Modeling the Asymmetric Reinsurance Revenues Data using the Partially Autoregressive Time Series Model: Statistical Forecasting and Residuals Analysis Article Swipe

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Salwa L. Alkhayyat , Heba Soltan Mohamed , Nadeem Shafique Butt , Haitham M. Yousof , Emadeldin I. A. Ali ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.18187/pjsor.v19i3.4123

The autoregressive model is a representation of a certain kind of random process in statistics, insurance, signal processing, and econometrics; as such, it is used to describe some time-varying processes in nature, economics and insurance, etc. In this article, a novel version of the autoregressive model is proposed, in the so-called the partially autoregressive (PAR(1)) model. The results of the new approach depended on a new algorithm that we formulated to facilitate the process of statistical prediction in light of the rapid developments in time series models. The new algorithm is based on the values of the autocorrelation and partial autocorrelation functions. The new technique is assessed via re-estimating the actual time series values. Finally, the results of the PAR(1) model is compared with the Holt-Winters model under the Ljung-Box test and its corresponding p-value. A comprehensive analysis for the model residuals is presented. The matrix of the autocorrelation analysis for both points forecasting and interval forecasting are given with its relevant plots.

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Mathematics

Time Series

Partial Autocorrelation Function

Statistics

Paleontology

Biology

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Autoregressive model Autocorrelation STAR model Mathematics Series (stratigraphy) Time series Econometrics Partial autocorrelation function SETAR Moving-average model Autoregressive integrated moving average Statistics Applied mathematics Paleontology Biology

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Type: article
Language: en
Landing Page: https://doi.org/10.18187/pjsor.v19i3.4123
PDF: https://pjsor.com/pjsor/article/download/4123/1271
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DOI: https://doi.org/10.18187/pjsor.v19i3.4123

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Title: Modeling the Asymmetric Reinsurance Revenues Data using the Partially Autoregressive Time Series Model: Statistical Forecasting and Residuals Analysis

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Language: en

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Publication year: 2023

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Authors: Salwa L. Alkhayyat, Heba Soltan Mohamed, Nadeem Shafique Butt, Haitham M. Yousof, Emadeldin I. A. Ali

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Concepts: Autoregressive model, Autocorrelation, STAR model, Mathematics, Series (stratigraphy), Time series, Econometrics, Partial autocorrelation function, SETAR, Moving-average model, Autoregressive integrated moving average, Statistics, Applied mathematics, Paleontology, Biology

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Cited by: 6

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