A Domain-Driven Approach for Detecting Event Patterns in E-Markets
A Case Study in Financial Market Surveillance
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In this research, we look at the problem of detecting complex situations arising in e-markets which have been growing in size rapidly over the past few years. Existing tools available today still cannot overcome the main challenges such as processing a large amount of incoming real-time data from market feeds and the ability to extract data efficiently at a high level. We propose to address these problems using the Event Processing concept and refer to an e-market as a distributed event-driven system, e-market transactions as events and data analysis tools as Event Processing Systems (EPSs). O...
In this research, we look at the problem of
detecting complex situations arising in e-markets
which have been growing in size rapidly over the
past few years. Existing tools available today still
cannot overcome the main challenges such as
processing a large amount of incoming real-time data
from market feeds and the ability to extract
data efficiently at a high level. We propose to
address these problems using the Event Processing
concept and refer to an e-market as a
distributed event-driven system, e-market
transactions as events and data analysis tools as
Event Processing Systems (EPSs). Our solution is
based on the new EPS architecture that allows the
integration of several existing EPSs (slave EPSs)
under a unified domain-specific user interface and
execution environment. It also includes the unified
e-market data model and event pattern framework for
composing and executing event patterns. Selected
event patterns used for market surveillance in
several stock exchanges have been used in the
evaluation process. We sucessfully developed a
system prototype using two sophisticated commercial
systems, Coral8 and SMARTS, as slave EPSs.
detecting complex situations arising in e-markets
which have been growing in size rapidly over the
past few years. Existing tools available today still
cannot overcome the main challenges such as
processing a large amount of incoming real-time data
from market feeds and the ability to extract
data efficiently at a high level. We propose to
address these problems using the Event Processing
concept and refer to an e-market as a
distributed event-driven system, e-market
transactions as events and data analysis tools as
Event Processing Systems (EPSs). Our solution is
based on the new EPS architecture that allows the
integration of several existing EPSs (slave EPSs)
under a unified domain-specific user interface and
execution environment. It also includes the unified
e-market data model and event pattern framework for
composing and executing event patterns. Selected
event patterns used for market surveillance in
several stock exchanges have been used in the
evaluation process. We sucessfully developed a
system prototype using two sophisticated commercial
systems, Coral8 and SMARTS, as slave EPSs.
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