I do not believe everything I read in the magazine, of course. But I had been asking myself for a long time what exactly were these puzzling and shadowy stock market transactions in which banks were risking billions of dollars and making tons of money in highly unregulated ways.
This article from the magazine has clarified many questions. I think it should be required reading as an introduction to our 21st century's economy.
You and I have always understood that a bank receives our money as a deposit with the purpose of keeping it safe in the first place, then lend it with a maximum care to businesses or individuals engaging in business, or even granting mortgage loans to solvent persons so that they can purchase a home.
Things have changed. Banks are not at all interested in lending to John Smith or Mary Jones the money they need to open their shop or expand their restaurant. They are not even interested in giving a loan to a small or medium sized corporation.
Banks now have changed their trade to:
1) Credit Cards.
2) Asset Management.
3) High level transactions such as corporate buyouts.
4) Selling "forced insurance" at ten times its costs to people whose mortgages they are holding, under any convoluted excuse.
5) Nickel-and-diming their customers (but the total profits are staggering), with all kinds of abusive charges and fees.
6) Taking people's money in deposit and paying hardly any interest to the depositor, thanks to our Federal Reserve's policy of the last few years, while they lend it (see item #1) at interest rates that can reach an effective annual 30% in many cases.
7) And of course, from time to time, get involved in massive mortgage business....(oops!) but this could be the subject of another article.
.... and a few more, I guess.
But you guys, children of the internet, super-computers savvy, intelligent phones users, algorithms apprentices, will surely want to know about some incredible facts that have sunk our country in the deepest recession in many years, and are still threatening our way of life with no relief in sight.
For example, when you hear "STOCK MARKET" you understand that it is a mechanism used by the common person to purchase shares of corporations with his or her savings, invest carefully and get a decent return in profits (dividends) of a successful enterprise, and even make some profit by selling these shares at a higher price later in the future, due to their appreciation.
Right?
Wrong.
Read on:
You will learn how things are done nowadays, you ignorant.
Sorry, it's a bit too long, but still worth a few minutes of your busy time.
Here is the article I am talking about:
Too Fast to Fail: Is High-Speed Trading the Next Wall
Street Disaster?
Computer
algorithms swap thousands of stocks each instant—and could set off a financial
meltdown.
—By Nick
Baumann
At 9:30 A.M. on August 1, a software
executive in a spread-collar shirt and a flashy watch pressed a button at the New
York Stock
Exchange, triggering a bell that signaled the start of the trading
day. Milliseconds after the opening trade, buy and sell orders began zapping
across the market's servers with alarming speed. The trades were obviously
unusual. They came in small batches of 100 shares that involved nearly 150
different financial products, including many stocks that normally don't see
anywhere near as much activity. Within three minutes, the trade volume had more than doubled from the
previous week's average.
Soon complex computer programs
deployed by financial firms swooped in. They bought undervalued
stocks as the unusual sales drove their prices down and sold
overvalued ones as the purchases drove their prices up. The algorithms were
making a killing, and human traders got in on the bounty too.
Within minutes, a wave of urgent
email alerts deluged top officials at the Securities and Exchange Commission.
On Wall Street, NYSE officials scrambled to isolate the source of the bizarre
trades. Meanwhile, across the Hudson River, in the Jersey City offices of a
midsize financial firm called Knight Capital, panic was setting in. A program
that was supposed to have been deactivated had instead gone rogue, blasting out
trade orders that were costing Knight nearly $10 million per minute. And
no one knew how to shut it down. At this rate, the firm would be insolvent
within an hour. Knight's horrified employees
spent an agonizing 45 minutes digging through eight sets of trading and routing
software before they found the runaway code and neutralized it.
By then it was shortly after 10
a.m., and officials from the NYSE, other major exchanges, and the Financial
Industry Regulatory Authority were gathering for an emergency conference
call. It didn't end until 4 p.m.Ads by CouponDropDown
In the four years since the collapse of Lehman Brothers
drove the global financial system to the brink of oblivion, new technologies
have changed Wall Street beyond recognition. Despite efforts at reform, today's
markets are wilder, less transparent, and, most importantly, faster than ever
before. Stock exchanges can now execute trades in less than a half a millionth
of a second—more than a million times faster than the human mind can make a
decision. Financial firms deploy sophisticated algorithms to battle for fractions
of a cent. Designed by the physics nerds and math geniuses known as quants,
these programs exploit minute movements and long-term patterns in the markets,
buying a stock at $1.00 and selling it at $1.0001, for example. Do this 10,000
times a second and the proceeds add up. Constantly moving into and out of
securities for those tiny slivers of profit—and ending the day owning
nothing—is known as high-frequency trading.
