Risk Management

The FIORD project has the potential to prevent the triggering of financial markets plummeting, which was the case of the United States stock market crash on May 6th, 2010 (known as the ‘Flash Crash’) in which the Dow Jones Industrial Average plunged by 1,000 points (about 9%) only to recover those losses in minutes. 

FIORD would contribute to the forensic review increasing the reliability and security of markets leading to heightened investor confidence and greater market liquidity and help prevent turning economies into frenzy which was the case on May 6th 2010. FIORD presents semantic solutions to the market participants. In turn it gains applied knowledge of the industry and the use of data there-in. This knowledge will be captured in open versions of the ontologies and semantic algorithms, which in turn will be put forth as draft standards for the financial services industry. It brings an important but volatile industry forward. We focus on Europe but the issue is global and the benefits worldwide.


Thus, a regulator like the recently proposed EU Single Supervisory Mechanism or a large market participant would be able to:
  • Perform complex and rapid queries on the large volume of trades that can be generated in just seconds on a set of trading platforms run by exchanges and market participants in any particular market or the market overall;
  • Use these queries to analyse market activity, potentially in real time and detect hazardous events as they occur allowing immediate response, speedy resolution and detailed after action review of such events;
  • Provide collated data to a suite of reporting tools that would allow rapid analysis and understanding of the changing position in the market in a visually intuitive style through trigger mechanisms and other display and dash boarding devices.
The benefits of the Big GRC Data FIORD platform for the end user stakeholders (i.e. financial services, governance, data protection and security agencies) are:
  • Measured step towards a common trading knowledge management base for Europe’s financial regulators, market participants and policy makers. This would allow a competitive trading environment in the European Union, while protecting citizens and the financial stability of the region; 
  • Early engagement of end user stakeholders and transparency of basic trading knowledge, including standards to stimulate a return on trading investment;
  • Effective utilisation of critical research for trading knowledge to provide for a higher degree of collaboration between the end users’ stakeholders from their perspectives;
  • Excellent channel for rapid update to the stakeholders in relation to new trading trends and activities;
  • Interoperability opportunities, increasing collaborative advantage, potential efficiency opportunities as a result of mutual knowledge sharing between financial regulators, financial service professionals, large data storage organisations, ICT SMEs and centers of excellent academic research;
  • Significant possibilities for increasing public confidence and increasing business community confidence within the EU as a result of the ready access to real time querying and analysis of market data and review of events that threaten the stability of EU financial markets.

The Big GRC Data platform can also be a tool and knowledge aid to other ongoing and related research projects currently as a central point of contact for current trends and emerging threats.

Case Study: Flash Crash and High Frequency Trading
The State-of-the-Art in areas such as High Frequency Trading (HFT) operations is best exemplified when markets, from the perspectives of pricing and liquidity, behave erratically and unpredictably with potentially damaging consequences for national or even global economies where the root cause is technological rather than related to market participants’ trading strategies or tactics. 

No single event demonstrates these conditions more aptly than the ‘flash crash’ of May 2010 when the prices of U.S. equity products suffered rapid and irrational decline and subsequent recovery. In a single day (May 6) equity indices in both the futures and securities markets, which were already performing over 4% below the previous day’s close, suddenly fell a further 5 to 6% in a matter of minutes after which they recovered almost as quickly. 

This effect was experienced across many of the almost 8,000 individual equity securities and exchange traded funds (“ETFs”) traded that day. Some experienced price declines of 5%, 10% or even 15% before recovering most of the losses. But there were some equities that experienced even more exaggerated price fluctuations... down and then back up. Studies conducted by the staffs of the US CFTC and SEC reported  that, ‘over 20,000 trades across more than 300 securities were executed at prices more than 60% away from their values just moments before. Moreover, many of these trades were executed at prices of a penny or less, or as high as $100,000, before prices of those securities returned to their “pre-crash” levels’.

The overall effect was an evaporation of buy-side liquidity in light of the highly unstable movements in prices which, in turn, created more downward pressure on prices with further evaporation of market liquidity.

The mayhem lasted approximately 20 minutes. As market participants completed their risk assessments and were able to verify the reliability of their data and systems the market began to normalise. Studies and analyses subsequently conducted of what occurred during that 20 minute period revealed more than 20,000 trades, predominantly retail customer orders, across more than 300 securities that included 12 that were executed at as much as 60% removed from the prices that existed prior to the commencement of the 20 minute period of mayhem. The respective market authorities agreed to the cancellation of these trades invoking the ‘clearly erroneous’ criteria.

The response of markets in turbulent market conditions is to trigger exceptionally high trading volumes that in no way represent the liquidity available in the market. It is a perverse outcome of automated trading mechanisms such as HFT that as markets become disorderly trading volumes tend to increase rather than decrease. Scalability of monitoring systems at these times is critical to give market users the information they to react to a rapidly changing market. Incomplete information will only add to panic; a robust semantic system with existing connections to other market information will help to give a real-time picture of what is happening and how to respond.