Abstract
Investors often exhibit behavioral biases (e.g., loss aversion) that are
putatively underpinned by mechanisms supporting reinforcement learning
in the brain, which are largely evolutionarily conserved across
mammalian species. Although previous research has demonstrated that
rats, similar to humans, exhibit behavioral economic biases in certain
contexts, asset market contingencies have gone largely unexplored. Thus,
we developed an experimental “stock market”’ task in which cohorts of 4
rats drove asset prices up and down by selecting and subsequently
buying, selling, or holding “stocks” to earn sweet liquid reward.
Profits and losses were operationalized as reward volumes larger than
and smaller than a reference volume of reward, respectively. Following a
loss, rats moved more slowly to collect the reward and spent less time
licking at the reward spigot, indicative of lower motivation to approach
and “savor” a loss reward. Rats also tended to respond suboptimally
following a loss, which corresponded to an increase in risk-seeking
behavior characterized by a bias against the optimal “hold” option in
that context. Rats’ choice of the sell option demonstrated a robust
tendency toward realizing gains more quickly than losses, which is
characteristic of the “disposition effect” in human stock markets. Our
results indicate that rats exhibit behavioral biases similar to human
investors, emphasizing the suitability of the rat stock market model to
future work into the behavioral neuroscience of suboptimal financial
decision-making.
Original language | English |
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Pages (from-to) | 204-229 |
Journal | Journal of Neuroscience, Psychology, and Economics |
Volume | 13 |
Issue number | 4 |
DOIs | |
Publication status | Published - Dec 2020 |
Keywords
- Neuroeconomics
- Decision-making
- Behavioral finance
- Loss aversion
- Behavioral economics
- Animal learning
- Anchoring
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Bull, bear, or rat markets: Rat ‘stock market’ task reveals human-like behavioral biases (dataset)
Bowman, E. M. (Creator) & Hutunnen, A. (Creator), University of St Andrews, 13 Apr 2021
DOI: 10.17630/ce567640-f8d9-4599-a8ed-bcd9a50c1b2a
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