This rapid churn has reduced the average holding period
of a stock: Half a century ago it was eight years; today it is around five
days. Most experts agree
that high-speed trading algorithms are now responsible for more than half of US
trading. Computer programs send and cancel orders tirelessly in a never-ending
campaign to deceive and outrace each other, or sometimes just to slow each
other down. They might also flood the market with bogus trade orders to throw
off competitors, or stealthily liquidate a large stock position in a manner
that doesn't provoke a price swing. It's a world where investing—if that's what
you call buying and selling a company's stock within a matter of seconds—often
comes down to how fast you can purchase or offload it, not how much the company
is actually worth.
As technology
has ushered in a brave new world on Wall Street, the nation's watchdogs remain
behind the curve, unable to effectively monitor, much less regulate, today's
markets. As in 2008, when regulators only seemed to realize after the fact the
threat posed by the toxic stew of securitization, the financial whiz kids are
again one step—or leap—ahead.
- Circuit breaker: A mechanism to shut down trading when the market falls too fast or individual securities trade dramatically outside the normal range.
- Dark pools: Broker-run markets outside the public stock exchanges that allow investors to trade large batches of stocks anonymously.
- Holding period: The time an investor owns a security.
- Latency: How long it takes to execute a financial transaction over a network connection. This winter, two tech companies hope to launch the lowest-latency link yet between Illinois and New Jersey, a 733-mile chain of microwave towers to hurtle data in 8.5 milliseconds round-trip.
- Liquidity: A liquid asset can be easily bought or sold without changing in value—cash, for example, is more liquid than stocks.
- Proprietary trading: When financial institutions trade for the benefit of their companies, rather than for their customers. The Dodd-Frank financial reforms put some restrictions on proprietary trading at big banks, but loopholes abound.
- Quote stuffing: Placing and quickly rescinding a large number of buy or sell orders to confuse or slow down rival traders.
- Spread: In trading, commonly the difference between the highest price a buyer will pay and the lowest price a seller will take.
The Knight episode was "a
canary in the mine," says Michael Greenberger, a
University of Maryland law professor and former regulator at the Commodity
Futures Trading Commission (CFTC). "We've been lucky so far that this
hasn't been more serious."
Knight wasn't the worst-case
scenario. Not even close. A lot of high-frequency trading is done by small
proprietary trading firms, subject to less oversight than brand name financial
institutions. But big banks have also tried to get in on the act. Imagine a
runaway algorithm at a too-big-to-fail company like Bank of America, which
manages trillions, not billions, in assets. Or, says Bill Black, a former
federal regulator who helped investigate the S&L crisis of the '80s and
'90s, imagine trading algorithms causing "a series of cascade
failures"—like the domino effect that followed Lehman's collapse. "If
enough of these bad things occur at the same time," he says,
"financial institutions can begin to fail, even very large ones."
It's not a question of whether this will happen, Black warns. "It is a
question of when."
Years of mistakes and bad decisions
led to the 2008 collapse. But when the next crisis happens, it may not develop
over months, weeks, or even days. It could take seconds.
Alpha, New Jersey, is a sleepy
hamlet in the Lehigh Valley, near the Delaware River. Somewhere in town (the
owners won't say exactly where) is one of 10 2,000-square-foot amplifier
facilities that dot the landscape every 75-or-so miles between Chicago and New
York City, ensuring that fiber-optic signals travel between the two points as
clearly and quickly as possible. Spread Networks, the firm that operates the
facility, may have seen some poetry in the community's name—"alpha"
is the term investment managers use to describe the performance of an
investment after adjusting for risk.
Spread is part of a growing industry
dedicated to providing hyperspeed connections for financial firms. A faster
trader can sell at a higher price and buy at a lower one because he gets there
first. A connection that's just one millisecond faster than the competition's
could boost a high-speed firm's earnings by as much as $100 million per year,
according to one estimate.
Because of this, trading firms are
increasingly pushing the limits to establish the fastest connections between
trading hubs like New York, Chicago, and London. Every extra foot of
fiber-optic cable adds about 1.5 nanoseconds of delay; each additional mile
adds 8 microseconds. That's why companies like Spread
have linked financial centers to each other by the shortest routes possible.
