Offering wider market access – Cloud Computing proves well suited to FX >>>
another data center which forms part of Equinix’s global network.
Johnston also expects a flourishing of the hybrid cloud model, in which institutions choose to have some services in-house and others on the cloud. “You could
have a very high performance system pushing orders into the market, while a public cloud is used to do daily batch risk analysis,” says Johnston.
Latency issues
In financial markets becoming increasingly dominated by ultra-low latency trading, in which leading banks and trading firms battle each other in a race to achieve ever faster trading speeds, Manicom believes the cloud may not be the best solution for front office trading systems. “If you want to fire an algorithmic generated FX order at a time when you are ahead of the market by 100 microseconds, you do not want to run the risk of your cloud server being busy at that point,” he says.
Popescu of Boston Technologies takes a similar view on the potential latency pitfalls in implementing cloud-based solutions for ultra-low latency trading. “For the masses, for the majority of traders I think the cloud is the best. But for some of the institutional market and for the highly competitive, sophisticated market, I do not think it is,” he says.
Manicom offers that the multi-tenant environment of shared server racks within the data center of a cloud computing provider can create potential latency problems for ultra-fast FX trading. He says a so-called “noisy neighbour” problem can emerge, should a resident in the data center perform an extraordinary task which involves a large amount of compute capacity. “If number crunching for risk checking a batch of data takes one hour and ten minutes instead of an hour, that’s not the end of the world. But if a trade takes 500 microseconds instead of 50 microseconds, that translates to real costs,” says Manicom.
Sam Johnston
“You could have a very high performance system pushing orders into the market, while a public cloud is used to do daily batch risk analysis,”
However, Sandhu of Integral does not agree that the cloud creates problems for latency, arguing that in fact the cloud can be even more robust than internal systems used by major sell side firms in withstanding spikes of market stress. He points out that Integral’s systems are continuously monitored for potential latency issues. “On the week after the Japanese earthquake, we experienced a six-fold spike in volume in Japanese Yen trading in one hour. Yet there was no perceptible latency issues whereas two of the top five banks in the world shut systems down because they could not handle the load,” he says.
Sandhu says Integral’s customers benefit from its “distributive network” of participants which can be robust in rare incidents of market stress, in contrast to systems reliant upon a single order book to provide liquidity. “In times of volume or liquidity stress – both of which took place in the flash crash of May 2010 – you will have participants that fail,” explains Sandhu. “Te beauty of having a broader interconnected network is that elements of that network can fail but it is immediately supplemented by liquidity in other parts of the network.”
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