Humans, Robots and Market Crashes: A Laboratory Study ∗
- Author(s): Feldman, Todd
- Friedman, Daniel
- et al.
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) mar- kets, 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.