Debt Of Honor by Clancy, Tom

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 book-

keeper for the entire equities market. Their screens showed an accelerating

pace of activity, but the computers were all running Chuck Searls’ Electra-

Clerk 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 both-

ered 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 administra-

tive volume would have taxed the abilities of the entire industry. Instead, the

purpose of DTC was lo 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 mathe-

matical 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 spe-

cialty area and responsibility for a discrete number of issues grouped by

type. One firm might have eight to fifteen pharmaceutical issues, for exam-

ple. 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 Ex-

change 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, watch-

ing 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 work-

ing 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 mat-

tered in any case. Few people listened to the statement beyond the announce-

ment 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 hun-

dred 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 soft-

ware that resided on them, which was in turn written by people who estab-

lished 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 up-

dated 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 an-

nounced 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 electroni-

cally, dropping that issue an instant point and a half. That move on Chemical

Bank stock, linked with the fall of Citibank, attracted the immediate atten-

tion of other expert systems with the same operational protocols but differ-

ent 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 inter-

nal protocols for what a fall in bank-stock values indicated as the next defen-

sive move in other key industries.

With the money reali/.ed by the Treasury sales, Columbus started buying

gold, both in the form of stocks and in gold futures, starling a trend from

currency and into precious metals. The sudden jump there went out on the

wires as well, and was noted by traders, both human and electronic. In all

cases the analysis was pretty much the same: a sell-off of government bonds,

plus a sudden jump in the Discount Rate, plus a run on the dollar, plus a

building crash in bank stocks, plus a jump in precious metals, all combined

to announce a dangerous inflationary predictor. Inflation was always bad for

the equities market. You didn’t need to have artificial intelligence to grasp

that. Neither computer programs nor human traders were panicking yet, but

everyone was leaning forward and watching the wires for developing trends,

and everyone wanted to be ahead of the trend, the better to protect their own

and their clients’ investments.

By this time the bond market was seriously rattled. Half a billion dollars,

dumped at the right time, had shaken loose another ten. The Eurodollar man-

agers who had been called back to their offices were not really in a fit state to

make rational decisions. The days and weeks had been long of late with the

international trade situation, and arriving singly back at their offices, each

asked the others what the devil was going on, only to learn that a lot of U.S.

Treasuries had been sold very short, and that the trend was continuing, now

augmented by a large and very astute American institution. But why? they