This is the final lecture in my series of lectures this year. And these lectures have been about the big ideas of finance. And so I've talked about five of those ideas already. And this is the final idea, the idea of market efficiency, right? So all these ideas, as I've always noted and before all my lectures, and this is, this is a plug, is basically taken from my textbook, which has six chapters. One for every idea of finance. So everything I talk about comes straight from there. Anyway, so what are these six ideas? The first idea of finance was that of net present value. This is probably the only idea of finance which did not win a Nobel Prize, mainly because it's so obvious that people said, well, you know, you can't pretend to have, you know, claimed to invent it. So that's an idea which no Nobel Prize was given, but the others five have won Nobel prizes. So the second idea of finance portfolio theory in the capital asset pricing model brought a Nobel Prize to Markowitz and Sharp. The third idea of capital structure theory, Nobel Prize to Morlani and Miller. The fourth idea option pricing shows on Merton. The fifth idea, which we covered last time, asymetic information was kerpen and Stalet. But today's idea, the fifth one, the sixth one, market efficiency. Lots of people have won Nobel prizes for this. And what's especially interesting is they won Nobel prizes in several times, several cases for saying exactly the opposite things from each other. So for example, Kahneman is a behavioral psychologist who was the first psychologist to get a Nobel Prize in economics. He said that markets, people act weirdly in markets and that affects prices. Pharma and Schiller got it in the same year in 2013 for saying exactly opposite things, pharma said, the market is completely efficient. We don't need to worry about psychology. This is the way we can treat everybody's completely rational. LER got it for saying, well, people are crazy and crazy people affect the market as well. This is the same year, right? So they're both getting Nobel Prizes, sharing the Nobel Prize was saying completely opposite things. Taylor got it a few years later for saying that Schiller was right. So who is right? Well, today I'm going to talk about farmer's idea. Next year's series of lectures, we'll talk more about Schiller and um, and Taylor. Okay, so what are these other five ideas? At its core, if you remember, finance is just one simple story. The question is, somebody comes to you and says, I want you to give me some money today, and in return, I'm going to give you possibly a huge amount of money tomorrow or next year or a hundred years from now or whenever. The point is, you have to pay the money today, but you'll get the money in the distant future. The question of finances, how much is this promise worth? That's all we want to find out, right? So how do you figure out the value of a promise? The first idea of net present value comes precisely to find out the value of that promise. So it tells, it tells you if you promised something five years from now, what's the present value of that? And you compare it to the value you're gonna pay today. If I asked to pay a hundred pounds, but I'm gonna get back less than a hundred pounds in the future, I don't invest. If I get back more than a hundred pounds, I invest. That's very straightforward. Common sense. Invest only if you get back more than you spent, right? Makes sense. There's a general formula for that. The problem with the general formula is to get those numbers back from the future to today, you need a discount rate. You need an interest rate. So that's the second idea of finance. The second idea of finance asks us what's the right discount rate to use? And remember the people who came up with this idea were Mark overs and shop, and they got an Nobel prize for this. So what did they say? They said, if people come to you and ask you to invest in a company, what do you need to ask yourself? You need to say, why should I give money to this guy? I mean, what could else could I have done with my money? In other words, what's my opportunity cost of investing in this company? By investing in these guys, I've given up the opportunity to invest in something else. So the return on that, something else should be the return, which I'm going to discount these cash flows. Fact. So, but that opportunity should have the same level of risk. What is that level of risk? Well, Markowitz and Sharp said, the idea is that everybody who's smart holds a market portfolio. We hold a portfolio consisting of every diversified asset in the world. So the risk is the core variance with that market portfolio that's called the beta. And the CAPM just says the discount rate is a risk free rate plus the beta times the market risk premium. This what you covered in the second lecture. The third one goes back to the company said, how much should a company borrow? They have multiple ways of raising capital. They can issue equity, they can go to the bank and they can borrow money, they can issue, they can use their own retained earnings. What's the best thing to do? Mullan And Miller said, in a perfect world with no taxes, no government, no lawyers, that's a perfect world. In that case, it doesn't matter how you finance your investment in a not so perfect world taxes, you should borrow as much as you can. But firms don't borrow as much as they can. Why? Not because of yet another imperfection. Those are lawyers. So if you have lawyers, unfortunately firms go bankrupt. There's a cost of financial distress. So firms tweet off the cost of financial distress against the benefits of taking on a tax sheet. The fourth idea of finance is about options. So what's your ability to change your mind, right? So someone comes to you and says, gimme money and I will give you back money in the future. So what you want to say is, can I put in a contract that if I get more information, I want my money back before the term comes through? So what is the value of being able to change your mind once you have made that investment? That's the idea of options. They're contingent investments. They're contingent on something else happening, right? So