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Lecture 2 - The Universal Principle of Risk Management: Pooling and the Hedging of Risks Overview:
Statistics and mathematics underlie the theories of finance. Probability Theory and various distribution types are important to understanding finance. Risk management, for instance, depends on tools such as variance, standard deviation, correlation, and regression analysis. Financial analysis methods such as present values and valuing streams of payments are fundamental to understanding the time value of money and have been in practice for centuries.
Reading assignment:
Jeremy Siegel, Stocks for the Long Run, chapter 1 and Appendix 2, p. 12
Financial Markets: Lecture 2 Transcript January 16, 2008
Professor Robert Shiller: Today I want to spend--The title of today's lecture is: The Universal Principle of Risk Management, Pooling and the Hedging of Risk. What I'm really referring to is what I think is the very original, the deep concept that underlies theoretical finance--I wanted to get that first. It really is probability theory and the idea of spreading risk through risk pooling. So, this idea is an intellectual construct that appeared at a certain point in history and it has had an amazing number of applications and finance is one of these. Some of you--This incidentally will be a more technical of my lectures and it's a little bit unfortunate that it es early in the semester. For those of you who have had a course in probability and statistics, there will be nothing new here. Well, nothing in terms of the math. The probability theory is new. Others though, I want to tell you that it doesn't--if you're shopping--I had a student e by yesterday and ask--he's a little rusty in his math skills--if he should take this course. I said, \tomorrow's lecture--that's today's lecture--then you should have no problem.\
I want to start with the concept of probability. Do you know what a probability is? We attach a probability to an event. What is the probability that the stock market will go up this year? I would say--my personal probability is .45. That's because I'm a bear but--Do you know what that means? That 45 times out of 100 the stock market will go up and the other 55 times out of 100 it will stay the same or go down. That's a probability. Now, you're familiar with that concept, right? If someone says the probability is .55 or .45, well you know what that means. I want to emphasize that it hasn't always been that way and that probability is really a concept that arose in the 1600s. Before that, nobody ever said that.
Ian Hacking, who wrote a history of probability theory, searched through world literature for any reference to a probability and could find none anywhere before 1600. There was an intellectual leap that occurred in the seventeenth century and DOC版本.
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it became very fashionable to talk in terms of probabilities. It spread throughout the world--the idea of quoting probabilities. But it was--It's funny that such a simple idea hadn't been used before. Hacking points out that the word probability--or probable--was already in the English language. In fact, Shakespeare used it, but what do you think it meant? He gives an example of a young woman, who was describing a man that she liked, and she said, I like him very much, I find him very probable. What do you think she means? Can someone answer that? Does anyone know Elizabethan English well enough to tell me? What is a probable young man? I'm asking for an answer. It sounds like people have no idea. Can anyone venture a guess? No one wants to venture a guess?
Student: fertile?
Professor Robert Shiller: That he can father children? I don't think that's what she meant but maybe. No, what apparently she meant is trustworthy. That's a very important quality in a person I suppose.
So, if something is probable you mean that you can trust it and so probability means trustworthiness. You can see how they moved from that definition of probability to the current definition. But Ian Hacking, being a good historian, thought that someone must have had some concept of probability going before, even if they didn't quote it as a number the way--it must have been in their head or in their idea. He searched through world literature to try to find some use of the term that preceded the 1600s and he concluded that there were probably a number of people who had the idea, but they didn't publish it, and it never became part of the established literature partly because, he said, throughout human history, there has been a love of gambling and probability theory is extremely useful if you are a gambler. Hacking believes that there were many gambling theorists who invented probability theory at various times in history but never wrote it down and kept it as a secret.
He gives an example--I like to--he gives an example from a book that--or it's a collection--I think, a collection of epic poems written in Sanskrit that goes back--it was actually written over a course of 1,000 years and it was pleted in the fourth century. Well, there's a story--there's a long story in the Mahabarahta about an emperor called Nala and he had a wife named Damayanti and he was a very pure and very good person. There was an evil demon called Kali who hated Nala and wanted to bring his downfall, so he had to find a weakness of Nala. He found finally some, even though Nala was so pure and so perfect--he found one weakness and that was gambling. Nala couldn't resist the opportunity to gamble; so the evil demon seduced him into gambling aggressively. You know sometimes when you're losing and you redouble and you keep hoping to win back what you've lost? In a fit of gambling, Nala finally gambled his entire kingdom and lost--it's a terrible story--and Nala then had to leave the kingdom and his wife. They wandered for years. He separated from her because of dire necessity. DOC版本.
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They were wandering in the forests and he was in despair, having lost everything. But then he meets someone by the name of--we have Nala and he meets this man, Rituparna, and this is where a probability theory apparently es in. Rituparna tells Nala that he knows the science of gambling and he will teach it to Nala, but that it has to be done by whispering it in his ear because it's a deep and extreme secret. Nala is skeptical. How does Rituparna know how to gamble? So Rituparna tries to prove to him his abilities and he says, see that tree there, I can estimate how many leaves there are on that tree by counting leaves on one branch. Rituparna looked at one branch and estimated the number of leaves on the tree, but Nala was skeptical. He stayed up all night and counted every leaf on the tree and it came very close to what Rituparna said; so he--the next morning--believed Rituparna. Now this is interesting, Hacking says, because it shows that sampling theory was part of Nala's theory. You don't have to count all the leaves on the tree, you can take a sample and you count that and then you multiply.
Anyway, the story ends and Nala goes back and is now armed with probability theory, we assume. He goes back and gambles again, but he has nothing left to wager except his wife; so he puts her and gambles her. But remember, now he knows what he's doing and so he really wasn't gambling his wife--he was really a very pure and honorable man. So he won back the entire kingdom and that's the ending.
Anyway, that shows that I think probability theory does have a long history, but--it not being an intellectual discipline--it didn't really inform a generation of finance theory. When you don't have a theory, then you don't have a way to be rigorous. So, it was in the 1600s that probability theory started to get written down as a theory and many things then happened in that century that, I think, are precursors both to finance and insurance.
One was in the 1600s when people started constructing life tables. What is a life table? It's a table showing the probability of dying at each age, for each age and sex. That's what you need to know if you're going to do life insurance. So, they started to do collecting of data on mortality and they developed something called actuarial science, which is estimating the probability of people living. That then became the basis for insurance. Actually, insurance goes back to ancient Rome in some form. In ancient Rome they had something called burial insurance. You could buy a policy that protected you against your family not having the money to bury you if you died. In ancient culture people worried a great deal about being properly buried, so that's an interesting concept. They were selling that in ancient Rome; but you might think, but why just for burial? Why don't you make it into full-blown life insurance? You kind of wonder why they didn't. I think maybe it's because they didn't have the concepts down. In Renaissance Italy they started writing insurance policies--I read one of the insurance policies, it's in the Journal of Risk and Insurance--and they translate a Renaissance insurance policy and it's very hard to DOC版本.
【视频】经济学：金融市场 02 风险管理 (The Risk Management)
