Logo do repositório
 
Publicação

Conformal prediction of option prices

dc.contributor.authorBastos, João A.
dc.date.accessioned2023-12-28T15:19:45Z
dc.date.available2023-12-28T15:19:45Z
dc.date.issued2023-12
dc.description.abstractThe uncertainty associated with option price predictions has largely been overlooked in the literature. This paper aims to fill this gap by quantifying such uncertainty using conformal prediction. Conformal prediction is a model-agnostic procedure that constructs prediction intervals, ensuring valid coverage in finite samples without relying on distributional assumptions. Through the simulation of synthetic option prices, we find that conformal prediction generates prediction intervals for gradient boosting machines with an empirical coverage close to the nominal level. Conversely, non-conformal prediction intervals exhibit empirical coverage levels that fall short of the nominal target. In other words, they fail to contain the actual option price more frequently than expected for a given coverage level. As anticipated, we also observe a decrease in the width of prediction intervals as the size of the training data increases. However, we uncover significant variations in the width of these intervals across different options. Specifically, out-of-the-money options and those with a short time-to-maturity exhibit relatively wider prediction intervals. Then, we perform an empirical study using American call and put options on individual stocks. We find that the empirical results replicate those obtained in the simulation experiment.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationBastos, João A. (2023). "Conformal prediction of option prices". REM Working paper series, nº 0304/2023pt_PT
dc.identifier.issn2184-108X
dc.identifier.urihttp://hdl.handle.net/10400.5/29690
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherISEG - REM - Research in Economics and Mathematicspt_PT
dc.relation.ispartofseriesREM Working paper series;nº 0304/2023
dc.relation.publisherversionhttps://rem.rc.iseg.ulisboa.pt/wps/pdf/REM_WP_0304_2023.pdfpt_PT
dc.subjectConformal predictionpt_PT
dc.subjectMachine learningpt_PT
dc.subjectOption pricept_PT
dc.subjectQuantile regressionpt_PT
dc.subjectAmerican optionspt_PT
dc.titleConformal prediction of option pricespt_PT
dc.typeworking paper
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typeworkingPaperpt_PT

Ficheiros

Principais
A mostrar 1 - 1 de 1
A carregar...
Miniatura
Nome:
REM_WP_0304_2023.pdf
Tamanho:
1.41 MB
Formato:
Adobe Portable Document Format
Licença
A mostrar 1 - 1 de 1
Miniatura indisponível
Nome:
license.txt
Tamanho:
1.71 KB
Formato:
Item-specific license agreed upon to submission
Descrição: