Playing with Statistics (The Economist)

Naturally, the airlines choose to measure the greenhouse gases they produce in the way that casts them in the best light—a trick they deploy on safety statistics, too. For instance, over half of aircraft accidents occur around take-off and landing. So accidents per passenger-mile compare very favourably with other means of transport. But at least one study has shown that, if accidents are measured per journey instead, aircraft are the second-most dangerous way of travelling, after motorcycles.

Likewise on greenhouse gases. IATA says an aircraft's fuel consumption is about the same as that of a family car, at 3.5 litres per 100 passenger-kilometres. So CO2 emissions are similar. But that is true only if the aircraft is full and the car's passenger seats are empty. And even then, a jumbo jet flying from London to Sydney would be like nearly 400 Volkswagen Polos each travelling just over 16,000km—the average distance a European drives in a year. In other words, although cars and aircraft discharge roughly the same amount of CO2 for each passenger-kilometre, the aircraft travel an awful lot farther.

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Artificial artificial intelligence (The Economist)

Last November Amazon unveiled a prototype of the system, which it calls “artificial artificial intelligence”. The premise is that humans are vastly superior to computers at tasks such as pattern recognition, says Peter Cohen, director of the project at Amazon, so why not let software take advantage of human strengths?

Mr Cohen credits Amazon's boss, Jeff Bezos, with the concept for the Turk. Other people have had similar ideas. Eric Bonabeau of Icosystem, an American firm that builds software tools modelled on natural systems, has built what he calls the “Hunch Engine” to combine human intelligence with computer analysis. The French postal service, for example, has used it to help its workers choose the best delivery routes, and pharmaceutical researchers are using it to determine molecular structures by combining their gut instincts with known results stored in a database. And a firm called Seriosity hopes to tap the collective brainpower of the legions of obsessive players of multiplayer online games such as “World of Warcraft”, by getting them to perform small real-world tasks (such as sorting/labelling photographs) while playing, and paying them in the game's own currency.

But even complicated tasks rate only a few dollars. iConclude, a software start-up aiming to automate corporate technical support, is using the Turk to evaluate developers who can help write its repair tools. It used the Turk to source a list of recommended fixes for common problems in IIS, Microsoft's widely used web-server software. One respondent submitted a superbly thought-out 20-step process made up in Visio, a software tool for making schematics. For this, iConclude paid $5. “If we'd hired a consultant, we would have paid $1,000-2,000,” says Helen Tang of iConclude. “I was flabbergasted.”

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Life in 2020 (Paul Brown)

In the new village of Hamstreet, in Kent, Richard Dumill goes to the bathroom and prepares for a new day. It is 2020 and as he flushes the toilet his sample is automatically analysed and sent to the local doctor. The cholesterol level is slightly high because of the heavy dinner of farmed cod and chips but the computer in the surgery discounts the readings as not exceptional.There is a slight hum as the family water purifier switches on, and as he walks down the hallway he taps the electricity meter and sees it shows that the family is in credit: his own windmill generator and solar panels are putting more energy into the grid than the household is using, adding to the family income.

Downstairs his wife, Sarah, is complaining. The so-called "smart fridge" has malfunctioned and the order for milk and bread which should have reached the local delivery service has not been sent. The grocer, who employs a refugee from Tuvalu, a Pacific island country that disappeared three years previously as sea levels rose, will have to be telephoned instead. Food deliveries go in a special lockable box rather than on the doorstep since theft of these increasingly expensive essentials is a growing problem.

Both parents now work to pay off the 55-year mortgage on their house. Sarah works as a counsellor for people who have a genetic predisposition to a variety of diseases like cancer and heart trouble that means they cannot qualify for insurance or mortgages. Richard normally works from home but is going in a shared hydrogen powered car to the office at the waste and recycling brokerage where he works. He rarely sees any of the recycled tin or plastic in which he deals but quotes prices for the futures market in which companies buy waste products to use in future manufacturing.

When working at home, a telephone gadget in his ear, which operates on electricity generated by his brain, allows his manager to speak to him at any time during working hours. This, among many new electronic devices which are supposed to make him more efficient, Richard regards with scepticism.

