The 2008 Financial Crisis: A Behavioral Finance Approach

we are going to talk about behavioral finance essentially today and we’re going to try to relate that to the financial crisis according to Chairman Bernanke’s what caused the financial crisis of 2007-2008 was the nobility vulnerabilities before the crisis in particular the bad mortgage products and the practices of course the real estate bubble so we’re going to look at this real estate bubble and how can bubbles can be explained and what are all the different theories that have been advanced to explain how bubbles form and then there are some amplification mechanisms and some very large failures of banks of insurance companies and we’re going to try to understand how these amplification mechanisms can work so we do concentrate today on behavioral finance aspects and this is basically a way through ecology and finance meet you did have the reference in your syllabus but one article by Nicholas Murray’s but the psychology and the financial crisis of 2007-2008 before we start we have behavioral finance what I’d like to do is to remind you of one of the main pillar of standard finance which here is the assumption of efficient markets and I’m pretty sure that all of you already heard about that is that correct but maybe some of you haven’t yet so I’m just going to recap very very rapidly what it is to assume that markets are efficient basically it means that there’s no way you’re going to find a $20 bill when you walk in the street why is that because somebody else already picked it up before you when markets are efficient all of the relevant information is automatically and instantly reflected into the prices on the market so this is a very strong assumption and this is an assumption that academics in finance have been working on for a very long time and basically what it says is that you shouldn’t waste your time reading The Wall Street Journal because anything that you would learn in the worst-hit journal is going to be already embedded into the prices I’m not advising that by the way you shouldn’t waste your time looking at past prices and that’s a very large category of people on the markets looking at past prices this is called technical analysis so technical analysis is trying to predict future prices by looking at the past prices and trying to infer something from the past and the way prices are going to behave in the future so this would be also a waste of time with the assumption of efficient market and so on of course when we’re talking about behavioral finance we’re challenging decide of efficient markets and what I’d like to do is to start with a very simple example that is a real one that has been run by financial times in long time ago 1997 and this was a contest suggested by Richard teller which are teller ears an economist and one of the founders of behavioral finance and basically the contest was asking readers to choose a number between 0 and 100 everybody would choose a number and then Financial Times would compute the average number and then the winning number would be the processed integer to 2/3 of the average entry so let’s try to figure out what number you should pick if you’re playing this game assume that everybody first is choosing a number at random if everybody is choosing around a number of random what’s going to be the average number 50 so 2050 should be 33 so everybody should pick 33 because everybody can do this calculation but then if everybody picks very free what would be the new average number for afree that would be the average number but 2/3 of 33 would be 22

so everybody should pick 22 etcetera everybody can figure out that the winning number should be at the end what do you think what actually because 2/3 of 1 the process into the reason what so everybody should know because we’re as humane when markets are efficient but also everybody is very smart and everybody can do these calculations so everybody should choose one as the winning entry what do you think was the winning entry you think it was one it was actually 13 what well different explanations are possible first expedition will be to say where everybody is very smart and we will defeat one but few people were actually choosing numbers at random because they were not smart enough to do these calculations and then it actually took the average and then the 2/3 of the average ended up to be 13th and then you can say where maybe people are even smarter than that maybe people will anticipate that other people might not be smart enough and are going to make mistakes so they shouldn’t pick one but pick a higher number than one because they need to anticipate mistakes of other people on the market and even if you’re really smart and you can figure out that it’s one the winning entry it should be one you’re going to pick up a number that is higher than that and of course if you do that you also pour the number up at the end this is a clear example that markets are not always efficient and that the winning entry is actually that one or tell through that so I think you know you can enter something like that well it needs to reflect it to market in the way that it needs to reflect the information that is available on the market and here you’re right in the way that there’s no exchange in this market that’s a very rough example well the only thing pushing you to be rational about your entry is ready to pick up the winning number so that’s a rough example and that’s an example where you see that the outcome of the game is that what would be rational if everybody was thinking exactly the way they should a lot of our examples exist and there is a huge case that is made against market efficiency on the market the first one and there would be a very long list of that so I just picked some of them the first one is that stock prices are too volatile why is that where if you took some finance courses before you know that stock prices should reflect present value of future dividends if you look at these stock prices that means that the volatility of the stock prices should be reflected by the volatility of the dividends and when you’re doing some more elaborated study on that and and this is something that you can sense from the markets themselves the volatility of the dividend is pretty low while the volatility of the stock prices is always extremely high so there is some discrepancy here between dividend volatility and stock prices volatility stock market bubbles exist well you’re all aware about that of course we can talk about stock market bubbles we can also talk about real estate bubbles we can talk about the late 90s with the stock market bubble for the tech stocks technology stocks were extremely high and then it blew one day and all the prices went down investors mood so we’re going into psychology here investors mood may drive prices away from the fair value the real value is usually called the fair value of the stock and depending on your mood if you’re more optimistic if it’s sunny are there there’s been some studies on that it seems that the markets can be more bullish with the Sun and if it’s a rainy day the market tends to be more bearish for no other reason than that so the

