Details
| Original language | English |
|---|---|
| Article number | 101476 |
| Journal | Journal of Behavioral and Experimental Economics |
| Volume | 84 |
| Early online date | 4 Oct 2019 |
| Publication status | Published - Feb 2020 |
Abstract
In this paper, we link stock market investors’ probability distortion to future economic growth. The empirical challenge is to quantify the optimality of today's decision making to test for its impact on future economic growth. Fortunately, risk preferences can be estimated from stock markets. Using monthly aggregate stock prices from 1926 to 2015, we estimate risk preferences via an asset pricing model with Cumulative Prospect Theory (CPT) agents and distill a recently proposed probability distortion index. This index negatively predicts GDP growth in-sample and out-of-sample. Predictability is stronger and more reliable over longer horizons. Our results suggest that distorted asset prices may lead to significant welfare losses.
Keywords
- Economic growth, Probability distortion, Suboptimal decision making
ASJC Scopus subject areas
- Psychology(all)
- Applied Psychology
- Economics, Econometrics and Finance(all)
- Economics and Econometrics
Research Area (based on ÖFOS 2012)
- SOCIAL SCIENCES
- Economics
- Economics
- Public finance
Sustainable Development Goals
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In: Journal of Behavioral and Experimental Economics, Vol. 84, 101476, 02.2020.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Probability distortion, asset prices, and economic growth
AU - Dierkes, Maik
AU - Germer, Stephan
AU - Sejdiu, Vulnet
N1 - Funding information: We are particularly grateful to the Dr. Werner Jackstädt Foundation for financial support. We thank an anonymous referee, Stefan Trautmann (the Editor), Florian Weigert, Giuliano Curatola, Ivalina Kalcheva, participants at the Swiss Finance Conference 2016, the German Finance Association Annual Meeting 2016, the Research in Behavioral Finance Conference 2016, and the Financial Management Association Annual Meeting 2018 for valuable comments and suggestions.
PY - 2020/2
Y1 - 2020/2
N2 - In this paper, we link stock market investors’ probability distortion to future economic growth. The empirical challenge is to quantify the optimality of today's decision making to test for its impact on future economic growth. Fortunately, risk preferences can be estimated from stock markets. Using monthly aggregate stock prices from 1926 to 2015, we estimate risk preferences via an asset pricing model with Cumulative Prospect Theory (CPT) agents and distill a recently proposed probability distortion index. This index negatively predicts GDP growth in-sample and out-of-sample. Predictability is stronger and more reliable over longer horizons. Our results suggest that distorted asset prices may lead to significant welfare losses.
AB - In this paper, we link stock market investors’ probability distortion to future economic growth. The empirical challenge is to quantify the optimality of today's decision making to test for its impact on future economic growth. Fortunately, risk preferences can be estimated from stock markets. Using monthly aggregate stock prices from 1926 to 2015, we estimate risk preferences via an asset pricing model with Cumulative Prospect Theory (CPT) agents and distill a recently proposed probability distortion index. This index negatively predicts GDP growth in-sample and out-of-sample. Predictability is stronger and more reliable over longer horizons. Our results suggest that distorted asset prices may lead to significant welfare losses.
KW - Economic growth
KW - Probability distortion
KW - Suboptimal decision making
UR - http://www.scopus.com/inward/record.url?scp=85076114622&partnerID=8YFLogxK
U2 - 10.1016/j.socec.2019.101476
DO - 10.1016/j.socec.2019.101476
M3 - Article
AN - SCOPUS:85076114622
VL - 84
JO - Journal of Behavioral and Experimental Economics
JF - Journal of Behavioral and Experimental Economics
SN - 2214-8043
M1 - 101476
ER -