deepVoxel EventAnalytics

deepVoxel EventAnalysis is an interactive, visual frameworks that supports practical work-flows that are encountered in a number of areas, including financial services and customer analytics. deepVoxel EventAnalytics is specifically designed to aid in analysis of time series and events. deepVoxel EventAnalysis works by applying highly granular, interactive views of event-based data with advanced statistics.

Application Description: Market Micro-Structure Analysis

Many problems in business rely on understanding relationships between time-series and events. The knowledge of how events relate to price action or volatility, for example, is a matter of great interest in the financial markets. Many analytic activities such as transaction cost analysis and attribution modeling depend on the ability to separate interactions between events and time-series.

Financial Markets and Complex Events

Financial markets are complex systems involving interactions between events. Markets have been likened to ecological systems where computers and humans compete for price action and liquidity. The drive to prevail in this competition has given rise to a new generation of technologies such as as CEP or 'Complex Event Processing'. These systems combine speed-of-execution with complex decision-making in order to gain competitive advantage. These very name 'Complex Event Processing' attests to the central role that events play in modern financial markets.

Market Events: Simple and Complex Query Patterns

Human judgement is required to untangle the constantly-evolving relationships between events. Identifying the root cause of a volatility clustering event, for example, would involve a multi-step query that is directed by a human. Answers to complex queries are valuable because they reveal insights into the drivers of market behavior. Market participants need finely engineered query systems to compete effectively speed the path to profitability.

deepVoxel EventAnalytics: Engineered to Produce Rapid Insight into Event-Interactions

deepVoxel EventAnalytics is specifically designed to aid in analysis of time series and events. deepVoxel EventAnalysis works by applying highly granular, interactive views of event-based data with advanced statistics.

Examples

An example list of queries that can be performed via deepVoxel EventAnalytics:

Cross-Sectional Event Study: Compare statistical differences before and after an interactively defined event. Assesses the level of impact of that an event has on price action.

Statistical Tail Events: Search for and identify infrequent events, such as price jumps. Patterns of rare events may share a common cause that can help isolate the effect of a risk.

Lead-lag analysis: Find lead-lag relationships between price histories that may indicate predictive or correlated activity.

Seasonality: Identify patterns of activity that reoccur on a periodic basis, such as minutely, daily and so on. These may reveal 'signals' or intentions of activity that can be used to optimize the timing of orders.

Volatility clustering: Interactively cluster instruments that share sudden bursts of activity. Finding a common root cause to these bursts may reveal underlying factors that drive market activity.