mood can actually have a direct impact on the markets which of course it’s not rational as we like to call rationality so without today’s questions looking at four different questions and I’m going to spend way more time actually on the first one and then lesson this time with all these questions the first one is to explain market bubbles and I’m going to try to find a rational explanation to market bubbles but then I’m also going to try some psychological explanations to market problems then the second one is why did the financial institutions take such large exposures Chairman Bernanke talked about that the exposures of these financial institutions were extremely risky and it didn’t seem rational to have these exposures that would potentially get this institutions bankrupt so how can that happen can we find some behavior explanations to that then what are the amplification mechanisms when the crisis comes what triggers an amplification of the crisis and then finally a little words about regulation and behavioral issues so I’m going to start with market bubbles and I’m going to actually look at two different classes of theories the first one is scored a belief based theory and then the second one will be a preference based theory so the first class of theory is based on individuals beliefs on what should happen on the market while the second class will be based on their preferences let’s start with an example and that’s the way I am going to structure here the lecture I’m always going to start with an example and then we’re going to try to understand what is the psychological principle behind it suppose that you have a stock that is currently traded only by the students in this class half of the class maybe this half of the class believes that the price should be $50 this half of the class believes that the price of the stock should be $30 you know that the way prices are determined by the market is for the law of supply and demand so having different beliefs about what is the fair price is a good driver of the markets I’m assuming here that short sellers are not allowed does everybody know what is a short sale on the stock market no I see some no yes or no so I’m assuming that some of you do and some don’t let me try to explain that very rapidly when you believe that the price should go down what you would like to do is to sell the stock but it’s not always possible because maybe you don’t own the stock in your portfolio so how can you sell something that you don’t own what you do is actually that you go and borrow this talk and then you sell it and later on when the price goes down as you believe suggested you will buy it back on the market and give it back to the power to the lender so that’s the mechanism for being able to sell something that you don’t sell short sales are actually very important on the markets so what’s going to happen here if short sales are not allowed well the people who believe that the price should be $30 if the current price is $40 they would want to sell but short sells are not allowed assume that nobody owns this stuff in the classroom so what’s going to happen is that the price is going to be driven only one by by one class of individuals on the market these are the bullish investors the ones who believe that the price should go up so what will probably be the equilibrium price in that particular case would you think 50 it’s going to go up and only the bullish investors who believe that the price will go up actually going to drive the price on the markets so the price will then reflect the views of the bullish investors army clearly that gives a rational explanation of pocket