Spread's Alpha facility is one of more than a dozen similar centers arrayed
along the path of its 825-mile-long, $300 million fiber-optic cable between
Wall Street and the Chicago Mercantile Exchange. Spread reportedly charges
traders as much as $300,000 a month to use its network. Exchanges like the NYSE
charge thousands of dollars per month to firms that want to place their servers
as close to the exchanges as possible in order to boost transaction speeds.
Industry experts estimate that high-speed traders spent well over $2 billion
on infrastructure in 2010 alone.
Traders' need for speed has grown so
voracious that two companies are currently building underwater cables (price tag:
around $300 million each) across the Atlantic, in an attempt to join Wall
Street and the London Stock Exchange by the shortest, fastest route possible.
When completed in 2014, one of the cables is expected to shave five to six
milliseconds off trans-Atlantic trades.
But why stop there? One trading
engineer has proposed positioning a
line of drones over the ocean, where they would flash microwave data from one
to the next like the chain of mountaintop signal fires in The Lord of the
Rings. "At what point do you say, 'This is fast enough'?" asks
Brent Weisenborn, a former NASDAQ vice president.
The acceleration of Wall Street
cannot be separated from the automation of Wall Street. Since the dawn of the
computer age, humans have worried about sophisticated artificial
intelligence—HAL, Skynet, the Matrix—seizing control. But traders, in their
quest for that million-dollar millisecond, have willingly handed over the
reins. Although humans still run the banks and write the code, algorithms now
make millions of moment-to-moment calls in the global markets. Some can even
learn from their mistakes. Unfortunately, notes Weisenborn, "one thing you
can't teach a computer is judgment."
One set of signals the programs have
to weigh are countless trade orders other algorithms send out and then quickly
rescind. There's a fierce debate about what these abortive trades might be.
Some speculate they are new algorithms being tested or strategic feints, the
equivalent of sonar pings probing the market for a response. Some of the fake
trades could be aimed purely at gobbling up bandwidth to slow down competitors.
"There are doubtless former [high-speed traders] who could tell us,"
Black says. "If I worked for the CFTC or the SEC I would be seeking them
out to try to learn what was going on."
On the afternoon of May 6, 2010,
CNBC viewers could have mistaken the channel's programming for an apocalyptic
blockbuster. The Dow, already down 400 points on bad news from Europe, had
suddenly plummeted another 600. Erin Burnett, wide-eyed, gesticulated at charts
to illustrate the "unprecedented" 1,000-point drop. The typically
manic Jim Cramer reached a new level of frenzy, shouting at viewers to
buy—BUY!—Procter & Gamble, which had fallen 25 percent, and wagging his
finger at the screen: "If that stock is there, you just go and buy it. It
can't be there. That's not a real price!"
Prices of nearly every stock and
exchange-traded fund had plunged in minutes. Some 300 securities experienced
wild gyrations, with trades executed at prices as low as a penny and as high as
$100,000 a share. During the same second, shares of the consulting firm
Accenture traded at both $0.01 and $30.
In what was later dubbed the
"flash crash," nearly $1 trillion in
shareholder value was wiped out in a matter of minutes before the market
rebounded, eventually closing down 3 percent from the previous day.
Almost five
months later, regulators would conclude that, on a day when traders had already
been shaken by the Greek debt numbers, a single massive sell order executed by
an algorithm belonging to a firm in Kansas had triggered a series of knock-on
events that sent the market into a tailspin. The analysis portrayed "a market
so fragmented and fragile that a single large trade could send stocks into a
sudden spiral," the Wall Street Journal reported.
The flash crash spurred regulators
to action—but spurs can only make a horse gallop so fast. No one in Washington
makes an extra million bucks a year for moving a millisecond faster, and it
shows. So far, Congress and the nation's financial watchdogs have done more
hand-wringing than regulating. In classic Washington fashion, when a Senate
subcommittee held a hearing in late September on the "rules of the
road" for algorithmic trading, the only consensus to emerge was that more
hearings were needed.
"Thanks to technology, our
securities markets are more efficient and accessible than ever before,"
then-SEC chair Mary Schapiro said at an October market technology roundtable.
