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00:01During the following program, look for NOVA's web markers which lead you to more information at our website.
00:16It was a brilliant discovery that revolutionized modern finance.
00:22When I saw the formula, I knew enough about it to know that this is the answer.
00:27This solved the ancient problem of risk and return in the stock market.
00:34It was recognized by the profession for what it was as a real tour de force.
00:41An elegant mathematical formula that helped create a multi-trillion dollar industry.
00:48Up until the time that they came up with their insight, the world was full of uncertainty and risk.
00:55Uncontrollable and unanalyzable.
00:59And then, in a moment of tremendous clarity, they realized that two risky positions taken together can effectively eliminate risk itself.
01:09This bold idea shaped one of the most ambitious investment strategies in history.
01:19Attracting the elite of Wall Street until it confronted them with the biggest risk of all.
01:26Markets began to act in ways that had never been seen before.
01:33And they began to lose a hundred million and more day after day after day.
01:38Until finally there was one day when they dropped half a billion dollars.
01:42Five hundred million in a single day.
01:43These money machines, driven by mathematical models, had earned fantastic sums.
01:54Now, as they spiraled out of control, investors froze in terror.
01:59Everyone in the marketplace thought the sky was falling.
02:04And there was instant reaction.
02:06The fear was incredible.
02:08People thought, oh my God, what's going to happen next?
02:11The crisis threatened to bring markets around the world to the brink of collapse.
02:19Could a global economic meltdown be avoided?
02:23Major funding for NOVA is provided by the Park Foundation.
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03:04which has been protecting families and businesses for generations.
03:08Have you heard from The Quiet Company?
03:11Northwestern Mutual Life.
03:23CNET.com, helping you choose the right technology product.
03:29And by the Corporation for Public Broadcasting.
03:32And by contributions to your PBS station from viewers like you.
03:53Since the dawn of capitalism, there has been one golden rule.
04:13If you want to make money, you have to take risks.
04:17Then came one of the most ambitious intellectual endeavors of the century.
04:24The attempt to find a mathematical way to conquer risk.
04:29To turn finance into a science.
04:35If it worked, it would open new realms for the world's financial exchanges.
04:40And forever change the way traders trade.
04:43I've seen many people come and go.
04:48People come in with a good, fresh attitude, but they just can't survive.
04:53Or they just can't handle the competition.
04:55It's not for the meek.
04:58It's not for the weak.
05:00If you can't handle it, you can't be there.
05:02And it's simple.
05:04Otherwise, the people just take your money.
05:06And they don't feel bad.
05:08Every day when I walk into the exchange, I walk in with a clear mind.
05:13No emotion.
05:15The emotion builds up.
05:17Almost like a volcano.
05:18Ready to explode.
05:20And when I walk in that pit, it explodes.
05:32It's crazy.
05:33I'll communicate by going, buy 20% and sell you 20%.
05:36Constant chaos.
05:37It's constant chaos.
05:38The market's always moving.
05:40Yelling, screaming, grabbing, whatever it takes to get people's attention to make the market move.
05:45Constantly going, where am I?
05:47Where am I? Where am I?
05:48Meaning, what is my position?
05:50Give me an exact total.
05:51Give me an exact figure.
05:52What do I have to do to get out of the position?
05:54Here at the Chicago Mercantile Exchange, the products that are traded are strange and complex things, like pork belly futures, interest rate swaps, and currency derivatives.
06:06Their prices are constantly fluctuating as market sentiment shifts.
06:12The job of the trader is to try to guess what these prices will be next year, next week, or in 10 seconds' time.
06:20On any given day, you can lose six figures.
06:24Millions and millions of dollars exchanged hands in these pits every day.
06:28Me, personally, I've lost a lot of money.
06:31On any given day, I'm not going to give you a figure, but you can lose a car, put in an apartment, a house, whatever.
06:40On any given day, if you make a simple mistake.
06:42A successful mathematical model that could improve the trade-off between risk and reward would have to beat the instincts of an ordinary trader on the floor.
