Repository logo
 
Publication

Neural network pricing of american put options

dc.contributor.authorGaspar, Raquel
dc.contributor.authorLopes, Sara D.
dc.contributor.authorSequeira, Bernardo
dc.date.accessioned2020-04-14T14:57:05Z
dc.date.available2020-04-14T14:57:05Z
dc.date.issued2020-04
dc.description.abstractIn this paper we use neural networks (NN), a machine learning method, to price American put options. We propose two distinct NN models – a simple one and a more complex one. The performance of two NN models is compared to the popular Least-Square Monte Carlo Method (LSM). This study relies on market American put option prices, with four large US companies as underlying – Bank of America Corp (BAC), General Motors (GM), Coca-Cola Company (KO) and Procter and Gamble Company (PG). Our dataset includes all options traded from December 2018 to March 2019. All methods show a good accuracy, however, once calibrated, NNs do better in terms of execution time and Root Mean Square Error (RMSE). Although on average both NN models perform better than LSM, the simpler model (NN model 1) performs quite close to LSM. On the other hand our NN model 2 substantially outperforms the other models, having a RMSE ca. 40% lower than that of the LSM. The lower RMSE is consistent across all companies, strike levels and maturities.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationGaspar, Raquel, Sara D. Lopes and Bernardo Sequeira (2020). "Neural network pricing of american put options". Instituto Superior de Economia e Gestão – REM Working paper nº 0122 – 2020pt_PT
dc.identifier.issn2184-108X
dc.identifier.urihttp://hdl.handle.net/10400.5/20015
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherISEG - REM - Research in Economics and Mathematicspt_PT
dc.relationResearch in Economics and Mathematics
dc.relation.ispartofseriesREM Working paper;nº 0122 – 2020
dc.relation.publisherversionhttps://rem.rc.iseg.ulisboa.pt/wps/pt_PT
dc.subjectMachine Learningpt_PT
dc.subjectNeural Networkspt_PT
dc.subjectAmerican Put Optionspt_PT
dc.subjectLeast-Square Monte Carlopt_PT
dc.titleNeural network pricing of american put optionspt_PT
dc.typeworking paper
dspace.entity.typePublication
oaire.awardTitleResearch in Economics and Mathematics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05069%2F2020/PT
oaire.fundingStream6817 - DCRRNI ID
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeworkingPaperpt_PT
relation.isProjectOfPublication776d1ee1-e5e8-4d3e-9ec5-a8e9decada99
relation.isProjectOfPublication.latestForDiscovery776d1ee1-e5e8-4d3e-9ec5-a8e9decada99

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
REM_WP_0122_2020.pdf
Size:
2.22 MB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: