(2012, May)THE AUTHORS CREATED A MODEL OF AN ORDER BOOK "WHICH IS POPULATED BY A COMMUNITY OF HFT-ERS AND A COMMUNITY OF (SLOW) LIQUIDITY TRADERS. THE HFT-ERS OPERATE AT A MUCH FASTER SCALE THAN THE LIQUIDITY PROVIDERS. THEY ALSO PLACE AND CANCEL A LARGE NUMBER OF ORDERS (WHICH IS INDEED WHAT HAPPENS; HFT CAN ACCOUNT FOR OVER HALF OF THE TRADES ON A TYPICAL DAY).
Hedge funds caught red-handed using flaws in the NASDAQ market exchange to manipulate the price silver using high-speed computer trading algorithms.
Despite documented flaws in the way market exchanges handles high speed trades at high volumes, which are attributed to the DOW flash crash, electronic trading systems still have not been patched to fix the issue.
The vulnerability stems from bad timestamps assigned to orders when traders flood the system which causes trades to executed on quotes before they even yet exist in the system.
Earlier today high frequency traders were caught in act by NANEX taking advantage of the flaw to exploit the NASDAQ silver ETF by barraging the system with a whopping 75,000 trades per second.
The exploit then triggered other trading robots to execute trades based on the high volume of trades quickly plummeting silver price.
Read The Rest…
Silver Manipulation Caught in the Act; HFT Swamps NASDAQ with 75K SLV Sell Orders Per Second
Ironically, just days after noted analyst Ted Butler came on the show to explain how silver and other markets are manipulated through the use of high frequency trading, the real-time data feed company, Nanex, showed how the silver ETF (SLV) was forced downwards by a rapid number of machine-generated quotes exceeding a rate of 75,000 per second. Before you start to think that this was merely a bunch of people hitting the sell button all at once, consider this: They were all launched within the space of 25 milliseconds—ten times faster than you and I can blink!
Here's a chart of the second by second market activity in SLV where you can see the massive lightning-quick spike occurring at 13:22:33.
Ted Butler Explains the Whole Process
"What's happening is that these commercials [or large traders], through HFT, can set the price suddenly down. It didn't go down because there was massive selling from the commercials, they just set the price down. They know how to do it with their computers by putting in actual orders, and faking it, and spoofing, canceling them right away; but what happens is when the price moves down then the selling comes, which is the intended effect and result. Commercials basically put the price down in order to set off stops because everybody seems to be some type of technical trader in the market that reacts to prices."
(Click here for interview and full transcript)
Read The Rest…
Financial black swans driven by ultrafast machine ecology
Neil Johnson1, Guannan Zhao1, Eric Hunsader2, Jing Meng1, Amith Ravindar1, Spencer Carran1 and
1 Physics Department, University of Miami, Coral Gables, Florida 33124, U.S.A.
2 Nanex LLC, Evanston, Illinois, U.S.A.
3 The MITRE Corporation, McLean, VA 22102, U.S.A.
4 Complex Systems Center, University of Vermont, Burlington, VT 05405, U.S.A.
Society's drive toward ever faster socio-technical systems1-3, means that there is an urgent need to understand the threat from 'black swan' extreme events that might emerge4-19. On 6 May 2010, it took just five minutes for a spontaneous mix of human and machine interactions in the global trading cyberspace to generate an unprecedented system-wide Flash Crash4. However, little is known about what lies ahead in the crucial sub-second regime where humans become unable to respond or intervene sufficiently quickly20,21. Here we analyze a set of 18,520 ultrafast black swan events that we have uncovered in stock-price movements between 2006 and 2011. We provide empirical evidence for, and an accompanying theory of, an abrupt system-wide transition from a mixed human-machine phase to a new all-machine phase characterized by frequent black swan events with ultrafast durations (<650ms for crashes, <950ms for spikes). Our theory quantifies the systemic fluctuations in these two distinct phases in terms of the diversity of the system's internal ecology and the amount of global information being processed. Our finding that the ten most susceptible entities are major international banks, hints at a hidden relationship between these ultrafast 'fractures' and the slow 'breaking' of the global financial system post-2006. More generally, our work provides tools to help predict and mitigate the systemic risk developing in any complex socio-technical system that attempts to operate at, or beyond, the limits of human response times.