Cowboying Stock Market Herds with Robot Traders
Authored by Jaqueson K Galimberti, Nicolas Suhadolnik, Silva Sergio Da
Date Published: 2017
DOI: 10.1007/s10614-016-9591-2
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Mathematical description
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Abstract
One explanation for large stock market fluctuations is its tendency to
herd behavior. We put forward an agent-based model where instabilities
are the result of liquidity imbalances amplified by local interactions
through imitation, and calibrate the model to match some key statistics
of actual daily returns. We show that an ``aggregate market-maker{''}
type of liquidity injection is not successful in stabilizing prices due
to the complex nature of the stock market. To offset liquidity
shortages, we propose the use of locally triggered contrarian rules, and
show that these mechanisms are effective in preventing extreme returns
in our artificial stock market.
Tags
Agent-based model
behavior
herding
Expectations
Model
Business cycles
Financial-markets
Prices
Criticality
Robot trading
Financial regulation
Condorcets jury theorem
Economic-fluctuations
Correlated votes