Real-time financial surveillance via quickest change-point detection methods

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Pepelyshev, Andrey; Polunchenko, Alexey;

We consider the problem of efficient financial surveillance aimed at “on-the-go” detection of structural breaks (anomalies) in “live”-monitored financial time series. With the problem approached statistically, viz. as that of multicyclic sequential (quickest) change-poi... View more
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    University, Cardiff, Wales, UK), and the Editor-in-Chief, Prof. Heping Zhang (Yale University, New Haven, Connecticut, USA), for the time and effort they invested to produce this special issue of the Journal. The authors are also personally thankful to Prof. Zhigljavsky for the invitation to contribute this work to the special issue. The constructive feedback provided by the two anonymous referees is greatly appreciated as well. The effort of A.S. Polunchenko was supported, in part, by the Simons Foundation ( via a Collaboration Grant in Mathematics (Award # 304574). A.S. Polunchenko is also equally indebted to the Office of [19] Lai, T. L. (1998). Information bounds and quick detection of parameter changes in stochastic systems. IEEE Transactions on the Dean of the Harpur College of Arts and Sciences at the Information Theory 44 2917-2929.

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