Article2013

Mortality Modeling With Non‐Gaussian Innovations and Applications to the Valuation of Longevity Swaps

Chou‐Wen Wang · Hong‐Chih Huang · I‐Chien Liu

28 citations0/0 files storedJournal of Risk & Insurance

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Insurance, Mortality, Demography, Risk Management Stochastic processes and financial applications Probability and Risk Models

Abstract

ABSTRACT This article provides an iterative fitting algorithm to generate maximum likelihood estimates under the Cox regression model and employs non‐Gaussian distributions—the jump diffusion (JD), variance gamma (VG), and normal inverse Gaussian (NIG) distributions—to model the error terms of the Renshaw and Haberman ( ) (RH) model. In terms of mean absolute percentage error, the RH model with non‐Gaussian innovations provides better mortality projections, using 1900–2009 mortality data from England and Wales, France, and Italy. Finally, the lower hedge costs of longevity swaps according to the RH model with non‐Gaussian innovations are not only based on the lower swap curves implied by the best prediction model, but also in terms of the fatter tails of the unexpected losses it generates.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 28 citations exist upstream.

References

1992Modeling and Forecasting U. S. Mortality 2002The Fine Structure of Asset Returns: An Empirical Investigation 1995Hyperbolic Distributions in Finance 2006A Two‐Factor Model for Stochastic Mortality with Parameter Uncertainty: Theory and Calibration 2006A cohort-based extension to the Lee–Carter model for mortality reduction factors 2002A Poisson log-bilinear regression approach to the construction of projected lifetables 2009A Quantitative Comparison of Stochastic Mortality Models Using Data From England and Wales and the United States 2000A Class of Distortion Operators for Pricing Financial and Insurance Risks

Cited by

2015Age-specific copula-AR-GARCH mortality models 2017Modeling Multicountry Longevity Risk With Mortality Dependence: A Lévy Subordinated Hierarchical Archimedean Copulas Approach 2014Longevity Risk and Capital Markets: The 2012–2013 Update 2019ANALYZING MORTALITY BOND INDEXES VIA HIERARCHICAL FORECAST RECONCILIATION

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.