NDLI: Nonparametric monitoring of financial time series by jump-preserving control charts

Content Provider	Springer Nature Link
Author	Steland, Ansgar
Copyright Year	2002
Abstract	Since structural changes in a possibly transformed financial time series may contain important information for investors and analysts, we consider the following problem of sequential econometrics. For a given time series we aim at detecting the first change-point where a jump of size a occurs, i.e., the mean changes from, say, m 0to m 0+ a and returns to m 0after a possibly short period s. To address this problem, we study a Shewhart-type control chart based on a sequential version of the sigma filter, which extends kernel smoothers by employing stochastic weights depending on the process history to detect jumps in the data more accurately than classical approaches. We study both theoretical properties and performance issues. Concerning the statistical properties, it is important to know whether the normed delay time of the considered control chart is bounded, at least asymptotically. Extending known results for linear statistics employing deterministic weighting schemes, we establish an upper bound which holds if the memory of the chart tends to infinity. The performance of the proposed control charts is studied by simulations. We confine ourselves to some special models which try to mimic important features of real time series. Our empirical results provide some evidence that jump-preserving weights are preferable under certain circumstances.
Starting Page	401
Ending Page	422
Page Count	22
File Format	PDF
ISSN	09325026
Journal	Statistical Papers
Volume Number	43
Issue Number	3
e-ISSN	16139798
Language	English
Publisher	Springer-Verlag
Publisher Date	2002-01-01
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Digital image processing EWMA control chart financial econometrics nonparametric smoothing structural changes Statistics for Business/Economics/Mathematical Finance/Insurance Probability Theory and Stochastic Processes Economic Theory Operations Research/Decision Theory
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Statistics, Probability and Uncertainty

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