Essec\Faculty\Model\Profile {#2216
#_id: "B00072302"
#_source: array:40 [
"bid" => "B00072302"
"academId" => "2040"
"slug" => "fulop-andras"
"fullName" => "Andras FULOP"
"lastName" => "FULOP"
"firstName" => "Andras"
"title" => array:2 [
"fr" => "Professeur"
"en" => "Professor"
]
"email" => "fulop@essec.edu"
"status" => "ACTIF"
"campus" => "Campus de Cergy"
"departments" => []
"phone" => "+33 (0)1 34 43 36 47"
"sites" => []
"facNumber" => "2040"
"externalCvUrl" => "https://faculty.essec.edu/en/cv/fulop-andras/pdf"
"googleScholarUrl" => "https://scholar.google.com/citations?user=9S-HHKUAAAAJ"
"facOrcId" => "https://orcid.org/0000-0003-0873-5020"
"career" => array:9 [
0 => Essec\Faculty\Model\CareerItem {#2236
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2006-09-01"
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"isInternalPosition" => true
"type" => array:2 [
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]
"label" => array:2 [
"fr" => "Professeur assistant"
"en" => "Assistant Professor"
]
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
1 => Essec\Faculty\Model\CareerItem {#2237
#_index: null
#_id: null
#_source: array:7 [
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]
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"fr" => "Professeur associé"
"en" => "Associate Professor"
]
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"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
2 => Essec\Faculty\Model\CareerItem {#2238
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2005-06-01"
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"isInternalPosition" => true
"type" => array:2 [
"en" => "Other appointments"
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]
"label" => array:2 [
"fr" => "Chercheur Visitant"
"en" => "Visiting Researcher"
]
"institution" => array:2 [
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"en" => "Hungarian National Bank, Research Division"
]
"country" => array:2 [
"fr" => "Hongrie"
"en" => "Hungary"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
3 => Essec\Faculty\Model\CareerItem {#2239
#_index: null
#_id: null
#_source: array:7 [
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]
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]
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"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
4 => Essec\Faculty\Model\CareerItem {#2240
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2016-10-01"
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"isInternalPosition" => true
"type" => array:2 [
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"fr" => "Autres positions"
]
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]
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"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
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]
]
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}
5 => Essec\Faculty\Model\CareerItem {#2241
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2006-09-01"
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"isInternalPosition" => true
"type" => array:2 [
"en" => "Professional appointments"
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]
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"en" => "Training on Credit Derivatives"
]
"institution" => array:2 [
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"en" => "Eurotitrisation"
]
"country" => array:2 [
"fr" => "Hongrie"
"en" => "Hungary"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
6 => Essec\Faculty\Model\CareerItem {#2242
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2012-06-01"
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]
"label" => array:2 [
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]
"institution" => array:2 [
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"en" => "Hungarian National Bank, Research Division"
]
"country" => array:2 [
"fr" => "Hongrie"
"en" => "Hungary"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
7 => Essec\Faculty\Model\CareerItem {#2243
#_index: null
#_id: null
#_source: array:7 [
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]
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"fr" => "Bundesbank"
"en" => "Bundesbank"
]
"country" => array:2 [
"fr" => "Allemagne"
"en" => "Germany"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
8 => Essec\Faculty\Model\CareerItem {#2244
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2022-09-01"
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"type" => array:2 [
"en" => "Other Academic Appointments"
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]
"label" => array:2 [
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]
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"fr" => "Corvinus Institute for Advanced Studies"
"en" => "Corvinus Institute for Advanced Studies"
]
"country" => array:2 [
"fr" => "Hongrie"
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]
]
+lang: "en"
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}
]
"diplomes" => array:3 [
0 => Essec\Faculty\Model\Diplome {#2218
#_index: null
#_id: null
#_source: array:6 [
"diplome" => "DIPLOMA"
"type" => array:2 [
"fr" => "Diplômes"
"en" => "Diplomas"
]
"year" => "2006"
"label" => array:2 [
"en" => "Ph.D. in Finance"
"fr" => "Ph.D. en Finance"
]
"institution" => array:2 [
"fr" => "Rotman School of Management"
"en" => "Rotman School of Management"
]
"country" => array:2 [
"fr" => "Canada"
"en" => "Canada"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
1 => Essec\Faculty\Model\Diplome {#2220
#_index: null
#_id: null
#_source: array:6 [
"diplome" => "DIPLOMA"
"type" => array:2 [
"fr" => "Diplômes"
"en" => "Diplomas"
]
"year" => "2000"
"label" => array:2 [
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"fr" => "M.A. en Economie"
]
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"fr" => "University of Toronto"
"en" => "University of Toronto"
]
"country" => array:2 [
"fr" => "Canada"
"en" => "Canada"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
2 => Essec\Faculty\Model\Diplome {#2217
#_index: null
#_id: null
#_source: array:6 [
"diplome" => "DIPLOMA"
"type" => array:2 [
"fr" => "Diplômes"
"en" => "Diplomas"
]
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]
"institution" => array:2 [
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"en" => "Budapest University of Economic Sciences"
]
"country" => array:2 [
"fr" => "Hongrie"
"en" => "Hungary"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
]
"bio" => array:2 [
"fr" => null
"en" => null
]
"department" => array:2 [
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]
"site" => array:2 [
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]
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"researchFields" => array:2 [
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]
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]
"distinctions" => array:12 [
0 => Essec\Faculty\Model\Distinction {#2245
#_index: null
#_id: null
#_source: array:6 [
"date" => "2000-01-01"
"label" => array:2 [
"fr" => "Harvey Rourke Fellowship"
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]
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]
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]
]
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}
1 => Essec\Faculty\Model\Distinction {#2246
#_index: null
#_id: null
#_source: array:6 [
"date" => "1999-01-01"
"label" => array:2 [
"fr" => "University of Toronto Fellowship"
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"fr" => "Bourses"
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]
"country" => array:2 [
"fr" => "Canada"
"en" => "Canada"
]
]
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+"parent": Essec\Faculty\Model\Profile {#2216}
}
2 => Essec\Faculty\Model\Distinction {#2247
#_index: null
#_id: null
#_source: array:6 [
"date" => "1999-01-01"
"label" => array:2 [
"fr" => "Soros Foundation Fellowship"
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"fr" => "Soros Foundation"
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]
"country" => array:2 [
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]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
3 => Essec\Faculty\Model\Distinction {#2248
#_index: null
#_id: null
#_source: array:6 [
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"label" => array:2 [
"fr" => "Bourse de Recherche de l'Europlace Institute of Finance and Labex Louis Bachelier"
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]
+lang: "en"
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}
4 => Essec\Faculty\Model\Distinction {#2249
#_index: null
#_id: null
#_source: array:6 [
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]
]
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+"parent": Essec\Faculty\Model\Profile {#2216}
}
5 => Essec\Faculty\Model\Distinction {#2250
#_index: null
#_id: null
#_source: array:6 [
"date" => "2008-01-01"
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"fr" => "Bourse de recherche de NYSE-Euronext (en collaboration avec L. Lescourret)"
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]
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}
6 => Essec\Faculty\Model\Distinction {#2251
#_index: null
#_id: null
#_source: array:6 [
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]
]
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}
7 => Essec\Faculty\Model\Distinction {#2252
#_index: null
#_id: null
#_source: array:6 [
"date" => "2015-09-01"
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"fr" => "Meilleur Article sur les Dérivées (sponsorisé par l'IFSID, Montreal Institute of Structured Finance and Derivatives), décerné lors du meeting annuel de la Northern Finance Association, pour leur papier "Transparency Regime Initiatives and Liquidity in the CDS Market.""
"en" => "Best Paper Award on Derivatives, IFSID, Montreal Institute of Structured Finance and Derivatives, Northern Finance Association Annual meeting, for the article "Transparency Regime Initiatives and Liquidity in the CDS Market"."
