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We synthesize the distribution extracted from a panel of option prices and exploit linear relationships between risk\u2010neutral cumulants and latent factors within the continuous time affine stochastic volatility framework. We find that fitting the Andersen et al.\u00a0(<jats:italic>Journal of Financial Economics<\/jats:italic>, 2015, <jats:italic>117<\/jats:italic>(3), 558\u2013584) option valuation model to risk\u2010neutral moments captures the bulk of the information in option prices. Our estimation strategy is effective, easy to implement, and robust, as it allows for a direct linear filtering of the latent factors and a quasi\u2010maximum likelihood estimation of model parameters. From a practical perspective, employing risk\u2010neutral moments instead of option prices also helps circumvent several sources of numerical errors and substantially lessens the computational burden inherent in working with a large panel of option contracts.<\/jats:p>","DOI":"10.1002\/jae.2630","type":"journal-article","created":{"date-parts":[[2018,5,28]],"date-time":"2018-05-28T10:35:49Z","timestamp":1527503749000},"page":"1007-1025","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Risk\u2010neutral moment\u2010based estimation of affine option pricing models"],"prefix":"10.1002","volume":"33","author":[{"given":"Bruno","family":"Feunou","sequence":"first","affiliation":[{"name":"Bank of Canada  Ottawa Ontario Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"C\u00e9dric","family":"Okou","sequence":"additional","affiliation":[{"name":"Department of Finance Universit\u00e9 du Qu\u00e9bec 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