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Erschienen in:
Fundamental Concepts Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

26. Time Series

verfasst von : Geon Ho Choe

Erschienen in: Stochastic Analysis for Finance with Simulations

Verlag: Springer International Publishing

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Abstract

A time series is a sequence of collected data over a time period. Theoretically, we usually assume that a given sequence is infinitely long into the future and sometimes also into the past, and it is regarded as an observed random sample realized from a sequence of random variables. Time series models are used to analyze historical data and to forecast future movement of market variables. Since financial data is collected at discrete time points, sometimes it is appropriate to use recursive difference equations rather than differential equations which are defined for continuous time. Throughout the chapter we consider only the discrete time models. A process is stationary if all of its statistical properties are invariant in time, and a process is weakly stationary if its mean, variance and covariance are invariant in time.

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Vorheriges Kapitel Numerical Estimation of Volatility
Nächstes Kapitel Random Numbers
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Metadaten
Titel
Time Series
verfasst von
Geon Ho Choe
Copyright-Jahr
2016
Buch
Stochastic Analysis for Finance with Simulations

Print ISBN: 978-3-319-25587-3

Electronic ISBN: 978-3-319-25589-7

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-25589-7_26