06:57It would also have to compete with the accumulated wisdom of an acknowledged expert in his office high above the pit.
07:05Yeah.
07:06You see it?
07:07Hey, six even.
07:08They went inside seven even.
07:11Six even is last.
07:12NASDAQ is unchanged.
07:16All right, get me out.
07:17All right.
07:19I'll be back. Don't hang up.
07:21Leo Malamed, one of the chief architects of Financial Futures, has been trading successfully for over 30 years.
07:28What I do is I pick up the phone to my clerk who is at the pit. She's at the edge of the pit. And she flashes in the order via hand signal to the broker in the pit who handles my account. And he then executes the order that I gave, gives her the confirmation of its execution. All of that is within seconds.
07:54Up here, it's kind of sterile and quiet. I get other kinds of information they don't get, but I don't get what they get, which is the screaming and the noise. And that noise level changes from time to time. And it also provides information, as does the fear in the eyes of the traders around you. That, too, is information.
08:14I go in the morning and the day is before me and I have to figure out which direction any one of a dozen markets is going to go in. Additionally, you have to figure out from reading the newspapers, from being a psychiatrist, as it were, of the public attitude, which way are they going today?
08:41What are they going to do? Is this information going to make them bullish? Is this information going to make them fear? And if I can figure that out, I can beat the market.
08:50Traders like Melamed are convinced that success in the markets involves human judgment, business savvy, and intuition, qualities that could never be reduced to a series of equations.
09:05But an important group of financial economists who study the markets mathematically believes that such success is largely a matter of luck.
09:20In flipping a coin, if you flip it long enough, there may be a long run of heads, which doesn't at all imply that the person flipping it had the ability to make it come up heads.
09:38It could just be the luck of the toss.
09:41This strange view arose from an unexpected discovery.
09:49After the stock market crash of 1929, economists decided to find out whether traders really could predict how prices moved by looking at past patterns.
10:00They decided to run a series of experiments.
10:07In one of them, they simply picked stocks at random.
10:11They threw darts at the Wall Street Journal while blindfolded.
10:16At the end of the year, this random choice outperformed the predictions of top traders.
10:21This was a revelation.
10:22This was a revelation.
10:24Prices must be moving totally at random.
10:27And although patterns came and went, they were there by chance alone and had no predictive value.
10:34The economists arrived at a devastating conclusion.
10:39It seemed just as plausible to attribute the success of top traders to sheer luck rather than skill.
10:46When some individual made a fortune in the stock market, we have a tendency to assume that that was because he knew something.
11:00And of course, the individual himself is happy to reinforce that belief.
11:06Yes, I was a genius.
11:07I was very clever.
11:08I always said Microsoft was going to make me rich.
11:12But what you don't see are the thousands, hundreds of thousands, perhaps millions of people, who are going,
11:22I always said that ABC Company was going to make me rich, and ABC Company went bust.
11:30If there's 10,000 people looking at the stocks and trying to pick winners, well, one in 10,000 is going to score by chance alone a great coup.
11:47And that's all that's going on.
11:50It's a chance operation, and people think they are doing something purposeful, but they're really not.
11:56This view disgusted most traders, and continues to do so today.
12:02Listen, academics, as a rule, make terrible traders.
12:08So for me to think that I'm going to listen to their theory about trading, I beg to differ.
12:14According to economists, when traders like Malabed dig up information and quickly act upon it, the resulting prices move to reflect that research.
12:28Ironically, the very act of predicting prices makes them less predictable.
12:34But economists knew that mathematics had been successfully used to study random phenomena before, from population growth to the weather.
12:47Using esoteric theories of probability, they could model market fluctuations in their quest to master risk.
12:55We can deal with random series in a way that to the layman maybe is just chaos, but no, no, no, no, no.
13:05Once you tell me that the series is random, and you've got probability distributions, we can use some of the apparatus of modern mathematical statistics to do analyses.
13:17The hope that the mathematical theory of probability and statistics could be a skeleton key to help you understand the nature of chance, perhaps to predict it better, perhaps to control it, that was born at that time, and the rest is, as they say, history.