Today as he drives to work he carefully picks his route to avoid congestion charges on the motorway or in any of the towns on the way. His company long ago moved out of its central London headquarters to cut costs.

The former industrial estates, which gradually emptied and became derelict as manufacturing declined to 9% of gross domestic product, have been taken down and replaced with water-and energy-efficient housing estates. The whole area is planted with trees to form what has been christened the Dartford Forest.

The couple have a daughter Britney, adopted like many other children: sperm counts for the average male in Britain have dropped to 30% of 1940s level, because the chemicals widely used in food and farming have so damaged fertility. It is no satisfaction that many big food manufacturers have gone bankrupt in the last few years because of class actions brought by people no longer able to have children.

The clampdown on preservatives in food and high oil prices mean that sending fresh food long distances is prohibitively expensive. The family keep chickens to have a supply of fresh eggs and grow vegetables because so much imported food is now an expensive luxury. The warmer climate means melons can be grown outdoors, although it also has led to a malaria scare in nearby Tunbridge Wells.

Worldwide there are serious problems for less technology based societies. Large parts of central Africa are becoming uninhabitable because of climate change. The sea is encroaching on many low lying coastal areas causing a huge refugee crisis.

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The ‘Hurricaneomic’ Effect (Darrell Jobman)

Should storms of the magnitude of 2005's Katrina, Rita, and Wilma strike again, the expanding hurricane impact on financial markets will have a ripple effect on global markets and consumers far removed from the vicinity of the storm.

One of the first markets that typically is affected at the first hint a tropical storm is brewing is natural gas, as traders anticipate that a severe hurricane might disrupt Gulf production and shipping. In the aftermath of disastrous hurricanes will come demand for building materials, which will drive up demand and prices for commodities such as lumber, copper and other materials needed to rebuild.

But all those are the obvious plays, the moves the professionals are likely to foresee and capture before most investors realize what is happening. Successful traders who are aware of the hurricaneomic effect expand their view from the eye of the storm to opportunities beyond its immediate reach.

For example the shift to ethanol as a clean air additive, has sparked a big increase in demand. A major source of ethanol in the United States is corn. The shock of the U.S. Department of Agriculture's most recent supply/demand estimates is not that the planted acreage of corn has declined from 2005, as expected, but that the usage of corn for ethanol will increase dramatically in the season ahead. With reduced production and higher usage, spurred by energy demand, competition for corn could become intense.

Market prices of ethanol are currently over $3 per gallon, and ethanol producers could pay near $7 a bushel a corn and still have positive returns, estimates Chris Hurt, Purdue University extension marketing specialist. Corn at $7 is a far cry from the price a little over $2 a bushel that livestock producers have paid in recent years. Hurricanes, past or future, won't be totally responsible for corn prices, of course, but at least part of the current demand for corn for fuel can be attributed to the 2005 hurricanes. If another severe hurricane season exacerbates the current energy situation or if weather in either 2006 or 2007 reduces corn production, corn may be the next bull market.

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How We Know What Isn’t So (Thomas Gilovich)

It is widely believed that infertile couples who adopt a child are subsequently more likely to conceive than similar couples who do not. The usually explanation for this remarkable phenomenon involves the alleviation of stress. Couples who adopt, it is said, become less obsessed with their reproductive failure, and their new-found peace of mind boosts their chances for success.

In reality, couples who conceive after adopting are noteworthy. Their good fortune is reported by the media, transmitted by friends and neighbours, and therefore is more likely to come to our attention than the fate of couples ho adopt but do no conceive, or those who conceive without adopting.

Several things are clear at the outset. First, people do not hold questionable beliefs simply because they have not been exposed to the relevant evidence. Erroneous beliefs plague both experienced professionals and less informed laypeople alike.

Many questionable and erroneous beliefs have purely cognitive origins, and can be traced to imperfections in our capacities to process information and draw conclusions. We hold many dubious beliefs, in other words, not because they satisfy some important psychological need, but because they seem to be the most sensible conclusions consistent with the available evidence. People hold such beliefs because they seem, in the words of Robert Merton, to be the “irresistible products of their own experience.” They are the products, not of irrationality, but of flawed rationality.

