariance. Because, if one is above its mean, and the other is below its mean, the product is going to be a negative number. If we get a lot of negative products like that, it means that they tend to move opposite each other. And if they are unrelated to each other, then the covariance tends to be 0. And this is the core concept that I was talking about. Some idea of unrelatedness underlies a lot of our thinking in risk. So, if x and y are independent, theyre generated [independently]-- suppose IBM's business has just nothing at all to do with GM's businesses, they're so different. Then I'd say the covariance is probably 0. And then we can use that as a principle, which will underlie our later analysis. Correlation is a scaled covariance. And it's a measure of how much two variables move together. But it's scaled, so that it varies only over the range of minus 1 to plus 1. So, the correlation between two random variables is their covariance divided by the product of their standard deviations. And you can show that that always ranges between minus 1 and plus 1. So, if two variables have a +1 correlation, that means they move exactly together. When one moves up 5%, the other one moves up 5% exactly. If they have a correlation of -1, it means the move exactly opposite each other. These things don't happen very often in finance, but in theory that's what happens. If they have a zero correlation, that means there's no tendency for them to move together at all. If two variables are independent, then their correlation should be zero. OK, the variance of the sum of two random variables is the variance of the first random variable, plus the variance of the second random variable, plus twice the covariance of the random variables. So, if the two random variables are independent of each other, then their covariance is zero, and then the variance of the sum is the sum of the variances. But that is not necessary. That's true if the random variables are independent, but we're going to see that breakdown of independence is the story of this lecture right now. We want to think about independence as mattering a lot. And it's a model, or a core idea, but when do we know that things are independent? Chapter 4. Independence and Failure of Independence as a Cause for Financial Crises [00:26:29] OK, this is a plot. I was telling you earlier about the--let me see, OK, let me just hold off on that a minute. Well, I'll tell you what that was. That was a plot of the stock market from 2000 to 2010 in the U.S. And I'm going to come back to that. These are the crises I was telling you about. This is the decline in the stock market from 2000 to 2002 or 2003 and this is the more recent decline from 2007 to 2009. Those are the cumulative effects of a lot of little shocks that didn't happen all at once. It happened over years. And we want to think about the probability of those shocks occurring. And that's where I am going. But what I want to talk about is the core concept of independence leading to some basic principles of risk management. The crisis that we've seen here in the stock market is the accumulation of--you see all these ups and downs in the stock market, and then all these ups and downs on the way up. There were relatively more downs in the period from 2000 and 2002 and there were relatively more ups from the period 2003 to 2006. But how do we understand the cumulative effect of it, which is what matters? So, we have to have some kind of Probability Model. The question immediately is, are these shocks that affected the stock market, are they independent, or are they somehow related to each other? And that is a core question that made it so difficult for us to understand how to deal with the potential of such a crisis, and why so many people got in trouble dealing with this crisis. So, we had a big financial crisis in the United States in 1987, when there was a stock market crash that was bigger than any before in one day. We'll be talking about that. But after the 1987 crash, companies started to compute a measure of the risk to their company, which is called Value at Risk. I'll write it up like that. I capitalized the first and the last letter, so you'll know that I'm not--this is not the same thing as variance. This is Value at Risk. And what companies would do after 1987 to try to measure the risk of their activities is to compute a number something like this. They would say, there's a 5% probability that we will lose $10 million in a year. That's the kind of bottom line that Value at Risk calculations would make. And so, you need a Probability Model to make these calculations. And so, you need probability theory in order to do that. Many companies had calculated Value at Risk numbers like this, and told their investors, we can't do too badly because there's no way that we could lose--the probability is only 5% that we could lose $10 million. And they'd have other numbers like this. But they were implicitly making assumptions about independence, or at least relative independence. And that's the concept I'm trying to emphasize here. It's a core concept in finance. And it's not one that is easy to be precise about. We have an intuitive idea that, you know--we see the ups and downs on the stock market, and we notice them, and they all average out to something not too bad. The problem that brought us this crisis is