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.
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.
In 2012, Zero Hedge reported that a whopping 84% of ALL stock trades are conducted by high frequency trading computer systems. 84%!!
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.