Forecasting mortality rates with functional signatures Article Swipe

PDF

Zhong Jing Yap , Dharini Pathmanathan , Sophie Dabo‐Niang ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2407.15461

This study introduces an innovative methodology for mortality forecasting, which integrates signature-based methods within the functional data framework of the Hyndman-Ullah (HU) model. This new approach, termed the Hyndman-Ullah with truncated signatures (HUts) model, aims to enhance the accuracy and robustness of mortality predictions. By utilizing signature regression, the HUts model is able to capture complex, nonlinear dependencies in mortality data which enhances forecasting accuracy across various demographic conditions. The model is applied to mortality data from 12 countries, comparing its forecasting performance against variants of the HU models across multiple forecast horizons. Our findings indicate that overall the HUts model not only provides more precise point forecasts but also shows robustness against data irregularities, such as those observed in countries with historical outliers. The integration of signature-based methods enables the HUts model to capture complex patterns in mortality data, making it a powerful tool for actuaries and demographers. Prediction intervals are also constructed with bootstrapping methods

Related Topics

Economics

Computer Science

Concepts

Econometrics Economics Computer science

Metadata

Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2407.15461
PDF: https://arxiv.org/pdf/2407.15461
OA Status: green
Related Works: 10
OpenAlex ID: https://openalex.org/W4406073110

All OpenAlex metadata

Raw OpenAlex JSON

OpenAlex ID: https://openalex.org/W4406073110

Canonical identifier for this work in OpenAlex
DOI: https://doi.org/10.48550/arxiv.2407.15461

Digital Object Identifier
Title: Forecasting mortality rates with functional signatures

Work title
Type: preprint

OpenAlex work type
Language: en

Primary language
Publication year: 2024

Year of publication
Publication date: 2024-07-22

Full publication date if available
Authors: Zhong Jing Yap, Dharini Pathmanathan, Sophie Dabo‐Niang

List of authors in order
Landing page: https://arxiv.org/abs/2407.15461

Publisher landing page
PDF URL: https://arxiv.org/pdf/2407.15461

Direct link to full text PDF
Open access: Yes

Whether a free full text is available
OA status: green

Open access status per OpenAlex
OA URL: https://arxiv.org/pdf/2407.15461

Direct OA link when available
Concepts: Econometrics, Economics, Computer science

