Finding the Correct Path Through Market Turbulence

Issue 08 Q1 2008
Automated Trader Magazine

Recent months have seen financial markets experience more turbulence than perhaps ever before. Market corrections, war in the Middle East, sub-prime crisis, bulls and bears not sure which they are, and more recently the return of the 'big style' rogue trader have caused more volatility, I would suggest, than most have ever experienced.

Jon Carp

Jon Carp, Head of Alternative Execution Sales Europe at CA Cheuvreux

This raises some interesting questions relating as to how execution algorithms and automated trading systems react to such sharp market and price movements. Surely, when algorithms are mathematically formulated, it is almost impossible to build in the prediction analysis required to cope with the uncertainty we have been experiencing recently. Algorithms use history as a guide to their future behaviour so, when markets are acting in a way perhaps never seen before, how do they cope?

Tuning the engine

I believe it is widely accepted that 'black boxes' have exaggerated the market movements over the past year due to this new market behaviour and a lack of comparable historical market data. The wide spread of percentage gains and losses recorded by European-based quantitative hedge funds in 2007 perhaps prove that machines need fine tuning.

While the majority report gains for the year, far more show negatives for the final six months when the volatility really kicked in.

So if algorithms are experiencing unknown territory it would follow that their usage would reduce. Why would traders trust algorithms when they are operating in a potential minefield?

Interestingly, our experience at Cheuvreux is the opposite. The steady rise in usage of our algorithmic strategies, by our clients, over the first half of 2007 was suddenly accelerated during the second half, and the chart sharpens even further as we enter 2008, with huge daily market movements. Perhaps the previous 12 months has provided more relevant data for the algorithms to perform better. Maybe traders prefer to put ‘noise’ trades in the machine while they focus on the others. Evidence from our own clients suggests the former. It is noticeable that the average size of the 'parent' order has substantially increased. ...