  The DEBS Grand Challenge (GC) is an annual programming competition open to
practitioners from both academia and industry. The GC 2022 edition focuses on
real-time complex event processing of high-volume tick data provided by Infront
Financial Technology GmbH. The goal of the challenge is to efficiently compute
specific trend indicators and detect patterns in these indicators like those
used by real-life traders to decide on buying or selling in financial markets.
The data set Trading Data used for benchmarking contains 289 million tick
events from approximately 5500+ financial instruments that had been traded on
the three major exchanges Amsterdam (NL), Paris (FR), and Frankfurt am Main
(GER) over the course of a full week in 2021. The data set is made publicly
available. In addition to correctness and performance, submissions must
explicitly focus on reusability and practicability. Hence, participants must
address specific nonfunctional requirements and are asked to build upon
open-source platforms. This paper describes the required scenario and the data
set Trading Data, defines the queries of the problem statement, and explains
the enhancements made to the evaluation platform Challenger that handles data
distribution, dynamic subscriptions, and remote evaluation of the submissions.