Top concepts (fields/topics) attached by OpenAlex
Cited by: 0

Total citation count in OpenAlex
Related works (count): 10

Other works algorithmically related by OpenAlex

Full payload

id	https://openalex.org/W4406073110
doi	https://doi.org/10.48550/arxiv.2407.15461
ids.doi	https://doi.org/10.48550/arxiv.2407.15461
ids.openalex	https://openalex.org/W4406073110
fwci	0.0
type	preprint
title	Forecasting mortality rates with functional signatures
biblio.issue
biblio.volume
biblio.last_page
biblio.first_page
topics[0].id	https://openalex.org/T12011
topics[0].field.id	https://openalex.org/fields/33
topics[0].field.display_name	Social Sciences
topics[0].score	0.9919000267982483
topics[0].domain.id	https://openalex.org/domains/2
topics[0].domain.display_name	Social Sciences
topics[0].subfield.id	https://openalex.org/subfields/3317
topics[0].subfield.display_name	Demography
topics[0].display_name	Insurance, Mortality, Demography, Risk Management
is_xpac	False
apc_list
apc_paid
concepts[0].id	https://openalex.org/C149782125
concepts[0].level	1
concepts[0].score	0.45490536093711853
concepts[0].wikidata	https://www.wikidata.org/wiki/Q160039
concepts[0].display_name	Econometrics
concepts[1].id	https://openalex.org/C162324750
concepts[1].level	0
concepts[1].score	0.36917203664779663
concepts[1].wikidata	https://www.wikidata.org/wiki/Q8134
concepts[1].display_name	Economics
concepts[2].id	https://openalex.org/C41008148
concepts[2].level	0
concepts[2].score	0.3264043927192688
concepts[2].wikidata	https://www.wikidata.org/wiki/Q21198
concepts[2].display_name	Computer science
keywords[0].id	https://openalex.org/keywords/econometrics
keywords[0].score	0.45490536093711853
keywords[0].display_name	Econometrics
keywords[1].id	https://openalex.org/keywords/economics
keywords[1].score	0.36917203664779663
keywords[1].display_name	Economics
keywords[2].id	https://openalex.org/keywords/computer-science
keywords[2].score	0.3264043927192688
keywords[2].display_name	Computer science
language	en
locations[0].id	pmh:oai:arXiv.org:2407.15461
locations[0].is_oa	True
locations[0].source.id	https://openalex.org/S4306400194
locations[0].source.issn
locations[0].source.type	repository
locations[0].source.is_oa	True
locations[0].source.issn_l
locations[0].source.is_core	False
locations[0].source.is_in_doaj	False
locations[0].source.display_name	arXiv (Cornell University)
locations[0].source.host_organization	https://openalex.org/I205783295
locations[0].source.host_organization_name	Cornell University
locations[0].source.host_organization_lineage	https://openalex.org/I205783295
locations[0].license
locations[0].pdf_url	https://arxiv.org/pdf/2407.15461
locations[0].version	submittedVersion
locations[0].raw_type	text
locations[0].license_id
locations[0].is_accepted	False
locations[0].is_published	False
locations[0].raw_source_name
locations[0].landing_page_url	http://arxiv.org/abs/2407.15461
locations[1].id	doi:10.48550/arxiv.2407.15461
locations[1].is_oa	True
locations[1].source.id	https://openalex.org/S4306400194
locations[1].source.issn
locations[1].source.type	repository
locations[1].source.is_oa	True
locations[1].source.issn_l
locations[1].source.is_core	False
locations[1].source.is_in_doaj	False
locations[1].source.display_name	arXiv (Cornell University)
locations[1].source.host_organization	https://openalex.org/I205783295
locations[1].source.host_organization_name	Cornell University
locations[1].source.host_organization_lineage	https://openalex.org/I205783295
locations[1].license
locations[1].pdf_url
locations[1].version
locations[1].raw_type	article-journal
locations[1].license_id
locations[1].is_accepted	False
locations[1].is_published
locations[1].raw_source_name
locations[1].landing_page_url	https://doi.org/10.48550/arxiv.2407.15461
indexed_in	arxiv, datacite
authorships[0].author.id	https://openalex.org/A5115772072
authorships[0].author.orcid
authorships[0].author.display_name	Zhong Jing Yap
authorships[0].author_position	first
authorships[0].raw_author_name	Yap, Zhong Jing
authorships[0].is_corresponding	False
authorships[1].author.id	https://openalex.org/A5016896235
