Time series analysis

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Abstract

This chapter deals with the analysis of measurements over time, called time series analysis. Examples of time series include inflation and unemployment indices, stock prices, currency cross rates, monthly sales, the quarterly number of claims made to an insurance company, outstanding liabilities of a company over time, internet traffic, temperature and rainfall, and the number of mortgage defaults. Time series analysis aims to explain and model the relationship between values of the time series at different points of time. Models include ARIMA, structural, and stochastic volatility models and their extensions. The first two classes of models explain the level and expected future level of a time series. The last class seeks to model the change over time in variability or volatility of a time series. Time series analysis is critical to prediction and forecasting. This chapter explains and summarizes modern time series modeling as used in insurance, actuarial studies, and related areas such as finance. Modeling is illustrated with examples, analyzed with the R statistical package.

LanguageEnglish
Title of host publicationPredictive Modeling Applications in Actuarial Science
Subtitle of host publicationVolume I : Predictive Modeling Techniques
EditorsEdward W. Frees, Richard A. Derrig, Glenn Meyers
Place of PublicationCambridge
PublisherCambridge University Press
Pages427-448
Number of pages22
ISBN (Electronic)9781139342674
ISBN (Print)9781107029873
DOIs
Publication statusPublished - 2014

Fingerprint

Time series analysis
Modeling
Stochastic volatility model
Prediction
World Wide Web
Currency
Relationship value
Rainfall
Finance
Unemployment
Insurance
Stock prices
Insurance companies
ARIMA models
Mortgage default
Temperature
Inflation
Liability

Cite this

de Jong, P. (2014). Time series analysis. In E. W. Frees, R. A. Derrig, & G. Meyers (Eds.), Predictive Modeling Applications in Actuarial Science: Volume I : Predictive Modeling Techniques (pp. 427-448). Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9781139342674.017
de Jong, Piet. / Time series analysis. Predictive Modeling Applications in Actuarial Science: Volume I : Predictive Modeling Techniques. editor / Edward W. Frees ; Richard A. Derrig ; Glenn Meyers. Cambridge : Cambridge University Press, 2014. pp. 427-448
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de Jong, P 2014, Time series analysis. in EW Frees, RA Derrig & G Meyers (eds), Predictive Modeling Applications in Actuarial Science: Volume I : Predictive Modeling Techniques. Cambridge University Press, Cambridge, pp. 427-448. https://doi.org/10.1017/CBO9781139342674.017

Time series analysis. / de Jong, Piet.

Predictive Modeling Applications in Actuarial Science: Volume I : Predictive Modeling Techniques. ed. / Edward W. Frees; Richard A. Derrig; Glenn Meyers. Cambridge : Cambridge University Press, 2014. p. 427-448.

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

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de Jong P. Time series analysis. In Frees EW, Derrig RA, Meyers G, editors, Predictive Modeling Applications in Actuarial Science: Volume I : Predictive Modeling Techniques. Cambridge: Cambridge University Press. 2014. p. 427-448 https://doi.org/10.1017/CBO9781139342674.017