bubbles when you don’t allow short sales only investors with bullish expectations on the prices will drive prices well there’s a clear example of that which is with real estate with real estate you cannot short sale in a short sale you cannot borrow a house to sell it on the market and then repay it later on it’s just that something possible on the market so with real estate market by definition and construction the way it functions real estate market is more prone to market bubbles that’s the first explanation and it’s actually not to behavior explanation so I still need to give you some rational explanations here though that’s not the intent of the lecture today the intent of the lecture is ready to go to the behavioural explanations so we’re going to move the second belief based explanation and I’m going to ask you a question here what is the number of countries in Africa as a percentage of all UN countries is it more than 7.5% or less than 7.5% do you think so it’s more you would choose a you choose a Emily a a not giving you the response right now this is why I didn’t want you to have the slides in advance because that would be cheating what is the number of countries in Africa as a percentage of all UN countries this is the same question but I’m not giving you two possibilities here what do you think what did you say seven and a half like 6% okay yeah they did 12% now I’m giving you the answer 24 percent so you were pretty good most people respond to that but 10% 12% 15% what is the psychological bias that I wanted to highlight here is the fact that there’s some anchoring just because you had these number before of 7.5% is going to drive your response for the second question because you have that in mind and maybe that’s about habit from school actually that you know that when you have an exam there’s a right answer when you have multiple choice there’s a right answer in there right so I was giving you a multiple choice initially maybe and you thought that 7.5% had to do something so there are some anchoring there’s some mental attachment to a specific number or to specific parts why is it important for market bubbles where when house prices are going up 10% every year for a very long period of time people tend to think that 10% is the right number and they tend to be attached to this particular number and they tend to think that it’s going to go on forever with this 10% the current flipping contest that’s a pretty cool example so we’re going to assume here that there are six billion people on this planet I know it’s there for now more those and we’re going to assume that everybody’s playing everybody is betting $1 on this game heads you stay in tails you’re up very simple game one person every every every everybody I’m sorry is flipping a coin here and the game is very simple you need to get heads as long as possible to be able to stay in the game so after one round there’s basically three billion people who are still in after 10 rounds there’s about 6 million people that are still in the game imagine you’re flipping the coin and you get 10 heads in a row it’s pretty hard to get right so you got rid of a lot of people here only one thousands of the people are staying in people believe start to believe that they’re very good flippers and maybe they’re not just

lucky maybe they just know how to flip a coin after 20 rounds around 6,000 people on your left you have to flip a coin 20 times in a row and heads and get heads blackhole’s becomes heroes and then you continually after 25 rounds 180 flippers are still around on average of if the game stuffed now you’re just going to share all of the initial pets you would get more than 33 million dollars these people write books about conflict they’re so good about conflicting that they can take advantage of that right they’re going to explain the strategy they have and how they can flip a coin so they write books about that and there are techniques and there are strategies etcetera it probably takes about thirty two rounds to actually end again with a maximum of two winners so they would split the six billion dollars finishing what’s the question here if you’re imagine there’s only one winner is the winner actually good at flipping or is just is it just pure luck cheering we’re assuming that there’s no way to cheat so assuming that there’s no way to cheat is it just pure luck but it’s very small probability right to get that it’s about one in six billion to get heads thirty two times in a row so is it just luck so if we’re saying that this way right we can think that on the markets sometimes it’s just pure luck when you play the lottery and you get the winning lottery ticket maybe it’s just pure luck was probably actually at least with the flipping contest you can think that you have something to do with the lottery tickets it’s a little more difficult well is it that I wanted to show here is the matter of a over extrapolation there’s anchoring and there’s over except elation when you’re good at flipping you think that you will continue to be good at flipping when high prices are going up are they going to go up forever people would think so and that would wait matter they want to be in they don’t want to miss that opportunity they see house prices going up they do want to participate in that and they want to enjoy the ride like everybody else so that’s for the second belief based explanation here third belief based explanation you have another example looking at the Dow Jones Industrial Average one of the main index on the market 2003 that’s pretty old number you want to do all the calculation so that’s where I used the market closed at ten thousand four hundred and fifty for the price index you know now you know at least that this does nothing who’d reinvested dividends so it’s only about the prices of the stock the way the index is calculated it never includes the investing of dividends assume now that instead of not including the reinvested dividends we were to include the invested dividend since the creation of the DOE Jones Industrial Average so it was created in January 1929 and at that time its value was 300 what do you think would be the value of the index at the closing of 2003 if we were to include all of the reinvested dividends I’m asking you to give me your best guess and then a low guess and then a hiatus yes just the actual amount of dividends so whatever it was defined because the definition of the index is changing over time depending on the different companies that are composing the index whatever it was defined way of just

