Experience capital gains using Low Latency Trading infrastructure

Capital Markets live and work on just one thing – Speed. Speed is seen in terms of speculation, execution and analysis. However, in the world of capital markets, the tick price of the financial instruments changes rapidly. In such scenarios, sometimes there is a delay between execution of orders and change of tick price. This delay is termed as Latency.

It’s high time since capital markets have shifted into the electronic domain and employ the use of computers and networks. Electronic Trading has taken place of traditional ring trading and is now governed by the control of exchanges. However, most of the times, the stock prices seem to change in a fraction of milliseconds and a time gap is introduced before the updated prices are visible to the users. To tackle this delay, exchanges and firms are constantly looking to implement a low latency trading infrastructure.

Latency introduced in the realm of capital markets is of two types. First type involves the delay between the actual price and price shown on the screen. The second type of delay involves the difference between the price at which order is placed and what it gets executed. Market participants and capital firms are constantly striving to reduce the latency in order to gain a competitive edge.

Many of the leading IT firms came up with a solution to inhibit or reduce latency significantly. They have introduced an infrastructure of systems, which comprises of high speed network connections and fast trading platforms. The collaboration of both these entities is believed to decrease the problem of latency. The infrastructure developed is called Low Latency Trading Infrastructure and is actively deployed on leading stock exchanges around the globe.

The first component comprises of network elements for connectivity. High speed routers and reliable internet connections are used. Further, to tackle issues of disconnection, leased lines are used. Internet Service Providers (ISP) provides data lines from servers having the least downtime. Thus, any change in the stock price will be immediately given to the trading software.

The second component consists of high speed trading platforms. The systems work on real time basis and instantly show responses displayed. They also facilitate instant order placements and the turnaround time taken to place an order from the user terminal to the exchange is dramatically reduced. Apart from this, all the tick prices are displayed on the client’s terminal on real time basis. So, instant change in price is quickly visible on the trader’s screen.

Low Latency trading platform has been implemented by New York Stock Exchange in association with popular investment and capital trading firms. It has immensely improved the scope of trading and helped individuals attain profitable returns.

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10 reasons to choose Big Data Analytics

Big Data is a recent concept that has struck the IT industry in a hard and fast way. It is seen that all kinds of new technologies are first adopted by larger enterprises and then considered by midsized companies. With time, the amount of data to be processed is going to increase drastically. In order to mitigate the risk of managing loads of data, Big Data Analytics is said to be a feasible solution.

Before you choose any kind of analytics, here are the top 10 reasons you should consider

1) Enterprise wide real-time indexing of data from any machine

Big Data uses NoSQL databases like Hadoop. Hadoop uses file indexing instead of data indexing carried in typical relational databases. Thus, it is able to handle diverse data comprising of different sources. Here, data is stored as it comes with definition left to analysis stage.

2) Easy search and analysis of data

Data – real time or historical needs to be recalled quickly as possible for the sake of analysis. Big Data provides search tools for calling unstructured data using text search. Thus, faster responses can be provided.

3) Automatic knowledge discovery from data

Data mining and predictive analytics technologies discover the data to propose statistical models. Based on these models, continuous evaluation is automatically carried to find valuable insights.

4) Real time data monitoring-

Big Data provides continuous monitoring and processing of coming data. Based on any anomalies, real time alerts are passed out. This is essential for every business to flourish.

5) Powerful ad hoc query processing

Based on the requirements of management, different reports are needed, and ad hoc queries need to be passed. Big Data provides ad hoc analysis and report generation and aids in the short term decision making.

6) Ability to build custom dashboards and views

It is very difficult for having custom views for unstructured data. Big Data overcomes this problem by providing custom views. One can write custom Hive statements and get the necessary views.

7) Efficient data scaling

Big data analytics uses unstructured data storage, and data is stored as it comes without any problems of indexing.

8) Provide Role based security         

Data in Big Data Analytics is diverse and comprises of different segments. At this level, security regarding access of data becomes a crucial concern. Big Data provides Access control lists to maintain confidentiality of data stored.

9) Flexible deployment

When new technologies are adopted, a considerable time is spent to learn and experiment it. Big Data comes with a smooth learning curve utilizing minimum implementation time and faster deployment.

10) Portable interfacing

Big Data is versatile and can be interfaced with any programming API. Thus, different programs can be written based on capabilities of the developer.

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