As it becomes increasingly clear that fewer and fewer hands control the
wealth of the planet, the manipulation of the market seems obvious enough.
No doubt, technology is playing an important role, but few have any real
idea about the extent to which the notion of day trading from the floor of
some market is completely obsolete, and how completely orchestrated things
really are.
Today, high frequency trading is conducted by computer algorithms that
predict market behavior and make rapid investment decisions mere mortals
could never keep up with.
In 2012, Zero Hedge reported that a whopping 84% of ALL stock
trades are conducted by high frequency trading computer systems. 84%!!
A new study of related technology patents confirms that this is
taking place on a larger scale that anyone even realized:
The way financial assets are traded, and the nature of the markets
themselves, has dramatically changed over the last two decades, says
study co-author Dr Ivan Diaz-Rainey of the University’s Department of
Accountancy and Finance.
“Trading a share-once a hands-on transaction taking around two
minutes-is now handled in mere nanoseconds by computers in many markets
around the world,” he says.
“A ‘technology arms race’ is well underway as firms vie to shave even more
time off trading and maintain their competitive edge. But it’s not just about
trading speed. We’re seeing technology used more when firms are first
issuing securities and even the use of neural networks in portfolio
selection.”
Yes, neural networks. As if the Federal Reserve era of finance wasn’t
skewed enough already, for some time now there have been computers actively
learning how to better game the system (and you).
And they have taken over almost everything.
A paper titled “Portfolio Selection with Predicted Returns Using Neural
Networks“:
The Markowitz’s Portfolio Selection Model defines the return and risk
variables as first-order statistical measurements, which have made this model
to be known as mean-variance model. We carried out investment simulations
using real data with the Markowitz’s model and our model. These simulations
shown that the prediction-quadratic deviation model can achieve a
return 12.39% higher than the mean-variance model.
Our experiments show that … the prediction-quadratic deviation model
selects higher proportions of stocks with predicted returns higher than the
mean returns used in the original model, and also because it can pick
solutions on regions of the return-risk space that are unknown for the
classical model.
Keep in mind that these formulas for computer-based investments are
literally getting better all the time, as they are learning as they go.
Moreover, they are starting with awareness of many market factors the average
person knows nothing about, and even insiders can’t realistically factor into
human-only trading.
Automated trading strategies are drawing from a wealth of data about
market performance and consumer trends to making investment decisions in a
fraction of a second.
In a paper titled, “Making markets: infrastructures, engineers and the
moral technologies of finance,” sociologists from the London School of Economics argue
that:
The electronic order book grounded the single most
important qualitative revolution in recent finance: its adoption
displaced trading from the floors of stock exchanges onto global electronic
trading networks, changing the spatial scope and interactional
character of the marketplace. Its adoption also transformed the speed
and politics of financial markets, as illustrated by the rise of automated
trading strategies that exploit the affordances of computers and
communication networks to generate profits in fractions of a second.
Between 2000 and 2009, the aggregate value of trading in global stock
markets grew by 61%; the number of trades, however, grew by 700%. Trades
today are smaller than what they were ten years ago, and they take place at
higher speeds — turnover velocity 1 in most mature markets is generally above
80% (the NYSE Euronex and NASDAQ are notable examples: their turnover
velocities are 138.5% and 300% respectively).
This means that those firms using this and other emerging technologies,
which has only come to light through an investigation into the development of
industry-related patents, have a definite edge on the market.
Financial trading expert and critic Max Keiser called the entire system a hologram, capable
of masking deflation and inflation through the feedback loop of these
computer algorithms, programmed behind the scenes to manipulate for human
interests:
In place of reliable price signals (based on the supply and demand
of buying and selling) we have price signals that are generated by computer
algorithms; i.e., computers executing program trading, high frequency trading
and algorithmic trading — that account for up to 70% of the trading activity
on the NYSE (or 100%, if you consider any shares traded — not
involved in program trading — can’t buck the pricing monopoly of the
computers).
Program traders have a virtually infinite line of credit, pay virtually
zero commissions, and are backed by banks on Wall St. with strong political
connections who are ready to bail out any losing bets these computers make.
Plus, the computers are able to do something normal buyers and
sellers can’t do. They can pick a price they want a security to trade at and
then fill in all the necessary trading volume needed to get the price of the
security to that point. In other words, you can program computers to rig
markets.
In this new rigged market capitalist model, the corrupt bank picks
the price it wants a security to trade at and the computers buy and sell with
each other until that price is reached; thus providing an audit
trail of trades that looks on the surface like actual price discovery.
And each price manufactured by computers generates a reaction price in
every other security and commodity as the rigged market price signal
ripples throughout the interconnected securities market around the world.
The average investor just doesn’t stand a chance, unless they are part of
the system that is rapidly buying up and developing these investment
technologies.
The researchers have equated this to a technological arms
race that is empowering the already dominant ‘incumbent’ firms on Wall Street
and London, and also making way for influence by emerging tech-trading firms:
New Zealand researchers said Monday they have traced the origins
of a “technological arms race” that gives Wall Street an advantage in the
international markets.
The University of Otago researchers scanned the United States Patent and
Trademark Office database for market infrastructure (MI) patents for software
or hardware using in trading filed between January 1976 and December 2013.
[...]
“Established economic theory tells us that new firms will play a leading
role in transforming an industry. However, traditional finance firms
are powerful and commercially astute so it is reasonable to assume at least
some will have responded aggressively by patenting new MI technologies
themselves,” said Diaz-Rainey.
“We identified software companies and smaller brokerage firms that have
invested heavily in technology internally and through market acquisitions,
right alongside major incumbent firms like the Chicago Mercantile
Exchange and Goldman Sachs.”
The study revealed that the leading MI patentee was not an
established firm, but a private software firm, Trading Technologies
International.
[...]
“At a basic level, all markets are increasingly integrated — if
Wall Street sneezes, New Zealand is likely to catch a financial cold.
So I guess a question is do we want to move towards this?” said Diaz-Rainey.
By the way, Trading Technologies International lead by CEO Rick Lane, who worked for Google after making significant developments
in the high frequency trading field, before rejoining Trading Technologies.
He has extensive experience in the very areas he is in the midst of
transforming:
Rick worked for a proprietary trading firm, where he developed trading
algorithms for the Chicago futures markets. Before entering the financial sector,
he worked at consulting firm Booz Allen Hamilton, where he developed
defense-analysis software for the U.S. Department of Defense and
other government agencies.
The question is, with a market this sophisticated and so … tilted, err…
rigged for the establishment players and their cronies, how long will it be
until the next crisis hits, and takes everything from the little people?
Or will this system ever be recognized as inherently corrupt, flawed and
dismantled in time to save the economies of the globe?
Because this technology has everything to do with the looming and
completely disastrous derivatives weight that could come crashing down with
absolute force at any time. Based on little more than a complex illusion.
Ponder the thought.