"But we also know that technology has pitfalls. And when it doesn't work
quite right, the consequences can be severe. Just imagine what can happen if an
automated traffic light flashes green rather than red, if a wing flap on a
plane goes up rather than down, if a railroad track switches and sends the
train right rather than left."
Politicians and regulators realize
there's an issue, but by the time Washington gets a handle on the situation,
some experts fear, the damage may already be done. "We're always fighting
the last fire," says Dave Lauer, a market technology expert who has worked
for high-speed trading firms.
If it's a fire the SEC needs to
fight, the agency is working with equipment that's more reminiscent of bucket
brigades. The New York Times has called regulators' tech
"rudimentary." David Leinweber, the director of the Center for
Innovative Financial Technology at Lawrence Berkeley National Laboratory, has
slammed the SEC and the CFTC for running an "IT museum"—and taking nearly
five months to analyze the flash crash, which was essentially over in five
minutes.
One mysterious algorithm was
described as running "like a bat out of hell on crystal meth with a red
bull chaser."
To enhance its market-monitoring
capacity, the SEC has had to turn to industry—specifically, a firm called
Tradeworx that specializes in very-high-speed trades—for a new computer program
to analyze trading data. That program, called Midas, was scheduled to go online
at the end of 2012. But even Midas won't give the SEC a comprehensive picture
of the markets. It offers no data on so-called "dark pools," private
markets where buyers and sellers can trade anonymously, and it won't tell the
SEC who is responsible for a given trade.
To fill those gaps, the SEC plans to
ask market participants to submit comprehensive information about every trade
in the US markets—creating what is called a consolidated audit trail. But the
SEC won't receive this information in real time. Instead, the audit information
will be due by 8 a.m. the next day.
"When that data does come in,
since we have every single step, we will be able to reconstruct it exactly as
it happens," says Gregg Berman, an ex-physicist and SEC adviser who led
the agency's inquiry into the flash crash. "The only thing we miss is the
opportunity to do something the same day. But given that a robust and
defensible analysis of even a small portion of the trading day can itself take
many days, we don't give up much by waiting until the next day to receive a
complete record of the day's events." Studying this market data will help
the agency develop rules to address problems in the market—but only after they
occur.
Meanwhile, the financial world is
getting even more fast-paced, opaque, and downright mysterious. The same week
Schapiro spoke at the SEC roundtable, an algorithm consumed 10 percent of the
bandwidth of the US stock market. It "ran like a bat out of hell on
crystal meth with a red bull chaser, to mix a few metaphors," Leinweber
wrote on his Forbes blog. "It generated 4% of U.S. stock market quote
activity," but the program "didn't make a SINGLE TRADE, cancelling
every order. That is pretty darn weird." Leinweber suspects that the
culprit was a new algorithm being tested, but that's just a guess—no one knows
for sure, least of all the SEC. It used up "10% of the communications
capacity of our overly wired market," Leinweber noted. "Ten of these
guys could use the whole market...Scary stuff."
So far, the problems caused by
algorithms appear to be mostly accidental. But what if someone designed a
program intended to wreak havoc? John Bates, a computer scientist who, in the
early 2000s, designed software behind complicated trading algorithms, worries
that the kind of tools he's created could end up in the wrong hands.
"Fears of algorithmic terrorism, where a well-funded criminal or terrorist
organization could find a way to cause a major market crisis, are not
unfounded," he wrote in 2011. "This type of scenario could cause
chaos for civilization and profit for the bad guys and must constitute a matter
of national security."
Ask the Wall Street lobbyists about
things like cascade failures or algorithmic terrorism and they'll tell you not
to worry. They'll note that transaction costs have never been lower and that
the average investor can execute trades faster and cheaper than ever before. In
their view, the fact that Knight lost $440 million and didn't take the rest of
the financial sector down with it suggests that the market isn't nearly as
fragile as detractors claim.
Thanks to these arguments, and the
nearly $200 million Wall Street spent lobbying Congress around the Dodd-Frank
financial reform bill in 2010, that law did almost nothing to regulate
high-speed trading. In the absence of actual rules, the most widely discussed
safeguards are now the "kill switches" or "circuit
breakers" that kick in when a certain threshold is breached. After Black
Monday in 1987, when the Dow Jones dropped by nearly a quarter in one day, the
New York Stock Exchange instituted circuit breakers that halt trading
temporarily when the market falls by 10 percent and shut it down entirely when
it falls by 30 percent. Neither of these fail-safes, though, was triggered by
the flash crash—the market fell in a blink, but it fell less than 10 percent.
