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Estimating Conditional Value at Risk in Non-Cyclical Sector Companies Using the Extreme Value Theory Approach

Estimasi Conditional Value at Risk Pada Perusahaan Sektor Consumer Non-Cyclicals Menggunakan Pendekatan Extreme Value Theory

Jurnal Matematika, Statistika dan Komputasi · Vol. 21 No. 1 (2024) · pp. 159–175

DOI
10.20956/j.v21i1.35849
ISSN
2614-8811, 1858-1382
Published
2024-09-15
Publisher
Department of Mathematics, Hasanuddin University
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

English

Conditional Value at Risk (CVaR) is an estimate of the risk of loss that exceeds the Value at Risk (VaR) level. VaR is one of the most commonly used stock risk measurement methods to assess the risk of large investments. Extreme Value Theory (EVT) is a method used to analyze data that contains extreme values. The goal of EVT is to estimate the probability of an extreme event occurring by examining the tails of a distribution based on observed extreme values. There are two general distributions used in EVT, namely Generalized Extreme Value (GEV) and Generalized Pareto Distribution (GPD). This research aims to determine the estimated level of loss that investors may experience when investing in PT Hanjaya Mandala Sampoerna Tbk (HMSP) and PT Japfa Comfeed Indonesia Tbk (JPFA). The L-Moment method is applied to estimate the parameters in this distribution so that an explicit parameter form is obtained. Based on CVaR analysis using the Block Maxima (BM) approach, investors in HMSP and JPFA are estimated to experience losses of 20.0752% and 29.6537% respectively. Using the Peaks Over Threshold (POT) approach, the estimated losses are 0.966% and 1.548% for HMSP and JPFA, respectively. Based on CVaR calculations using both approaches, the POT approach with GPD provides a more accurate and reliable investment risk estimate than the BM approach with GEV distribution

Bahasa Indonesia

Conditional Value at Risk (CVaR) merupakan perkiraan risiko kerugian yang melebihi tingkat Value at Risk (VaR). VaR adalah salah satu metode pengukuran risiko saham yang paling umum digunakan untuk menilai risiko investasi besar. Extreme Value Theory (EVT) adalah metode yang digunakan untuk menganalisis data yang mengandung nilai ekstrem. Tujuan EVT adalah memperkirakan kemungkinan terjadinya peristiwa ekstrem dengan memeriksa ujung distribusi berdasarkan nilai ekstrem yang diamati. Terdapat dua distribusi umum yang digunakan dalam EVT yaitu Generalized Extreme Value (GEV) dan Generalized Pareto Distribution (GPD). Penelitian ini bertujuan untuk mengetahui perkiraan tingkat kerugian yang mungkin dialami investor ketika berinvestasi pada PT Hanjaya Mandala Sampoerna Tbk (HMSP) dan PT Japfa Comfeed Indonesia Tbk (JPFA). Metode L-Moment diterapkan untuk mengestimasi parameter pada distribusi tersebut sehingga diperoleh bentuk parameter yang eksplisit. Berdasarkan analisis CVaR dengan pendekatan Block Maxima (BM), investor pada HMSP dan JPFA diperkirakan mengalami kerugian masing-masing sebesar 20,0752% dan 29,6537%. Dengan menggunakan pendekatan Peaks Over Threshold (POT), estimasi kerugian masing-masing sebesar 0,966% dan 1,548% untuk HMSP dan JPFA. Berdasarkan perhitungan CVaR menggunakan kedua pendekatan tersebut, pendekatan POT dengan GPD memberikan perkiraan risiko investasi yang lebih akurat dan andal dibandingkan pendekatan BM dengan distribusi GEV.