]
"type" => array:2 [
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]
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]
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}
8 => Essec\Faculty\Model\Distinction {#2253
#_index: null
#_id: null
#_source: array:6 [
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"fr" => "Fondation ESSEC Prix White Project"
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]
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]
]
+lang: "en"
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}
9 => Essec\Faculty\Model\Distinction {#2254
#_index: null
#_id: null
#_source: array:6 [
"date" => "2017-01-01"
"label" => array:2 [
"fr" => "Prix du Meilleur Article, China International Risk Forum"
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]
"country" => array:2 [
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]
]
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}
10 => Essec\Faculty\Model\Distinction {#2255
#_index: null
#_id: null
#_source: array:6 [
"date" => "2023-12-19"
"label" => array:2 [
"fr" => "Best paper award at the 21st edition of the EUROFIDAI-ESSEC Paris Finance Meeting (December 2023)"
"en" => "Best paper award at the 21st edition of the EUROFIDAI-ESSEC Paris Finance Meeting (December 2023)"
]
"type" => array:2 [
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]
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"fr" => "European Financial Data Institute (EUROFIDAI)"
"en" => "European Financial Data Institute (EUROFIDAI)"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
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}
11 => Essec\Faculty\Model\Distinction {#2256
#_index: null
#_id: null
#_source: array:6 [
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]
]
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}
]
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0 => Essec\Faculty\Model\TeachingItem {#2234
#_index: null
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]
"country" => array:2 [
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"en" => "France"
]
]
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}
1 => Essec\Faculty\Model\TeachingItem {#2233
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]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
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}
2 => Essec\Faculty\Model\TeachingItem {#2235
#_index: null
#_id: null
#_source: array:7 [
"startDate" => null
"endDate" => "2023"
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"type" => array:2 [
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"en" => "ESSEC Business School"
]
"country" => array:2 [
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"en" => "France"
]
]
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}
3 => Essec\Faculty\Model\TeachingItem {#2232
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2013"
"endDate" => "2019"
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"en" => "Three essays on empirical asset pricing"
]
"type" => array:2 [
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"en" => "Thesis co-director"
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"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
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]
]
+lang: "en"
}
]
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0 => Essec\Faculty\Model\ExtraActivity {#2221
#_index: null
#_id: null
#_source: array:9 [
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]
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]
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}
1 => Essec\Faculty\Model\ExtraActivity {#2215
#_index: null
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#_source: array:9 [
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]
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2 => Essec\Faculty\Model\ExtraActivity {#2219
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0 => Essec\Faculty\Model\These {#2257
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2 => Essec\Faculty\Model\These {#2259
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3 => Essec\Faculty\Model\These {#2260
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0 => Essec\Faculty\Model\Contribution {#2262
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1 => Essec\Faculty\Model\Contribution {#2264
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2 => Essec\Faculty\Model\Contribution {#2266
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3 => Essec\Faculty\Model\Contribution {#2263
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4 => Essec\Faculty\Model\Contribution {#2267
#_index: "academ_contributions"
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5 => Essec\Faculty\Model\Contribution {#2261
#_index: "academ_contributions"
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]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
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]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
6 => Essec\Faculty\Model\Contribution {#2265
#_index: "academ_contributions"
#_id: "6180"
#_source: array:18 [
"id" => "6180"
"slug" => "inferring-volatility-dynamics-and-variance-risk-premia-in-efficient-bayesian-approach"
"yearMonth" => "2016-08"
"year" => "2016"
"title" => "Inferring Volatility Dynamics and Variance Risk Premia in Efficient Bayesian Approach"
"description" => "FULOP, A. et LI, J. (2016). Inferring Volatility Dynamics and Variance Risk Premia in Efficient Bayesian Approach. Dans: 2016 Asian Meeting of the Econometric Society."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "LI Junye"
]
]
"ouvrage" => "2016 Asian Meeting of the Econometric Society"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
7 => Essec\Faculty\Model\Contribution {#2268
#_index: "academ_contributions"
#_id: "6181"
#_source: array:18 [
"id" => "6181"
"slug" => "inferring-volatility-dynamics-and-variance-risk-premia-an-efficient-bayesian-approach"
"yearMonth" => "2014-08"
"year" => "2014"
"title" => "Inferring Volatility Dynamics and Variance Risk Premia: An Efficient Bayesian Approach"
"description" => "LI, J. et FULOP, A. (2014). Inferring Volatility Dynamics and Variance Risk Premia: An Efficient Bayesian Approach. Dans: UT/Princeton Tripartite Workshop on Financial Econometrics."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "LI Junye"
]
]
"ouvrage" => "UT/Princeton Tripartite Workshop on Financial Econometrics"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
8 => Essec\Faculty\Model\Contribution {#2269
#_index: "academ_contributions"
#_id: "6182"
#_source: array:18 [
"id" => "6182"
"slug" => "inferring-volatility-dynamics-and-variance-risk-premia-an-efficient-bayesian-approach"
"yearMonth" => "2015-07"
"year" => "2015"
"title" => "Inferring Volatility Dynamics and Variance Risk Premia: An Efficient Bayesian Approach"
"description" => "LI, J. et FULOP, A. (2015). Inferring Volatility Dynamics and Variance Risk Premia: An Efficient Bayesian Approach. Dans: 2015 China International Conference in Finance."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "LI Junye"
]
]
"ouvrage" => "2015 China International Conference in Finance"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
9 => Essec\Faculty\Model\Contribution {#2270
#_index: "academ_contributions"
#_id: "6183"
#_source: array:18 [
"id" => "6183"
"slug" => "inferring-volatility-dynamics-using-stock-prices-and-variance-swap-rates"
"yearMonth" => "2017-06"
"year" => "2017"
"title" => "Inferring Volatility Dynamics Using Stock Prices and Variance Swap Rates"
"description" => "LI, J. et FULOP, A. (2017). Inferring Volatility Dynamics Using Stock Prices and Variance Swap Rates. Dans: 2017 China Meeting of the Econometric Society."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "LI Junye"
]
]
"ouvrage" => "2017 China Meeting of the Econometric Society"
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
10 => Essec\Faculty\Model\Contribution {#2271
#_index: "academ_contributions"
#_id: "6444"
#_source: array:18 [
"id" => "6444"
"slug" => "learning-about-bubbles-a-bayesian-approach"
"yearMonth" => "2013-07"
"year" => "2013"
"title" => "Learning about Bubbles: A Bayesian Approach"
"description" => "FULOP, A. (2013). Learning about Bubbles: A Bayesian Approach. Dans: Seventh Annual Risk Management Conference."
"authors" => array:1 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
]
"ouvrage" => "Seventh Annual Risk Management Conference"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
11 => Essec\Faculty\Model\Contribution {#2272
#_index: "academ_contributions"
#_id: "1116"
#_source: array:18 [
"id" => "1116"
"slug" => "estimating-the-structural-credit-risk-model-when-equity-prices-are-contaminated-by-trading-noises"
"yearMonth" => "2009-01"
"year" => "2009"
"title" => "Estimating the Structural Credit Risk Model When Equity Prices Are Contaminated by Trading Noises"
"description" => "DUAN, J.C. et FULOP, A. (2009). Estimating the Structural Credit Risk Model When Equity Prices Are Contaminated by Trading Noises. <i>Journal of Econometrics</i>, 150(2), pp. 288-296."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "DUAN J.-C."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2020-12-17 17:55:06"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "288-296"
"volume" => "150"
"number" => "2"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
12 => Essec\Faculty\Model\Contribution {#2273
#_index: "academ_contributions"
#_id: "580"
#_source: array:18 [
"id" => "580"
"slug" => "a-stable-estimator-of-the-information-matrix-under-em-for-dependent-data"
"yearMonth" => "2011-01"
"year" => "2011"
"title" => "A Stable Estimator of the Information Matrix Under EM for Dependent Data"
"description" => "DUAN, J.C. et FULOP, A. (2011). A Stable Estimator of the Information Matrix Under EM for Dependent Data. <i>Statistics and Computing</i>, 21(1), pp. 83-91."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "DUAN J.-C."
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Particle filter"
1 => "EM"
2 => "Information matrix"
3 => "Kalman filter"
4 => "GARCH"
5 => "Maximum likelihood"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://link.springer.com/article/10.1007%2Fs11222-009-9149-4"
"publicationInfo" => array:3 [
"pages" => "83-91"
"volume" => "21"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "This article develops a new and stable estimator for information matrix when the EM algorithm is used in maximum likelihood estimation. This estimator is constructed using the smoothed individual complete-data scores that are readily available from running the EM algorithm. The method works for dependent data sets and when the expectation step is an irregular function of the conditioning parameters. In comparison to the approach of Louis (J. R. Stat. Soc., Ser. B 44:226¿233, 1982), this new estimator is more stable and easier to implement. Both real and simulated data are used to demonstrate the use of this new estimator."
"en" => "This article develops a new and stable estimator for information matrix when the EM algorithm is used in maximum likelihood estimation. This estimator is constructed using the smoothed individual complete-data scores that are readily available from running the EM algorithm. The method works for dependent data sets and when the expectation step is an irregular function of the conditioning parameters. In comparison to the approach of Louis (J. R. Stat. Soc., Ser. B 44:226¿233, 1982), this new estimator is more stable and easier to implement. Both real and simulated data are used to demonstrate the use of this new estimator."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
13 => Essec\Faculty\Model\Contribution {#2274
#_index: "academ_contributions"
#_id: "710"
#_source: array:18 [
"id" => "710"
"slug" => "bayesian-analysis-of-bubbles-in-asset-prices"
"yearMonth" => "2017-10"
"year" => "2017"
"title" => "Bayesian Analysis of Bubbles in Asset Prices"
"description" => "FULOP, A. et YU, J. (2017). Bayesian Analysis of Bubbles in Asset Prices. <i>Econometrics</i>, 5(4), pp. 47."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "YU J."
