Stream Processing Empowers Traders

You're already losing in trading if you're late. Processing of high volume data feeds is necessiated to monitor fast markets. Forex markets utilize advanced technologies to generate the computing power that they didn't get before. Sophisticated analysis of real time, low frequency data requires speed. It isn't possible for strategies to keep up unless they have the support of historical database and low latency processing of volume of data feed. Among other things, this turns into a very specific challenge in Forex owing to its nature as an over the counter type market equipped with logistical hurdles. The industry's solution is a new way to process data called stream processing. Real time streaming data could not executed queries or computed items if it wasn't for stream processing. Programming languages such as C++ & Java have traditionally been used by coders to create real time analytical applications.

But custom coding and the use of low level tools can translate into high development costs. The way stream processing handles data has led to faster performance, easier programming as well as integrated access to historical data and real time data. Stream processing engines utilize inbound processing.

There is a continuous increase in forex transaction volumes. Even as excessive liquidity results in greater depth of opportunity, the long trading hours, wide ranging participants and profit potential in dwindling markets, the opportunity window keeps on reducing due to increase in algorithmic trading tools and automation. These characteristics necessitate customizable real time applications that can be adapted or adjusted on the fly. This is a scenario where the stream processing technology shines.

Everything, from price sourcing, setting, publishing to trade processing needs to be continuously optimized by forex institutions for the sell side. Price quality becomes the key differentiator owing to the high market volatility and the buyers increased options. The pivotal point for data cleaning and price setting is latency, this forms the basis for pricing engine tasks. The desire for sub-second latencies is existant regardless of the manual operation.

As for the buy side the trend towards combined access to various sell side institutions as well as liquidity portals has generated new opportunities for arbitrage & cross market trading. With algorithmic trading, the latency requirements get drastically smaller. The difference is made in a matter of few milliseconds. The price differences from multiple liquidity providers is being arbitraged to leverage the inefficiencies by forex based hedge funds.

Real time queries about historical trends or analysis can be performed by new applications if they are empowered by 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.

In the long run, the forex market will look increasingly more like the exchange market, where stream processing has already proven its value within a short time. The advantages of stream processing engines, such as performance, flexibility and agility shall lead them to be a key component in the next generation forex platforms.

By: Timothy Ortega

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