Keywords

Collaboration network of the authors

34 authors · 89 co-authorship links · 1 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Sultan Ageng Tirtayasa University
  • Universitas Halu Oleo
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Anisa AnisaSultan Ageng Tirtayasa University4
Nirwan IlyasAffiliation unknown2
La Podje TalangkoAffiliation unknown2
Sitti SahrimanAffiliation unknown2
Rusydah KhaeratiAffiliation unknown1
Grace Oktavia YusufAffiliation unknown1
Fitriatusakiah FitriatusakiahAffiliation unknown1
Raupong RaupongAffiliation unknown1
Andi Tenri Riski AmaliaAffiliation unknown1
Georgina Maria TinungkiAffiliation unknown1
Andi Isna YunitaAffiliation unknown1
Najiha AlimatunAffiliation unknown1
Nasrah SirajangAffiliation unknown1
Reski AmalahAffiliation unknown1
Nur Fuadil Maqnun WahabAffiliation unknown1
Nurtit SunusiAffiliation unknown1
Ainul FajriAffiliation unknown1
Anisa Haura Salsa Fatih YusufAffiliation unknown1
Nurtiti SunusiAffiliation unknown1
Ika Pratiwi HayaAffiliation unknown1
Anna IslamiyatiAffiliation unknown1
Andi Ummi Melin Aicha AichaAffiliation unknown1
Wa Ode Sitti Amni AmniAffiliation unknown1
Amalia AndrianingrumAffiliation unknown1
Erna Tri HerdianiAffiliation unknown1
Fadhila Febriyanti NajamuddinAffiliation unknown1
Nur ErawatiAffiliation unknown1
Sunarti SunartiUniversitas Halu Oleo1
Niswar AliansaAffiliation unknown1
Sutrianah BurhanAffiliation unknown1
Siswanto SiswantoAffiliation unknown1
Arief Rahman NurAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/jmsk/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Estimating Conditional Value at Risk in Non-Cyclical  Sector Companies Using the Extreme Value Theory Approach</dc:title>
	<dc:title xml:lang="id">Estimasi Conditional Value at Risk Pada Perusahaan  Sektor Consumer Non-Cyclicals Menggunakan  Pendekatan Extreme Value Theory</dc:title>
	<dc:creator xml:lang="en">Hakam, Andi Muhammad </dc:creator>
	<dc:creator xml:lang="en">Jaya, Andi Kresna </dc:creator>
	<dc:subject xml:lang="en">L-Moment, Conditional Value at Risk, Generalized Extreme Value, Generalized Pareto Distirbution.</dc:subject>
	<dc:subject xml:lang="id">Keywords: L-Moment, Conditional Value at Risk, Generalized Extreme Value, Generalized Pareto Distirbution.</dc:subject>
	<dc:subject xml:lang="id">L-Moment, Conditional Value at Risk, Generalized Extreme Value, Generalized Pareto Distirbution.</dc:subject>
	<dc:description xml:lang="en">Conditional Value at Risk (CVaR) is an estimate of the risk of loss that exceeds the Value at Risk (VaR) level. VaR is one of the most commonly used stock risk measurement methods to assess the risk of large investments. Extreme Value Theory (EVT) is a method used to analyze data that contains extreme values. The goal of EVT is to estimate the probability of an extreme event occurring by examining the tails of a distribution based on observed extreme values. There are two general distributions used in EVT, namely Generalized Extreme Value (GEV) and Generalized Pareto Distribution (GPD). This research aims to determine the estimated level of loss that investors may experience when investing in PT Hanjaya Mandala Sampoerna Tbk (HMSP) and PT Japfa Comfeed Indonesia Tbk (JPFA). The L-Moment method is applied to estimate the parameters in this distribution so that an explicit parameter form is obtained. Based on CVaR analysis using the Block Maxima (BM) approach, investors in HMSP and JPFA are estimated to experience losses of 20.0752% and 29.6537% respectively. Using the Peaks Over Threshold (POT) approach, the estimated losses are 0.966% and 1.548% for HMSP and JPFA, respectively. Based on CVaR calculations using both approaches, the POT approach with GPD provides a more accurate and reliable investment risk estimate than the BM approach with GEV distribution</dc:description>
	<dc:description xml:lang="id">Conditional Value at Risk (CVaR) merupakan perkiraan risiko kerugian yang melebihi tingkat Value at Risk (VaR). VaR adalah salah satu metode pengukuran risiko saham yang paling umum digunakan untuk menilai risiko investasi besar. Extreme Value Theory (EVT) adalah metode yang digunakan untuk menganalisis data yang mengandung nilai ekstrem. Tujuan EVT adalah memperkirakan kemungkinan terjadinya peristiwa ekstrem dengan memeriksa ujung distribusi berdasarkan nilai ekstrem yang diamati. Terdapat dua distribusi umum yang digunakan dalam EVT yaitu Generalized Extreme Value (GEV) dan Generalized Pareto Distribution (GPD). Penelitian ini bertujuan untuk mengetahui perkiraan tingkat kerugian yang mungkin dialami investor ketika berinvestasi pada PT Hanjaya Mandala Sampoerna Tbk (HMSP) dan PT Japfa Comfeed Indonesia Tbk (JPFA). Metode L-Moment diterapkan untuk mengestimasi parameter pada distribusi tersebut sehingga diperoleh bentuk parameter yang eksplisit. Berdasarkan analisis CVaR dengan pendekatan Block Maxima (BM), investor pada HMSP dan JPFA diperkirakan mengalami kerugian masing-masing sebesar 20,0752% dan 29,6537%. Dengan menggunakan pendekatan Peaks Over Threshold (POT), estimasi kerugian masing-masing sebesar 0,966% dan 1,548% untuk HMSP dan JPFA. Berdasarkan perhitungan CVaR menggunakan kedua pendekatan tersebut, pendekatan POT dengan GPD memberikan perkiraan risiko investasi yang lebih akurat dan andal dibandingkan pendekatan BM dengan distribusi GEV.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2024-09-15</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://journal.unhas.ac.id/index.php/jmsk/article/view/35849</dc:identifier>
	<dc:identifier>10.20956/j.v21i1.35849</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 21 No. 1 (2024): SEPTEMBER 2024; 159-175</dc:source>
	<dc:source>2614-8811</dc:source>
	<dc:source>1858-1382</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/jmsk/article/view/35849/12006</dc:relation>
	<dc:relation>10.20956/j.v21i1.35849.g12006</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2024 Jurnal Matematika, Statistika dan Komputasi</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
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