that the Value at Risk calculations were too optimistic. Companies all over the world were estimating very small numbers here, relative to what actually happened. And that's a problem. I wanted to emphasize core concepts here. Intuitive concepts that you probably already have. One of these concepts is something we'll call the law of large numbers. And the law of large numbers says that, there's many different ways of formulating it, but putting it in its simplest form, that if I have a lot of independent shocks, and average them out, on average there's not going to be much uncertainty. If I flip a coin once, let's say I'm making a bet, plus or minus. If it comes up heads, I win a dollar; if it comes up tails, I lose a dollar. Well, I have a risk. I mean, I have a standard deviation of $1 in my outcome for that. But if I do it 100 times and average the result, there's not going to be much risk at all. And that's the law of large numbers. It says that the variance of the average of n random variables that are all independent and identically distributed goes to 0 as the number of elements in the average goes to infinity. And so, that's a fundamental concept that underlies both finance and insurance. The idea that tossing a coin or throwing a die in a small number of--it has uncertainty in a small number of observations, but the uncertainty vanishes in a large number of observations, goes back to the ancient world. Aristotle made this observation, but he didn't have probability theory and he couldn't carry it further. The fundamental concept of insurance relies on this intuitive idea. And the idea was intuitive enough that insurance was known and practiced in ancient times. But the insurance concept depends on independence. And so, independence is something that apparently breaks down at times like these. Like these big down crises that we've seen in the stock market, in the two episodes in the beginning of the 20th century. So, the law of large numbers has to do with the idea that if I have a large number of random variables, what is the variance of--the variance of x1 + x2 + x3 + + xn? If they're all independent, then all of the covariances are 0. So, it equals the variance of x1, plus the variance of x2, , plus the variance of xn. There's n terms, I'm not showing them all. OK? So, if they all have the same variance, then the variance of the sum of n of them is n times their variance, OK. And that means the standard deviation, which is the square root of the variance, is equal to the square root of n times the standard deviation of one of them. The mean is divided by n. So, that means that the standard deviation of the mean is equal to the standard deviation of one of the x's divided by the square root of n. So, as n goes large, you can see that the standard deviation of the mean goes to 0. And that's the law of large numbers. OK. But the problem is, so you know, you can look at a financial firm, and they have returns for a number of years, and those returns can be cumulated to give some sense of their total outcome. But does the total outcome really behave properly? Does it become certain over a longer interval of time? Well, apparently not, because of the possibility that the observations are not independent. So, we want to move from analysis of variance to something that's more--I told you that VaR came in 1987 or thereabouts, after the stock market crash of '87. There's a new idea coming up now, after this recent crisis, and it's called CoVaR. And this is a concept emphasized by Professor Brunnermeier at Princeton and some of his colleagues, that we have to change analysis of variance to recognize, I'm sorry, we have to change Value at Risk to recognize that portfolios can sometimes co-vary more than we thought. That there might be episodes when everything goes wrong at the same time. So, suddenly the covariance goes up. So, CoVaR is an alternative to Value at Risk that does different kinds of calculations. In the present environment, I think, we recognize the need for that. Chapter 5. Regression Analysis, Systematic vs. Idiosyncratic Risk [00:38:58] So, this is the aggregate stock market, and let me go to another plot which shows both the same aggregate stock market, that's this blue line down here, and one stock. The one stock I have shown is Apple, the computer company. And this is from the year 2000--this is just the first decade of the twentieth century. Can you see this? Is my podium in the way for some of you? You might be surprised to say, wait a minute, did I hear you right? Is this blue line the same line that we just saw? But you know if Ill go back, it is the same line. It's just that I rescaled it. There it is, it's a blue line. This looks scary, doesn't it? The stock market lost something like almost half of its value. It dropped 40% between 2000 and 2002. Wow. Then it went all the way back up, and then it dropped almost 50%. These are scary numbers, right? But when I put Apple on the same plot, the computer had to, because Apple did such amazing things, it had to compress. And that's the same curve that you were just looking at. It's just compressed, so that I can plot it together. I put both of them at 100 in the year 2000. So, what I'm saying here is that somehow Apple did rather differently than the--this is the S&P 500. It's a measure of the whole stock market. Apple computer