13:39Unknown to the economists of the 1930s, a French graduate student at the turn of the century, Louis Bachelier, had already exploited the structure of randomness in his doctoral thesis titled The Theory of Speculation.
13:58He compared the behavior of buyers and sellers to the random movements of particles suspended in fluid, anticipating key insights later developed by Einstein and the mathematics of probability.
14:16But Bachelier's accomplishments would go unnoticed for decades.
14:23In the early 1950s, I was able to locate, by chance, this unknown book rotting in the library of the University of Paris.
14:36And when I opened it up, it was as if a whole new world was laid out before me.
14:44In fact, as I was reading it, I arranged to get a translation in English, because I really wanted every precious pearl to be understood.
15:01Using a series of equations, Bachelier created the first complete mathematical model of stock market fluctuations.
15:11He, too, believed stock prices moved at random, and that it was impossible to make exact predictions about them.
15:21But then, Bachelier said he had found a way to control risk through an obscure financial contract called an option.
15:30He realized options could protect investors from market fluctuations, and made the first attempt to figure out how to price them.
15:41But his superiors were unimpressed. His academic career faltered.
15:51After the discovery of Bachelier's work, there suddenly came to the mind of all the eager workers the notion of what the Holy Grail was.
16:03There was the next step needed. It was to get the perfect formula to evaluate and to price options.
16:14Economists returned eagerly to the markets to investigate this strange contract which had so intrigued Bachelier.
16:26They discovered options were a form of insurance that allowed investors to buy or sell stock for a specific amount, the strike price, by a specific date.
16:39For example, if you buy a stock today, the price could drop in the future, and you could lose money.
16:46But if you buy an option, you have the right to sell the stock at some agreed price in the future.
16:54If the stock drops, you have insurance.
16:58If it rises, you profit.
17:02Options can be an effective way to control risk.
17:06But how much should an investor pay for such absolute peace of mind?
17:11The value seemed to depend on each individual's level of confidence in the market.
17:17No one could agree on a standardized way to price options.
17:21It was a bewildering problem that the economists were determined to solve.
17:27No one could agree on that.
17:32Throughout the 1960s, they developed their mathematical models based on what seemed to be a hopeless quest to describe mathematically the emotional state of the typical investor.
17:46They invented symbols for the level of satisfaction, for reasonableness and aggressiveness.
17:55Symbols for the guesses of other traders, for defensiveness, for safety.
18:02Soon they had a giant mathematical edifice.
18:05But would it work?
18:10The mathematical models that were being developed during the 50s and 60s depended on inputs that were completely unobservable in the real world.
18:22Like expectations of investors, which might differ very much from one investor to another.
18:33And how did you actually come up with a number? How could you come up with a number to input?
18:38They would talk about people's utility structure. They would talk about people's risk aversion.
18:43And this made all the models seem more like psychotherapy than real science.
18:51By the end of the 60s, economists were no nearer to pricing options than they'd ever been.
18:58But this was about to change.
19:01From an early age, I was very, very fascinated by uncertainty.
19:19My parents, having lived in a gold mining part of the world in northern Canada, would be always buying penny stocks.
19:27Or the family would tend to be buying stocks that had very low prices.
19:31Because there'd be some rumor that there'd be another gold find or a silver find.
19:37And so the prices would shoot up or not shoot up.
19:40I mean, the family wouldn't seem to be getting rich, though.
19:45That got me very interested in why was it the case that these prices tend to fluctuate.
19:53In 1968, economist Myron Scholz and his colleague Fisher Black set out to tackle the problem of options.
20:05When I first discovered options, I became very excited about the possibilities that here was a contract that enabled you to only be able to take the upside of the returns and not the downside.
20:18And that being able to take the upside only had value, and that was really exciting.
20:26It was a goal that had eluded the greatest minds in economics.
20:30They knew that every stock price constantly moved up and down.
20:35As it did so, the value of an option on a particular stock fluctuated, too.
20:41But there was no predictable relationship.