that's the question. And the thing is, can you change your mind after making the investment? Or can you wait to make up your mind till you get more information? Now, what are the two common assumptions behind all these ideas? One assumption is everybody has the same information. The second assumption is everyone analyzes the information in the same way. So in my last lecture on Asymetic information, I relax the first resumption. That is not everybody has the same information. People have different levels of information. That's why it's called asymmetric information. In a world with asymetic information, what we showed was the people who are hurt by asymmetric information are not the people with less information. That's because the people with less information know they have less information. So they won't pay full price for anything. They'll pay the average price between the good players and the bad products. So the people who are hurt are the people with more information and the superior product because they unable to convince the less informed people that they indeed have a superior product. So the ones who love asymetic information are the ones with more information and an inferior product because they're pretending to have a superior product in order to sell that stuff. And so good players use signaling to distinguish themselves from the badge players. And of course, if you're less informed, use screening to distinguish them. That was everything we have done in the last five lectures. So what are we gonna do today? Well, we are going to relax a second assumption. The second assumption, remember, was that everyone analyzes information in the same way. So what does market efficiency mean? This is a cover of, uh, from taken from the Economist in November, 1997 after the Southeast Asian crisis. And the economist basically said, well, this guy's on the phone. He says, I've got a stock here that could really excel. Somebody overhears him really Excel. Excel, Excel sounds like Excel. So everybody panics the markets panic saying Sell and markets crash. Crash, market prices crash. Somebody says, this is madness. Can't take anymore. Goodbye. Someone's like, buy. Everybody goes crazy screaming, bye. So the question is, is that what the market is like? Is that exactly, is that a market or are people careful? Rational human beings? Cal, calculate MP, V, do all the steps in finance you have talked about for the past five minutes and apply them appropriately. That's what we want to find out today. So what did academics think before 1960? Why 1960? 1960 is where finance, modern finance began before 1960. We were just like the other areas of management strategy, organizational behavior. Uh, well if my colleagues are listening to this on YouTube, I apologize, but they never watch finance videos, so I'm usually safe. But anyway, so but before 1960s we didn't have a way of thinking about these issues. We just basically said, you know, we describe what people do, but we didn't have a theory. So what we were describing, what did people do to analyze companies? There were two approaches. Approach. One was what we call fundamental analysis. What fundamental analysis means is simple. You sit in front of giant computers like this one, you analyze the companies in excruciating detail. You figure out like balance sheets, you figure out the income statements, you figure out everything about them, and then you compute the true value of their shares with the value of their shares is high, but the market price is low. You buy otherwise you sell pretty straightforward. It's called fundamental analysis. The big proponent of this was actually two people in 1934 who wrote a book called Security Analysis. That book is in pub, is in print even today, right? And Warren Buffet wrote a forward written a forward for the latest edition. That's because he was a student of Ben Graham and he attributes all his success to Benham. This is one of the richest people in the world. And he says, that's what you need to do. This is the approach we need to follow. But then you have another group of people who basically do something called technical analysis, also known as charting. The idea here is I don't need to know anything about a company. I don't care who the CEO is. I don't care what business model they have, I care about nothing. All I do is I set up a computer like this guy over here who's stealing his daughter's breakfast, but he's basically written a coding program where all he does is to analyze prices and he sees patterns in prices. Can I find a pattern? Can I trade on it? Can I make money? Literally, it's all automated. You're not doing anything at all. The computer is doing it all for you. The computer needs to know nothing about the company, it just looks at prices. So these were the two big approaches. And until the 1960s, as I said, we had very little to add, but what happened in the 1960s? Well, the first thing was in economics, we came up with this concept of general equilibrium. What general equilibrium meant was we would take into account people's reactions when deciding how to react. In other words, I need to look at, I need to figure out in any interaction how you're going to react. I'm gonna figure out how you're going to react, thinking about how I'm going to react. I'm going to figure out how I'm going to react, knowing that you're going to react to how I'm thinking, you're gonna react and goes on forever. To give you a sense of that, let me start by asking you guys a question. Let's suppose you have a stock price that can range anywhere uniformly between zero and a hundred, right? Could be anywhere. All you have to do is to choose a number that is closest to two thirds of the average of all the numbers chosen in this room. What that means is if everybody chooses a hundred, if your number is 66, you win. But if everybody chooses 66, your, you have to be close to 44 in order to win. If everybody be 50, you have to, your number has to be 33 in order to win. You guys ready to play? Yeah. Okay, let's do it. Go ahead. Use the scan on your phone and then drag your number to anywhere between zero and a hundred and tell me what you will pay. You