Loss aversion, overconfidence and their effects on a virtual stock exchange - Bertella, Mario A. [UNESP]; Silva, Jonathas N. [UNESP]; Stanley, H. Eugene (Elsevier, 2020)
This paper studies the effects of overconfidence and loss aversion in an artificial stock exchange. When we model only fundamentalists we find results that are consistent with homogeneous agent models. Adding 5% of chartists increases the stock return rate but also increases other variables, including volatility and kurtosis. We find that the inclusion of confidence in 5% of chartists raises the trading volume as empirical evidences corroborate and price volatility increases considerably. On the other hand, loss aversion in 5% of chartists substantially decreases the trading volume, although chartist traders now have a higher percentage of stocks in their portfolios, and a buy and hold strategy is adopted to mitigate losses.
Keywords: Agent-based models; Behavioral finance; Stock exchange