We have had the flash crash, the breathtaking 1000-point drop-then-surge that happened on May 6th, 2010. In the near future we will have a new worry – prepare for the “Splash Crash”, which will cross asset barriers in a single bound.
As asset classes outside equities – energy, commodities, FX, derivatives – become increasingly automated there will be more flash crashes. Increased interdependence of asset classes will lead to cross asset flash crashes – a domino effect where the crashes ‘splash’ across asset classes, possibly wreaking havoc for market participants and regulators.
As regulators said following the flash crash: “a complex web of traders and trading strategies” links the fragmented multitude of markets here in the U.S. And, like dominoes, when one goes the rest follow. The dominos are no longer limited to one asset class. Algorithms are becoming increasingly sophisticated, encompassing all of the elements that may impact a trade in a certain instrument. If a trader wants to take a substantial position in a foreign equity, for example, there are many ingredients that can affect its market price.
Consider news events such as the BP oil spill or the current political crises in Egypt and Tunisia. The impact of these events has illustrated the close relationship between the oil price, equities, foreign exchange, commodity futures and the bond markets. Extreme and possibly unexpected events coinciding can trigger a cascade. We saw with the flash crash how instability in European economies caused nervousness in the market and then an algorithm did something unexpected – causing a cascading effect across futures and equities markets. As the cross-dependencies grow and algorithms become more inter-twined, so the risks for a “splash crash” grow.
It’s not hard to consider a splash crash scenario given the growing inter-linking of markets. For oil companies, such as BP, equity trader’s positions can be affected by the price of the pound and UK interest rates, as well as the dollar and any countries currencies where it is exploring or supplying oil. Oil prices will impact the bottom line, therefore the share price. Political events such as wars in oil-producing countries are important, as are disruptive events such as oil spills, and can impact oil, equity, bond, commodity future and foreign exchange prices. What if China’s economy falters and its oil consumption is predicted to fall? Oil prices globally fall, dragging the US dollar higher. Oil derivatives predicting that prices would stay high for the next year or two or three also fall. Share prices for the whole oil sector including BP, Exxon Mobil, Texaco, Chevron, Philips, Sinochem, etc. collapse. Debt markets are stunned and bond rates rally.
All of these factors can be programmed into an algorithm that monitors and makes trading decisions on the BP position. If large banks and hedge funds also have substantial positions in BP, the dollar, the debt and the derivatives and they also have algorithms that will kick in when certain parameters are met. If enough instability and unexpected conditions occur and then one of these algorithms does something strange or unexpected, the cascading impact could be enormous across all asset classes. For example, massive automated sell orders for oil shares, energy futures and derivatives and buy orders for USD and Treasuries. Trading systems could clog up, limited bandwidth could choke orders, exchanges could freeze up – splashing across all of the affected asset classes. Pandemonium.
Splash Crash Prevention Tips
Luckily there exist ever more responsive and intelligent algorithms that can react instantaneously to market anomalies and anticipate interruptions to liquidity. These rapid response algorithms could help to prevent the next flash crash by alerting risk managers of impending issues, or by changing trading strategies to accommodate market glitches.
On top of smarter algos, there are a few other splash crash prevention measures:
- Use real-time pre-trade analytics and risk management. If the mutual fund in question on May 6th or its executing broker had done a thorough back-test of its trading strategy, using some of the dire indicators present, it might have thought twice about selling so aggressively – possibly preventing the crash.
- “Light up” the algorithmic trading process. Visibility during the trading process is crucial. Surveillance technology exists than can monitor the markets for anomalous behaviour and alert the parties involved if it is spotted. Give the regulators the tools, too.
- Homogenize trading rules across all exchanges and ECNs. When one halts trading they all halt – for the same amount of time.