Grouped multivariate and functional time series forecasting: an application to annuity pricing

DOI10.1016/j.insmatheco.2017.05.007zbMath1394.62146arXiv1705.08001OpenAlexW2620093294WikidataQ58288546 ScholiaQ58288546MaRDI QIDQ2364018

Steven Haberman, Han Lin Shang

Publication date: 17 July 2017

Published in: Insurance Mathematics \& Economics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1705.08001

zbMATH Keywords

Lee-Carter methodbottom-up methodhierarchical time seriesforecast reconciliationJapanese mortality databaseoptimal-combination method

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Mathematical geography and demography (91D20)

Related Items

A forecast reconciliation approach to cause-of-death mortality modeling, Forecasting mortality rates with a coherent ensemble averaging approach, Dynamic principal component regression for forecasting functional time series in a group structure, FORECASTING MULTIPLE FUNCTIONAL TIME SERIES IN A GROUP STRUCTURE: AN APPLICATION TO MORTALITY, How can a cause-of-death reduction be compensated for by the population heterogeneity? A dynamic approach, Understanding forecast reconciliation, Assessing mortality inequality in the U.S.: what can be said about the future?, DYNAMIC PRINCIPAL COMPONENT REGRESSION: APPLICATION TO AGE-SPECIFIC MORTALITY FORECASTING, ANALYZING MORTALITY BOND INDEXES VIA HIERARCHICAL FORECAST RECONCILIATION

Uses Software

• R
• Rainbow
• forecast
• Forecast
• shiny
• StFinMetrics

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