20:45What they wanted to find was a formula that would calculate the correct price of an option at any moment in time,
20:52just by knowing the current price of the stock.
20:55But they couldn't see their way through the massive equations they'd inherited.
21:00I read the literature, tried to see what others had done,
21:06and I became dissatisfied with the various models,
21:12because they had assumptions that didn't seem to make that much sense to me.
21:18Then Black and Scholes decided to try something different.
21:23One by one, they dropped any symbol which represented something unmeasurable.
21:30Their loss didn't affect the calculations at all.
21:34Now, for the first time, Black and Scholes were left with the bare bones of the problem.
21:39The elements that everyone agreed were necessary to value an option.
21:46The stock price, its volatility, the strike price, the duration of the contract,
21:54the interest rate, and the overall riskiness of the option.
21:58They were all measurable, except one, the level of risk.
22:07I could do that first part, and then I got stock.
22:15So Black and Scholes decided if they couldn't measure the risk of an option exactly,
22:21perhaps they could somehow make it less significant.
22:23The method they devised was to become one of the most important discoveries in economics in this century.
22:31They started with the old idea of hedging,
22:34in which gamblers hedged their bets by betting in the opposite direction.
22:39They created a theoretical portfolio, a mixture of stocks and options.
22:45Then, whenever either fluctuated up or down,
22:48they tried to cancel the movement out by making another risky move in the opposite direction.
22:54Their aim was to keep the overall value of the portfolio in perfect balance.
23:02Since prices moved at random,
23:05at first they could cancel out only small fluctuations.
23:08But eventually, using complex mathematics and a mass of calculations,
23:13they found they could precisely balance out virtually any movement.
23:19After the fact, we call this dynamic hedging.
23:24What that means, dynamically hedging,
23:27is you want to be able to eliminate the uncertainty of the movements in the stock.
23:35They soon discovered that dynamic hedging reduced risk by creating a perfect equilibrium,
23:44in which fluctuations in the portfolio cancelled each other out.
23:47Black and Scholes had found a theoretical way to neutralize risk.
23:59Risk now dropped out of their equation.
24:04And without risk, the unmeasurable element,
24:09they finally had a mathematical formula which could give them the price of any option.
24:13They had solved the problem that had eluded generations of economists.
24:21It was a marvelous achievement.
24:23But there was a practical problem with their formula.
24:27It assumed that markets were always in equilibrium,
24:33that supply equals demand.
24:34In the fast-moving markets of the real world,
24:40their calculations for dynamic hedging might quickly be thrown out of kilter.
24:45What was needed was a way to instantly rebalance a portfolio of stocks and options
24:51to keep offsetting their fluctuations.
24:53Unbeknownst to Black and Scholes, someone had found a way.
25:00He was kind of a wunderkind.
25:13He was just recognized from the very beginning as an extraordinary intellectual talent.
25:20His creative powers, the power of the analytical techniques, mathematical techniques,
25:30that he was bringing to bear on some age-old questions in economics.
25:36Savings behavior, investment behavior.
25:39It was just obvious that here was a guy who was going to make intellectual history in our field.
25:49In college, I started studying the stock market.
25:55I went down to the stock exchange, watched all the activity from the visitors' gallery.
25:59Of people running around, calling numbers, shouting, and all the paper flying, and the bells ringing.
26:07Of course, that was exciting.
26:09And it seemed to lend itself to my analytical skills.
26:16Bob Merton had developed a reputation for using exotic mathematical methods
26:21to study financial contracts like options.
26:24He was the perfect person for Black and Scholes to meet.
26:27In the fall, I went over our ideas that we had with Bob
26:34and spent a lot of time arguing with him about whether our results were robust and exact
26:42or whether there was flaws in our methodology.
26:45So I'm going to reframe and reformulate their problem in the context of my modeling that I had developed.
26:52In constructing his own complex mathematical models,
26:55Merton explored theories no one in finance had even heard of.
27:06Turning to rocket science,
27:08he studied the theories of a Japanese mathematician,
27:11Kyoshi Ito, who'd faced a similar problem to Black and Scholes.
