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A note on the time series which is the product of two stationary time series

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  • Wecker, William E.

Abstract

The time series [...,x-1y-1,x0y0,x1y1,...]> which is the product of two stationary time series xt and yt is studied. Such sequences arise in the study of nonlinear time series, censored time series, amplitude modulated time series, time series with random parameters, and time series with missing observations. The mean and autocovariance function of the product sequence are derived.

Suggested Citation

  • Wecker, William E., 1978. "A note on the time series which is the product of two stationary time series," Stochastic Processes and their Applications, Elsevier, vol. 8(2), pages 153-157, December.
    • Handle: RePEc:eee:spapps:v:8:y:1978:i:2:p:153-157
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    Cited by:

    1. Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big data analytics: a new perspective," Globalization Institute Working Papers 268, Federal Reserve Bank of Dallas.
    2. A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2018. "A One Covariate at a Time, Multiple Testing Approach to Variable Selection in High‐Dimensional Linear Regression Models," Econometrica, Econometric Society, vol. 86(4), pages 1479-1512, July.
    3. Adamek, Robert & Smeekes, Stephan & Wilms, Ines, 2023. "Lasso inference for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 235(2), pages 1114-1143.
    4. Leschinski, Christian, 2017. "On the memory of products of long range dependent time series," Economics Letters, Elsevier, vol. 153(C), pages 72-76.
    5. Julia Adamska & Łukasz Bielak & Joanna Janczura & Agnieszka Wyłomańska, 2022. "From Multi- to Univariate: A Product Random Variable with an Application to Electricity Market Transactions: Pareto and Student’s t -Distribution Case," Mathematics, MDPI, vol. 10(18), pages 1-29, September.

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    Keywords

    time series product nonlinear;

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