The Gateway to Algorithmic and Automated Trading

Exploring a distributed world

Published in Automated Trader Magazine Issue 30 Q3 2013

Anna Reitman speaks to a range of experts to get to the bottom of some of the more common issues that come up when trading firms adopt distributed computing systems.

Traders are an increasingly intrepid group these days.

The days of making money simply by being super-fast and focusing on a few markets have been dwindling, with reports such as Automated Trader's Trading Trends survey showing ever-rising interest from firms to add asset classes and geographies. As the trading community discovers those new opportunities, they have to navigate their way through the world of distributed technology.

They will run into significant challenges, from the need to keep a lid on trading fees related to fragmented liquidity to more nuts-and-bolts issues such as network infrastructure complications. And those challenges go well beyond latency issues. Automated Trader spoke to a range of firms involved with distributed systems, as well as some users to gain some insight.

One firm that has wrestled with some of the issues is Mansard Capital. Its Mansard Macro Systematic fund covers 60 individual instruments in developed and emerging markets across asset classes including fixed income, FX and commodities. It uses systematic strategies, with trading based on signals generated from closing prices.

Leon Diamond, a founding partner and chief investment officer, said the firm does not rely on low latency strategies (he said playing the high frequency "game" required throwing money at it to constantly become faster). But it still needs to make sure that trading signals flow seamlessly across the network and generate the correct trades.

"The trends in the markets that can have a strong risk-reward payoff we try to spot are occurring anywhere from five to 30 days," Diamond said. "We are constantly modelling our slippage and taking that into account into our trading, taking model signals and seeing what impacts each of them has on the portfolio."

Mansard uses a vendor as well as banking systems for execution, but it has built the rest of its systems in-house.

A major task is to make sure there are no differences between the signals and what gets executed. "The consequences are being overweight or underweight that instrument in the market," he said.

It has been a significant hurdle, Diamond said, because an account could fluctuate tens of millions of pounds in response to model signals throughout the day. Or, the system could be signalling to trade an instrument in a month where there is not as much liquidity and trading the next month's contract becomes a better option.

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