multiply all the numbers by a hundred. So this is like 24. Excellent. So we have about 45 responses here. Uh, 47. Very nice. Of course, if you're an economist, there's only one right answer that's zero. Why zero? Because the idea is you are anticipating what everybody's doing. So if everybody does a hundred, you have to do 66. But if you're one level smarter, you say, well, everybody's gonna think that way. So they're gonna vote 66, I'm gonna go two thirds of 66, 44. The third level person will say, I know everybody's going to do two levels. They're gonna do 44, so I'll do two thirds of that. And you have to do this backwards until literally the only equilibrium number is zero. As you can see, nobody thinks that way except economists, right? So the question here is, Are we economists in the sense that we carefully analyze everything? Are we human beings? In this lecture, I'm gonna talk about us being automatons. Basically, economists who think this way, and I'll give you a reason why we believe that's the case. So coming back in here, what this is basically saying is the nice bit about general equilibrium theory is that it involves heavy duty math. And math is a really good topic. Why? Because no one can understand it. So if you're an economist and you use heavy duty math, people will say, wow, this guy's so smart, they won't question you so you can charge high salaries. That's when finance took off as a respectable academic field. And that's when finance professors began to make more money than any other professor, because nobody could understand what we were saying.<laugh>. So that's the development of modern finance, okay? So general equilibrium theory at that point made, uh, finance a respectable field. And the idea was, in a market like this, with everybody smart and everybody's analyzing everybody's behavior, what's happening is that it's a market with perfect competition. And in a perfectly competitive market, there is no such thing as a free lunch. This is something I mentioned in my first lecture last year, and I'm coming back to that today in the final lecture. No free lunch. This was the basic idea behind market efficiency. No one gives you something for nothing. So what is the definition of an efficient capital market? The answer is pharma's definition. Pharma basically said, an efficient capital market is a market that's efficient in processing information. That means the price of any security at any time is the value of all the information available at that time. That means the market price will reflect only the available information. This is an interesting definition, and of course, not everybody believes that. Warren Buffet said I'd be a bum in the street begging with a tin cup if markets were efficient. So he did not get to be the smartest, you know, one of the richest people in the world with, you know, um, apparently believing in market efficiency. But we leave that to a side for a second. Let me start with an example. Let's suppose you have a company, the WhatsApp company, which is developing a new bulb, which will have double the lifespan of bulbs currently available in the market, right? So, but is having problems developing the bulb? The question at this stage is, what will the price of a share in the company depend on, right? Obviously it'll depend on the probability that the new bulb will be developed, right? The higher the probability, the more people willing to pay for a share in this company. The sharing in the profits of this company when the company eventually develops a bulb, right? Common sense. Alright, now, today, June the 10th, the company announces that a well-known professor will join the company on leave for his university for one year on January 1st, 2025, in order to help develop the bulb, right? The good news is that professor will improve the chances the bulb will be brought to market one year early. So the professor joins super smart guy, the bulb will developed one year faster than before. The question for you at this stage, is this good or bad news for the company? What do you think? Go ahead and vote. Keep your phones open. I'm gonna ask a lot of questions. Okay. The dominant answer is indeed that it's good news and it's probably most likely good news, right? I mean, the guy's an expert, he's gonna, he's going to develop the ball faster. Good news, which means if you're an investor, should you buy the shares or not? Obviously you should, right? So, which means the share price should go up, that's okay. The question for us is, when does that increase happen? The three dates. Date number one, today, professor hasn't joined the company, nothing has happened. Professor hasn't joined the company, he hasn't developed anything, nothing. Okay? Date number two. January 1st. Next year, the professor had just joined the company but hasn't actually got around to developing the bulb. And then the third date is January 1st. Two years from now, the professor has been with the firm for one year and has successfully developed the bulb. Alright? So the question for you is, when do you expect the share price to go up? So three dates today, January 1st, next year when the professor joins January 1st, two years from now when the professor actually gets around to developing the bulb. Excellent. So quite a few answers. Most of them saying today, but some saying one year from now, two years from now. Oh, okay, let's see what market efficiency means, right? Let's suppose indeed that this is the right answer. So that means two years from now, the professor is relatable, the price should go up. But if you're smart, when do you buy the share? You don't buy it on January 1st. You buy it on December 31st because you, the other guys will buy the share on December, January 1st. You buy it one day early. So you make money if you're smarter, you buy it on December 30th, if you're even smarter December 29th. And in fact you wind your way backwards until literally that's the only day when you can even hope to make money, right? If you wait too, even in one day it's gone too late. Somebody else was already bought the shares before you, the share price has gone up. Okay? So the idea again here is, remember