After the flash crash, the SEC
implemented new circuit breakers that kick in when an individual stock
experiences rapid, unusual price swings. But those didn't prevent the Knight
debacle—it was mostly trading volume, not unusual prices, that cost the company
hundreds of millions. New SEC rules slated to take effect in February will halt
trading for five minutes if prices of individual stocks move outside of a set
range for more than 15 seconds. But those are "a Band-Aid," complains
Lauer, the technology expert. "You're treating the symptom, not the
cause."
Lawmakers have proposed a
financial-transactions tax to limit high-speed trading churn, and raise
revenue.
Most participants at the SEC's
October market tech roundtable endorsed the idea of installing more kill
switches at various levels—for individual firms, individual stocks, and perhaps
for the market as a whole. But there's a problem: If a kill switch or circuit
breaker is automatic, it does nothing to reintroduce human judgment. Conversely,
if a person has to pull a kill switch, he or she has to take responsibility for
doing so—which creates its own problems
. "No one wants to be the guy who
cried wolf and got you onto the front page of the Wall Street Journal,"
Black says. "The word that's going to be used is that [you]
panicked."
So, if kill switches and circuit
breakers don't prevent future problems (and they haven't before), how do you
avoid the algorithmic apocalypse? Reformers are advocating what amount to speed
limits.
One of their proposals involves implementing what could be viewed as a
temporary "no backsies" rule, requiring trading firms to honor the
prices they quote for a minimum amount of time unless they execute the trade or
make a better offer. Even a minimum quote life of just 50 milliseconds
"would have eliminated the flash crash," says Eric Hunsader, the CEO
of Nanex, a company that makes software for high-speed traders.
In a more far-reaching proposal,
Rep. Peter DeFazio (D-Ore.) and Sen. Tom Harkin (D-Iowa) have proposed levying
a financial-transactions tax—they suggest 0.03 percent—on each trade, as a way
of discouraging churn and raising revenue. (The United States had such a tax
until 1966.) Economists, activists, and even some finance big shots—Warren
Buffett among them—have endorsed the idea. "Even at the modest level we've
proposed, [the tax] would raise $35 billion a year, which would either be used
to defray the deficit or be used for job-creating investments by the
government," DeFazio told me. Eleven European Union countries (though not
the United Kingdom) are pressing ahead with the idea—and they've talked about a
tax as high as 0.1 percent. Wall Street lobbyists have pushed back against both
speed limits and bringing back the transaction tax.
But in the wake of the
Knight episode, some industry experts are expressing doubts about the status
quo.
"I believe this latest event
was handled better than the flash crash, but the larger question is whether our
markets are adequate to deal with the technology that is out there,"
Arthur Levitt Jr., a former chairman of the SEC and a dean of the financial
establishment, told the New York Times in August. "I don't think they
are." That view is becoming more widely accepted, even among corporate
CEOs, traders, and the algorithm builders themselves.
The chief executives of publicly
traded companies—who are hired and fired based on stock prices—increasingly
worry that their shares could be sent into a free fall by an algorithmic
feeding frenzy. The current markets have created a "somewhat disjointed
world between what a company does and what its stock does," the CEO of one
billion-dollar, NYSE-traded company told Mother Jones.
According to Ben Willis, a longtime
NYSE trader, "When you have the heads of the Fortune 500 companies say,
'Hey, wait a minute, guys: Our stocks look like hell and...no one can tell me
with any certainty who is doing what to my stock and why,'" the critics
might gain political momentum. Then again, the financial sector has a pretty
solid track record of stymieing reform. And, given the extent to which the
international financial markets are intertwined, would slowing down Wall Street
make a difference if similar measures weren't taken in London and Hong Kong?
As market-shaking episodes pile up,
even some of the tech geniuses who helped usher in Wall Street 2.0 now worry
about their innovations running amok. Wall Street Journal reporter Scott
Patterson's book on high-speed trading, Dark Pools, recounts the story of
Spencer Greenberg, a young math genius who built a hugely successful trading
algorithm named Star but later came to have reservations about what he had
unleashed on the world. "In the hands of people who don't know what
they're doing," Greenberg warned a gathering of algorithmic traders in
2011, "machine learning can be disastrous."
