The Gateway to Algorithmic and Automated Trading

Finding the time

Published in Automated Trader Magazine Issue 28 Q1 2013

Automated Trader talks to Steffen Gemuenden about the Automated Trader Survey.

Steffen Gemuenden

Steffen Gemuenden

CEO, RTS Realtime Systems

Markets continue to evolve very quickly, presenting huge challenges for all participants. The initial survey results accurately reflect the challenges or opportunities that our customers are asking us to help them address. There are two areas in particular that stand out.

Firstly, latency imperatives are without doubt shifting. That doesn't mean that firms are giving up on the race to zero. On the contrary, latency is just as important as ever. But the focus has altered. The marginal gains where execution latency is concerned have now become so small that firms are putting other parts of their trade processes under the microscope to find precious fragments of time.

Secondly, firms want to extract greater value from their trading infrastructure by allowing efficiencies to flow through the trade lifecycle, adding value to other processes. As such, the latency race has morphed into what Automated Trader describes as "decision latency" and "value latency".

Decision latency affects not just the speed at which a trading signal can be generated, but many other essential functions which impact, and are impacted by, both the decision and value latency inherent in other areas of the trade lifecycle. Risk management is a good example of this, but other functions such as dynamic hedging of currency risk, collateral management, post trade analysis and portfolio analytics all have value and decision latency implications elsewhere in the trade lifecycle.

The challenges are compounded by the strong trends towards multi-asset class and multi-region trading and with that, the need to be able to monitor, control and extract value from multiple algorithmic trading engines running in different locations globally. With pre- and post-trade functions more inter-dependent than ever before, the design and management of distributed algorithmic deployments, and the efficiency of the processes that they feed, looks set to become one of the key determinants of overall trading performance.

Further details on the survey findings can be found here