reinvesting dividends that’s all does anybody has a best guess yeah just to guess that’s fine 60,000 okay so that’s the best gets I’m assuming that everybody would come up with a different one but it’s very doesn’t matter so it’s just against right 60,000 what about a low gets 20 and what about our high gets 150 thousand and you’re 90% confident that the answer lies between your low and high days okay that’s the answer 250 1000 most people are first not well calibrated but at least it’s not an easy question anyway it’s a lot of calculation to come up with the number but more and that’s just what you said overconfident there’s another example of overconfidence how good of a driver are you you’re driving in here right are you above average or below average as a driver who’s above average who’s below average when we ask this question to college students 82% of college students are above average good illustration of overconfidence right and don’t worry it works with graduate students as well I tried that so that’s our confidence and more than that whenever you are trying to rank the best guess although you didn’t spend too much time on that we were kind of rushed in that but whenever you’re putting some efforts into providing your guess and sometimes it’s a little complicated you need to do calculations you need to figure out exactly what the question is you need to see what’s coming in the index definition etc etc whenever you’re putting down some efforts that there’s a natural tendency to over estimate the precision of the focused why because you put some efforts in that there’s no way you’re going to be that wrong so the more efforts you’re putting into the forecast and the more you’re going to assign pretty high probabilities that your own forecast is actually W so now we’re going to switch to preference based the nation’s preference pays explanations the first one we’re going to consider the following situations first situation you toss a coin again heads you win $200 tails you lose $200 who would take you can good ray only one person if I had told you to $2.00 probably you would have done it right but $200 might be a lot of money right and on average when you get 0 nothing right so it’s a lot of reals and it’s a lot of money so most people wouldn’t play them and this is what’s happening in this class today assume now that you just won $1,000 and I’m offering you the same gap so you just have in your hands it’s important to have it in your hands right it’s deal so you have it in your hands you have $1,000 that you just won and you’re asking to play this gamble who’s going to play so not everybody but way movie right so what are we seeing here we’re saying that after experiencing some games although it should be exactly the same thing right the gamble by itself is exactly the same one but because you just experienced some gains more people are willing to take more risk you know that casinos not that very well right casino is cannot be happier when

somebody is winning because they know that this person will come back forever after the person wins so you always remember that you don’t remember the times when you love statue do you try to forget about that but the time when you win you will remember that and you will advertise that to everything right so I went to Vegas and I gets that amount of money of course that’s very important because when you live in a house and the price of the house is going up and happen up and you’re checking on zero calm every day the price of your house and you see that the price keeps going up where you want to take more risk because you’re just winning by living in a house in some cases in a lot of cases actually people were making more money by buying your house living in our house than going to that job every day and of course they want to be in the right so they are going to be willing to take more risk what does it mean being willing to take more risk on the real estate market it means that maybe they will buy sell their house and get a huge mansion and so they can win even more money or maybe they will stay in their house but they will start buying more houses on the market just to enjoy the ride with everybody else second preference pays explanation lottery tickets kind of talked about it already you know that it costs $1 I think last week there was a huge lottery going on very well so assume probability of winning is 1 over 100 million and when you win you win big you win 60 million dollars should anybody buy lottery tickets what do you think silly people saying yes and they’re not saying now if assume you’re rational rational means that look at the return here that you’re making on average what’s going to be the return on this investment you’re investing $1 right what’s going to be the return it’s going to be negative when negative right there’s only 1 over 100 million chances to get 60 billion dollars right so this is very negative return is there a risk associated with this negative return huge risk standard deviation right is going to be huge in other words what you have here when you look at that as an investment you have an investment here with a very negative return and a lot of risk well if you took any finance course you should know that this is not something that it’s not on Jenna in general right and on the financial markets were assuming that when investors are getting returned it’s because high returns is because they’re accepting to take somewheres but they want to be compensated for the risk that they’re taking so the more risks that we take the higher the return on average they will require from this particular security obviously with the lottery ticket it doesn’t work but obviously at the same time a lot of people are buying lottery tickets so we’re kind of in trouble right we have some rationality definition that tells us that nobody should buy any lottery ticket and then in practice a lot of people are you know people like like a brand you know that gives the charity and all the money from all the money that’s given to the government which is about 50% let’s get it back to the states so that’s a positive outlook on that which this model doesn’t take into account also when you buy a lottery ticket it’s not sixty million dollars or zero dollars if you get like two numbers on the Powerball then you get part of the money so sometimes you bet and then you do come out even that’s why this is simplified but I can assure you that the return is negative so even if this is simplified the return is still negative I am Not sure that people are buying