27:14In order to plot the trajectory of rockets, you needed to know exactly where the missile was, not just second by second, but literally all the time.
27:28Ito had developed a way of dividing time into infinitely small parcels, smoothing it out until it became a continuum so that the trajectory could be constantly updated.
27:41Bob Merton adapted this idea to the Black-Scholes formula.
27:48Using the notion of continuous time, the value of the option could be constantly recalculated and risk eliminated continually.
27:59And then I discovered they were right.
28:03By following their procedure, their dynamic trading strategy in the stock and cash, at least in the context of my model, they could eliminate all of the risk.
28:15Bob phoned me up one Saturday morning and said that he had an alternative proof to our particular model and was convinced that it did work.
28:29He had used technology that I hadn't been aware of and Fisher hadn't been aware of called Edo Calculus to actually, you know, solve the problem in a more elegant way, in a more robust way, I think, than Fisher Black and I had done.
28:48The formula that Black, Scholes and Merton unleashed on the world in 1973 was sparse and deceptively simple.
29:00Yet this lean mathematical shorthand was the fulfillment of a 50 year quest.
29:08When we did get the final equation, obviously, that was Eureka.
29:11That was Eureka.
29:12This is great.
29:13I mean, it doesn't get much better than that when you solve a problem and you really know and you've cracked it.
29:22Here was a formula that would enable investors by dynamically hedging to control risks by spreading them across individuals, financial markets, and through time.
29:36Academics marveled at its elegance and sheer audacity.
29:41I know and can take my hat off to what that accomplishment was because I got near the North Pole, but near is no cigar.
30:00It exploded.
30:02Within a few years, it was the most widely cited article in finance, even, alas, outdoing some of my own articles.
30:09But barely had the academics time to celebrate their achievement when traders began to use the formula for real.
30:18In 1973, the Chicago Board of Options was launched.
30:29As options on financial securities exploded, traders desperately needed a benchmark for pricing.
30:35Now, they simply programmed the Black-Scholes formula into their calculators.
30:42By pressing a few buttons, they could find the exact price of any option at any time.
30:47Soon, men and women who had never heard of Bachelier, Ito, or Continuous Time were exploiting the novel formula to make money.
30:59Lots of it.
31:00They even realized it could be applied to other financial transactions.
31:05By allowing them to hedge their risks constantly, the traders could feel safe enough to conduct business on a scale they had never dreamt possible.
31:15The risks in stocks could be hedged against futures, those in futures against currency transactions, and all of them hedged against a panoply of financial derivatives, so-called because they derive their value from some other security.
31:31Derivatives, which include options, swaps, and futures, took on new forms to exploit Black-Scholes, transferring risk from those who did not want to bear it to those who were prepared to take it on and earn a profit.
31:50The basic dynamic of the Black-Scholes model is the idea that through dynamic hedging, we can eliminate risk.
31:59Now, what this means, ironically, is, contrary to Grandpa's wisdom, the more we trade, the less risk we have.
32:09So, we have a mathematical argument for trading a lot.
32:14What a wonderful thing for exchanges to hear.
32:19So, we have to have more contracts, more futures exchanges, we have to be able to trade Nikkei Futures in Japan,
32:26we have to be able to trade options in Germany.
32:30Basically, in order to reduce risk, we have to trade everywhere and all the time.
32:38The application of mathematics to risk management would lead to the creation of a multi-trillion dollar derivatives industry.
32:45Finally, 25 years after they came up with their formula, the architects of this revolution received the ultimate accolade.
32:55My first reaction on being awarded the Nobel Prize was actually thought of Fisher Black, my colleague.
33:05He unfortunately had passed away and there was no doubt in my mind that if he were still alive, he would have been a co-recipient of the Nobel Prize.
33:15And this is the medal. This is the Nobel Medal.
33:25And on the back of the medal is the insignia for the Royal Academy of Sciences.
33:32Now, there's nothing like it, not once in a lifetime, but once in many lifetimes.