what's special about today? Nothing. The professor hasn't joined. There is no new ball being developed. Nothing has happened. The only thing that's happened is the information about the professor has reached the market. That's farmer's definition. Prices react to information, not to the event. What happens on January 1st when the professor joins nothing, because all the information is right there. You don't need the guy to actually develop the bulb to actually buy the shares, right? If new information comes out, the bulb is not as good as before something else is replaceable, then the price will change again. But again, it's changing on the basis of information, not on the actual event. That's the idea of market efficiency. Okay? So an alternative definition of market efficiency is very simple. In an efficient market, it's impossible to consistently make abnormal returns on the basis of information. Okay? How does this definition make you feel? Let me ask you that. It's impossible to make money on the basis of information. A lot of people are not, don't really care about it one way or the other. Fine. That's good. These are economists. I'm kidding.<laugh>. Okay, excellent. So we see quite a few people are sad and indeed it is a sad thing, right? I mean, why are we studying finance? If there is no way to make money on the market, what's the point? Why don't we just have a good time, right? Finance is a good time, but you know, what better terms? Okay, so if you ask the question, do you like the efficient market hypothesis, most people will say, no way. This is very dismal. This is basically saying there's no way to consistently make money if a market's efficient, right? Unfortunately, not everybody believes this apart from classical finance professors. Otherwise you wouldn't have people out there on the Wall Street and other places desperately trying to make money, right? So why does not everybody wholeheartedly believe in the story of market efficiency? One is of course the truth is much less interesting, right? If you, if you say, I made a lot of money in the market, why did you make money? Eh? You know, stuff happens. Sometimes you make money, sometimes you lose money. People don't like that kind of explanation. We like to believe there's a reason for everything we do. There's some meaning in what we do. Shit happens is not a good, is not a good reason why. Most people like to believe, right? The truth is much less interesting. The second thing of course is there are lots of patterns. We find patterns everywhere. Human beings are pattern detecting machines. For example, how many of you have ever looked up at the clouds and said, oh, that looks like a person with a big nose, or that looks like an elephant. Anybody, right? We all do this all the time. We like finding patterns in everything. So, and stock prices are beautiful places to find patterns on. Like even astrology, I remember on my last flight back from India, I was reading, uh, cosmopolitan Magazine. It wasn't my magazine, it was the magazine, the seat next to me. Someone, no, I'm kidding. It was somebody else's magazine. Alright? Not there's anything wrong with reading Cosmo. But anyway, so I was looking at my own, uh, horoscope and I was taken aback. It described me perfectly. Everything about me was there. I was kindhearted, I was good, I was generous. I was like, this is me. But then I realized I was reading the wrong page. So it wasn't my horoscope, but every horoscope described me. So I was fine. Anyway, let's take an example. This is the VIX index, the CBU Volatility index. Can you see a pattern? I show it to you right here. What does that look like? Superhero movie, Batman, right? That's a rare Batman pattern in the stock market, Okay? But you know, you can find these patterns everywhere. So here's another example. This guy, this guy was extremely annoyed as the Guptas who were running South Africa. So he set up two accounts in a very thinly traded account for his own company and he started buying and selling shares to give a big middle finger to the CEO of the company. And he was arrested as he was drawing the bottom half of that and put a hundred thousand and fine. But yeah, you can find patterns everywhere. But wait a minute, we know of traders who made lots of money, right? For example, George Soro, it's well known that in 1992, Britain was trying to join the European Monetary Union as eventually we've had the Euro. Instead of having the pound, unfortunately, George Soros felt that the Bank of England had set too high in exchange rate for the pound, right? So what he said was, I'm going to sell the pound to drive the price down and buy foreign exchange. The Bank of England was trying to protect themselves. So they decided to buy the pound to keep the value up and sell foreign exchange. The Bank of England ran outta money before George Soros did. So Britain crashed outta the European Monetary Union, which meant that we'd never replaced the Euro with a pound, which then led to Brexit and then you know where we are. But, but anyway, he himself made a billion pounds that year. Okay? That's one example. Warren Buffet, if you had invested $100 in Berkshire Hathaway in 1965, that would've been worth it to to 20 14, 1 $0.8 million, 100 becomes $1.8 million. If it invested in the entire stock market, there'd been about $11,000. This is way better. He, this guy has beaten the market for nearly 30 years. Unbelievable. Or John Paulson. John Paulson was a sort of also ran on Wall Street until he realized in 2008 that the market was overvalued. The housing market in particular was very highly valued. So he created an instrument to short houses and what happened? He made a ton of money When the housing market collapsed, how much money did he make?