lottery tickets for charity purposes but you know you can convince me of that but I’m not quite sure it works that way although you write at the end maybe that’s a positive outcome these lottery tickets did I have another question yes and this is the good part right if you’re winning ones or if you look at the person winning once you think that you can be this person so you’re going to buy more retro tickets so it’s a good marketing example I suppose for the governments did you have a question yes anyway what I wanted to show here was that there is a psychological factor which is that the brain tends to other weights low probabilities basically but there’s two things in here first $1 is very small amount of money so people would consider this $1 as planned money even if they don’t have a rational behavior they can play with some small amounts but also one over 100 Millions probability it’s something that the brain has a very hard time to comprehend so this is such a low probability that probably it wouldn’t make any difference if I were to tell you one of her one minute for the probability it’s so low that we are having a very hard time understanding what it means and of course this is not advertised also when you buy you a lottery ticket it doesn’t sound a ticket what is the probability of your winning it does okay I need to buy one I’m too rational I never bought so sorry for that another example was the example of the tech stock bubble technology stocks new technologies it’s very difficult actually to help my hand whether these technologies are going to work on that and the probability of them working is probably very low so one of the factor that we can actually use to explain the tech stock bubble is the fact that these technologies have lower probability to actually succeed there’s a pretty high probability that these firms will go bankrupt at the end and and investors of the market would not apprehend that so this is the second preference based explanation I have a third one we have a lottery example another one this time we are going to assume that you have your lucky numbers you have been using the same numbers for of your birthdate in there you have whatever numbers are important for you you’re using in them and you have been playing every week for Mom from years maybe the same numbers all the time you have not yet well maybe one there but not yet a friend comes to you and suggests a different set of numbers tells you where your lucky numbers are not good I have better lucky numbers you should play these numbers these are going to make it win you’re going to switch numbers it doesn’t matter so you’re going to stay with your numbers right why is that called the fear of weak weapons you don’t want to be grant and there’s actually in psychology two different types of regrets the first one is called the regret of omission with whatever mission means that you’re sticking with the old numbers and the new ones with your friends no good but you said too bad sorry regret of commission this is you switch to your friends number and your old numbers we end that’s extremely painful right regret of commission is way more painful you don’t want to

regret so when all your friends are making more money just by living in their house rather than you going to work every day and with all this pain every day you want to be in the right with them you also want to buy a house and actually be able to enjoy the ride and make money on your house make money in the real estate market you want to buy more apartments you want to be there and make a lot of money with them you want to buy technology stocks when these prices are going up forever until one day the bubble burst and then the decline is very happy so that’s another explanation here for bubbles and this is we have the fear of regrets now we are going to move to the exposures that we’re the positions that were maintained by financial institutions so we’re going to try to understand the rational explanations first and then I move to behavioral explanation why did the bank’s the insurance companies were keeping such large exposures so much risk in the performance first reason and that’s something probably that you have in mind is called the bad incentives with what is the bad incentives reason traders executives in company we’re actually compensated in very large parts in particular with the bonuses on the profits that they were generating for the company so when the positions were actually profitable they would get a share of that if they were making losses they didn’t have a bonus but they wouldn’t have a negative bonus so they wouldn’t have to a part of the losses so all of the incentives for the traders for the executives were to take as much risk as possible because if you’re taking more risk it’s the first principle in finance right when you’re taking more risk on average you’re going to get a higher return from the financial markets so if you get a higher return on average there’s more chances that you’re going to get huge bonuses that’s what I call the lack of proper compensation scheme and this is a story that’s been in the news all the time right to explain these huge exposures so that’s the first reason that we can advance which is a very rational one second one is called the bad models with what is the bad models with a reason it says basically that the models are not well designed that the clowns you know who are the ones in the back people actually working on these models implementing these models for the trading rooms they were accused of implementing bad models there was too much capacity a lot of exotic instruments nobody knew exactly what they were where they were hidden to little understanding of what was going on with these models and then the ratings of these exotic securities Chairman Bernanke talked about that right with the CEOs the c.d.s on the market the ratings by the rating agencies were in general very high triple-a ratings for exotic securities and you’re not we’re not quite sure about the amount of risk that was in them that’s the bad models reason is it always the case that we’re going to get rid of the models or together on the markets no way it is just not going to happen but what we want to make sure is that we understand that we need to really understand the markets we cannot use models on the market without complete understanding of these models so whoever is using Morrow’s need to understand them and of course this is where education becomes even more important so this is something that comes back to the business schools I

