I was watching a SAS industry analyst webinar which was made
available via Linkedin the other day. There had been plenty of focus on mega
power analytics, big data and various memory computing. One speaker from
Gartner, one of the most respectable IT research institutions on the street,
spent most of his coverage illustrating the impact of big data on financial
services industry - especially on high
frequency trading. He particularly quoted an article in Wired about a new trend
in academia research on big data and high frequency trading. The study
indicated that there had been more than 1800 flash events in money markets that
were traded during the past five years. My boyfriend, who serves in the trading
floor of a bulge bracket firm, also commented that there has been a strong
economic incentive for all those Wall Street banks to relocate their systems
and vendors as near as possible to the exchanges, no matter in New York or in
Chicago. By placing and receiving an order a tenth of a second faster, the firm
would be able to fish on pop out events in the capital markets. Meanwhile, such
events could also massacre the players out of control. For example, last year
Citigroup got jerked around so crazily by high frequency trading that there was
little correlation coefficient between
the company’s fundamentals and the stock price per se.
Last year research institution SunGard summarized 10 trends
shaping big data utilization. Among the ten quotes, the very first one is
‘Companies require larger market data sets and deeper granularity to feed
predictive models to forecast profitability and hedge risks in trading
throughout the day’. It was not news that sales and trading look huge advantage
on data analytics. But my question is how big the push is? Some investment appraisers
even doubted traders would not be necessary after foreseeable decades.
Here are some numbers to answer that question. The
application of big data has improved the speed and accuracy of trading
transactions on average by 13% and that impact will grow to 37% over the next
fifteen years, according to Capgemini’s surveys of 600 executive level and
senior management from Wall Street. Three-fourths of these managers stated in
the study that they consider their trading activities to be “data-driven”.
However, it does not necessarily mean that the firm strategies and day-to-day
decision making is built on the basis of big data. “Data-driven” here is more
referring to data collection and information integration. In fact, even firms
like Morgan Stanley which actively seeking improvements by utilizing advanced
technologies would suffer some bad times caused by automatic trading. Morgan
Stanley’s fixed income trading revenue was $2.04 billion in the first half of
2012, down 60% from 2010, increasing pressure on Chairman and Chief Executive
James Gorman to guide the company to steadier financial footing. “They’ve moved
into electronic trading better than their peers,” said Robert Kapito, President
of investment management house BlackRock, “However, the new trading strategies
will not always secure profits and might even lead to potential added-in
risks.” Highlighting computer trading is Morgan Stanley’s latest effort to
bolster a business that analysts say it has repeatedly misjudged over the
years, even as rivals such as Goldman Sachs Group Inc., Deutsche Bank and J.P.
Morgan Chase earned billions of dollars in profits. Banks have long viewed
electronic trading as a mixed blessing because it has hurt the fees, or
“spreads,” that can be charged on each trade.
From my personal perspective, I totally believe the
automatic trading will improve the capital markets. However, I do not agree
with the opinion that traders will be replaced by computers. This is a lesson
that Knight Capital learned last summer as it lost $440,000,000 when its
automated trading software went nuts. At a rate of $10 million per minute,
Knight Capital burned through almost its entire 2011 profits when its computers
decided to buy and sell stocks in the millions. This leaves analysts wondering
whether or not Knight Capital would still be a player in the trading game for
very long.
This
isn’t the first time a software glitch has caused a stock market meltdown. In
2010, a computer glitch caused the stock market to plunge nearly 1,000 points
within an hour as automated systems from a number of different companies
reacted off of one-another by selling massive amounts of stocks in what was
perceived as an inevitable crash. That incident was quickly corrected and
reversed, but it could have resulted in a lot of people losing their life
savings, or worse.
Intuition
is definitely human being’s hugest strength over machines. Computers have the
ability to calculate which we probably cannot catch up with for millions of
years of evolution. By taking advantage of this capacity, capital markets can
be more efficient and diversified. But automated trading can never replace
traditional traders because investment is not only about crunching numbers – it
absolutely requires a certain type of intuition to crack the ration behind the
numbers. I wish one day computers can share this type of intuition though, thus
I am more than happy to let one write this little piece of blog for me. J
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