Abstract
Data streams (streaming data) consist of continuously observed, non-equally spaced and temporally evolving multidimensional data sequences that challenge our computational and/or inferential capabilities. In economics, data streams are among others related to electricity consumption monitoring, Internet user behavior in exploring, or order book forecasting in high-frequency financial markets. In this paper, we point out and discuss several open problems related to robust data stream analysis and propose three robust and conceptually very simple approaches in this context. We apply the proposals to real data sets related to the activity of investors in the futures contracts market.
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