authorships[1].author.orcid	https://orcid.org/0000-0002-3279-4031
authorships[1].author.display_name	Dharini Pathmanathan
authorships[1].author_position	middle
authorships[1].raw_author_name	Pathmanathan, Dharini
authorships[1].is_corresponding	False
authorships[2].author.id	https://openalex.org/A5049255136
authorships[2].author.orcid	https://orcid.org/0000-0002-4000-6752
authorships[2].author.display_name	Sophie Dabo‐Niang
authorships[2].author_position	last
authorships[2].raw_author_name	Dabo-Niang, Sophie
authorships[2].is_corresponding	False
has_content.pdf	False
has_content.grobid_xml	False
is_paratext	False
open_access.is_oa	True
open_access.oa_url	https://arxiv.org/pdf/2407.15461
open_access.oa_status	green
open_access.any_repository_has_fulltext	False
created_date	2025-10-10T00:00:00
display_name	Forecasting mortality rates with functional signatures
has_fulltext	False
is_retracted	False
updated_date	2025-11-06T06:51:31.235846
primary_topic.id	https://openalex.org/T12011
primary_topic.field.id	https://openalex.org/fields/33
primary_topic.field.display_name	Social Sciences
primary_topic.score	0.9919000267982483
primary_topic.domain.id	https://openalex.org/domains/2
primary_topic.domain.display_name	Social Sciences
primary_topic.subfield.id	https://openalex.org/subfields/3317
primary_topic.subfield.display_name	Demography
primary_topic.display_name	Insurance, Mortality, Demography, Risk Management
related_works	https://openalex.org/W2899084033, https://openalex.org/W2748952813, https://openalex.org/W4391375266, https://openalex.org/W2390279801, https://openalex.org/W4391913857, https://openalex.org/W2358668433, https://openalex.org/W4396701345, https://openalex.org/W2376932109, https://openalex.org/W2001405890, https://openalex.org/W4396696052
cited_by_count	0
locations_count	2
best_oa_location.id	pmh:oai:arXiv.org:2407.15461
best_oa_location.is_oa	True
best_oa_location.source.id	https://openalex.org/S4306400194
best_oa_location.source.issn
best_oa_location.source.type	repository
best_oa_location.source.is_oa	True
best_oa_location.source.issn_l
best_oa_location.source.is_core	False
best_oa_location.source.is_in_doaj	False
best_oa_location.source.display_name	arXiv (Cornell University)
best_oa_location.source.host_organization	https://openalex.org/I205783295
best_oa_location.source.host_organization_name	Cornell University
best_oa_location.source.host_organization_lineage	https://openalex.org/I205783295
best_oa_location.license
best_oa_location.pdf_url	https://arxiv.org/pdf/2407.15461
best_oa_location.version	submittedVersion
best_oa_location.raw_type	text
best_oa_location.license_id
best_oa_location.is_accepted	False
best_oa_location.is_published	False
best_oa_location.raw_source_name
best_oa_location.landing_page_url	http://arxiv.org/abs/2407.15461
primary_location.id	pmh:oai:arXiv.org:2407.15461
primary_location.is_oa	True
primary_location.source.id	https://openalex.org/S4306400194
primary_location.source.issn
primary_location.source.type	repository
primary_location.source.is_oa	True
primary_location.source.issn_l
primary_location.source.is_core	False
primary_location.source.is_in_doaj	False
primary_location.source.display_name	arXiv (Cornell University)
primary_location.source.host_organization	https://openalex.org/I205783295
primary_location.source.host_organization_name	Cornell University
primary_location.source.host_organization_lineage	https://openalex.org/I205783295
primary_location.license
primary_location.pdf_url	https://arxiv.org/pdf/2407.15461
primary_location.version	submittedVersion
primary_location.raw_type	text
primary_location.license_id
primary_location.is_accepted	False
primary_location.is_published	False
primary_location.raw_source_name
primary_location.landing_page_url	http://arxiv.org/abs/2407.15461
publication_date	2024-07-22
publication_year	2024
referenced_works_count	0
abstract_inverted_index.a	142
abstract_inverted_index.12	77
abstract_inverted_index.By	44
abstract_inverted_index.HU	87
abstract_inverted_index.an	3
abstract_inverted_index.as	116
