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Algorithmic Futures Trading


Futures trading is most commonly defined as the placing of a bet on price movement in commodities (pork bellies, sugar, soybeans, etc. to name a few), financials and currencies.  A good example of a futures trade is one effected by British Airways. When executives at BA decided that the price of oil would rise, they hedged against this development by taking long positions in oil. When oil prices rose, BA was locked in at their low hedged price and were, therefore, insulated against price rises when oil prices rose drastically.

Algorithmic futures trading makes use of certain software solutions for creating programmes and platforms to be used in implementing trading strategies and systems.  These systems will aim to get the most out of futures trading by way of automation, speed, and flexibility.

It takes two parties to effect a futures trade.  Typically, one is the company that uses the product being traded for ‘hedging’ or insurance purposes and the other is the speculator who believes prices will move in the opposite direction.  Notwithstanding the current political rhetoric, futures trading generally brings price stability to the items being traded.

Automated, computer-driven trading systems use complex calculations to determine when to buy or sell a certain futures contract. One of the most important features of any trading platform and software solution will be its capability in delivering low-latency, high frequency messages and trades. Latency is the time between the moment when a trade order is entered into the computer and when that order is actually executed. With the incredibly high volumes of futures being bought and sold today, automated computer-based trading serves a purpose by minimizing latency and therefore being able to react to a piece of news, or a corresponding market move, in the fastest way possible.

Algorithmic futures trading platforms can also be programmed with strict rules that are intended to enable professional traders to buy or sell multiple contracts at optimal times while having relatively little impact on the premium prices and the values of the underlying assets. This keeps trading costs down and helps prevent too much market volatility. Large institutional investors rely heavily on these platforms because they can buy and sell many contracts at a time during the course of a day.

Super-fast algorithmic trading systems help improve profitability from futures arbitrage. Patterns of price flux are analyzed and programmed into the model so that there is as little time lag as possible in the execution of multi-product strategies, subject to infrastructure constraints and the speed of light.

Of course, good algorithmic trading platforms need to be enabled and supported by good service providers. We at the Kyte Group have made significant investments into our own infrastructure to allow us to facilitate low latency, high frequency trading. We have cutting-edge remote hosting suites with detailed attention to cabling, air-conditioning and power in order to safely house state-of-the-art server hardware. We also provide the latest specification trading machines for less than list price and can host this kit in our purpose-built London data centres or in Chicago, Paris, and Frankfurt.



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EXECUTION

The Kyte Group Limited was founded by David Kyte in 1985 on LIFFE, the embryonic futures exchange in the heart of the City of London.
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Kyte's customers are market professionals, either sole traders, teams of market,
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Providing clearing and settlement services to professional traders who transact business on the world's leading exchanges.
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