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Resampling and Subsampling for Financial Time Series

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Handbook of Financial Time Series

Abstract

We review different methods of bootstrapping or subsampling financial time series.We first discuss methods that can be applied to generate pseudo-series of log-returns which mimic closely the essential dependence characteristics of the observed series. We then review methods that apply the bootstrap in order to infer properties of statistics based on financial times series. Such methods do not work by generating new pseudo-series of the observed log-returns but by generating pseudo-replicates of the statistic of interest. Finally, we discuss subsampling and self-normalization methods applied to financial data.

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Authors and Affiliations

  1. Department of Mathematics and Statistics, University of Cyprus, CY-1678, 20537, Stockholm, CYPRUS, Nicosia

    Efstathios Paparoditis

  2. Department of Mathematics, University of California, La Jolla, 92093-0112, CA, San Diego, USA

    Dimitris N. Politis

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  1. Efstathios Paparoditis
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  2. Dimitris N. Politis
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Correspondence to Efstathios Paparoditis .

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    Paparoditis, E., Politis, D.N. (2009). Resampling and Subsampling for Financial Time Series. In: Mikosch, T., Kreiß, JP., Davis, R., Andersen, T. (eds) Handbook of Financial Time Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71297-8_42

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