is the one of the breakout cases of dramatic success in investing. It went up 25 times. This incidentally is the adjusted price for Apple, because in 2005 Apple did a 2-for-1 split. You know what that means? By tradition in the United States, stocks should be worth about $30 per share. And there's no reason why they should be $30 per share. But a lot of companies, when the price hits $60 or something like that, they say, well let's just split all the shares in two. So, that they're back to $30. Apple went up more than double, but they only did one split in this period. So, we've corrected for that. Otherwise, you'd see a big apparent drop in their stock price on the day of the split. Are you with me on this split thing? It really doesn't matter, it's just a units thing. But you can see that an investment in Apple went up 25 times, whereas an investment in the S&P 500 went up only--well, it didn't go up, actually, it's down. So now, this is a plot showing the monthly returns on Apple. It's only the capital gain returns; I didn't include dividends. But it is essentially the return on these two, on the S&P 500 and on Apple. Now, this is the same data you were just looking at, but it looks really different now, doesn't it? It looks really different. They're unrecognizable as the same thing. You can't tell from this plot that Apple went up 25-fold. That matters a lot to an investor. Maybe you can, if you've got very good eyes. There's more up ones than there are down ones, more up months than down months. There's a huge number of--enormous variability in the months. But I like to look at a picture like this, because it conveys to me the incredible complexity of the story. What was driving Apple up and down so many times? Really a pretty simple picture. Buy Apple and your money will go up 25-fold. Incidentally, if you were a precocious teenager, and you told your parents ten years ago, OK, where you into this then? But just imagine, you say, mom, let's take out a $400,000 mortgage on the house and put it all in Apple stock, OK. Your parents would thank you today if you told them to do that. Your parents could do that. They have probably paid off their mortgages, right; they could go get a second mortgage. Easily come up with $400,000. Most of your houses would be worth that. So, what would it be worth today? $10 million. Your father, your mother would be saying, you know, I've been working all ten years, and your little advice just got me $10 million. It's more than I made, much more than I made in all those years. So, these kinds of stories attract attention. But you know, it wasn't an even ride. That story seems too good to be true, doesn't it? I mean 25-fold? The reason why it's not so obvious is that the ride, as you're observing this happen, every month it goes opposite. It just goes [in] big swings. You make 30% in one month; you lose 30% in another month. It's a scary ride. And you can't see it happening unless you look at your portfolio and see what--you can't tell. It's just so much randomness from one month to the other. Incidentally, I was a dinner speaker last night for a Yale alumni dinner in New York City. And I rode in with Peter Salovey who's Provost at Yale. And on the ride back he reminded me of a story that I think I've heard, but it took me a while to remember this. But I'll tell you that it's an important Yale story. And that is that in 1979, the Yale class of 1954 had a 25th reunion, OK. This is history. Do you know this story? Do you know where I'm heading? So, somebody said, you know, we're here at this reunion, there's a lot of us here, let's all, as an experiment, chip in some money and ask an investor to take a risky portfolio investment for Yale and let's give it to Yale on our 50th anniversary, all right? Sounds like fun. So, they got a portfolio manager, his name was Joe McNay, and they said--they put together--it was $375,000. It's like one house, you know, for all the whole class of 1954, no big deal. So, they gave Joe McNay a $375,000 start. And they said, just have fun with this. You know, we're not conservative. If you lose the whole thing, go ahead. But just go for maximum return on this. So, Joe McNey decided to invest in Home Depot, Walmart, and Internet stocks, OK? And on their 50th reunion, that was 2004, they presented Yale University with $90 million dollars. That's an amazing story. But I'm sure it was the same sort of thing, same kind of roller coaster ride the whole time. And now, we're trying to decide, is Joe McNey a genius? What do you think, is he a genius? I think, maybe he is. But the other side of it is, I just told you what to do in just a few words. It's Walmart Home Depot, and Internet stocks. And the other thing is, he started liquidating in 2000, right the peak of the market. So, it must be partly luck. The thing is, how did he know that Walmart was a good investment in 1954 [correction: 1979]? I don't know. It's sort of--he took the risks. Maybe that's why--I'm just digressing a little bit to think about the way things go in history. But it seems that--I talked about the Forbes 400 people, and I mentioned last lecture about Andrew Carnegie's The Gospel of Wealth, and he says that some people are just very talented and they make it really big, and we should let them, then, give their money away, and it's kind of the American idea that we let