$3.7 billion. Right? Now for most of us, we think about billions of dollars. They're like, eh, what the hell is a billion dollars? Very difficult to visualize this number. So the way I like to think about is very simple. Suppose I were to give you a million dollars, okay, happy, right? Alright. Now I want you to go out and spend a thousand dollars a day. Can you do it? Probably okay, but you can't take any time off. Even if you are ill. And you're saying today I just wanna stay in bed. Sorry, that's not an option. You have to spend a thousand bucks a day. We do that, of course. Excellent. This is my man. Alright, fine. It means if I give him a million dollars, it would take him three years to get through the money. With a billion dollars. It would take him 3000 years to get through the money. Spending a thousand dollars a day. This guy when 3.7 billion in one year, right? So that's 12,000 years of spending a thousand bucks a day. And while he's spending the money, of course the remaining money is earning interest. So he literally never runs outta money regardless of how much he spends. That's one year salary. But other people are there too. George Soros, 2.9 billion that year. Let's take year after year. This was 2012. Look at the names on that list here you have some names. Ken Griffin, Steve Cohen, John Griffin, Andrea Halon, Philip Falcon, James Simmons names. Okay, let's look at some names there. Ken Griffin, James Simmons, Steve Cohen, Ray Dalio, David Tepper, David Shaw. These are the amount of money they earn on an annual basis. 2.2 billion, 1.7 billion, 1.4 billion 2014, Steve Cohen, Dalio, George Soros, Ken Griffin, James Simmons, same people again, billions of dollars. 2015, Ken Griffin, James Simmons, Steve Cohen, Dave Teer, David Shaw, oh, 2020. Jim Simmons, Ken Griffin, Steve Cohen, you've got, and Andreas Halston, David Shaw. Literally every single year, these guys are earning several billion dollars per year. And remember each year is 3000 years of spending a thousand dollars a day, right? So this is the top 20 in 2022. So the question is, how am I saying the market is efficient? You can't make money, and these guys are making billions of dollars every year. What's going on? How do I reconcile these two together? So what have we done in finance? What we have said is the efficient market hypothesis. The NPV and stuff we did right in the beginning said that investors need to find the value of something. The expected cash flows divided by one plus a discount rate, and they have an expected discount rate over there. They plug it in. The problem with the definition is it doesn't tell you what is the expected return to use. It just says whatever the market uses is, right? So in other words, the EMA just says the market value is the best S available estimate of the true value. That can be more using information set. If we don't know what the information set is, we cannot deny that P is equal to P star. So let's get back to this. So when our markets vision three conditions, condition number one, everybody's irrational, everybody uses the NPV, everybody uses the CAPM. Everybody uses all the ideas in finance we have done so far. Second, sometimes people are crazy, they're over optimistic or Oprah or pessimistic. No problem, as long as they don't behave the same way at the same time. I mean, some people are optimistic, some people are pessimistic, they cancel each other out. So that means that everybody has to behave the same way at the same time. Everybody has to buy shares together. Everybody has to sell shares together. That means if there, even if they rational, they all behave the same way. The smart arbitrage, the big guys like George Soros, like Steve Gohan, all these guys step into the market on the other side and they make the money. Okay, so three big stories over here. So let's go back to that definition. Impossible. Consistently make abnormal returns on the basis of information impossible. Doesn't say that you can never make money, you can every now and then you might make money. The point is, you shouldn't be your day job. That means not gonna do it every day. It's like buying. Um, if you want tickets to Taylor Swift, for example, maybe you'll be getting it now and then, but you won't get it. Every single concert, which it comes through town, right? That's the idea. So those are the words, impossible and consistently. But also, let's look at the word abnormal. Abnormal just says returns are beat a benchmark like the CAPM, which we've talked about. So for example, if you make 10% returns in this market, are you doing well? Answer is we don't know. The 10% is meaningless unless you have a benchmark. If the benchmark says the market made 5%, but you made 10 great, but maybe the market made 20 and you made 10, that's not so good. So 10% without appropriate benchmark means nothing. So you have to have the benchmark correct in order to make a conjecture on what you do. But the most important part is information. And I'm gonna talk about three types of information. They're nested within each other. The first one is all information and past prices. Second is all publicly available information. Third one is all public or private information, any kind of information at all. And there are three definitions of market efficiency. The first one is weak form. It says if you have any information at past prices, ignore it. It's not gonna make you any money. Second one says, if you have any public information about a company, forget it. That won't make you any money either. And strong form market efficiency says it doesn't matter what information you have, you never make any money full stock. Let's look at each of this and see how we prove it. So week four, market efficiency is a rule which says something like, if the stock price drops abruptly, I want you to buy the stock. It's looking cheap, let's buy it. It's like a sale for shoes in a supermarket. Stock prices are not like that. Just because there's a sale, it doesn't mean it's a sale, right? So basically these are totally useless. So let's see how we can actually show this. This is a biological graph on body mass index and body fat. What does this graph say? This graph says there's a positive relationship between body mass index and body fat, higher body mass index, higher body fat, right? That's a typical pattern which you find in biology. How would you translate that into finance? Well, you'd have returns today, returns tomorrow. If you see this pattern existing, what should you say? High returns today, buy because the returns tomorrow will be high. Low returns today sell