Suyeon Wang
ABSTRACT
Making timely-decisions amid the massive influx of financial data is one of the essential features of stock market analytics. Many stock market analytics should provide functionalities that compute multiple technical indicators simultaneously and detect breakout situations. The DEBS 2022 Grand Challenge (DEBS22 GC) competition requires to answering two types of queries: technical trend indicators and detection of crossover patterns. In response to the competition, we propose a real-time stock market analytic solution using PySpark and Docker. Our solution calculates the technical trend indicator---Exponential Moving Average(EMA)---in real-time with the window function. With the technical indicators computed, we detect the breakout pattern that helps determine either buy or sell stocks. Our solution not only improves the speed of deploying applications using a Docker container image but also can be accessed easily via a web-based Jupyter notebook.
- Sebastian Frischbier, Jawad Tahir, Christoph Doblander, Arne Hormann, Ruben Mayer, and Hans-Arno Jacobsen. 2022. The DEBS 2022 Grand Challenge: Detecting Trading Trends in Financial Tick Data. In The 16th ACM International Conference on Distributed and Event-based Systems (DEBS '22), June 27-June 30, 2022, Copenhagen. ACM, New York, NY, USA. Google Scholar
Digital Library
- Chris Bradley and Peter Stumpner. 2021. The impact of COVID-19 on capital markets, one year in. McKinsey.Google Scholar
- Sebastian Frischbier, Jawad Tahir, Christoph Doblander, Arne Hormann, Ruben Mayer, and Hans-Arno Jacobsen. 2022. DEBS 2022 Grand Challenge Data Set: Trading Data. Google ScholarCross Ref
- Raul Castro Fernandez, Matthias Weidlich, Peter Pietzuch, and Avigdor Gal. 2014. Scalable stateful stream processing for smart grids. In Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems, 276--281.Google ScholarDigital Library
- Vadlamani Ravi, Dadabada Pradeepkumar, and Kalyanmoy Deb. 2017. Financial time series prediction using hybrids of chaos theory, multi-layer perceptron and multi-objective evolutionary algorithms. Swarm and Evolutionary Computation 36, 136--149.Google ScholarCross Ref
- Jules S. Damji, Brooke Wenig, Tathagata Das, and Denny Lee. 2020. Learning Spark. O'Reilly Media.Google Scholar
- Anand Gupta, Hardeo Kumar Thakur, Ritvik Shrivastava, Pulkit Kumar, and Sreyashi Nag. 2017. A big data analysis framework using apache spark and deep learning. In 2017 IEEE international conference on data mining workshops (ICDMW), 9--16.Google ScholarCross Ref
- Pedro Silva, Wang Yue, and Tilmann Rabl. Incremental stream query analytics. 2020. In Proceedings of the 14th ACM International Conference on Distributed and Event-Based Systems(DEBS), 187--192.Google Scholar
- Vincenzo Gulisano, Daniel Jorde, Ruben Mayer, Hannaneh Najdataei, and Dimitris Palyvos-Giannas. 2020. The DEBS 2020 grand challenge. In Proceedings of the 14th ACM International Conference on Distributed and Event-Based Systems, 183--186.Google Scholar
- Sejin Chun, Seungjun Yoon, Jooik Jung, and Kyong-Ho Lee, 2019. Planning Operators of Concurrent RDF Stream Processing Queries. International Journal of Web and Grid Services (IJWGS), Volume 15. No. 1.Google ScholarCross Ref
Index Terms
- Real-time stock market analytics for improving deployment and accessibility using PySpark and Docker
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