Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/64514
Authors: 
Feldman, Todd
Friedman, Daniel
Year of Publication: 
2008
Series/Report no.: 
Working Papers, UC Santa Cruz Economics Department 645
Abstract: 
We introduce human traders into an agent based financial market simulation prone to bubbles and crashes. We find that human traders earn lower profits overall than do the simulated agents (robots) but earn higher profits in the most crash-intensive periods. Inexperienced human traders tend to destabilize the smaller (10 trader) markets, but otherwise they have little impact on bubbles and crashes in larger (30 trader) markets and when they are more experienced. Humans' buying and selling choices respond to the payoff gradient in a manner similar to the robot algorithm. Likewise, following losses, humans' choices shift towards faster selling. There are problems in properly identifying fundamentalist and trend-following strategies in our data.
Subjects: 
financial markets
agent-based models
experimental economics
JEL: 
C63
C91
D53
G10
Document Type: 
Working Paper

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