because the returns tomorrow will be low. That's what you should see if you have returns today and returns tomorrow. And if something like this, does a pattern like this exist? This is the s and p 500 returns today versus returns tomorrow. Can you see a pattern? No way, right? If you saw a pattern, the market would not be efficient because you can trade on that pattern to make money. Now this is two dimensions. Return today, return tomorrow, but maybe return last week was important. Maybe return three days ago was important. How do we test more than two dimensions? Answer, we use a regression. What does a regression look like? Return is expected return, that's your benchmark plus some past return. So it is RT minus one is return in some previous period. The question is, can I use the return in a previous period to explain my return tomorrow? Of course, if you don't like this, you can have more complicated regressions. Return yesterday, return two days ago. You can have even more complicated regression square that term there. Doesn't matter what you do. If the market's efficient in the weak form, none of this stuff should be able to explain that, which means that all you're testing for is this gamma is equal to zero. Very straightforward test. And F did that in 1970. This is a table he did. He did this by hand, by the way, because there were no computers in those days. So it's a lot of effort and that's why he deserved the Nobel Prize 30 years later, 40 years later, right? But what you can see, most of the numbers are close to zero. That means past returns do not predict future returns. And people tried all sorts of complicated things. They look at things like a cup and a handle pattern. If you see a cup and then a handle, the price will go up later, doesn't work. They saw things like a death cross. The 200 day moving average goes above the 50 day moving average doesn't work. Don't believe any of these signals, none of them make money. Okay, so now let's talk about semi strong form market efficiency. What this says is any information, any public information about the firm. So that should be there in the stock price. Let's take an example. The Titanic, right? The Titanic sank on April 14th, 1912. Quick question for you guys. How much should you like the movie <laugh>? Excellent. So a lot of people love the movie, most people sort of 3.5, which is pretty good. I myself hated the movie. Absolutely hated the movie. Why? Anybody you knew that was gonna end well, no, because they left out the most important thing. What was the most important thing? The stock price reaction. They never talked about it even once. It was crazy. I was looking through the movie like, wait a minute, what happened in the markets? Not once, but what happened in the market was actually very cool. So it sank on October, April 14th, 1912. No cell phones, no Twitter, no WeChat, no way of communication. And the the ship's owner, the International Mercantile Marine Corporation, has spent seven and a half million dollars to build the Titanic. But it had insurance for only five and a half million within two days of the ship going down in the middle of the Atlantic Ocean, two days, the stop price dropped by two and a half million dollars. 2 million is exactly the loss of insurance. Half a million maybe for the extra amount. A lot. Who wants to go on a ship built by the IMM, right? So that's right. I thought that's so cool. But it didn't mention the movie even once. Pathetic. Okay? More generally, in a semi strong form efficient market, what you're looking for is basically nothing happening. Information is released, the price should react instantly, and then nothing should happen after that. If the price goes up slowly, a delayed reaction, you can make money if the price overreacts and corrects, you can make money. The point about finances, market efficiency specially is no free lunch. So you should never be able to make money on the basis of any of these things. That means the only thing which is consistent with an efficient market Is this. That's it. Or of course, this, right? Good news or bad news, but you should never see anything before or after. So let's take a look. So this is from a paper written by Jeff Boen, cliff Green called Market Deficiency in Real Time. What these guys did was to look at CNBC's Midday call and it's a segment hold hosted by Maria Omo. And in this particular case, she does this every day and she was talking about a particular company. Every day she talks about a company. What you have on the left hand side will be heard talking about this company called Alza, right? The word alza. Over there on the right hand side, you're gonna see the moko. The white dots are the prices. What I'd like you to do is get ready with your stopwatches on your phone. She's gonna mention the word alza on the left hand side. I want you to tell me how fast it is before the stock price reacts. How many minutes? How many seconds? How many hours is it before the stock price reacts? Okay, everybody ready? Oops, sorry. Okay. And in today's midday call on Wall Street, bank of America Securities is telling clients today that early sales are strong for pharmaceutical company. AL'S News, stop the watch to treat attention deficit hyperactivity disorder. The drug is called Concerta, and it launched on August 21st. The Bank of America analyst, Jerry Repel, has been tracking the launch on a daily basis. He says in the midday meeting at Bank of America, that concerted prescriptions have already surpassed Novartis's extended release version of Ritalin, which was quite successful. He's forecasting $50 million in sales this year and says that he expects peak sales potential in excess of $300 million. How much time was that? 23 seconds, right? That's how efficient the market is. You have less than a minute before the price reacts to information. That's why we say markets are efficient in the semi strong form. Another way of looking at this is by looking at precisely those guys, those guys who are making so much money. Mutual fund managers, right? Remember, mutual fund managers do not claim they have insider information. If they traded on insider information, they will