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "Parameter learning"
1 => "Markov switching -MCMC"
2 => "Real time bubble detection"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://www.mdpi.com/2225-1146/5/4/47"
"publicationInfo" => array:3 [
"pages" => "47"
"volume" => "5"
"number" => "4"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We develop a new model where the dynamic structure of the asset price, after the fundamental value is removed, is subject to two different regimes. One regime reflects the normal period where the asset price divided by the dividend is assumed to follow a mean-reverting process around a stochastic long run mean. The second regime reflects the bubble period with explosive behavior. Stochastic switches between two regimes and non-constant probabilities of exit from the bubble regime are both allowed. A Bayesian learning approach is employed to jointly estimate the latent states and the model parameters in real time. An important feature of our Bayesian method is that we are able to deal with parameter uncertainty and at the same time, to learn about the states and the parameters sequentially, allowing for real time model analysis. This feature is particularly useful for market surveillance. Analysis using simulated data reveals that our method has good power properties for detecting bubbles. Empirical analysis using price-dividend ratios of S&P500 highlights the advantages of our method."
"en" => "We develop a new model where the dynamic structure of the asset price, after the fundamental value is removed, is subject to two different regimes. One regime reflects the normal period where the asset price divided by the dividend is assumed to follow a mean-reverting process around a stochastic long run mean. The second regime reflects the bubble period with explosive behavior. Stochastic switches between two regimes and non-constant probabilities of exit from the bubble regime are both allowed. A Bayesian learning approach is employed to jointly estimate the latent states and the model parameters in real time. An important feature of our Bayesian method is that we are able to deal with parameter uncertainty and at the same time, to learn about the states and the parameters sequentially, allowing for real time model analysis. This feature is particularly useful for market surveillance. Analysis using simulated data reveals that our method has good power properties for detecting bubbles. Empirical analysis using price-dividend ratios of S&P500 highlights the advantages of our method."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
14 => Essec\Faculty\Model\Contribution {#2275
#_index: "academ_contributions"
#_id: "711"
#_source: array:18 [
"id" => "711"
"slug" => "bayesian-estimation-of-dynamic-asset-pricing-models-with-informative-observations"
"yearMonth" => "2019-01"
"year" => "2019"
"title" => "Bayesian Estimation of Dynamic Asset Pricing Models with Informative Observations"
"description" => "FULOP, A. et LI, J. (2019). Bayesian Estimation of Dynamic Asset Pricing Models with Informative Observations. <i>Journal of Econometrics</i>, 209, pp. 114-138."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "LI Junye"
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Non-affineness"
1 => "Self-exciting jumps"
2 => "Optimal proposal density"
3 => "Auxiliary particle filter"
4 => "Common random numbers"
5 => "Sequential Monte Carlo sampler"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://www.sciencedirect.com/science/article/abs/pii/S0304407618302276?via%3Dihub"
"publicationInfo" => array:3 [
"pages" => "114-138"
"volume" => "209"
"number" => null
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "In dynamic asset pricing models, when the model structure becomes complex and derivatives data are introduced in estimation, traditional MCMC methods converge slowly, are difficult to design efficient proposals for parameters, and have large computational cost. We propose a two-stage sequential Monte Carlo sampler based on common random numbers and a smooth particle filter. This method is robust to potential model misspecification and can deliver almost full-likelihood-based inference at a much smaller computational cost. It is applied to estimate a class of volatility models that take into account price-volatility co-jumps, non-affineness, and self-excitation. An empirical study using S&P 500 index and variance swap rates shows that both non-affineness and self-excitation need to be introduced in modeling volatility dynamics."
"en" => "In dynamic asset pricing models, when the model structure becomes complex and derivatives data are introduced in estimation, traditional MCMC methods converge slowly, are difficult to design efficient proposals for parameters, and have large computational cost. We propose a two-stage sequential Monte Carlo sampler based on common random numbers and a smooth particle filter. This method is robust to potential model misspecification and can deliver almost full-likelihood-based inference at a much smaller computational cost. It is applied to estimate a class of volatility models that take into account price-volatility co-jumps, non-affineness, and self-excitation. An empirical study using S&P 500 index and variance swap rates shows that both non-affineness and self-excitation need to be introduced in modeling volatility dynamics."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
15 => Essec\Faculty\Model\Contribution {#2276
#_index: "academ_contributions"
#_id: "3364"
#_source: array:18 [
"id" => "3364"
"slug" => "a-first-look-at-the-microstructure-of-the-cds-market"
"yearMonth" => "2009-09"
"year" => "2009"
"title" => "A First Look at the Microstructure of the CDS Market"
"description" => "FULOP, A. et LESCOURRET, L. (2009). A First Look at the Microstructure of the CDS Market. Dans: <i>Financial Risks. New Developments in Structured Product & Credit Derivatives</i>. 1st ed. Economica, pp. 133-141."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:3 [
"name" => "LESCOURRET Laurence"
"bid" => "B00024824"
"slug" => "daures-laurence"
]
]
"ouvrage" => "Financial Risks. New Developments in Structured Product & Credit Derivatives"
"keywords" => []
"updatedAt" => "2021-09-06 14:06:32"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "133-141"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
16 => Essec\Faculty\Model\Contribution {#2277
#_index: "academ_contributions"
#_id: "961"
#_source: array:18 [
"id" => "961"
"slug" => "density-tempered-marginalized-sequential-monte-carlo-samplers"
"yearMonth" => "2015-04"
"year" => "2015"
"title" => "Density-Tempered Marginalized Sequential Monte Carlo Samplers"
"description" => "DUAN, J.C. et FULOP, A. (2015). Density-Tempered Marginalized Sequential Monte Carlo Samplers. <i>Journal of Business and Economic Statistics</i>, 33(2), pp. 192-202."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "DUAN J.-C."
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "Bayesian methods"
1 => "MCMC"
2 => "Particle filter"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://www.tandfonline.com/doi/abs/10.1080/07350015.2014.940081?journalCode=ubes20"
"publicationInfo" => array:3 [
"pages" => "192-202"
"volume" => "33"
"number" => "2"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We propose a density-tempered marginalized sequential Monte Carlo (SMC) sampler, a new class of samplers for full Bayesian inference of general state-space models. The dynamic states are approximately marginalized out using a particle filter, and the parameters are sampled via a sequential Monte Carlo sampler over a density-tempered bridge between the prior and the posterior. Our approach delivers exact draws from the joint posterior of the parameters and the latent states for any given number of state particles and is thus easily parallelizable in implementation. We also build into the proposed method a device that can automatically select a suitable number of state particles. Since the method incorporates sample information in a smooth fashion, it delivers good performance in the presence of outliers. We check the performance of the density-tempered SMC algorithm using simulated data based on a linear Gaussian state-space model with and without misspecification. We also apply it on real stock prices using a GARCH-type model with microstructure noise."
"en" => "We propose a density-tempered marginalized sequential Monte Carlo (SMC) sampler, a new class of samplers for full Bayesian inference of general state-space models. The dynamic states are approximately marginalized out using a particle filter, and the parameters are sampled via a sequential Monte Carlo sampler over a density-tempered bridge between the prior and the posterior. Our approach delivers exact draws from the joint posterior of the parameters and the latent states for any given number of state particles and is thus easily parallelizable in implementation. We also build into the proposed method a device that can automatically select a suitable number of state particles. Since the method incorporates sample information in a smooth fashion, it delivers good performance in the presence of outliers. We check the performance of the density-tempered SMC algorithm using simulated data based on a linear Gaussian state-space model with and without misspecification. We also apply it on real stock prices using a GARCH-type model with microstructure noise."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
17 => Essec\Faculty\Model\Contribution {#2278
#_index: "academ_contributions"
#_id: "3479"
#_source: array:18 [
"id" => "3479"
"slug" => "comprendre-le-marche-du-credit-default-swap-cds-et-le-risque-de-contrepartie"
"yearMonth" => "2009-01"
"year" => "2009"
"title" => "Comprendre le marché du credit default swap (CDS) et le risque de contrepartie"
"description" => "FULOP, A. (2009). Comprendre le marché du credit default swap (CDS) et le risque de contrepartie. Dans: <i>Le leadership responsable. Un allié sûr contre la crise</i>. 1st ed. Gualino. Lextenso éditions, pp. 233-243."
"authors" => array:1 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
]
"ouvrage" => "Le leadership responsable. Un allié sûr contre la crise"
"keywords" => []
"updatedAt" => "2021-09-06 16:57:03"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "233-243"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
18 => Essec\Faculty\Model\Contribution {#2279
#_index: "academ_contributions"
#_id: "1073"
#_source: array:18 [
"id" => "1073"
"slug" => "efficient-learning-via-simulation-a-marginalized-resample-move-approach"
"yearMonth" => "2013-10"
"year" => "2013"
"title" => "Efficient Learning via Simulation: A Marginalized Resample-Move Approach"
"description" => "FULOP, A. et LI, J. (2013). Efficient Learning via Simulation: A Marginalized Resample-Move Approach. <i>Journal of Econometrics</i>, 176(2), pp. 146-161."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "LI Junye"
]
]
"ouvrage" => ""
"keywords" => array:9 [
0 => "State–space models"
1 => "Particle filters"
2 => "Parameter learning"
3 => "State filtering"
4 => "Resample-move"
5 => "Markov chain Monte Carlo"
6 => "Lévy jumps"
7 => "Stochastic volatility"
8 => "Credit risk"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://www.sciencedirect.com/science/article/abs/pii/S0304407613001164"
"publicationInfo" => array:3 [
"pages" => "146-161"
"volume" => "176"
"number" => "2"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "In state–space models, parameter learning is practically difficult and is still an open issue. This paper proposes an efficient simulation-based parameter learning method. First, the approach breaks up the interdependence of the hidden states and the static parameters by marginalizing out the states using a particle filter. Second, it applies a Bayesian resample-move approach to this marginalized system. The methodology is generic and needs little design effort. Different from batch estimation methods, it provides posterior quantities necessary for full sequential inference and recursive model monitoring. The algorithm is implemented both on simulated data in a linear Gaussian model for illustration and comparison and on real data in a Lévy jump stochastic volatility model and a structural credit risk model."
