Powering Financial Spread Betting with In-Memory Computing White Paper
Monday, February 13 2017
During the past decade, financial spread betting has become a major growth market globally.
Spread betting offers some compelling advantages, including low entry and transaction costs, preferential tax treatment, and a diverse array of products and options. Traders can bet on any type of event for which there is a measurable outcome that might go in either of two directions – for example, housing prices, the value of a stock-market index, or the difference in the scores of two teams in a sporting event. Spread betting can be conducted through brokerages, asset managers, online gambling firms, and any other player who is willing to provide a spread, or range of outcomes, upon which traders can bet that the measured value will rise or fall. The upfront cost to place a bet is minimal and rewards can be substantial.
However, spread betting is also a high-volatility, minimally regulated market with significant risks. To limit these risks – and increase the rewards – financial institutions involved in spread betting are using advanced mathematical models to analyze large amounts of data, predict outcomes, and devise optimal strategies. These computationally intense actions must be performed at very high speeds to take advantage of current market conditions.
Fortunately, there are technologies today that provide the real-time speed needed for such strategies. In-memory computing platforms such as the GridGain in-memory computing platform, built on Apache® Ignite™, can provide both exceptional performance and other valuable features, such as scalability, high availability, and fully ACID-compliant transactions.
This white paper discusses the advantages and risks of spread betting, the technologies being used for it, and the reasons why in-memory computing is becoming the technology of choice for brokerages, asset managers, online gambling firms, and other players who want to succeed at spread betting.
Financial Spread Betting with In-Memory Computing
With spread betting emerging as a rapidly growing trend, participants looking for an edge are turning toward technology that can support 24/7 transactions, real-time responses, and the intensive analytics needed to hone predictive models and risk-management strategies. Fortunately, in-memory computing solutions can provide the level of performance and scale needed by brokerages, asset managers, online gambling firms, and other players seeking to lead in this market.
The key modules of the GridGain in-memory computing platform are that relevant to financial spread betting use cases are:
- Data grid – Essentially an in-memory key value store that can be queried
- SQL grid - provides the ability to interact with data in-memory using ANSI SQL-99 via JDBC or ODBC APIs
- Compute grid - A stateless grid that provides high-performance computation in memory using clusters of computers and parallel processing
- Service grid - A service grid in which grid service instances are deployed across the distributed data and compute grids
- Streaming – The ability to consume an endless stream of information and process it in real-time
- Advanced clustering – The ability to automatically discover nodes, eliminating the need to restart the entire cluster when adding new nodes
Powering Financial Spread Betting with In-Memory Computing - White Paper
If your organization is developing or trying to improve a financial spread betting solution, please download Powering Financial Spread Betting with In-Memory Computing, a new GridGain Systems white paper that takes a detailed look at financial spread betting requirements and how in-memory computing can deliver the performance and scale financial spread betting use cases demand.
As always, if you have questions or comments, please let us know!