In Forex Trading, Be On Time

You are losing if you are late in trading. Processing of high volume data feeds is necessiated to monitor fast markets. This computing power has been slow to come to forex, but new technologies are making it a reality. If one has the necessary speed, he can analyse low frequency data in a sophisticated fashion in real time. Low latency processing of large volume of data feeds is supported by historical databases that allow strategies to keep up. Since Forex depends on an over the counter type market as well as logistic hurdles, this becomes a major challenge for it. Stream Processing is the new solution being provided by the industry. If it wasn't for stream processing, it would only have been stored data that could execute queries or compute information, and not real time streaming data. Real Time Analytical Applications were traditionally coded in languages such as C++ & Java.

Low development costs cannot be achieved by using custom code or low level tools. Stream processing on the other hand takes data differently, allowing for faster performance, simpler coding and integrated access to both real time as well as historical data. Inbound Processing is utilized by Stream Processing Engines

The foreign exchange transaction volumes are continually growing. Long trading hours, varied participants, profit potential in declining markets, narrower opportunity windows because of improved automation and rising algorithmic trading tools all result even while the opportunity depth is soaring due to excessive liquidity. Real time applications need to be extremely customizable due to these characteristics and must be adaptable or adjustable on the fly. Stream Processing technology shines in the given case.

Everything, from price sourcing, setting, publishing to trade processing needs to be continuously optimized by forex institutions for the sell side. The buyer today has various options available, even the markets are volatile, this makes price quality the distinguishing factor and a function of speed. The most important tasks performed by a pricing engine are data cleaning and price setting and both of them require latency as a key requirement. Sub second latencies are wanted even with manual operations.

Liquidity portals and sell side institutions contribute to the increasing trend of arbitrage and cross market trading by integrated access. With algorithmic trading, the latency requirements get drastically smaller. The difference is made in a matter of few milliseconds. Specifically, Forex based hedge funds are aggressively leveraging the low efficiencies, this is being achieved by arbitraging price differences from various liquidity providers.

Applications can analyze historical information and trends for real time querries by using stream processing. Automated response to the electronic information sources shall be a reality in the near future because of the increasing automation in the fundamental analysis and risk taking models.

Since stream processing has already left a mark in the exchange market, we shall soon see similarities between it and the forex. We shall see stream processing engines turn into a key component for the future forex platforms because of their unparalleled performance, flexibility and agility advantages.