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Stock Exchange offers low latency feeds

Market data, fast as you like

Tags: algorithmic trading, hosting, lse

By Julian Goldsmith

Published: 10 June 2008 13:22 GMT

The London Stock Exchange (LSE) has agreed a deal for connectivity service provider Savvis to provide a proximity hosting service for member firms, hedge funds, market data vendors and the automated trading community.

The move is in response to a demand for low-latency, super high speed delivery of market data across many elements of the trading community. Savvis' service will connect investors to the exchange's Infolect and TradElect electronic trading platforms via the supplier's London Docklands data centre.

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In a statement, LSE head of real-time data Wendy Morgan said: "As trading volumes grow and latency becomes more crucial, it is essential that our customer have a wide variety of options when choosing to connect to the Exchange's markets. We therefore welcome investment in this service as it increases the number of direct participants in our markets."

The announcement came as the LSE itself boosted connectivity for member investors by offering Infolect data over 100MB lines. Called the Performance Channels service, the connection has already been signed up by 40 customers. Customers retain their existing connections, with the super-speed link cutting in only at peak times. The exchange claims the average speed of data traffic within the City of London has been cut to below a millisecond.

According to a spokeswoman at the Exchange, the service negates the need for investors to trade through third parties and gives them better access to accurate market data at peak trading times. It also means the Exchange will get a better share of the commission revenues for each trade made over the service, as it is made directly to the LSE.

In a statement, LSE CIO David Lester said: "The introduction 12 months ago of TradElect has facilitated record volume growth in our markets. The Performance Channels service gives member firms using algorithmic trading models greater visibility of the spikes and events that occur during periods of high trading activity."

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