"en" => "In state–space models, parameter learning is practically difficult and is still an open issue. This paper proposes an efficient simulation-based parameter learning method. First, the approach breaks up the interdependence of the hidden states and the static parameters by marginalizing out the states using a particle filter. Second, it applies a Bayesian resample-move approach to this marginalized system. The methodology is generic and needs little design effort. Different from batch estimation methods, it provides posterior quantities necessary for full sequential inference and recursive model monitoring. The algorithm is implemented both on simulated data in a linear Gaussian model for illustration and comparison and on real data in a Lévy jump stochastic volatility model and a structural credit risk model."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
19 => Essec\Faculty\Model\Contribution {#2280
#_index: "academ_contributions"
#_id: "6646"
#_source: array:18 [
"id" => "6646"
"slug" => "marginal-sequential-monte-carlo-samplers"
"yearMonth" => "2012-06"
"year" => "2012"
"title" => "Marginal Sequential Monte Carlo Samplers"
"description" => "FULOP, A. (2012). Marginal Sequential Monte Carlo Samplers. Dans: Fifth Annual Society for Financial Econometrics Conference."
"authors" => array:1 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
]
"ouvrage" => "Fifth Annual Society for Financial Econometrics Conference"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
20 => Essec\Faculty\Model\Contribution {#2281
#_index: "academ_contributions"
#_id: "6647"
#_source: array:18 [
"id" => "6647"
"slug" => "marginal-sequential-monte-carlo-samplers"
"yearMonth" => "2012-06"
"year" => "2012"
"title" => "Marginal Sequential Monte Carlo Samplers"
"description" => "FULOP, A. (2012). Marginal Sequential Monte Carlo Samplers. Dans: SMU-ESSEC Symposium on Empirial Finance and Financial Econometrics 2012."
"authors" => array:1 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
]
"ouvrage" => "SMU-ESSEC Symposium on Empirial Finance and Financial Econometrics 2012"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
21 => Essec\Faculty\Model\Contribution {#2282
#_index: "academ_contributions"
#_id: "6721"
#_source: array:18 [
"id" => "6721"
"slug" => "multiperiod-corporate-default-prediction-with-the-partially-conditioned-forward-intensity-co-author-jin-chual-duan"
"yearMonth" => "2012-12"
"year" => "2012"
"title" => "Multiperiod Corporate Default Prediction with the Partially Conditioned Forward Intensity (co-author Jin Chual Duan)"
"description" => "FULOP, A. (2012). Multiperiod Corporate Default Prediction with the Partially Conditioned Forward Intensity (co-author Jin Chual Duan). Dans: 2012 Asset Pricing and Portfolio Allocation in the Long Run Conference."
"authors" => array:1 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
]
"ouvrage" => "2012 Asset Pricing and Portfolio Allocation in the Long Run Conference"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
22 => Essec\Faculty\Model\Contribution {#2283
#_index: "academ_contributions"
#_id: "6852"
#_source: array:18 [
"id" => "6852"
"slug" => "parameter-learning-sequential-model-selection-and-bond-return-predictability"
"yearMonth" => "2017-11"
"year" => "2017"
"title" => "Parameter Learning, Sequential Model Selection, and Bond Return Predictability"
"description" => "FULOP, A., LI, J. et WAN, R. (2017). Parameter Learning, Sequential Model Selection, and Bond Return Predictability. Dans: 22nd Annual Meeting 2017 of the Latin American and Caribbean Economic Association."
"authors" => array:3 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "LI Junye"
]
2 => array:1 [
"name" => "WAN R."
]
]
"ouvrage" => "22nd Annual Meeting 2017 of the Latin American and Caribbean Economic Association"
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
23 => Essec\Faculty\Model\Contribution {#2284
#_index: "academ_contributions"
#_id: "6853"
#_source: array:18 [
"id" => "6853"
"slug" => "parameter-learning-sequential-model-selection-and-bond-return-predictability"
"yearMonth" => "2017-12"
"year" => "2017"
"title" => "Parameter Learning, Sequential Model Selection, and Bond Return Predictability"
"description" => "FULOP, A., LI, J. et WAN, R. (2017). Parameter Learning, Sequential Model Selection, and Bond Return Predictability. Dans: 2017 China International Risk Forum."
"authors" => array:3 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "LI Junye"
]
2 => array:1 [
"name" => "WAN R."
]
]
"ouvrage" => "2017 China International Risk Forum"
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
24 => Essec\Faculty\Model\Contribution {#2285
#_index: "academ_contributions"
#_id: "7014"
#_source: array:18 [
"id" => "7014"
"slug" => "real-time-learning-and-bond-return-predictability"
"yearMonth" => "2018-06"
"year" => "2018"
"title" => "Real-Time Learning and Bond Return Predictability"
"description" => "FULOP, A., LI, J. et WAN, R. (2018). Real-Time Learning and Bond Return Predictability. Dans: 11th Annual Meeting of the the Society for Financial Econometrics (SoFiE)."
"authors" => array:3 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "LI Junye"
]
2 => array:1 [
"name" => "WAN R."
]
]
"ouvrage" => "11th Annual Meeting of the the Society for Financial Econometrics (SoFiE)"
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
25 => Essec\Faculty\Model\Contribution {#2286
#_index: "academ_contributions"
#_id: "7015"
#_source: array:18 [
"id" => "7015"
"slug" => "real-time-learning-and-bond-return-predictability"
"yearMonth" => "2018-07"
"year" => "2018"
"title" => "Real-Time Learning and Bond Return Predictability"
"description" => "FULOP, A., LI, J. et WAN, R. (2018). Real-Time Learning and Bond Return Predictability. Dans: 2018 Frontiers in Econometrics Workshop."
"authors" => array:3 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "LI Junye"
]
2 => array:1 [
"name" => "WAN R."
]
]
"ouvrage" => "2018 Frontiers in Econometrics Workshop"
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
26 => Essec\Faculty\Model\Contribution {#2287
#_index: "academ_contributions"
#_id: "2478"
#_source: array:18 [
"id" => "2478"
"slug" => "self-exciting-jumps-learning-and-asset-pricing-implications"
"yearMonth" => "2015-03"
"year" => "2015"
"title" => "Self-Exciting Jumps, Learning, and Asset Pricing Implications"
"description" => "FULOP, A., LI, J. et JU, Y. (2015). Self-Exciting Jumps, Learning, and Asset Pricing Implications. <i>Review of Financial Studies</i>, 28(3), pp. 876-912."
"authors" => array:3 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "LI Junye"
]
2 => array:1 [
"name" => "JU Y."
]
]
"ouvrage" => ""
"keywords" => array:8 [
0 => "Self-Excitation"
1 => "Jump Clustering"
2 => "Tail Behaviors"
3 => "Parameter Learning"
4 => "Sequential Bayes Factor"
5 => "Excess Volatility"
6 => "Volatility Forecasting"
7 => "Option Pricing"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "http://dx.doi.org/10.2139/ssrn.1981024"
"publicationInfo" => array:3 [
"pages" => "876-912"
"volume" => "28"
"number" => "3"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The paper proposes a self-exciting asset pricing model that takes into account co-jumps between prices and volatility and self-exciting jump clustering. We employ a Bayesian learning approach to implement real-time sequential analysis. We find evidence of self-exciting jump clustering since the 1987 market crash, and its importance becomes more obvious at the onset of the 2008 global financial crisis. We also find that learning affects the tail behaviors of the return distributions and has important implications for risk management, volatility forecasting, and option pricing."
