Abstract
The increasing complexity of financial markets and the exponential growth of market data are placing unprecedented demands on quantitative trading infrastructure. Modern quantitative strategies require the ability to process massive volumes of high-frequency market data, calculate complex trading signals, perform large-scale backtesting, and support low-latency execution. However, traditional technology architectures often rely on fragmented systems and disparate programming environments for quantitative research, historical data analysis, and production trading. This separation creates inefficiencies, increases infrastructure complexity, and makes it difficult to translate research innovations into production strategies.
In this talk, Yangchun Chu will explore the evolving landscape of quantitative trading infrastructure and discuss emerging approaches to addressing these challenges. The discussion will focus on integrating market data management, real-time stream processing, historical time-series analytics, quantitative research, backtesting, and live trading within a more unified computing architecture.
About the Speaker
Yangchun Chu is Co-founder and Chief Operating Officer of DolphinDB. Prior to co-founding the company, he spent nine years working at leading financial institutions in the New York metropolitan area, including Soros Fund Management and AllianceBernstein, where he gained extensive experience in quantitative finance and investment management