Jack Ryan 8 - Debt of Honor (44 page)

When brokers returned to their desks from lunch, what had been a fairly calm Friday was something else entirely. Every office had a news board that gave shorthand announcements of national and international events, because such things had effects on the market. The notification that the Fed had jacked up its benchmark rate by a full point shocked most trading rooms to a full fifteen or thirty seconds of silence, punctuated by not a few Holy shits. Technical traders modeling on their computer terminals saw that the market was already reacting. A rise in the discount rate was a sure harbinger of a brief dip in the Dow, like dark clouds were of rain. This storm would not be a pleasant one.

The big houses, Merrill Lynch, Lehman Brothers, Prudential-Bache, and all the rest, were highly automated, and all were organized along similar lines. In almost every case there was a single large room with banks of computer terminals. The size of the room was invariably dictated by the configuration of the building, and the highly paid technicians were crowded in almost as densely as a Japanese corporate office, except that in the American business centers people weren't allowed to smoke. Few of the men wore their suit jackets, and most of the women wore sneakers.

They were all very bright, though their educational backgrounds might have surprised the casual visitor. Once peopled with products of the Harvard or Wharton business schools, the new crop of “rocket scientists” were just that—largely holders of science degrees, especially mathematics and physics. MIT was the current school of choice, along with a handful of others. The reason was that the trading houses all used computers, and the computers used highly complex mathematical models both to analyze and predict what the market was doing. The models were based on painstaking historical research that covered the NYSE all the way back to when it was a place under the shade of a buttonwood tree. Teams of historians and mathematicians had plotted every move in the market. These records had been analyzed, compared with all identifiable outside factors, and given their own mathematically drawn measure of reality, and the result was a series of very precise and inhumanly intricate models for how the market had worked, did work, and would work. All of this data, however, was dedicated to the idea that dice did have a memory, a concept beloved of casino owners, but false.

You needed to be a mathematical genius, everyone said (especially the mathematical geniuses), to understand how this thing operated. The older hands kept out of the way for the most part. People who had learned business in business schools, or even people who had started as clerks and made their way up the ladder through sheer effort and savvy, had made way for the new generation—not really regretting it. The half-life of a computer jockey was eight years or so. The pace on the floor was killing, and you had to be young and stupid, in addition to being young and brilliant, to survive out there. The older hands who had worked their way up the hard way let the youngsters do the computer-driving, since they themselves had only a passing familiarization with the equipment, and took on the role of supervising, marking trends, setting corporate policy, and generally being the kindly uncle to the youngsters, who regarded the supervisory personnel as old farts to whom you ran in time of trouble.

The result was that nobody was really in charge of anything—except, perhaps, the computer models, and everyone used the same model. They came in slightly different flavors, since the consultants who had generated them had been directed by each trading house to come up with something special, and the result was prosperity for the consultants, who did essentially the same work for each customer but billed each for what they claimed was a unique product.

The result, in military terms, was an operational doctrine both identical and inflexible across the industry. Moreover, it was an operational philosophy that everyone knew and understood only in part.

The Columbus Group, one of the largest mutual-fund fleets, had its own computer models. Controlling billions of dollars, its three main funds, Nina, Pinta, and
Santa Maria
, were able to purchase large blocks of equities at rock-bottom prices, and by those very transactions to affect the price of individual issues. That vast market power was in turn commanded by no more than three individuals, and that trio reported to a fourth man who made all of the really important decisions. The rest of the firm's rocket scientists were paid, graded, and promoted on their ability to make recommendations to the seniors. They had no real power per se. The word of the boss was law, and everybody accepted that as a matter of course. The boss was invariably a man with his own fortune in the group. Each of his dollars had the same value as the dollar of the smallest investor, of whom there were thousands. It ran the same risks, reaped the same benefits, and occasionally took the same losses as everyone else's dollar. That, really, was the only security built into the entire trading system. The ultimate sin in the brokerage business was to place your own interests before those of your investors. Merely by putting your interests alongside theirs, there came the guarantee that everyone was in it together, and the little guys who had not the barest understanding of how the market worked rested secure in the idea that the big boys who did know were looking after things. It was not unlike the American West in the late nineteenth century, where small cattle ranchers entrusted their diminutive herds to those of the large ranchers for the drive to the railheads.

It was
1:50P.M.
when
Columbus
made its first move. Calling his top people together, Raizo Yamata's principal lieutenant briefly discussed the sudden run on the dollar. Heads nodded. It was serious. Pinta, the medium-risk fund of the fleet, had a goodly supply of Treasury notes, always a good parking place in which to put cash in anticipation of a better opportunity for later on. The value of these notes was falling. He announced that he was ordering their immediate transfer for Deutschmarks, again the most stable currency in
Europe
. The Pinta manager nodded, lifted his phone, and gave the order, and another huge transaction was made, the first by an American trader.

“I don't like the way this afternoon is going,” the vice-chairman said next. “I want everybody close.” Heads nodded again. The storm clouds were coming closer, and the herd was getting restless with the first shafts of lightning. “What bank stocks are vulnerable to a weak dollar?” he asked. He already knew the answer, but it was good form to ask.

“Citibank,” the Nina manager replied. He was responsible for the blue-chip fund's management. “We have a ton of their stock.”

“Start bailing out,” the vice-chairman ordered, using the American idiom. “I don't like the way the banks are exposed.”

“All of it?” The manager was surprised. Citibank had just turned in a pretty good quarterly statement.

A serious nod. “All of it.”

“But—”

“All of it,” the vice-chairman said quietly. “Immediately.”