"en" => "The paper proposes a self-exciting asset pricing model that takes into account co-jumps between prices and volatility and self-exciting jump clustering. We employ a Bayesian learning approach to implement real-time sequential analysis. We find evidence of self-exciting jump clustering since the 1987 market crash, and its importance becomes more obvious at the onset of the 2008 global financial crisis. We also find that learning affects the tail behaviors of the return distributions and has important implications for risk management, volatility forecasting, and option pricing."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
27 => Essec\Faculty\Model\Contribution {#2288
#_index: "academ_contributions"
#_id: "7516"
#_source: array:18 [
"id" => "7516"
"slug" => "transparency-regime-initiatives-and-liquidity-in-the-cds-market"
"yearMonth" => "2015-10"
"year" => "2015"
"title" => "Transparency Regime Initiatives and Liquidity in the CDS Market"
"description" => "FULOP, A. et LESCOURRET, L. (2015). Transparency Regime Initiatives and Liquidity in the CDS Market. Dans: 2015 Financial Management Association (FMA) Annual Meeting."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:3 [
"name" => "LESCOURRET Laurence"
"bid" => "B00024824"
"slug" => "daures-laurence"
]
]
"ouvrage" => "2015 Financial Management Association (FMA) Annual Meeting"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
28 => Essec\Faculty\Model\Contribution {#2289
#_index: "academ_contributions"
#_id: "7517"
#_source: array:18 [
"id" => "7517"
"slug" => "transparency-regime-initiatives-and-liquidity-in-the-cds-market"
"yearMonth" => "2015-08"
"year" => "2015"
"title" => "Transparency Regime Initiatives and Liquidity in the CDS Market"
"description" => "FULOP, A. et LESCOURRET, L. (2015). Transparency Regime Initiatives and Liquidity in the CDS Market. Dans: 42nd Annual Meeting of the European Finance Association."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:3 [
"name" => "LESCOURRET Laurence"
"bid" => "B00024824"
"slug" => "daures-laurence"
]
]
"ouvrage" => "42nd Annual Meeting of the European Finance Association"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
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]
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]
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"fr" => null
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]
"countries" => array:2 [
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"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
29 => Essec\Faculty\Model\Contribution {#2290
#_index: "academ_contributions"
#_id: "7518"
#_source: array:18 [
"id" => "7518"
"slug" => "transparency-regime-initiatives-and-liquidity-in-the-cds-market"
"yearMonth" => "2015-09"
"year" => "2015"
"title" => "Transparency Regime Initiatives and Liquidity in the CDS Market"
"description" => "FULOP, A. et LESCOURRET, L. (2015). Transparency Regime Initiatives and Liquidity in the CDS Market. Dans: 2015 Northern Finance Association (NFA) Conference."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:3 [
"name" => "LESCOURRET Laurence"
"bid" => "B00024824"
"slug" => "daures-laurence"
]
]
"ouvrage" => "2015 Northern Finance Association (NFA) Conference"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
30 => Essec\Faculty\Model\Contribution {#2291
#_index: "academ_contributions"
#_id: "7519"
#_source: array:18 [
"id" => "7519"
"slug" => "transparency-regime-initiatives-and-liquidity-in-the-cds-market"
"yearMonth" => "2016-06"
"year" => "2016"
"title" => "Transparency Regime Initiatives and Liquidity in the CDS Market"
"description" => "FULOP, A. et LESCOURRET, L. (2016). Transparency Regime Initiatives and Liquidity in the CDS Market. Dans: 9th Annual Society for Financial Econometrics (SoFiE) Conference."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:3 [
"name" => "LESCOURRET Laurence"
"bid" => "B00024824"
"slug" => "daures-laurence"
]
]
"ouvrage" => "9th Annual Society for Financial Econometrics (SoFiE) Conference"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
31 => Essec\Faculty\Model\Contribution {#2292
#_index: "academ_contributions"
#_id: "7520"
#_source: array:18 [
"id" => "7520"
"slug" => "transparency-regime-initiatives-and-liquidity-in-the-cds-market"
"yearMonth" => "2016-06"
"year" => "2016"
"title" => "Transparency Regime Initiatives and Liquidity in the CDS Market"
"description" => "FULOP, A. et LESCOURRET, L. (2016). Transparency Regime Initiatives and Liquidity in the CDS Market. Dans: 2016 Financial Intermediation Research Society (FIRS) Conference."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:3 [
"name" => "LESCOURRET Laurence"
"bid" => "B00024824"
"slug" => "daures-laurence"
]
]
"ouvrage" => "2016 Financial Intermediation Research Society (FIRS) Conference"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
32 => Essec\Faculty\Model\Contribution {#2293
#_index: "academ_contributions"
#_id: "7521"
#_source: array:18 [
"id" => "7521"
"slug" => "transparency-regimes-and-liquidity-in-the-cds-market"
"yearMonth" => "2014-08"
"year" => "2014"
"title" => "Transparency Regimes and Liquidity in the CDS Market"
"description" => "LESCOURRET, L. et FULOP, A. (2014). Transparency Regimes and Liquidity in the CDS Market. Dans: 68th European Meeting of the Econometric Society."
"authors" => array:2 [
0 => array:3 [
"name" => "LESCOURRET Laurence"
"bid" => "B00024824"
"slug" => "daures-laurence"
]
1 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
]
"ouvrage" => "68th European Meeting of the Econometric Society"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
33 => Essec\Faculty\Model\Contribution {#2294
#_index: "academ_contributions"
#_id: "3654"
#_source: array:18 [
"id" => "3654"
"slug" => "filtering-methods"
"yearMonth" => "2012-01"
"year" => "2012"
"title" => "Filtering Methods"
"description" => "FULOP, A. (2012). Filtering Methods. Dans: <i>Handbook of Computational Finance</i>. 1st ed. Springer, pp. 439-467."
"authors" => array:1 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
]
"ouvrage" => "Handbook of Computational Finance"
"keywords" => []
"updatedAt" => "2021-09-06 14:06:32"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "439-467"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "This chapter surveys filtering methods, where the state of an unobserved dynamic model is inferred based on noisy observations. In linear and gaussian models, the Kalman Filter is applicable. We provide a brief description of the method and an example with a gaussian factor model of yields. More general models can be tackled using sequential monte carlo (SMC) techniques (also called particle filters). Here, the filtering distribution of the unobserved states is approximated by a swarm of particles and recursively update these particles using importance sampling and resampling. We give brief review of the methodology, illustrated throughout by the example of inferring asset values from noisy equity prices in a structural credit risk model. The MATLAB code implementing the examples is available."
"en" => "This chapter surveys filtering methods, where the state of an unobserved dynamic model is inferred based on noisy observations. In linear and gaussian models, the Kalman Filter is applicable. We provide a brief description of the method and an example with a gaussian factor model of yields. More general models can be tackled using sequential monte carlo (SMC) techniques (also called particle filters). Here, the filtering distribution of the unobserved states is approximated by a swarm of particles and recursively update these particles using importance sampling and resampling. We give brief review of the methodology, illustrated throughout by the example of inferring asset values from noisy equity prices in a structural credit risk model. The MATLAB code implementing the examples is available."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
34 => Essec\Faculty\Model\Contribution {#2295
#_index: "academ_contributions"
#_id: "6722"
#_source: array:18 [
"id" => "6722"
"slug" => "multiperiod-corporate-default-prediction-with-the-partially-conditioned-forward-intensity-co-author-jin-chual-duan"
"yearMonth" => "2012-12"
"year" => "2012"
"title" => "Multiperiod Corporate Default Prediction with the Partially Conditioned Forward Intensity (co-author Jin Chual Duan)"
"description" => "FULOP, A. (2012). Multiperiod Corporate Default Prediction with the Partially Conditioned Forward Intensity (co-author Jin Chual Duan). Dans: 5th International Conference of the ERCIM Working Group on Computing & Statistics."
"authors" => array:1 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
]
"ouvrage" => "5th International Conference of the ERCIM Working Group on Computing & Statistics"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
35 => Essec\Faculty\Model\Contribution {#2296
#_index: "academ_contributions"
#_id: "7515"
#_source: array:18 [
"id" => "7515"
"slug" => "transparency-regime-initiatives-and-liquidity-in-the-cds-market"
"yearMonth" => "2015-06"
"year" => "2015"
"title" => "Transparency Regime Initiatives and Liquidity in the CDS Market"
"description" => "LESCOURRET, L. et FULOP, A. (2015). Transparency Regime Initiatives and Liquidity in the CDS Market. Dans: 7th International Conference of the The International Finance and Banking Society (IFABS): The Future of Financial Institutions and Markets: Navigating the Challenges Ahead."
"authors" => array:2 [
0 => array:3 [
"name" => "LESCOURRET Laurence"
"bid" => "B00024824"
"slug" => "daures-laurence"
]
1 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
]
"ouvrage" => "7th International Conference of the The International Finance and Banking Society (IFABS): The Future of Financial Institutions and Markets: Navigating the Challenges Ahead"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
36 => Essec\Faculty\Model\Contribution {#2297
#_index: "academ_contributions"
#_id: "5489"
#_source: array:18 [
"id" => "5489"
"slug" => "bayesian-learning-of-impacts-of-self-exciting-jumps-in-returns-and-volatility"
"yearMonth" => "2012-07"
"year" => "2012"
"title" => "Bayesian Learning of Impacts of Self-Exciting Jumps in Returns and Volatility"
"description" => "FULOP, A. et LI, J. (2012). Bayesian Learning of Impacts of Self-Exciting Jumps in Returns and Volatility. Dans: 2012 China International Conference in Finance."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "LI Junye"
]
]
"ouvrage" => "2012 China International Conference in Finance"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The paper proposes a new class of continuous-time asset pricing models where negative jumps play a crucial role. Whenever there is a negative jump in asset returns, it is simultaneously passed on to diffusion variance and the jump intensity, generating self-exciting co-jumps of prices and volatility and jump clustering. To properly deal with parameter uncertainty and in-sample over-fitting, a Bayesian learning approach combined with an efficient particle filter is employed. It not only allows for comparison of both nested and non-nested models, but also generates all quantities necessary for sequential model analysis. Empirical investigation using S&P 500 index returns shows that volatility jumps at the same time as negative jumps in asset returns mainly through jumps in diffusion volatility. We find substantial evidence for jump clustering, in particular, after the recent financial crisis in 2008, even though parameters driving dynamics of the jump intensity remain difficult to identify."