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When Genius Failed (Roger Lowenstein) #5

Early in 1998, Long-Term began to short large amounts of equity volatility. But more than any other, “equity vol” was Long-Term’s signature trade. Equity vol comes straight from the Black-Scholes model. It is based on the assumption that the volatility of stocks is, over time, consistent. The stock market, for instance, typically varies by about 15 percent to 20 percent a year. Now and then, the market might be more volatile, but it will always revert to form. It was guided by the unseen law of large numbers, which assured the world of a normal distribution of brown cows and spotted cows and quiet trading days and market crashes. For Long-Term’s professors, with their supreme faith in markets, this was written in stone. It flowed from their Mertonian view of markets as efficient machines that spit out new prices with all the random logic of heat molecules dispersing through a cloud. And when the models told them that the markets were mispricing equity vol, they were willing to bet the firm on it.

There is no stock or security known as “equity vol,” no direct way of making a wager on it. But there is an indirect way. Remember that, according to the Black-Scholes formula, the key element in pricing an option is the expected volatility of the underlying asset. As the asset gets jumpier, the price of the option rises. Therefore, if you knew the price of an option, you could infer the level of volatility the market was expecting.

An analogy may be helpful. There is no direct way to bet on the weather in Florida—but in certain seasons, the price of orange juice futures fluctuates according to the likelihood of a frost. Indeed, an experienced trader could infer, if the price of juice was unusually high, that the market was expecting a chilly winter and thus a scarcity of oranges. And if the trader believed that the market’s weather forecast was wrong, he could try to profit on his opinion by shorting orange juice.

In a similar manner, Long-Term deduced that the options market was anticipating volatility in the stock market of roughly 20 percent. Long-Term viewed this as incorrect, because actual volatility was only about 15 percent. Thus, it figured that option prices would sooner or later fall. So Long-Term began to short options—specifically, options on the Standard & Poor’s 500 stock index and on the equivalent indices on the major exchanges in Europe. In their own argot, the professors were “selling volatility”.

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When Genius Failed (Roger Lowenstein) #4

The first modern swap was engineered in 1981. IBM had bonds denominated in Swiss francs and German marks and wanted to convert this debt to dollars. David Swensen, a Yale PhD newly arrived at Salomon, suggested that perhaps some other borrow could be persuaded to issue debt that, aside from being denominated in dollars, was identical to IBM’s. One obvious choice was the World Bank, which had an appetite for holding debt in a variety of currencies. As an inducement to borrow, Salomon gave the bank a slightly lower-than-market interest rate. Then the two borrowers switched—IBM winding up with the dollar debt, the World Bank with the foreign stuff—and voila! the world of swaps was born.

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When Genius Failed (Roger Lowenstein) #3

By 1997, Long-Term was under immediate pressure to park its capital somewhere, and equities loomed as a far larger and more tantalizing new frontier. It was an open frontier because most traders with Long-Term’s mathematical bent had naturally left equities alone. Although pricing a bond can largely be reduced to mathematics, valuing a stock is far more subjective. Wall Street and academe had devised many a formula to forecast the market, but none, no matter how esoteric or rigorous, had worked. Over the short run, stocks are subject to the whim of often emotional traders. Over the long run, they vary with business performance, which is subject to great uncertainty and is notoriously hard to forecast. It requires judgment—not merely math—of the sort that no computer has ever mastered. As the economist Burton Malkiel once observed, “God Almighty does not know the proper price-earning multiple for a common stock.”

Haghani had been researching equities, particularly in Europe, and he thought the field was ripe for a firm with the necessary quantitative skills. Rosenfeld, too, had been thinking about equity arbitrage since his days at Salomon. One attractive point was that equity arbitrage would (he supposed) be uncorrelated with bond arbitrage. Rosenfeld wanted random investment dice, and equities seemed of a different world apart from bonds.

Haghani focused his research on so-called paired shares. Various European stocks were doubly listed. Volkswagen, for instance, listed an ordinary share and a “preference” share, the latter with superior voting rights. BMW was another. Haghani also looked at pairs of stocks with related (but not identical) assets, such as Telecom Italia, the Italian phone company, and Telecom Italia Mobile, its subsidiary, or Louis Vuitton and Dior. For various reasons, one side of a given pair often traded at a discount to its partner. Hence, Haghani spotted the potential for arbitrage.