33:38Bob Merton.
33:43At the very height of their careers, Merton and Scholes were already multi-millionaires.
33:52Five years earlier, John Merriweather, the legendary bond trader at Solomon Brothers,
33:58had enticed Scholes and Merton to join him and 13 other partners in a new company he was launching,
34:03long-term capital management.
34:09In 1994, Business Week introduced the public to the dream team Merriweather had assembled.
34:18They were immediately seen as a unique enterprise.
34:22They had the best minds.
34:24They had a former vice chairman of the Federal Reserve.
34:27They had John Merriweather, a somewhat obscure figure, but a lionized one.
34:33And they had Merriweather's team, or the heart of Merriweather's team from Solomon,
34:37which had made essentially all of the money that Solomon had made over the past eight, ten years.
34:44So they were seen by individual investors, but particularly by banks and institutions that went in with them as a ticket to Easy Street.
34:51I first heard about LTCM from Bob Merton at lunch.
35:00He didn't have a name yet, but he was describing some new contraption.
35:07You know, it would be the analogy of a rocket scientist, you know, describing some new rocket.
35:15The idea of building something from scratch, but not a little prototype company, but something that would be quite large on a global basis, was too good to pass up.
35:27It was, for me, a way to see the application of ideas to practice.
35:35LTCM launched a giant hedge fund that promised to use mathematical models to make investors tremendous amounts of money.
35:48Merriweather's track record, along with Merton and Scholl's reputations, made it easy to raise capital.
35:54The most prestigious investors, banks, and institutions all competed to get in.
36:04The minimum investment allowed was $10 million, and it could not be withdrawn for three years.
36:11It was as though the Apostles had effectively come down to raise money at a bingo parlor.
36:20This was going to be the team of the century.
36:26They went around institutions who were considering investing, and this was an enormously powerful calling card,
36:33because many of the people making decisions had studied under Merton and Scholl's, that all read their books.
36:39They felt as if they were meeting a high priest, and almost as if they were honored to be asked to invest with them.
36:47Within months, they had raised $3 billion, and were ready to start investing across the globe.
36:53They set up not on Wall Street, but far away from ordinary traders, in Greenwich, Connecticut.
37:15From their headquarters, they devised one of the most ambitious investment strategies in history.
37:24Its success depended on absolute secrecy.
37:28Not even their investors were allowed to know what they were doing.
37:34Analyzing historical data, they used probability to bet that key prices would move roughly as they had in the past.
37:44To protect themselves against unwanted risk, they relied on an insight of the Black-Scholl's formula.
37:51Dynamic hedging.
37:52In effect, offsetting risk by taking bets in the opposite direction.
37:59Supremely confident, LTCM placed vast sums of money on the markets.
38:04The broad strategy of LTCM was to figure out how to hedge out the risks of your position, such that you can do a lot of it, much more than you can do if you didn't hedge out the risks.
38:17What they did was study the relationships between various markets all around the world, bond markets, eventually equity markets, interest rates, the rate at which those prices changed themselves.
38:31And when the relationships between these various markets got out of whack, which is to say, became different than what had been their historical norm.
38:41LTCM would place bets, the bets being that the historical relationships would reassert themselves. And they did this all over the world.
38:51And it worked. LTCM was a spectacularly successful money machine.
38:58Merton and Scholl's had proved that the science of finance could cut it in the real world. And they basked in their success.
39:08LTCM started out with three truly fabulous years. The first year they made 20%. That was after the partners had collected handsome fees.
39:24The second year they returned 43% to their investors. The third year another 41%.
39:30I asked him, what is it you guys are doing at LTCM? And Myron characterized it in a way of his. He said, well, you know, one way is to think of us as a gigantic vacuum cleaner sucking up nickels from all over the world.
39:50And it was as though the world was behaving exactly the way it had been written on the blackboard. Long term capital thought that they had discovered the path to nirvana.
40:04Here they are doing their day to day activities, playing golf in lush Greenwich or attending hedge fund conferences in Bermuda or raising funds in the con.