"en" => "The paper proposes a new class of continuous-time asset pricing models where negative jumps play a crucial role. Whenever there is a negative jump in asset returns, it is simultaneously passed on to diffusion variance and the jump intensity, generating self-exciting co-jumps of prices and volatility and jump clustering. To properly deal with parameter uncertainty and in-sample over-fitting, a Bayesian learning approach combined with an efficient particle filter is employed. It not only allows for comparison of both nested and non-nested models, but also generates all quantities necessary for sequential model analysis. Empirical investigation using S&P 500 index returns shows that volatility jumps at the same time as negative jumps in asset returns mainly through jumps in diffusion volatility. We find substantial evidence for jump clustering, in particular, after the recent financial crisis in 2008, even though parameters driving dynamics of the jump intensity remain difficult to identify."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
37 => Essec\Faculty\Model\Contribution {#2298
#_index: "academ_contributions"
#_id: "8045"
#_source: array:18 [
"id" => "8045"
"slug" => "feedback-effects-of-rating-downgrades"
"yearMonth" => "2006-10"
"year" => "2006"
"title" => "Feedback Effects of Rating Downgrades"
"description" => "FULOP, A. (2006). <i>Feedback Effects of Rating Downgrades</i>. ESSEC Business School."
"authors" => array:1 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2020-12-17 21:00:33"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Documents de travail"
"en" => "Working Papers"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "This paper addresses whether credit rating downgrades feed back on the asset value of the downgraded companies, causing real losses. To investigate this issue we construct a structural credit risk model incorporating ratings and the feedback loss. To estimate the parameters of the model we develop a maximum likelihood estimator using time series of equity prices and credit ratings. Implementing the model on a sample of US public firms downgraded from investment grade to junk, we find strong support for the existence of feedback losses. First, estimated feedback losses are significant for a third of our sample with the cross-sectional averages of the feedback loss around 7 %. Second, the behavior of estimated asset volatilities around downgrades in real data is consistent with the predictions of our model. We observe a hump-shaped pattern of estimated asset volatilities when feedback is ignored. Using the feedback model, the hump-shaped pattern disappears. These findings suggest that ignoring feedback can lead to the appearance of changing asset volatility even when the real volatility is constant. Last, accounting for feedback helps in asset volatility prediction."
"en" => "This paper addresses whether credit rating downgrades feed back on the asset value of the downgraded companies, causing real losses. To investigate this issue we construct a structural credit risk model incorporating ratings and the feedback loss. To estimate the parameters of the model we develop a maximum likelihood estimator using time series of equity prices and credit ratings. Implementing the model on a sample of US public firms downgraded from investment grade to junk, we find strong support for the existence of feedback losses. First, estimated feedback losses are significant for a third of our sample with the cross-sectional averages of the feedback loss around 7 %. Second, the behavior of estimated asset volatilities around downgrades in real data is consistent with the predictions of our model. We observe a hump-shaped pattern of estimated asset volatilities when feedback is ignored. Using the feedback model, the hump-shaped pattern disappears. These findings suggest that ignoring feedback can lead to the appearance of changing asset volatility even when the real volatility is constant. Last, accounting for feedback helps in asset volatility prediction."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
38 => Essec\Faculty\Model\Contribution {#2299
#_index: "academ_contributions"
#_id: "10016"
#_source: array:18 [
"id" => "10016"
"slug" => "maximum-likelihood"
"yearMonth" => "2004-09"
"year" => "2004"
"title" => "Maximum Likelihood"
"description" => "FULOP, A. et DUAN, J.C. (2004). Maximum Likelihood. Dans: <i>Encyclopedia of Actuarial Science</i>. 1st ed. Chichester: Wiley, pp. 1107-1115."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "DUAN Jin-Chuan"
]
]
"ouvrage" => "Encyclopedia of Actuarial Science"
"keywords" => array:1 [
0 => "actuarial sciencesmaximum likelihood"
]
"updatedAt" => "2020-12-17 18:37:46"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "1107-1115"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The Encyclopedia of Actuarial Science presents a timely and comprehensive body of knowledge designed to serve as an essential reference for the actuarial profession and all related business and financial activities, as well as researchers and students in actuarial science and related areas."
"en" => "The Encyclopedia of Actuarial Science presents a timely and comprehensive body of knowledge designed to serve as an essential reference for the actuarial profession and all related business and financial activities, as well as researchers and students in actuarial science and related areas."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
39 => Essec\Faculty\Model\Contribution {#2300
#_index: "academ_contributions"
#_id: "10122"
#_source: array:18 [
"id" => "10122"
"slug" => "estimating-the-structural-credit-risk-model-when-equity-prices-are-contaminated-by-trading-noises"
"yearMonth" => "2006-10"
"year" => "2006"
"title" => "Estimating the Structural Credit Risk Model When Equity Prices Are Contaminated by Trading Noises"
"description" => "JIN-CHUAN, D. et FULOP, A. (2006). <i>Estimating the Structural Credit Risk Model When Equity Prices Are Contaminated by Trading Noises</i>."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "JIN-CHUAN Duan"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Credit Risk"
1 => "Maximum Likelihood"
2 => "Microstructure"
3 => "Option Pricing"
4 => "Particle Filtering"
]
"updatedAt" => "2021-07-13 14:31:27"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Documents de travail"
"en" => "Working Papers"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Ce papier étend la méthode proposée par Duan (1994) concernant l'estimation des modèles de crédit, en incorporant la présence de bruits générés par les frictions du marché."
"en" => "The transformed-data maximum likelihood estimation (MLE) method for structural credit risk models developed by Duan (1994) is extended to account for the fact that observed equity prices may have been contaminated by trading noises. With the presence of trading noises, the likelihood function based on the observed equity prices can only be evaluated via some nonlinear filtering scheme. We devise a particle filtering algorithm that is practical for conducting the MLE estimation of the structural credit risk model of Merton (1974). We implement the method on the Dow Jones 30 firms and on 100 randomly selected firms, and find that ignoring trading noises can lead to significantly over-estimating the firm's asset volatility. The estimated magnitude of trading noise is in line with the direction that a firm's liquidity will predict based on three common liquidity proxies. A simulation study is then conducted to ascertain the performance of the estimation method."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
40 => Essec\Faculty\Model\Contribution {#2301
#_index: "academ_contributions"
#_id: "10738"
#_source: array:18 [
"id" => "10738"
"slug" => "data-cloning-smc2-a-global-optimizer-for-maximum-likelihood-estimation-of-latent-variable-models"
"yearMonth" => "2020-03"
"year" => "2020"
"title" => "Data-cloning SMC2: A global optimizer for maximum likelihood estimation of latent variable models"
"description" => "DUAN, J.C., FULOP, A. et HSIEG, Y.W. (2020). Data-cloning SMC2: A global optimizer for maximum likelihood estimation of latent variable models. <i>Computational Statistics and Data Analysis</i>, 143."
"authors" => array:3 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "DUAN J.-C."
]
2 => array:1 [
"name" => "HSIEG Y.-W."
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Sequential Monte Carlo"
1 => "Data clone"
2 => "Latent variable"
3 => "Maximum likelihood"
4 => "Monte Carlo optimization"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://doi.org/10.1016/j.csda.2019.106841"
"publicationInfo" => array:3 [
"pages" => null
"volume" => "143"
"number" => null
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "A data-cloning SMC2 algorithm is proposed as a general-purpose, global optimization routine for the maximum likelihood estimation of models with latent variables. In the SMC2 phase, the method first marginalizes out the latent variable(s) by applying one layer of SMC at a fixed parameter value and then searches for the optimal parameters through another layer of SMC. The data-cloning phase is deployed to ensure global convergence by dampening multi-modality and to reduce the Monte Carlo error associated with SMC. This new method has broad applicability and is massively parallelizable through leveraging modern multi-core CPU or GPU computing."
"en" => "A data-cloning SMC2 algorithm is proposed as a general-purpose, global optimization routine for the maximum likelihood estimation of models with latent variables. In the SMC2 phase, the method first marginalizes out the latent variable(s) by applying one layer of SMC at a fixed parameter value and then searches for the optimal parameters through another layer of SMC. The data-cloning phase is deployed to ensure global convergence by dampening multi-modality and to reduce the Monte Carlo error associated with SMC. This new method has broad applicability and is massively parallelizable through leveraging modern multi-core CPU or GPU computing."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
41 => Essec\Faculty\Model\Contribution {#2302
#_index: "academ_contributions"
#_id: "11158"
#_source: array:18 [
"id" => "11158"
"slug" => "bayesian-estimation-of-long-run-risk-models-using-sequential-monte-carlo"
"yearMonth" => "2022-05"
"year" => "2022"
"title" => "Bayesian Estimation of Long-Run Risk Models Using Sequential Monte Carlo"
"description" => "FULOP, A., HENG, J., LI, J. et LIU, H. (2022). Bayesian Estimation of Long-Run Risk Models Using Sequential Monte Carlo. <i>Journal of Econometrics</i>, 228(1), pp. 62-84."