believe in the way that we need to teach these models before people go on the market and actually use them because we want to make sure that everything that is implemented out there he is completely understood by the people who are using these models there are the rational reason the bad luck reason what is a bad look with it it means that I don’t know if you heard about this book by the simple lab called Black Swan and it basically talks about the impact of highly improbable things so this would never happen her ability is extremely low but it just happens so this was basically the story that was given by LTCM remember our TCM long term tableau the hedge fund that went bankrupt it was just a series of bad luck at the same time happening at the same time the probability of these events happening are so low that nobody could anticipate that it would happen a series of events catastrophe is always a series of events right the series of events that would happen with extremely low probabilities is just bad it’s a little difficult to be completely convinced by this story actually in the case of the financial crisis so I don’t know if I go with that but this is something that has been advanced in the literature so I wanted to mention it I want to provide here behavior explanation and these behavioral explanation is about cognitive dissonance and I want to start with an advertising campaign some of you knew that video already right I could see that some of you knew what was going on and what was coming up you were expecting an advertising for the car right nice car nice environment the cow goes behind the trees you’re expecting the car to come out of the trees and everything’s going fine and then you see a monster coming up screaming what is cognitive dissonance dissonance this year’s about the feeling of discomfort that you sensed when two inconsistent folds or ideas are coming together so you are not expecting the monster right the monster in a different setting maybe you wouldn’t be afraid of that because you were expecting something going on that was very smooth and so and just the monster so this is that makes you extremely uncomfortable and you will have to learn how to deal with that the most standard example of cognitive dissonance is about smoking I like to smoke I know that smoking is bad smoking is bad for the health I can die from it but I still like to smoke so I convinced myself that when I know these people he lived here 95 years old he smoked all his life it was perfectly fine I don’t want to think too much that smoking is bad or don’t know it’s written under the secret spots to remind you all the time that smoking is bad right but these two folds are conflicting this is called cognitive dissonance what about our financial crisis how do we are cognitive dissonance in our financial crisis traders bankers knew for the most part I’m having a very hard time to believe that they didn’t know that their positions were extremely risky they knew about they just didn’t want to see them so they knew that their positions could actually bankrupt their

companies but they liked making lots of money right at the same time they also wanted to have a very good self-image everybody wants to have a good self-image right everybody wants to believe that his job is valuable to society there’s nobody out there that would say I don’t care if there’s a global economic crisis nobody would say that and it and it’s because of me nobody would ever say that right so these are two conflicting folks they can actually bankrupt their company with their positions but at the same time they don’t like thinking that they’re bad guys so these two thoughts are contradictory and this is what we call cognitive dissonance how do we solve that how do we deal with it the way most people deal with cognitive dissonance is by some manipulation of their beliefs so as I told you when you smoke you want to remember the very old person who smoked all their life and it didn’t do anything to them when you’re a trader and you have a very large risky position what are you going to do most probably maybe you’re not going to assess the risk of your position anymore maybe all the tools you have at your disposal for risk assessment you’re not going to use them anymore so you’re going to hide that for yourself not for the other people but for yourself you need to convince yourself that what you’re doing is not bad so it’s a matter of self conviction here and of course it was made even easier because of the complexity of the products it was very difficult it was all embedded right you had all these CD or CD s that were embedded in each other and because they were all embedded with each other it’s even easier actually to pretend that you don’t know the risks that is attached to that because it becomes very complex so there’s some beliefs manipulation here and and of course you see that with these beliefs manipulation you can explain a lot of the exposures risky exposures that we’re out there I’m going now to the third section here about the amplification mechanism we’re assuming here that the crisis began and we know that the first trigger it accelerated very very happy I was actually teaching in 2007 the 4 of 2007 and horror course in finance here and I had lots of trouble to teach what I was supposed to teach in the syllabus because every time I went to the classroom there was a new huge event on the financial markets that I needed to talk about and at the same time I needed to cover whatever I was covering right because these are these are the background for the sighted students it was very important that I would cover that but this was very challenging time for me that case just teaching the syllabus so let’s try to understand these amplification mechanisms and I’m going to refer here to the Ellsberg’s paradox it’s a very non paradox in economics we’re going to assume that we’re going to draw a ball from a bag and whether we have a big bag and it contains 50 red balls and 50 black box and you’re drawing a ball from that if you get a red ball you get $1,000 if you get a black ball you get dividends how much are you willing to pay to pay to play this game who would pay one dollar for that would pay ten dollars who would pay $100 $200 250 300 350 that’s interesting we want to read first all the way to 500 let’s say like an

