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Prediction of 0-1-events for short- and long-memory time series

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Author Info
Jan Beran () (Department of Mathematics and Statistics, University of Konstanz)
Abstract

The problem of predicting 0-1-events is considered under general conditions, including stationary processes with short and long memory as well as processes with changing distribution patterns. Nonparametric estimates of the probability function and prediction intervals are obtained.

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Publisher Info
Paper provided by Center of Finance and Econometrics, University of Konstanz in its series CoFE Discussion Paper with number 02-11.

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Length: 12 pages
Date of creation: Mar 2002
Date of revision:
Handle: RePEc:knz:cofedp:0211

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Related research
Keywords: 0-1-events; long-range dependence; short-range dependence; antipersistence; kernel smoothing; bandwidth; prediction;

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Jan Beran & Yuanhua Feng, 2002. "Local Polynomial Fitting with Long-Memory, Short-Memory and Antipersistent Errors," Annals of the Institute of Statistical Mathematics, Springer, vol. 54(2), pages 291-311, June. [Downloadable!] (restricted)
  2. Beran, Jan & Feng, Yuanhua, 2002. "SEMIFAR models--a semiparametric approach to modelling trends, long-range dependence and nonstationarity," Computational Statistics & Data Analysis, Elsevier, vol. 40(2), pages 393-419, August. [Downloadable!] (restricted)
  3. Chiu, Shean-Tsong, 1989. "Bandwidth selection for kernel estimate with correlated noise," Statistics & Probability Letters, Elsevier, vol. 8(4), pages 347-354, September. [Downloadable!] (restricted)
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