The paired-share trades weren’t perfect arbitrages, because the two sides of each trace were never precisely equivalent. A preference share of Volkswagen was worth a premium over an ordinary share, especially as, in Germany and elsewhere in Europe, managements did not feel the same obligation as in the United States to treat all stock-holders fairly. No one could say precisely what the “right” premium was, only that the 40 percent premium in VW’s case, for example, seemed excessive. But the spread could persist or even widen—the models be damned.

Haghani found about fifteen paired-share trades, and Haghani bet on them in staggering size. His favorite was Royal Dutch/Shell was owned by two listed companies, Royal Dutch Petroleum of the Netherlands and Shell Transport of England. Although Royal Dutch and Shell got their income from the same source—that is from dividends on Royal Dutch/Shell—the English firm had historically traded at an 8 percent or so discount to its Dutch cousin. The stocks were owned by distinct pools of investors, and the Dutch stock was typically more liquid. But there was no good reason for the price differential. With Europe becoming a single economic unit, Haghani reckoned that national differences would matter less and less, and the spread between Royal Dutch and Shell would contract. This was a popular view.

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When Genius Failed (Roger Lowenstein) #2

There is a reason why financial markets run to extremes more often than coin flips. A key condition of random events is that each new flip is independent of the previous one. The coin doesn’t remember that it landed on tails three times in a row; the odds on the fourth flip are still fifty-fifty.

But markets have memories. Sometimes a trend will continue just because traders expect (or fear) that it will. Investors may slavishly follow the trend for no other reason than that they think enough others will do likewise. Such momentum trading has nothing to do with logically appraising securities; it doesn’t fit the ideal of rational investors in efficient markets. But it’s human. After three bad “flips” in the market, the fourth flip may no longer be completely random. Some traders may have taken losses and be forced to sell; other investors, looking over their shoulders, may panic and decide to beat them to it—as happened with Treasury bonds during Long-Term’s inaugural spring.

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When Genius Failed (Roger Lowenstein) #1

One of Long-Term’s first trades involved the thirty-year Treasury bond. Treasurys are, of course, issued by the U.S. government to finance the federal budget. Some $170 billion of them trade each day, and they are considered the least risky investments in the world. But a funny thing happens to thirty-year Treasurys six months or so after they are issued: investors stuff them into safes and drawers for long-term keeping. With fewer left in circulation. the bonds become harder to trade. Meanwhile, the Treasury issues a new thirty-year bond, which now has its day in the sun. On Wall Street, the older bond, which has about 29.5 years left to mature, is known as off the run; the shiny new model is on the run. Being less liquid, the off-the-run bond is considered less desirable. It begins to trade at a slight discount. As arbitrageurs would say, a spread opens.

In 1994, Long-Term noticed that this spread was unusually wide. The February 1993 issue was trading at a yield of 7.36%. The bond issued six months later, in August, was yielding only 7.24%, or 12 basic point, less. In one of the meetings at Long-Term, several partners proposed that they bet on this 12-point gap to narrow. It wasn’t enough to say, “One bond is cheaper, one bond is dearer.” The professors needed to know why a spread existed, which might shed light on the paramount issue of whether it was likely to persist or even to widen. In this case, the spread seemed almost silly. After all, the U.S. government is no less likely to pay off a bond that matures in 29.5 years than it is one that expires in thirty. But some institutions were so timid, so bureaucratic, that they refused to own anything but the most liquid paper. Long-Term believed that many opportunities arose from market distortions created by the sometimes arbitrary demands of institutions. The latter were willing to pay a premium for on-the-run paper, and Long-Term’s partners, who had often done this trade at Salomon, happily collected it. They call it a “snap trade,” because the two bonds usually snapped together after only a few months. In effect, Long-Term would be collecting a fee for its willingness to own a less liquid bond.

