Essec\Faculty\Model\Contribution {#2216
#_index: "academ_contributions"
#_id: "14091"
#_source: array:26 [
"id" => "14091"
"slug" => "fast-filtering-with-large-option-panels-implications-for-asset-pricing"
"yearMonth" => "2023-06"
"year" => "2023"
"title" => "Fast Filtering with Large Option Panels: Implications for Asset Pricing"
"description" => "DUFAYS, A., JACOBS, K., LIU, Y. et ROMBOUTS, J. (2023). Fast Filtering with Large Option Panels: Implications for Asset Pricing. <i>Journal of Financial and Quantitative Analysis</i>, In press, pp. 1-56."
"authors" => array:4 [
0 => array:3 [
"name" => "ROMBOUTS Jeroen"
"bid" => "B00469813"
"slug" => "rombouts-jeroen"
]
1 => array:1 [
"name" => "DUFAYS Arnaud"
]
2 => array:1 [
"name" => "JACOBS Kris"
]
3 => array:1 [
"name" => "LIU Yuguo"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Option Valuation"
1 => "Particle MCMC"
2 => "Posterior Density"
3 => "Option Panels"
4 => "Risk Premia"
]
"updatedAt" => "2023-06-28 16:47:11"
"publicationUrl" => "https://doi.org/10.1017/S0022109023000753"
"publicationInfo" => array:3 [
"pages" => "1-56"
"volume" => "In press"
"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" => "The cross-section of options holds great promise for identifying return distributions and risk premia, but estimating dynamic option valuation models with latent state variables is challenging when using large option panels. We propose a particle MCMC framework with a novel filtering approach and illustrate our method by estimating workhorse index option pricing models. Estimates of the variance risk premium, variance mean reversion, and higher moments differ from the literature. We show that these differences are due to the composition of the option sample. Restrictions on the option sample's maturity dimension have the strongest impact on parameter inference and option fit in these models."
"en" => "The cross-section of options holds great promise for identifying return distributions and risk premia, but estimating dynamic option valuation models with latent state variables is challenging when using large option panels. We propose a particle MCMC framework with a novel filtering approach and illustrate our method by estimating workhorse index option pricing models. Estimates of the variance risk premium, variance mean reversion, and higher moments differ from the literature. We show that these differences are due to the composition of the option sample. Restrictions on the option sample's maturity dimension have the strongest impact on parameter inference and option fit in these models."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-12-03T16:21:42.000Z"
"docTitle" => "Fast Filtering with Large Option Panels: Implications for Asset Pricing"
"docSurtitle" => "Journal articles"
"authorNames" => "<a href="/cv/rombouts-jeroen">ROMBOUTS Jeroen</a>, DUFAYS Arnaud, JACOBS Kris, LIU Yuguo"
"docDescription" => "<span class="document-property-authors">ROMBOUTS Jeroen, DUFAYS Arnaud, JACOBS Kris, LIU Yuguo</span><br><span class="document-property-authors_fields">Information Systems, Data Analytics and Operations</span> | <span class="document-property-year">2023</span>"
"keywordList" => "<a href="#">Option Valuation</a>, <a href="#">Particle MCMC</a>, <a href="#">Posterior Density</a>, <a href="#">Option Panels</a>, <a href="#">Risk Premia</a>"
"docPreview" => "<b>Fast Filtering with Large Option Panels: Implications for Asset Pricing</b><br><span>2023-06 | Journal articles </span>"
"docType" => "research"
"publicationLink" => "<a href="https://doi.org/10.1017/S0022109023000753" target="_blank">Fast Filtering with Large Option Panels: Implications for Asset Pricing</a>"
]
+lang: "en"
+"_type": "_doc"
+"_score": 8.35097
+"parent": null
}