abstract_inverted_index.in	58, 119, 137
abstract_inverted_index.is	51, 71
abstract_inverted_index.it	141
abstract_inverted_index.of	18, 41, 85, 126
abstract_inverted_index.to	35, 53, 73, 133
abstract_inverted_index.Our	93
abstract_inverted_index.The	69, 124
abstract_inverted_index.and	39, 147
abstract_inverted_index.are	151
abstract_inverted_index.but	108
abstract_inverted_index.for	6, 145
abstract_inverted_index.its	80
abstract_inverted_index.new	24
abstract_inverted_index.not	101
abstract_inverted_index.the	14, 19, 27, 37, 48, 86, 98, 130
abstract_inverted_index.(HU)	21
abstract_inverted_index.HUts	49, 99, 131
abstract_inverted_index.This	0, 23
abstract_inverted_index.able	52
abstract_inverted_index.aims	34
abstract_inverted_index.also	109, 152
abstract_inverted_index.data	16, 60, 75, 113
abstract_inverted_index.from	76
abstract_inverted_index.more	104
abstract_inverted_index.only	102
abstract_inverted_index.such	115
abstract_inverted_index.that	96
abstract_inverted_index.tool	144
abstract_inverted_index.with	29, 121, 154
abstract_inverted_index.data,	139
abstract_inverted_index.model	50, 70, 100, 132
abstract_inverted_index.point	106
abstract_inverted_index.shows	110
abstract_inverted_index.study	1
abstract_inverted_index.those	117
abstract_inverted_index.which	9, 61
abstract_inverted_index.(HUts)	32
abstract_inverted_index.across	65, 89
abstract_inverted_index.making	140
abstract_inverted_index.model,	33
abstract_inverted_index.model.	22
abstract_inverted_index.models	88
abstract_inverted_index.termed	26
abstract_inverted_index.within	13
abstract_inverted_index.against	83, 112
abstract_inverted_index.applied	72
abstract_inverted_index.capture	54, 134
abstract_inverted_index.complex	135
abstract_inverted_index.enables	129
abstract_inverted_index.enhance	36
abstract_inverted_index.methods	12, 128, 156
abstract_inverted_index.overall	97
abstract_inverted_index.precise	105
abstract_inverted_index.various	66
abstract_inverted_index.accuracy	38, 64
abstract_inverted_index.complex,	55
abstract_inverted_index.enhances	62
abstract_inverted_index.findings	94
abstract_inverted_index.forecast	91
abstract_inverted_index.indicate	95
abstract_inverted_index.multiple	90
abstract_inverted_index.observed	118
abstract_inverted_index.patterns	136
abstract_inverted_index.powerful	143
abstract_inverted_index.provides	103
abstract_inverted_index.variants	84
abstract_inverted_index.actuaries	146
abstract_inverted_index.approach,	25
abstract_inverted_index.comparing	79
abstract_inverted_index.countries	120
abstract_inverted_index.forecasts	107
abstract_inverted_index.framework	17
abstract_inverted_index.horizons.	92
abstract_inverted_index.intervals	150
abstract_inverted_index.mortality	7, 42, 59, 74, 138
abstract_inverted_index.nonlinear	56
abstract_inverted_index.outliers.	123
abstract_inverted_index.signature	46
abstract_inverted_index.truncated	30
abstract_inverted_index.utilizing	45
abstract_inverted_index.Prediction	149
abstract_inverted_index.countries,	78
abstract_inverted_index.functional	15
abstract_inverted_index.historical	122
abstract_inverted_index.innovative	4
abstract_inverted_index.integrates	10
abstract_inverted_index.introduces	2
abstract_inverted_index.robustness	40, 111
abstract_inverted_index.signatures	31
abstract_inverted_index.conditions.	68
abstract_inverted_index.constructed	153
abstract_inverted_index.demographic	67
abstract_inverted_index.forecasting	63, 81
abstract_inverted_index.integration	125
abstract_inverted_index.methodology	5
abstract_inverted_index.performance	82
abstract_inverted_index.regression,	47
abstract_inverted_index.dependencies	57
abstract_inverted_index.forecasting,	8
abstract_inverted_index.predictions.	43
abstract_inverted_index.Hyndman-Ullah	20, 28
abstract_inverted_index.bootstrapping	155
abstract_inverted_index.demographers.	148
abstract_inverted_index.irregularities,	114
abstract_inverted_index.signature-based	11, 127
cited_by_percentile_year
countries_distinct_count	0
institutions_distinct_count	3
citation_normalized_percentile.value	0.53104391
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	False