Long-Term, with trademark precision, calculated that owning one bond and shorting another was one twenty-fifth as risky as owning either bond outright. Thus, it reckoned that it could prudently leverage this long/short arbitrage twenty-five times. This multiplied its potential for profits but—as we have seen—also its potential for loss. In any case, borrow it did. It paid for the cheaper, off-the-run bonds with money that it borrowed from a Wall Street bank, or from several banks. And the other bonds, the ones it sold short, it obtained through a loan, as well.

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Liar’s Poker (Michael Lewis) #4

Having attracted tens of billions of dollars to his new speculative market, Michael Milken, by 1985, was faced with more money than places to put it. It must have been awkward for him. He simply could not find enough worthy small-growth companies and old fallen angels to absorb the cash. He needed to create junk bonds to satisfy the demand for them. His original premise—that junk bonds are cheap because lenders are too chicken to buy them—was shot to hell. Demand now exceeded natural supply. Huge pools of funds across America were dedicated to the unbridled pursuit of risk. Milken and his Drexel colleagues fell upon the solution: They’d use junk bonds to finance raids on undervalued corporations, by simply pledging the assets of the corporations as collateral to the junk bond buyers. A take-over of a large corporation could generate billions of dollars’ worth of junk bonds, for not only would new junk be issued, but the increased leverage transformed the outstanding bonds of a former blue-chip corporation to junk.

The process by which a take-over occurs is frighteningly simple—in view of its effects on community, workers, shareholders, and management. A paper manufacturer in Oregon appears cheap to a twenty-six-year-old playing with his computer late one night in New York or London. He writes his calculations on a telex, which he sends to any party remotely interested in paper, in Oregon, or in buying cheap companies. Like the organizer of a debutante party, the twenty-six-year-old keeps a file on his desk of who is keen on whom. But he isn’t particularly discriminating in issuing invitations. Anyone can buy because anyone can borrow using junk bonds. The papermaker in Oregon is now a target.

The next day the papermaker reads about himself in the “Heard on the Street” column of the Wall Street Journal. His stock price is convulsing like a hanged man because arbitrageurs like Ivan Boesky have begun to buy his company’s shares in hopes of making a quick buck by selling out to the raider. The papermaker panics and hires an investment banker to defend him, perhaps even the same twenty-sex-year-old responsible for his misery. Five other twenty-six-year-old at five hitherto unoccupied investment banks read the rumors and begin to scourge the landscape for a buyer of the paper company. Once a buyer is found, the company is officially “in play”. At the same time the army of young overachievers check their computers to see if other paper companies in America might not also be cheap. Before long the entire paper industry is up for grabs.

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Liar’s Poker (Michael Lewis) #3

Look away from the initial focus of investor interest and seek secondary and tertiary effects.

Remember Chernobyl? When news broke that the Soviet nuclear reactor had exploded, Alexander called. Only minutes before, yet Alexander had already bought the equivalent of two supertankers of crude oil. The focus of investor attention was on the New York Stock Exchange, he said. In particular it was on any company involved in nuclear power. The stocks of those companies were plummeting. Never mind that, he said. He had just purchased, on behalf on his clients, oil futures. Instantly in his mind less supply of nuclear power equaled more demand for oil, and he was right. His investors made a large killing.

Minutes later, Alexander called back. “Buy potatoes,” he said. “Gotta hop.” Then he hung up. Of course. A cloud of fallout would threaten European food and water supplies, including the potato crop, placing a premium on uncontaminated American substitutes. Perhaps a few folks other than potato farmers think of the price of potatoes in America minutes after the explosion of a nuclear reactor in Russian, but I have never met them.

But Chernobyl and oil are a comparatively straightforward example. There was a game we played called What if? All sorts of complications can be introduced into What if? Imagine, for example, you are an institutional investor managing several billion dollars. What if there is a massive earthquake in Tokyo? Tokyo is reduced to rubble. Investors in Japan panic. They are selling yen and trying to get their money out of the Japanese stock market. What do you do?

Well, along the lines of pattern number one (contrarian approach), what Alexander would do is put money into Japan on the assumption that since everyone was trying to get out, there must be some bargains. He would buy precisely those securities in Japan that appeared the least desirable to others. First, the stocks of Japanese insurance companies. The world would probably assume that ordinary insurance companies had a great deal of exposure, when in fact, the risk resides mainly with Western insurers and with a special Japanese earthquake insurance company that’s been socking away premiums for decades. The shares of ordinary insurers would be cheap.