At the Depository Trust Company the accelerated trading activity was noted by the staffers whose job it was to note every transaction. Their purpose was to collate everything at the end of the trading day, to note which buyer had purchased which stock from which seller, and to post the money transfers from and to the appropriate accounts, in effect acting as the automated bookkeeper

for the entire equities market. Their screens showed an accelerating pace of activity, but the computers were all running Chuck Searls' ElectraClerk 2.4.0 software, and the Stratus mainframes were keeping up. There were three outputs off each machine. One line went to the monitor screens. Another went to tape backups. A third went to a paper printout, the ultimate but most inconvenient record-keeping modality. The nature of the interfaces demanded that each output come from a different internal board inside the computers, but they were all the same output, and as a result nobody bothered with the permanent records. After all, there were a total of six machines divided between two separate locations. This system was as secure as people could make it.

Things could have been done differently. Each sale/purchase order could have been sent out immediately, but that was untidy-the sheer administrative volume would have taxed the abilities of the entire industry. Instead, the purpose of DTC was to bring order out of chaos. At the end of each day, the transactions were organized by trading house, by stock issue, and by client, in a hierarchical way, so that each house would write a limited number of checks—funds transfers were mostly done electronically, but the principle held. This way the houses would both save on administrative expense and generate numerous means by which every player in the game could track and measure its own activity for the purposes of internal audit and further mathematical modeling of the market as a whole. Though seemingly an operation of incomprehensible complexity, the use of computers made it as routine and far more efficient than written entries in a passbook savings account.

“Wow, somebody's dumping on Citibank,” the sys-con said.

The floor of the New York Stock Exchange was divided into three parts, the largest of which had once been a garage. Construction was under way on a fourth trading room, and local doomsayers were already noting that every time the Exchange had increased its space, something bad had happened. Some of the most rational and hard-nosed business types in all the world, this community of professionals had its own institutional superstitions. The floor was actually a collection of individual firms, each of which had a specialty area and responsibility for a discrete number of issues grouped by type. One firm might have eight to fifteen pharmaceutical issues, for example. Another managed a similar number of bank stocks. The real function of the NYSE was to provide both liquidity and a benchmark. People could buy and sell stocks anywhere from a lawyer's office to a country-club dining room. Most of the trading in major stocks happened in
New York
because …it happened in
New York
, and that was that. The New York Stock Exchange was the oldest. There were also the American Stock Exchange, Amex, and the newer National Association of Securities Dealers Automatic Quotation, whose awkward name was compensated for by a snappy acronym, NASDAQ. The NYSE was the most traditional in organization, and some would say that it had been dragged kicking and screaming into the world of automation. Somewhat haughty and stodgy—they regarded the other markets as the minor leagues and themselves as the majors—it was staffed by professionals who stood for most of the day at their kiosks, watching various displays, buying and selling and, like the trading houses, living off the “middle” or “spread” positions which they anticipated. If the stock market and its investors were the herd, they were the cowboys, and their job was to keep track of things, to set the benchmark prices to which everyone referred, to keep the herd organized and contained, in return for which the best of them made a very good living that compensated for a physical working environment which at best was chaotic and unpleasant, and at its worst really was remarkably close to standing in the way of a stampede.     The first rumblings of that stampede had already started. The sell-off of Treasury notes was duly reported on the floor, and the people there traded nervous looks and headshakes at the unreasonable development. Then they learned that the Fed had responded sharply. The strong statement from the chairman didn't—couldn't—disguise his unease, and would not have mattered in any case. Few people listened to the statement beyond the announcement of a change in the Discount Rate. That was the news. The rest of it was spin control, and investors discounted all of that, preferring to rely on their own analysis.

The sell orders started coming. The floor trader who specialized in bank stocks was stunned by the phone call from
Columbus
, but that didn't matter. He announced that he had “five hundred Citi at three,” meaning five hundred thousand shares of the stock of First National City Bank of
New York
at eighty-three dollars, two full points under the posted price, clearly a move to get out in a hurry. It was a good, attractive price, but the market hesitated briefly before snapping them up, and then at “two and a half.”

Computers also kept track of trading because the traders didn't entirely trust themselves to stay on top of everything. A person could be on the phone and miss something, after all, and therefore, to a remarkable degree, major institutions were actually managed by computers, or more properly the software that resided on them, which was in turn written by people who established discrete sets of monitoring criteria. The computers didn't understand the market any more than those who programmed them, of course, but they did have instructions: If “A” happens, then do “B.” The new generation of programs, generically called “expert systems” (a more attractive term than “artificial intelligence”) for their high degree of sophistication, were updated on a daily basis with the status of benchmark issues from which they electronically extrapolated the health of whole segments of the market. Quarterly reports, industry trends, changes in management, were all given numerical values and incorporated in the dynamic databases that the expert systems examined and acted upon, entirely without the judgmental input of human operators.

In this case the large and instant drop in the value of Citibank stock announced to the computers that they should initiate sell orders on other bank stocks. Chemical Bank, which had had a rough time of late, the computers remembered, had also dropped a few points in the last week, and at the three institutions that used the same program, sell orders were issued electronically, dropping that issue an instant point and a half. That move on Chemical Bank stock, linked with the fall of Citibank, attracted the immediate attention of other expert systems with the same operational protocols but different benchmark banks, a fact that guaranteed a rippling effect across the entire industry spectrum. Manufacturers
Hanover
was the next major bank stock to head down, and now the programs were starting to search their internal protocols for what a fall in bank-stock values indicated as the next defensive move in other key industries.