Essec\Faculty\Model\Contribution {#2233
#_index: "academ_contributions"
#_id: "10836"
#_source: array:26 [
"id" => "10836"
"slug" => "variance-swap-payoffs-risk-premia-and-extreme-market-conditions"
"yearMonth" => "2020-01"
"year" => "2020"
"title" => "Variance swap payoffs, risk premia and extreme market conditions"
"description" => "ROMBOUTS, J., STENTOFT, L. et VIOLANTE, F. (2020). Variance swap payoffs, risk premia and extreme market conditions. <i>Econometrics and Statistics</i>, 13, pp. 106-124."
"authors" => array:3 [
0 => array:3 [
"name" => "ROMBOUTS Jeroen"
"bid" => "B00469813"
"slug" => "rombouts-jeroen"
]
1 => array:1 [
"name" => "STENTOFT L."
]
2 => array:1 [
"name" => "VIOLANTE Francesco"
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Variance risk premium"
1 => "Variance swaps"
2 => "Return predictability"
3 => "Factor model"
4 => "Kalman filter"
5 => "CAPM"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://doi.org/10.1016/j.ecosta.2019.05.003"
"publicationInfo" => array:3 [
"pages" => "106-124"
"volume" => "13"
"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" => "The variance risk premium (VRP) is estimated directly from synthetic variance swap payoffs. Since variance swap payoffs are highly volatile, the VRP is extracted by using signal extraction techniques based on a state-space representation of the model in combination with a simple economic constraint. The proposed approach, only requiring option implied volatilities and daily returns for the underlying asset, provides measurement error free estimates of the part of the VRP related to normal market conditions, and allows constructing variables indicating agents’ expectations under extreme market conditions. The latter variables and the VRP generate different return predictability on the major US indices. A factor model is proposed to extract a market VRP which turns out to be priced when considering Fama and French portfolios."
"en" => "The variance risk premium (VRP) is estimated directly from synthetic variance swap payoffs. Since variance swap payoffs are highly volatile, the VRP is extracted by using signal extraction techniques based on a state-space representation of the model in combination with a simple economic constraint. The proposed approach, only requiring option implied volatilities and daily returns for the underlying asset, provides measurement error free estimates of the part of the VRP related to normal market conditions, and allows constructing variables indicating agents’ expectations under extreme market conditions. The latter variables and the VRP generate different return predictability on the major US indices. A factor model is proposed to extract a market VRP which turns out to be priced when considering Fama and French portfolios."
]
"authors_fields" => array:2 [
"fr" => "Finance"
"en" => "Finance"
]
"indexedAt" => "2024-12-21T12:21:50.000Z"
"docTitle" => "Variance swap payoffs, risk premia and extreme market conditions"
"docSurtitle" => "Articles"
"authorNames" => "<a href="/cv/rombouts-jeroen">ROMBOUTS Jeroen</a>, STENTOFT L., VIOLANTE Francesco"
"docDescription" => "<span class="document-property-authors">ROMBOUTS Jeroen, STENTOFT L., VIOLANTE Francesco</span><br><span class="document-property-authors_fields">Finance</span> | <span class="document-property-year">2020</span>"
"keywordList" => "<a href="#">Variance risk premium</a>, <a href="#">Variance swaps</a>, <a href="#">Return predictability</a>, <a href="#">Factor model</a>, <a href="#">Kalman filter</a>, <a href="#">CAPM</a>"
"docPreview" => "<b>Variance swap payoffs, risk premia and extreme market conditions</b><br><span>2020-01 | Articles </span>"
"docType" => "research"
"publicationLink" => "<a href="https://doi.org/10.1016/j.ecosta.2019.05.003" target="_blank">Variance swap payoffs, risk premia and extreme market conditions</a>"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 8.394928
+"parent": null
}