Predicting loss aversion behavior with machine-learning methods.
This paper proposes to forecast an important cognitive phenomenon called the Loss Aversion Bias via Hybrid Machine Learning Models. One of the unique aspects of this study is using the reaction time (milliseconds), psychological factors (self-confidence scale, Beck’s hopelessness scale, loss-aversio...
| Published in: | Humanities & Social Sciences Communications pp. 1 - 15 |
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| Main Authors: | , , , , |
| Format: | Article |
| Published: |
Springer Nature
4/27/2023
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=163476146&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 163476146 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: MVR0 jtl: Humanities & Social Sciences Communications maglogo: N pubinfo: dt: 4/27/2023 pid: 237 pub: Springer Nature artinfo: ui: 163476146 10.1057/s41599-023-01620-2 ppf: 1 ppct: 14 formats: tig: atl: Predicting loss aversion behavior with machine-learning methods. aug: au: Saltık, Ömür Rehman, Wasim ul Söyü, Rıdvan Değirmen, Süleyman Şengönül, Ahmet affil: Department of Economics, Konya Food and Agriculture University, Konya, Turkey Department of Business Administration, University of Punjab, Gujranwala Campus, Gujranwala, Pakistan Department of Computer Engineering, Toros University, Mersin, Turkey Department of Econometrics, Sivas Cumhuriyet University, Sivas, Turkey sug: ab: This paper proposes to forecast an important cognitive phenomenon called the Loss Aversion Bias via Hybrid Machine Learning Models. One of the unique aspects of this study is using the reaction time (milliseconds), psychological factors (self-confidence scale, Beck’s hopelessness scale, loss-aversion), and personality traits (financial literacy scales, socio-demographic features) as features in classification and regression methods. We found that Random Forest was superior to other algorithms, and when the positive spread ratio (between gain and loss) converged to default loss aversion level, decision-makers minimize their decision duration while gambling, we named this phenomenon as “irresistible impulse of gambling”. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2023 holdings: @attributes: islocal: N |
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