This Is What A Singularity Looks Like

Too fast, too furious. The people operating these weapons of mass financial destruction are engineering intentional market instabilities by destabilising exchange operations through basically dDOS financial attacks and are simply rent seeking (by camping in locations close to the exchanges by light travel time) and add nothing to the marketplace in terms of providing liquidity or counter-party risk distribution. This is why we need to spray a minute quantity of a globalised fractional transaction tax, ala “Tobin Tax“, to control these roaches:

Analyzing millisecond-scale data for the world’s largest and most powerful techno-social system, the global financial market, we uncover an abrupt transition to a new all-machine phase characterized by large numbers of subsecond extreme events. The proliferation of these subsecond events shows an intriguing correlation with the onset of the system-wide financial collapse in 2008. Our findings are consistent with an emerging ecology of competitive machines featuring ‘crowds’ of predatory algorithms … [This figure] demonstrates a coupling between extreme market behaviours below the human response time and slower global instabilities above it, and shows how machine and human worlds can become entwined across timescales from milliseconds to months

(A) Crash. Stock symbol is ABK. Date is 11/04/2009. Number of sequential down ticks is 20. Price change is −0.22. Duration is 25 ms (i.e. 0.025 seconds). The UEE duration is the time difference between the first and last tick in the sequence of jumps in a given direction. Percentage price change downwards is 14% (i.e. crash size is 0.14 expressed as a fraction). (B) Spike. Stock symbol is SMCI. Date is 10/01/2010. Number of sequential up ticks is 31. Price change is + 2.75. Duration is 25 ms (i.e. 0.025 seconds). Percentage price change upwards is 26% (i.e. spike size is 0.26 expressed as a fraction). Dots in price chart are sized according to volume of trade. (C) Cumulative number of crashes (red) and spikes (blue) compared to overall stock market index (Standard & Poor's 500) in black, showing daily close data from 3 Jan 2006 until 3 Feb 2011. Green horizontal lines show periods of escalation of UEEs. Non-financials are dashed green horizontal lines, financials are solid green. 20 most susceptible stock (i.e. most UEEs) are shown in ranked order from bottom to top, with Morgan Stanley (MS) having the most UEEs.

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