put in jail, right? So they're not allowed to do that. So they say we have only public information and we are gonna analyze it better than anybody. So how do we know whether these guys actually beat the market or not? Well, the answer is very straightforward. Same regression. What you have the return, you have that benchmark, whatever benchmark they're having. And then you want to look at whether they earn a positive alpha, a return above the benchmark. If they earn a return above the benchmark, they're beating the market. The market is not efficient. The question is, is alpha positive or negative? If it's negative, that's not a problem because they're losing money and that's totally fine. If it's zero, not a problem. They're earning it in line with a benchmark. But alpha positive means they're beating the benchmark. So the first study did, did this was 1969 by Michael Johnson, and he said, do they have a positive alpha? And what he found he did with 115 mutual funds, ran 115 regressions to get 115 alphas. Most alphas were on zero before expenses. The average alpha was negative after expenses, it was even more negative. He said, there is zero evidence of fund managers scale. This was 1969. Maybe stuff has changed, maybe things are getting better answer no. Right? So if you look at even the latest evidence, if you go back to the CAPM line, that was the line we talked about in part in the second lecture. Most of these guys are below the line, which means the earning returns, which are less than predicted by that benchmark. They're not making money, they're earning less than you would have got had you invested in the benchmark yourself. So maybe some fund managers do well. So this is another study which looked at, if you beat your benchmark by one year, what's the chance you're gonna beat your benchmark by in the second year? Answer 50% chance you beat your benchmark two years in a row. What's the chance you're going to beat your benchmark in year three, 52%. You beat your benchmark five years in a row, what's your chance? You're going to beat your benchmark in the sixth year, 46%. So what kind of game gives you a 50% chance of winning and a 50% chance of losing anybody? I coin toss. So let's evaluate mutual fund performance using a different approach. Luck. Okay, let's line up every investor in the world. And there are lots of them, right? There's six, seven and a half billion people today. So about one and a half billion in China, one and a half billion in India. People around the world and take everybody who's invest in the stock market, probably about a billion people line them up. Toss a point. If you get heads, you stay in the market, get tails, you leave the market, everybody. Okay? So year one, 1 billion becomes 500 million, two 50 million, one 25 million, 62 million, 31 million, 15,000,007 and a half million, 4 million, 2 million, 1 million. 10 years later you've got one a million people who have tossed heads 10 times in a row. Pure luck. You do this again, 1,500,000, 500,000 to 50, 62 0.5, 31.5, 15 seven and a half, uh, 4, 2, 1 20 times in a row. You have a thousand people who have tossed heads. If you go to 30 years in a row, you could have one person who have done that 30 years in a row, you're guaranteed to have a Warren Buffet by pure luck. It's just the pure number of people who are participating in the market. You have to have somebody who just beat the market. There's nothing inconsistent with luck in that story. Okay? But wait, this is just, you know, I'm telling you the story. I'm, you know, I, I did work in the fund industry and I got to say I didn't perform very well. That's why I'm an economist and not a fund manager.<laugh>, Maybe I have no clue, right? How as a professor though, how might I tell who's the smartest student in my class, right? One way I might do this is by looking at which student the every other student is copying the answers from and says, I don't know who the smartest one is, but the kids know who the smartest one is. So the question is, maybe other mutual fund managers can detect the super superior guys. I'm not, I'm an economist, I just, I don't talk to these guys, but these guys hang out in bars. They say, oh yeah, if you want a mutual fund manager, that man's a god, right? So question is, do they know who these fund managers are? So there's a study which is done by a brilliant professor at Cambridge that me, sorry. But anyway, what we did was to look at every mutual fund manager in the market and we saw which fund manager copied everybody else. So in other words, there's a gap of three quar, one quarter between your holdings and the other holdings. And we said, how are these guys basing that information? If these guys really know who the good managers are, they should the, the guys who they're copying should outperform. They don't find that. What we find is the guys who are being copied are the guys who did well in the past, precisely the same things we use to try to figure out what a fund manager is, good or bad past information, which doesn't tell you anything about future information. So they don't know. We don't know, right? Let's give you a last problem. It's 1943. You are working with a statistical research group here in England, and planes are flying over Germany to bomb Germany. Attrition rate is very high. Most planes do not come back. So your job is to put armor on the plane. The problem with armor. Armor is heavy. Put too much armor, the plane crashes, put too little armor, the plane gets shot down. You have to put armor in precisely the right spots. So you've noticed that on the planes that come back from Germany, the engines have 12 bullet holes. The main body of the plane, the fuselage has 39 bullet holes. The wings have 18 bullet holes, the tail has 25 bullet holes. So where do you choose to put the extra armor, The fuselage maximum of bullet holes, the engines minimum number of bullet holes, the wings or the tail, just basing on the evidence which you have. Okay? This, by the way, is precisely the original word survivorship bias. Because what you're seeing here are the planes that come back, the survivors. So the survivors, if you have 13 bullet holes in