average here let’s say that 300 is the average so $300 play this game okay I’m repeating the game the only difference here is that I have a bag containing 100 balls some of them are red some of them are blocks but I don’t know how many Reds I don’t know how many but the only thing I know is that the number of red and blacks is random completely run if you draw a red ball you get $1,000 if you draw a black ball you get you how much are you willing to bet $1 10 using lots of people here hundred 200 would you bet on average more or less than the in the previous case let’s everybody kind of agrees on that right you would bet let’s first people actually bet less although the same should actually be the right answer mathematically if you compute that mathematically the same should be the right answer because the number of red balls is random so if you take all the cases and you assume that and then you compute whatever it is you should find exactly the same number that risk even though the app even though the average of the expected would still be fifty rather than fifty black there’s an element of risk there that actually does not any other element of risk I’m going to convince you with doing something new I’m going to flip a coin no heads you’re going to draw a red bow and get $1,000 tails this is when you draw a blackboard that you get $1,000 so depending on the results of me flipping the coin you’re going to have either the thousand dollar with the red or the black ball how much are you willing to bet same thing then initially $300 on average we said for the class but that’s interesting we’re adding some uncertainty to the uncertainty and then it resolves the uncertainty in other words by adding more uncertainty with me flipping a coin here I can actually go back to this situation when I had 5050 so what is it that we don’t like in that psychologically because this is a psychological issue psychologically but we really don’t like is what we call the difference between risk and uncertainty however one of the first time that you heard that there’s a difference between risk and uncertainty it’s a matter of definitional so what would be risk risk is quantifiable but as it mean it means that you can assign probabilities to it so it’s the first case you know that the probability is 1/2 so it makes you more confident into going on and again when you can actually assign probability uncertainty you cannot assign a probability so it’s not quantifiable people don’t like uncertainty you like to be able to feel in control you like to flip the coin because you can feel that you know how to flip the coin you like to play blackjack because you make some kind of decision when you’re playing feeling in control is something that is more valuable which means that when uncertainty becomes more important on the financial markets people tend to freeze and this is exactly what we observe doing the credit crunch when credit was no longer available nobody knew what was going on everybody lost track of the probabilities of events and in that case everybody’s freezing and just waiting to see what’s going on this

is what we call ambiguity aversion we don’t like ambiguity so we’re willing to take risk as long as we can measure it when we cannot measure the risk we’re more in trouble and verification mechanisms suppose another example that you face a choice between rulers of 7500 or taking a chance that there’s a 75% chance you will lose 10,000 and 25% chance you will lose nothing when you learn better that’s right you most people would take the chance yes David oh it would actually be the rational decision but I’m not asking you for with your rational decision you understand that self but we’re doing today right I’m asking you for your in instinct on that and the instinct is to say well I already don’t like losing money this is big amounts of money right so I’m going to try to get a chance not to lose anything and most people just because of that because you have 1/4 chance of not losing anything most people we choose to although that is not your heart nor decision so it’s not a matter of the rational decisions here but the matter of the actual decisions most people lose truth sorry – and this is what we call loss aversion when you start losing money you honey unhappy and in the real estate market this is something very important loss aversion why is that when you want to sell your house and the real estate market is down and keeps going down very rapidly and you always remember the price you paid for the house another price is here and these difference of price is your loss right you’re trying to hold on to your house as long as possible you don’t want to lose money so you’re trying to hold down and you’re trying it’s only when you’re absolutely desperate that you actually putting your house on the market and you accept the loss what does it mean it means that is going to amplify the decrease of the prices and that’s becoming more and more important the loss aversion is not even constant it becomes more and more important when you when you lose more and more money yes your losses are so great that you propose then you would rationally take more risk with with the chance that you might be able to get out of it and then the downside is you’re still bankrupt or a closed upon here you’re just as poor off so wouldn’t that make like loss wouldn’t that make that the second decision – right he’s like let’s say instead of it being seventy five hundred seventy five hundred dollar loss spent ten thousand dollar loss it was losing your home or losing their home obviously you’d pick the second one because there is some small chance anymore that’s right but see if you can avoid to be bankrupt at the same time that would be your preference because it’s going to be even more difficult you know if it’s only losing your home that’s one thing but it’s a if it’s also going bankrupt at the same time then it’s going to be very hard to go back on the market so so to some extent that’s right there’s a you know it’s not as clear than a simple example but but you’re becoming more and more loss averse as more regulation and behavior issues very rapidly I there is it’s quite interesting actually that there’s very little literature on that and I was thinking that this is maybe a topic for papers for you that would be really interesting is to look at all these behavioral issues and try to send how that can impact regulation regulators and the Fed in particular the Guerrero’s are subject to the same where the human beings so they are subject to the same behavior biases in general they are better educated than the general