Then Alexander would buy a couple of hundred million dollars’ worth of Japanese government bonds. With the economy in temporary disrepair, the government would lower interest rates to encourage rebuilding and simply order the banks to lend at those rates. Japanese banks would comply as usual with their government’s request. Lower interest rates would mean higher bond prices.

Also, the short-term panic could well be overshadowed by the long-term repatriation of Japanese capital. Japanese companies have massive sums invested in Europe and America. Eventually they would withdraw those investments, turn inward, lick their wounds, repair their factories, and bolster their stock. What would that mean?

Well, to Alexander, it would suggest buying yen. The Japanese would buy yen, selling their dollars, francs, marks and pounds to do so. The yen would appreciate not just because the Japanese were buying it but because foreign speculators would eventually see the Japanese buying it and rush to join them. If the yen collapsed immediately after the quake, it would only further encourage Alexander, who sought always to do the unexpected, that his idea was a good one. On the other hand, if the yen rose, he might sell it.

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Liar’s Poker (Michael Lewis) #2

Trading money was nonetheless trading. It required at least one iron testicle and the same peculiar logic as bond trading. Witness: One day earlier in his career Dall was in the market to buy (borrow) fifty million dollars. He checked around and found the money market was 4 to 4.25 percent, which meant he could buy (borrow) at 4.25 percent or sell (lend) at 4 percent. When he actually tried to buy fifty million dollars at 4.25 percent, however, the market moved to 4.25 to 4.5 percent. The sellers were scared off by a large buyer. Dall bid 4.5. The market moved again, to 4.5 to 4.75 percent. He raised his bid several more times with the same result, then went to Bill Simon’s office to tell him he couldn’t buy money. All the sellers were running like chickens.

“Then you be the seller,” said Simon.

So Dall became the seller, although he actually needed to buy. He sold fifty million dollars at 5.5 percent. He sold another fifty million dollars at 5.5 percent. Then, as Simon had guessed, the market collapsed. Everyone wanted to sell. There were no buyers. “Buy them back now,” said Simon when the market reached 4 percent. So Dall not only got his fifty million dollars at 4 percent but took a profit on the money he had sold at higher rates. That was how a Salomon bond trader thought: He forgot whatever it was that he wanted to do for a minute and put his finger on the pulse of the market. If the market felt fidgety, if people were scared or desperate, he herded them like sheep into a corner, then make them pay for their uncertainty. He sat on the market until it puked gold coins. Then he worried about what he wanted to do.

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Liar’s Poker (Michael Lewis) #1

The biggest myth about bond traders, and therefore the greatest misunderstanding about the unprecedented prosperity on Wall Street in the 1980s, are that they make their money by taking large risks. A few do. And all the traders take small risks. But most traders act simply as toll takers. The source of their fortune has been nicely summarized by Kurt Vonnegut (who, oddly, was describing lawyers):"There is a magic moment, during which a man has surrendered a treasure, and during which the man who is about to receive it has not yet done so. An alert lawyer [read bond trader] will make that moment his own, possessing the treasure for a magic microsecond, taking a little of it, passing it on.”

In other words, Salomon carved a tiny fraction out of each financial transaction. This adds up. The Solomon salesman sells $50 million worth of new IBM bonds to pension fund X. The Salomon trader, who provides the salesman with the bond, takes for himself an eighth (of a percentage point), or $62500. He may, if he wishes, take more. In the bond market, unlike in the stock market, commissions are not openly stated.

Now the fun begins. Once the trader knows the location of the IBM bonds and the temperament of their owner, he doesn’t have to be outstandingly clever to make the bonds (the treasure) move again. He can generate his own microseconds. He can, for example, pressure one of his salesmen to persuade insurance company Y that the IBM bonds are worth more than pension fund X paid for them initially. Whether it is true is irrelevant. The trader buys the bonds from X and sells them to Y and takes out another eighth, and the pension fund is happy to make a small profit in such a short time.

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Random Quotes

Wisdom come with age, but sometimes age comes alone.

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