your engine, what happens? Your plane never comes back. You have 30 bullet holes in your main body, the plane comes back. So the main body is much less vulnerable than the engines. The engines can bear the least number of bullet holes before you never see them again. The sample consists of only the planes that came back. You never see the planes that were shot down over Germany. So in other words, for us, if you look at a sample of great investors consistently outperformed the market and we conclude the market is not efficient. You're drawing the wrong conclusion. We are looking at the survivors. We don't look at the millions of people who started and never made it right? So in other words, we don't need to know that Warren Buffet beat the market for 30 years. You could have done it any number of ways. We need to know who the next Warren Buffett is. And unfortunately nobody knows the answer to that question. So let's go back to these great investors. There are two parts to this. So this was a graph I showed you football, and the two parts is the yellow part and the pink part. The yellow part is their performance fees and the pink part are the gains on that personal investment. What does that mean? Well, let's take a look at, say even 2021. Look at Ken Griffin. The green stuff is a fun performance fees. The pink stuff is gains on personal investment. What that means is every year when they say these guys made billions of dollars, the two parts it, one is the money he made running his fund. The other is the money he made on the previous billions of dollars he already had. And if even if you earn 1% on a billion dollars, that's a ton of money. So moral of the story is how do you get to be a billion? How do we get to be a, you know, a billionaire Start with a billion dollars. That's why they say the first billion. That's always the hardest <laugh>. Okay, so the last part is strong form market efficiency. What that basically says any kind of information public or private is in the market price. How is that possible? If private information, nobody knows this. Let's take an example. Let's say we are in Cambridge, right? And I would need a couple of people, uh, would you like to be a volunteer? Sure. Okay, so you are the CEO of a company, okay? And I have here somebody who wants to be the CFO of the same company. Now I have to point out, Hugh Purr is a friend of mine and he's also a black belt in Aikido. He's a big, huge guy. He's terrifying on the dojo floor. So he's your CFO, okay? Anyway, you're both going for a punting on trip on the cam. And Hugh confesses to you. He says, look, the company is losing money. And by sheer coincidence, I've taken the last million pounds of the firm's money and I have it in a bag right here. I'm telling you this because you're a friend. I am going to the punt arrives on the other side. I've got a taxi waiting for me. The taxi will take me to the airport. I'm going to South America. You will never see me again. Now, this is private information. She's the only person who's heard this. It's in a punt in the middle of the river. Can, no one else has ever heard this information. How does it get into the stock price? Like if your market is efficient in the strong form, it should be there in the stock price. But how he's gone off to South America, she can't, he's a big guy. She can't hopefully. Are you a black belt at something? No. Okay, so you can't hold him down and keep him there until the police arrive. So he's gone with the money, right? He, no one's going to hear from him. How does your information get in the stock price? The answer is, if insider trading is not illegal at that time, all you have to do is she calls a broker. She says, sell all my shares right now. But what does a broker say? Broker said, wait, she's the CEO, the CEO's desperate to unload her shares. Is this good news or bad news? Definitely bad news, right? So even before the broker executes their order, what's the first thing the broker's gonna do? Sell all his own shares. Call all his friends to tell their shares. It doesn't matter what the information is. The moment you recognize an insider is buying or selling, that's information for the market, right? That's why the market might be efficient in the strong form. Unfortunately, most insiders are try not to be dumb. They sell their shares through, you know, friends, family, whatever. So it's difficult to find, you know, um, difficult to find cases when it's obvious that this is an insider who's trading. And that's why insiders do make money, which is why it's also illegal, right? So that's the one thing which you cannot stop, but semi strong form market efficiency, you can pretty much say yes, the market's efficient, weak form market efficiency. You can say yes, the market's efficient, but strong form insider information will still make you money. And that's why you should not do it because you'd get put in jail. Okay? So big takeaway. For a long time finance, academics thought the market was efficient. Competition between traders would drive prices to fundamental values and irrational traders will be completely driven outta the market. Unfortunately, many people are realizing now that this is not true. Investors make systematic mistakes and they affect prices in ways that are difficult to predict. That will be the subject of my next year's series of lectures where I talk about the human side of finance. How do people actually behave? All I've talked about in these series, series is about what the theory says we should do. Next year's series will be all about what do we actually do? How does it, how does the market actually work? So what have we done this year? Six basic ideas in finance. NPV portfolio, theory, CAPM, capital structure, option pricing, asymetic information, and market efficiency. Today, all the ideas fit together. If any of these ideas don't work, nothing works. Right? All have to work. That's why finance is so elegant. Everything fits together. But at its core, finance actually only has one big idea. No free lunch. Nobody gives you something for free. If you take that away, you will be a wealthier, more cynical human being. B <laugh>. Okay, thank you.