"authors" => array:4 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:3 [
"name" => "HENG Jeremy"
"bid" => "B00760223"
"slug" => "heng-jeremy"
]
2 => array:1 [
"name" => "LI Junye"
]
3 => array:1 [
"name" => "LIU Hening"
]
]
"ouvrage" => ""
"keywords" => array:7 [
0 => "Asset Pricing"
1 => "Long-Run Risk"
2 => "Autoregressive Gamma Process"
3 => "Log-linearization"
4 => "Projection Methods"
5 => "Particle Filters"
6 => "Sequential Monte Carlo Sampler"
]
"updatedAt" => "2023-07-10 17:16:50"
"publicationUrl" => "https://www.sciencedirect.com/science/article/pii/S0304407621000531"
"publicationInfo" => array:3 [
"pages" => "62-84"
"volume" => "228"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We propose a likelihood-based Bayesian method that exploits up-to-date sequential Monte Carlo methods to efficiently estimate long-run risk models in which the conditional variance of consumption growth follows either an autoregressive (AR) process or an autoregressive gamma (ARG) process. We use the U.S. quarterly consumption and asset returns data from the postwar period to implement estimation. Our findings are: (1) informative priors on the preference parameters can help to improve model performance; (2) expected consumption growth has a very persistent component, whereas consumption volatility is less persistent; (3) while the ARG-based model performs better than the AR-based one statistically, the latter could fit asset returns better; and (4) the solution method matters more for estimation in the AR-based model than in the ARG-based model."
"en" => "We propose a likelihood-based Bayesian method that exploits up-to-date sequential Monte Carlo methods to efficiently estimate long-run risk models in which the conditional variance of consumption growth follows either an autoregressive (AR) process or an autoregressive gamma (ARG) process. We use the U.S. quarterly consumption and asset returns data from the postwar period to implement estimation. Our findings are: (1) informative priors on the preference parameters can help to improve model performance; (2) expected consumption growth has a very persistent component, whereas consumption volatility is less persistent; (3) while the ARG-based model performs better than the AR-based one statistically, the latter could fit asset returns better; and (4) the solution method matters more for estimation in the AR-based model than in the ARG-based model."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
42 => Essec\Faculty\Model\Contribution {#2303
#_index: "academ_contributions"
#_id: "12369"
#_source: array:18 [
"id" => "12369"
"slug" => "real-time-bayesian-learning-and-bond-return-predictability"
"yearMonth" => "2022-09"
"year" => "2022"
"title" => "Real-time Bayesian learning and bond return predictability"
"description" => "WAN, R., FULOP, A. et LI, J. (2022). Real-time Bayesian learning and bond return predictability. <i>Journal of Econometrics</i>, 230(1), pp. 114-130."
"authors" => array:3 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "WAN Runqing"
]
2 => array:1 [
"name" => "LI Junye"
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Bayesian learning"
1 => "Bond return predictability"
2 => "Non-overlapping bond returns"
3 => "Parameter uncertainty"
4 => "Model combinations"
5 => "Real-time macroeconomic information"
]
"updatedAt" => "2022-09-12 15:55:47"
"publicationUrl" => "https://doi.org/10.1016/j.jeconom.2020.04.052"
"publicationInfo" => array:3 [
"pages" => "114-130"
"volume" => "230"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The paper examines statistical and economic evidence of out-of-sample bond return predictability for a real-time Bayesian investor who learns about parameters, hidden states, and predictive models over time. We find some statistical evidence using information contained in forward rates. However, such statistical predictability can hardly generate any economic value for investors. Furthermore, we find that strong statistical and economic evidence of bond return predictability from fully-revised macroeconomic data vanishes when real-time macroeconomic information is used. We also show that highly levered investments in bonds can improve short-run bond return predictability."
"en" => "The paper examines statistical and economic evidence of out-of-sample bond return predictability for a real-time Bayesian investor who learns about parameters, hidden states, and predictive models over time. We find some statistical evidence using information contained in forward rates. However, such statistical predictability can hardly generate any economic value for investors. Furthermore, we find that strong statistical and economic evidence of bond return predictability from fully-revised macroeconomic data vanishes when real-time macroeconomic information is used. We also show that highly levered investments in bonds can improve short-run bond return predictability."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
43 => Essec\Faculty\Model\Contribution {#2304
#_index: "academ_contributions"
#_id: "12798"
#_source: array:18 [
"id" => "12798"
"slug" => "efficient-likelihood-based-estimation-via-annealing-for-dynamic-structural-macrofinance-models"
"yearMonth" => "2021-12"
"year" => "2021"
"title" => "Efficient Likelihood-based Estimation via Annealing for Dynamic Structural Macrofinance Models"
"description" => "FULOP, A., HENG, J. et LI, Y. (2021). Efficient Likelihood-based Estimation via Annealing for Dynamic Structural Macrofinance Models. Dans: 2021 European Winter Meetings of the Econometric Society. Barcelona."
"authors" => array:3 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:3 [
"name" => "HENG Jeremy"
"bid" => "B00760223"
"slug" => "heng-jeremy"
]
2 => array:3 [
"name" => "LI Yan"
"bid" => "B00132135"
"slug" => "li-yan"
]
]
"ouvrage" => "2021 European Winter Meetings of the Econometric Society"
"keywords" => []
"updatedAt" => "2023-01-27 01:00:42"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => ""
"volume" => ""
"number" => ""
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => ""
"en" => ""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
44 => Essec\Faculty\Model\Contribution {#2305
#_index: "academ_contributions"
#_id: "12828"
#_source: array:18 [
"id" => "12828"
"slug" => "standardization-transparency-initiatives-and-liquidity-in-the-cds-market"
"yearMonth" => "2022-06"
"year" => "2022"
"title" => "Standardization, transparency initiatives, and liquidity in the CDS market"
"description" => "DAURES-LESCOURRET, L. et FULOP, A. (2022). Standardization, transparency initiatives, and liquidity in the CDS market. <i>Journal of Financial Markets</i>, 59, Part A, pp. 100718."
"authors" => array:2 [
0 => array:3 [
"name" => "DAURES-LESCOURRET Laurence"
"bid" => "B00024824"
"slug" => "daures-laurence"
]
1 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
]
"ouvrage" => ""
"keywords" => array:4 [
0 => "Credit default swap"
1 => "Liquidity, Transparency"
2 => "Small bang"
3 => "Counterparty risk"
]
"updatedAt" => "2023-01-27 01:00:42"
"publicationUrl" => "https://doi.org/10.1016/j.finmar.2022.100718"
"publicationInfo" => array:3 [
"pages" => "100718"
"volume" => "59, Part A"
"number" => ""
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We investigate liquidity changes in the credit default swap (CDS) market around two events that increased market transparency and standardization during the Great Financial Crisis: the dissemination of CDS positions starting in November 2008, and the implementation of the Small Bang in July 2009. We build an econometric model based on bid and ask quotes to measure liquidity in thinly traded CDSs. We find that, after the release of CDS positions, the market-wide deterioration in liquidity is less important for banks, consistent with information revelation alleviating systemic risk uncertainty. The Small Bang also improved liquidity, particularly for more illiquid CDSs."
"en" => "We investigate liquidity changes in the credit default swap (CDS) market around two events that increased market transparency and standardization during the Great Financial Crisis: the dissemination of CDS positions starting in November 2008, and the implementation of the Small Bang in July 2009. We build an econometric model based on bid and ask quotes to measure liquidity in thinly traded CDSs. We find that, after the release of CDS positions, the market-wide deterioration in liquidity is less important for banks, consistent with information revelation alleviating systemic risk uncertainty. The Small Bang also improved liquidity, particularly for more illiquid CDSs."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
45 => Essec\Faculty\Model\Contribution {#2306
#_index: "academ_contributions"
#_id: "14100"
#_source: array:18 [
"id" => "14100"
"slug" => "computational-doob-h-transforms-for-online-filtering-of-discretely-observed-diffusions"
"yearMonth" => "2023-07"
"year" => "2023"
"title" => "Computational Doob h-transforms for Online Filtering of Discretely Observed Diffusions"
"description" => "CHOPIN, N., FULOP, A., HENG, J. et THIERY, A.H. (2023). Computational Doob h-transforms for Online Filtering of Discretely Observed Diffusions. Dans: <i>Proceedings of the 40th International Conference on Machine Learning, PMLR 202:5904-5923</i>. Honolulu: Proceedings of Machine Learning Research."
