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Random Processes

In: Time Series in Economics and Finance

Author

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  • Tomas Cipra

    (Charles University, Faculty of Mathematics and Physics)

Abstract

Data typical for economic and financial practice are time data, i.e., values of an economic variable (or variables in multivariate case) observed in a time interval with a given frequency of records (each trading day, in moments of transactions, monthly, etc.). The frequency of records is understood either as the lengths of intervals between particular observations (e.g., calendar months) or the regularity of observations (e.g., each trading day). As to the regularity, financial data are often irregularly observed (irregularly spaced data), e.g., the stock prices in stock exchanges are quoted usually in moments of transactions from the opening to closing time of trading day, the frequency of transactions being usually lower in the morning after opening, during the lunch time, and later in the afternoon before closing (a possible approach in such a situation assigns the closing or prevailing price to this day). The important property of time data is the fact that they are ordered chronologically in time.

Suggested Citation

  • Tomas Cipra, 2020. "Random Processes," Springer Books, in: Time Series in Economics and Finance, chapter 0, pages 5-38, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-46347-2_2
    DOI: 10.1007/978-3-030-46347-2_2
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