Can competition between forecasters stabilize asset prices in learning to forecast experiments?

We conduct a learning to forecast asset pricing experiment that assumes that financial advisors and professional forecasters attract more investors when their price forecasts are more accurate. The competition between forecasters implies that the impact of their forecasts on realized market prices evolves endogenously. We investigate how these endogenous impacts affect price dispersion and mispricing relative to the fundamental price. Our results show that the effect of endogenous impacts depends on (i) the type of market dynamics (stable/unstable) and (ii) the sensitivity of impacts with respect to forecast accuracy (low/high). Compared to the baseline treatment, where impacts are constant and independent of forecast accuracy, price dispersion and mispricing is somewhat lower in stable markets when impacts are moderately sensitive to forecast accuracy. In contrast, impacts that are strongly sensitive to forecast accuracy can further destabilize unstable markets, amplifying price dispersion and mispricing.