public but still they’re human beings so sometimes you know it’s not because you know what should your decision be if you were rational that you’re still not doing a decision that is rational so you can still have irrational decisions even when you know what the rational decision should be and then the second step to that is that regulators need to be aware of these behavior biases because they need to understand better how to design efficient regulations that would take deeds to account so I’m not saying here by no means that behavioral issues are the only drivers on the mappings right I gave you a lot of optional explanations as well but these are drivers that shouldn’t be neglected especially in the case of financial crises because I do believe that it’s more important in the case of extreme behaviors financial crisis than it is when the markets are pretty steady conclusion what did we learn today where three main points here the market bubbles with all the different examples restriction on ourselves was the rational one anchoring over extrapolation overconfidence over estimation of forecasts the brain over weights very low probabilities and the fear of regret Bank large exposures bad incentives bad model bad luck and then cognitive dissonance and greed amplification mechanisms with the ambiguity aversion and the loss aversion to conclude we understood from the four lectures of Chairman Bernanke’s the importance of the feds decisions on monetary policies for economic stability and for financial crisis situations we know that any declaration by the chairman of the Fed as huge impacts on the market it is not always completely rational but this is a fact the markets are listening to all the announcements so sometimes you can think that this is a behavioral biases from the market right and then we also heard Chairman Bernanke saying that financial crises were unavoidable and that we should prepare to probably have more and I would very much agree with that but what’s very important I thing for our future years to learn the lessons from the past and whenever we see financial crisis it’s very important to spend time to analyze these financial crisis understand what was going on understand how the regulations can actually be better terrible to avoid these financial crisis doesn’t mean that we are not going to have another one later on but maybe we can avoid lots of them in the future when we learn a lot more than us so that’s how I wanted to do it for election love happening but isn’t like the Black Swan theory focused on the fact that one Black Swan event one single event when actually he didn’t validate or shift the bell curve because things aren’t events aren’t independent there’s correlation especially during extreme moments so we thought be like a legitimate basis of yeah this is a very good point actually one way to look at the financial crisis when you’re looking in a more technical way to the CEOs for example the way they were structured was very smart technically in the way that you are different trenches and by having different trenches you could actually manufacture triple a CDO from two videos that were double-a only for example the problem that most people didn’t see is that in the case of a bad event the correlations are going to change between all of the financial securities on the market and because the correlation are

usually going up they are much less diversification effect in the portfolios and a way higher probability of these events being amplified so I didn’t want to go too technical in all that but you know in my presentation today but this is something that we did observe on the market which is shifting the correlation in the case when the financial crisis is started and because of this shift in the correlation that was not accounted for the triple-a ratings did not stand anymore so you’re right and that’s something that should be analyzed more precisely in in the financial models I’m not sure what behave myself this book we are now halfway through the class has been focused on economic but Isabelle done a great job of segue us into second class we’re looking at other factors other issues so the emotions are one when we come out on Tuesday we will continue the interactive division because have Peterson will be here and as a law professor Todd doesn’t lecture he just ask questions that’s what lawyer law professors do and so I would be prepared for lots of questions and somatic compass and we will talk about or he will talk about where we will discuss whether the Fed is even constitutional or not and what difference it is or what it was okay have a good weekend