40:15And then slowly and totally unexpectedly, a change in the market dynamics began to become apparent.
40:29The first hint of trouble was that in 1997 LTCM's returns fell from 40% to 17.
40:38There was a reason why the returns fell, which is that when someone discovers a good game on Wall Street, he's bound to be imitated after a while.
40:48And that had happened to LTCM. So there was less room for them to exploit these little market discrepancies where they were drawing their profits from.
40:57And at the end of 1997, they returned much of their partners capital. However, they did not reduce the size of their assets so that they now had the same level of assets and investments, but less capital.
41:13That meant that if there were trouble, the trouble would hurt them much more quickly.
41:21In the summer of 1997, across Thailand, property prices plummeted.
41:28This sparked a panic that swept through Asia.
41:30As banks went bust from Japan to Indonesia, people took to the streets, events so improbable, they had never been included in anyone's models.
41:44Everyone in the marketplace thought the sky was falling. And there was instant reaction. The market broke, then rallied, then broke, then rallied. We didn't know what to believe.
42:00As prices leapt and plunged as never before, the models traders used began to give them strange results. So they relied instead on their instincts.
42:11In a time of crisis, cash is king. Traders stopped borrowing and dropped risky investments.
42:18You got to be able to get out while they're getting out is good. But that's true for any investment you make. That's true for real estate. That's true in every sort of business.
42:33You can't ignore an error. Once you realize that you've made an error, the best thing is to get out of that error and start again fresh. And that's what a good trader does.
42:46But at LTCM, the models told them everything would return to normal soon. There was no reason to panic. After all, they were hedged. With enough time, their bets would converge.
43:03All they needed was patience. But their bets diverged. As LTCM lost money, its ratio of assets to liquid capital reached 30 to 1. The fund's debts exceeded $100 billion.
43:20If I have $100 billion of a position and I lose 1%, I've lost $1 billion. And if all I have to start out with is $3 billion, if I lose 3% on my portfolio, in aggregate, I'm going to be wiped out.
43:42Despite its extreme leverage, LTCM could continue to hedge, as long as the economic upheaval in Asia did not spread.
44:00That's an old market rule. The market will test you and do what you don't expect it to do.
44:12In August, Russia, suddenly and without explanation, refused to pay all its international debts.
44:22LTCM's models had not accounted for this unprecedented event.
44:27As frantic investors all sought liquidity, LTCM could not unload its positions, which continued to diverge.
44:35In August of 1998, after the Russian default, all the relations that tended to exist in the recent past seemed to disappear.
44:50Models that they were using, not just Black Scholes models, but all kinds of models, were based on normal behavior in the markets.
45:01And when the behavior got wild, no models were able to put up with it.
45:06Although their models told them that they shouldn't expect to lose more than $50 million or so on any given day, they began to lose $100 million and more day after day after day,
45:21until finally there was one day, four days after Russia defaulted, when they dropped half a billion dollars, $500 million in a single day.
45:28In Greenwich, LTCM faced bankruptcy.
45:35But if the company went down, it would also take with it the total value of the positions it held across the globe.
45:43By some accounts, $1.25 trillion, the same amount as the annual budget of the US government.
45:51The elite of Wall Street would suffer heavy losses.
45:57The Federal Reserve Bank called upon the world's top financial regulators to discuss the crisis.
46:04Suddenly they seem to be staring at this nightmare where one firm linked up to every major firm on Wall Street was going to be seized up and markets might just stop working.
46:16That was the great fear.
46:17On Sunday, September 20th, officials of the Federal Reserve and US Treasury headed for Greenwich, Connecticut.
46:28What really was the shock for me when we went up to long-term capital and the partners gave us an overview of their positions and the risks and the pressures they were under was the extraordinary scope of the risks that they had taken on.
46:44The breadth of the portfolio and yet how utterly their effort to diversify the portfolio had failed them.
46:53How this wide set of positions across all markets had all come in and were all behaving the same way.
47:02Everything had come up heads.
