Research

Publications

Can Peo­ple Learn About ‘Black Swans’? Exper­i­men­tal Evi­dence (code|data)

– Review of Finan­cial Stud­ies, vol 31 issue 12, Decem­ber 2018

Elise Payzan-LeNestour

 

Vari­ance After-Effects Bias Risk Per­cep­tion in Humans  (code|data)

– Cur­rent Biol­o­gy, vol 26, June 2016

Media cov­er­age: Syd­ney Morn­ing Her­ald, Uniken, Busi­ness Think, The Australian Finan­cial Review

Elise Payzan-LeNestour, Bernard Balleine, Tony Berrada & Joel Pearson

 

Learn­ing About Unsta­ble, Pub­licly Unob­serv­able Pay­offs (code|data)

 — Review of Finan­cial Stud­ies, vol 28 issue 7, June 2015

Elise Payzan-LeNestour and Peter Bossaerts

 

The Neur­al Rep­re­sen­ta­tion of Unex­pect­ed Uncer­tain­ty Dur­ing Val­ue-Based
Deci­sion Mak­ing

 — Neu­ron, vol 79 issue 1, 191 – 201, 2013

Media cov­er­age: ABC TV The Busi­ness, Uniken, Busi­ness Think, Syd­ney Morn­ing Her­ald

Elise Payzan-LeNestour, Simon Dunne, Peter Bossaerts & John O’Doherty

 

Do Not Bet On The Unknown Ver­sus Try To Find Out More: Esti­ma­tion Uncer­tain­ty And ”Unex­pect­ed Uncer­tain­ty” Both Mod­u­late Explo­ration (Open Access link)

 — Fron­tiers in Neu­ro­science 6:150, 2012

Elise Payzan-LeNestour and Peter Bossaerts

 

Risk, Unex­pect­ed Uncer­tain­ty, and Esti­ma­tion Uncer­tain­ty: Bayesian Learn­ing in Unsta­ble Set­tings (Open Access link)

 — PLoS Com­pu­ta­tion­al Biol­o­gy 7(1), 2011

Elise Payzan-LeNestour and Peter Bossaerts

 

Current Working Papers

 

“Out­lier Blind­ness”: Effi­cient Cod­ing Gen­er­ates an Inabil­i­ty to Rep­re­sent Extreme Val­ues (link)

– August 2020 (R&R, The Jour­nal of Finan­cial Eco­nom­ics)

Pre­sent­ed at the AFA 2019

Joint with MICHAEL WOODFORD

 

The “Water­fall Illu­sion” in the Finan­cial Mar­kets: Risk Per­cep­tion Is Dis­tort­ed after Pri­or Expo­sure to Extreme Risk (link)

– July 2020 (under review)

Select­ed for the NBER Sum­mer Insti­tute 2015 (Eco­nom­ic Fluc­tu­a­tions Behavioral/Macro). Best Paper Award 2017, Behav­iour­al Finance and Cap­i­tal Mar­kets Con­fer­ence, spon­sored by Cap­i­tal Mar­kets CRC. WINNER Best Paper Award 2019, “Mea­sure­ment of Traders in the Field”, spon­sored by P&K Pühringer Foun­da­tion and cere­neo

Joint with LIONNEL PRADIER AND TALIS PUTNINS

 

Friend or Foe: The Influ­ence of Ambi­ent Sound on Risk Per­cep­tion^NEW (link)

– August 2020 (under review)

Joint with BERNARD BALLEINE, JAMES DORAN, GIDI NAVE AND LIONNEL PRADIER

 

Crav­ing for Mon­ey? Empir­i­cal Evi­dence from the Lab­o­ra­to­ry and the Field^NEW (link)

– August 2020 (under review)

Joint with JAMES DORAN

 

Work in Progress

 

The Neur­al Sub­strates of the “Pick­ing Pen­nies Bias”

Joint with GIUSEPPE UGAZIO and NINA MARIE SOOTER

 

Involve­ment of the Mesolim­bic DA path­way in the “Pick­ing Penies Bias”: Genet­ic Study

Joint with MICHAEL FRANK, MATT NASSAR and MEHDI ADIBI

 

Build­ing “super­fore­cast­ing” skills in i.i.d envi­ron­ments? Lab­o­ra­to­ry exper­i­ments

Joint with TONY BERRADA

 

A Neu­roe­co­nom­ic inves­ti­ga­tion of crav­ing for high-stakes mon­e­tary gam­bles

Joint with BERNARD BALLEINE and MIKE LEPELLEY

 

“Atten­tion Util­i­ty The­o­ry”: Mod­el­ing deci­sion-mak­ing under risk using neu­ro­chem­istry

Joint with CHEW SOO HONG, RICHARD EBSTEIN, SERENELLA TOLOMEO AND ZHONG SONGFA

 

Using biofeed­back for improv­ing mar­ket effi­cien­cy: A proof-of-con­cept har­ness­ing the lat­est neu­ro­fi­nance, psy­chophys­i­ol­o­gy, and machine learn­ing sci­ences

Joint with BERNARD BALLEINE, JAMES DORAN, ANDREW LO AND NIGEL LOVELL

 

Previous working papers

 

Pick­ing Pen­nies (link|down­load data)

– Octo­ber 2019

Elise Payzan-LeNestour

Fooled by Ran­dom­ness? Finan­cial Deci­sion-Mak­ing under Tail Risk

 — Novem­ber 2015

Elise Payzan-LeNestour

Close Cousins? Bayesian ver­sus Adap­tive Learn­ing under Mod­el Uncer­tain­ty about Tail Risk

— Novem­ber 2016

Elise Payzan-LeNestour