"authors" => array:4 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:3 [
"name" => "HENG Jeremy"
"bid" => "B00760223"
"slug" => "heng-jeremy"
]
2 => array:1 [
"name" => "CHOPIN Nicolas"
]
3 => array:1 [
"name" => "THIERY Alexandre H."
]
]
"ouvrage" => "Proceedings of the 40th International Conference on Machine Learning, PMLR 202:5904-5923"
"keywords" => array:10 [
0 => "Computational Doob h-transforms"
1 => "Online filtering"
2 => "Discretely observed diffusions"
3 => "Machine learning"
4 => "Stochastic processes"
5 => "Bayesian filtering"
6 => "State estimation"
7 => "Hidden Markov models"
8 => "Sequential Monte Carlo methods"
9 => "Probabilistic inference"
]
"updatedAt" => "2024-10-31 13:51:19"
"publicationUrl" => "https://proceedings.mlr.press/v202/"
"publicationInfo" => array:3 [
"pages" => null
"volume" => "202"
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => "Royaume-Uni"
"en" => "United Kingdom"
]
"abstract" => array:2 [
"fr" => "This paper is concerned with online filtering of discretely observed nonlinear diffusion processes. Our approach is based on the fully adapted auxiliary particle filter, which involves Doob’s htransforms that are typically intractable. We propose a computational framework to approximate these h-transforms by solving the underlying backward Kolmogorov equations using nonlinear Feynman-Kac formulas and neural networks. The methodology allows one to train a locally optimal particle filter prior to the data-assimilation procedure. Numerical experiments illustrate that the proposed approach can be orders of magnitude more efficient than state-of-the-art particle f ilters in the regime of highly informative observations, when the observations are extreme under the model, or if the state dimension is large."
"en" => "This paper is concerned with online filtering of discretely observed nonlinear diffusion processes. Our approach is based on the fully adapted auxiliary particle filter, which involves Doob’s htransforms that are typically intractable. We propose a computational framework to approximate these h-transforms by solving the underlying backward Kolmogorov equations using nonlinear Feynman-Kac formulas and neural networks. The methodology allows one to train a locally optimal particle filter prior to the data-assimilation procedure. Numerical experiments illustrate that the proposed approach can be orders of magnitude more efficient than state-of-the-art particle f ilters in the regime of highly informative observations, when the observations are extreme under the model, or if the state dimension is large."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
46 => Essec\Faculty\Model\Contribution {#2307
#_index: "academ_contributions"
#_id: "14233"
#_source: array:18 [
"id" => "14233"
"slug" => "news-indices-on-country-fundamentals"
"yearMonth" => "2023-09"
"year" => "2023"
"title" => "News indices on country fundamentals"
"description" => "FULOP, A. et KOCSIS, Z. (2023). News indices on country fundamentals. <i>Journal of Banking & Finance</i>, 154, pp. 106951."
"authors" => array:2 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "KOCSIS Zalan"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Financial media"
1 => "Textual data"
2 => "Regular expressions"
3 => "Sequential Monte Carlo"
4 => "Sovereign credit risk"
]
"updatedAt" => "2023-08-30 09:10:25"
"publicationUrl" => "https://doi.org/10.1016/j.jbankfin.2023.106951"
"publicationInfo" => array:3 [
"pages" => "106951"
"volume" => "154"
"number" => ""
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We propose a novel method to extract textual information about macro fundamentals. The method has two pillars, a set of pre-defined regular expressions and a Bayesian feature selection model. We apply our technique to a 2007–2022 Reuters news corpus from Factiva to create news indices of country fundamentals. Compared to several literature alternatives, we find our method to better identify and discriminate among fundamentals based on both (i) observed economic surprises (macro announcements compared to Bloomberg survey expectations) and (ii) labels on a manually classified test sample. In an application that investigates the determinants of sovereign credit spreads, we show that including our news indices next to traditional macro variables significantly raises the explanatory power attributed to fundamentals. We also show that part of the covariance between sovereign spreads and the VIX and US high yield indices is related to global fundamentals captured by our indices."
"en" => "We propose a novel method to extract textual information about macro fundamentals. The method has two pillars, a set of pre-defined regular expressions and a Bayesian feature selection model. We apply our technique to a 2007–2022 Reuters news corpus from Factiva to create news indices of country fundamentals. Compared to several literature alternatives, we find our method to better identify and discriminate among fundamentals based on both (i) observed economic surprises (macro announcements compared to Bloomberg survey expectations) and (ii) labels on a manually classified test sample. In an application that investigates the determinants of sovereign credit spreads, we show that including our news indices next to traditional macro variables significantly raises the explanatory power attributed to fundamentals. We also show that part of the covariance between sovereign spreads and the VIX and US high yield indices is related to global fundamentals captured by our indices."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
47 => Essec\Faculty\Model\Contribution {#2308
#_index: "academ_contributions"
#_id: "14840"
#_source: array:18 [
"id" => "14840"
"slug" => "estimating-and-testing-long-run-risk-models-international-evidence"
"yearMonth" => "2024-08"
"year" => "2024"
"title" => "Estimating and Testing Long-Run Risk Models: International Evidence"
"description" => "FULOP, A., LI, J., LIU, H. et YAN, C. (2024). Estimating and Testing Long-Run Risk Models: International Evidence. <i>Management Science</i>, In press."
"authors" => array:4 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:1 [
"name" => "LI Junye"
]
2 => array:1 [
"name" => "LIU Hening"
]
3 => array:1 [
"name" => "YAN Cheng"
]
]
"ouvrage" => ""
"keywords" => array:1 [
0 => "Long-Run Risk Models"
]
"updatedAt" => "2024-10-31 13:51:19"
"publicationUrl" => "https://doi.org/10.1287/mnsc.2022.04054"
"publicationInfo" => array:3 [
"pages" => null
"volume" => "In press"
"number" => null
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We estimate and test long-run risk models using international macroeconomic and financial data. The benchmark model features a representative agent who has recursive preferences with a time preference shock, a persistent component in expected consumption growth, and stochastic volatility in fundamentals characterized by an autoregressive gamma process. We construct a comprehensive data set with quarterly frequency for 10 developed countries and employ an efficient likelihood-based Bayesian method that exploits up-to-date sequential Monte Carlo methods to make full econometric inference. Our empirical findings provide international evidence in support of long-run risks, time-varying preference shocks, and countercyclicality of the stochastic discount factor. We show the existence of a global long-run consumption factor driving equity returns across individual countries."
"en" => "We estimate and test long-run risk models using international macroeconomic and financial data. The benchmark model features a representative agent who has recursive preferences with a time preference shock, a persistent component in expected consumption growth, and stochastic volatility in fundamentals characterized by an autoregressive gamma process. We construct a comprehensive data set with quarterly frequency for 10 developed countries and employ an efficient likelihood-based Bayesian method that exploits up-to-date sequential Monte Carlo methods to make full econometric inference. Our empirical findings provide international evidence in support of long-run risks, time-varying preference shocks, and countercyclicality of the stochastic discount factor. We show the existence of a global long-run consumption factor driving equity returns across individual countries."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
48 => Essec\Faculty\Model\Contribution {#2309
#_index: "academ_contributions"
#_id: "14942"
#_source: array:18 [
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"slug" => "computational-doobs-h-transforms-for-online-filtering"
"yearMonth" => "2024-03"
"year" => "2024"
"title" => "Computational Doob's h-transforms for Online Filtering"
"description" => "CHOPIN, N., FULOP, A., HENG, J. et THIERY, A.H. (2024). Computational Doob's h-transforms for Online Filtering. Dans: 6th Workshop on Sequential Monte Carlo Methods 2024. Edinburgh."
"authors" => array:4 [
0 => array:3 [
"name" => "FULOP Andras"
"bid" => "B00072302"
"slug" => "fulop-andras"
]
1 => array:3 [
"name" => "HENG Jeremy"
"bid" => "B00760223"
"slug" => "heng-jeremy"
]
2 => array:1 [
"name" => "CHOPIN Nicolas"
]
3 => array:1 [
"name" => "THIERY Alexandre H."
]
]
"ouvrage" => "6th Workshop on Sequential Monte Carlo Methods 2024"
"keywords" => []
"updatedAt" => "2024-07-16 18:56:37"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => ""
"volume" => ""
"number" => ""
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => ""
"en" => ""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-22T13:21:43.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.6480036
+"parent": null
}
]
"avatar" => "https://faculty.essec.edu/wp-content/uploads/avatars/B00072302.jpg"
"contributionCounts" => 49
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1 => "<a href="https://scholar.google.com/citations?user=9S-HHKUAAAAJ" target="_blank">Google scholar</a>"
]
"docTitle" => "Andras FULOP"
"docSubtitle" => "Professor"
"docDescription" => "Department: Finance<br>Campus de Cergy"
"docType" => "cv"
"docPreview" => "<img src="https://faculty.essec.edu/wp-content/uploads/avatars/B00072302.jpg"><span><span>Andras FULOP</span><span>B00072302</span></span>"
"academ_cv_info" => ""
]
#_index: "academ_cv"
+lang: "en"
+"_type": "_doc"
+"_score": 5.0369525
+"parent": null
}
