Real-Time Analysis of Financial Data: Part 1

Nowadays financial enterprises are confronted with a plethora of demanding challenges, resulting from highly volatile markets, huge amounts of market data, and the growing number of financial derivates. The crucial question in providing valuable and trustworthy financial services is typically not how to access the latest financial data, but when and how to analyze and react to the data.


A flexible software which analyzes massive data volumes in real-time by means of an easy-to-express application logic will become indispensable for decision-making in financial enterprises.


Strategic decisions made on sophisticated and well-founded real-time analysis results will give financial organizations the competitive edge.


Complex Event Processing software helps meet the challenging requirements for analyzing high-speed market data in real-time. In order to keep pace with current market trends, CEP software provides an intuitive and standardized interface that facilitates the definition of complex application logic and its direct use to market data.


Besides a powerful processing engine, performance and scalability have been main design goals of the best CEP solutions. Both properties are essential for coping with the rapid growth of market data.


With a Java-based implementation, Complex Event Processing software can be seamlessly integrated at low cost into existing IT landscapes.


The software collects, processes and analyzes data, which continuously arrives from different sources, in real-time. For the sake of proactive reaction to current market trends, it enables easy definition and integration of sophisticated application logic at low cost.


Users can express, alter, and apply complex analytical algorithms on-the-fly, without detailed programming skills. You can, for instance, use it to tackle the typical tasks in financial services in a fast and cost-efficient manner:

• Support a trader to find his/her position for option pricing and hedge coefficients

• Execute the global risk analysis and determine trade limits to assess and limit risks

• Develop and optimize automatic trading algorithms for electronic trading.


The moment new market data arrives, the software immediately reacts by updating and propagating the new analysis results. Hence, it can feed financial services in real-time.


To support decision making in financial enterprises, a comprehensive data collection comprising up-to-date information about market trends, risk coefficients etc. is of utmost importance. On account of this necessity, the best software will provide a modular and well-approved framework for the integration of arbitrary data sources.


Not only does this framework allow for the connection of active sources, which continuously deliver data, but also of passive sources, which provide historical data stored in databases, data warehouses, or files.


Instead of using home-brewed or single-purpose data analysis solutions for decision making, the most optimal solution will offer easy-to-use but powerful interfaces for defining and modifying the required application logic on-the-fly.


It can use SQL to define application logic in a declarative manner. SQL is since decades the well-established standard in databases. It also can provide a graphical interface to compose application logic in a visual manner, similar to workflow diagrams.