47:03Fearing a global economic collapse, the Federal Reserve organized a bailout of LTCM with Wall Street's biggest power brokers.
47:16Fourteen firms put up $3.6 billion to buy out the fund.
47:21This consortium would now oversee all trading and had power to veto decisions made by the partners.
47:31Meriwether, Merton and Scholes lost millions.
47:36So did their investors.
47:40Then the public recriminations began.
47:43We expect that they're going to explain to the members of this committee why the Federal Reserve has organized a $3.5 billion bailout for billionaires.
47:54Why Americans should be worried about the gambling practices of the Wall Street elites.
48:05How much dependence should be placed on financial modeling, which for all its sophistication can get too far ahead of human judgment?
48:14It's like getting hit by a truck.
48:18I can't imagine anyone wouldn't feel very deep emotions of loss, of why, and I'm no different from that.
48:34Some people have asked me how I felt going through the LTCM experience,
48:38and obviously I felt quite badly for investors, for others who had worked with us,
48:51generally because it was the case that we had a great idea and a great franchise,
48:58a great application of these ideas to problem solving and essentially realizing that that was very difficult to affect.
49:06Math doesn't drive financial markets. People drive financial markets. And people are not predictable.
49:17We do not yet have a universal theory of human behavior or human motivation.
49:23Given that that's so, we're not likely to have robust models of financial market behavior that will always work.
49:31And I think the hubris of the mathematician is to ignore that fact.
49:37Individuals suspect that the models were flawed and essentially that was the reason why LTCM ended up in its difficulties.
49:46I personally don't think that that's the reason.
49:51It could be inputs to the models, it could be the models themselves, it could be a combination of many things.
49:57And so just saying models were flawed is not necessarily the right answer.
50:01Out of the 16 original partners, only five have remained to work for Meriwether.
50:09Myron Scholes has embarked on a new online trading venture.
50:14Robert Merton has remained at Harvard and consults for JP Morgan.
50:25In December 1999, LTCM fully repaid the banks that had prevented its collapse.
50:30Weeks later, the fund was quietly closed down.
50:37Some investors are still sitting on losses.
50:43Meriwether has launched a new hedge fund that will employ similar investment strategies as LTCM.
50:50But were those strategies responsible for one of the largest financial collapses in history?
51:00Or was it simply colossal bad luck?
51:06The question that I don't yet know the answer to, and I suppose what the partners at Long Term Capital,
51:12I can suppose what their answer would be.
51:14But I don't yet know the balance between whether this was a random event,
51:19or whether this was negligence on theirs and their creditors' parts.
51:23If a random bolt of lightning hits you when you're standing in the middle of the field,
51:28that feels like a random event.
51:31But if your business is to stand in random fields during lightning storms,
51:36then you should anticipate, perhaps a little more robustly, the risks you're taking on.
51:42In complex financial markets, the Black-Scholes formula is now an essential tool,
51:54one that continues to be used millions of times each day by traders around the world.
52:00Like many mathematical models, it relies on inputs and assumes a functioning market.
52:08It is a powerful way to manage risk, but it's not a crystal ball.
52:16When do you admit that you're wrong? Start all over again.
52:23Or when do you hang on and assume that the markets will turn around in your way?
52:28That's the biggest decision we all have to make.
52:33However, there's one thing that's clear.
52:36Over the last several hundred years,
52:40we've been able to identify some people that can do it better than others.
52:45They don't necessarily go to MIT.
52:49They don't necessarily have degrees in mathematics,
52:53so that doesn't automatically rule them out.
52:55They're the kind of people that can make that judgment that says,
53:01something's different here.
53:03I'm going back to harbor until I figure it out.
53:06Those are the kind of people you want running your money.
53:10There is a tempting and fatal fascination of mathematics.
53:14Albert Einstein warned against it.
53:16He said, elegance is for tailors.
53:19Don't believe in something because it's a beautiful formula.
53:25There will always be room for judgment.
53:27You don't have to be a mathematician to understand the basics behind the Black-Scholes formula.
53:52Take a closer look at the formula that shook the financial world
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