We develop a simple agent-based financial market model in which speculators' market entry decisions are subject to herding behavior and market risk. Moreover, speculators' orders depend on price trends, market misalignments and fundamental news. Using a mix of analytical and numerical tools, we...

Using the Heterogeneous Agent Model framework, we incorporate an extension based on Prospect Theory into a popular agent-based asset pricing model. The extension covers the phenomenon of loss aversion manifested in risk aversion and asymmetric treatment of gains and losses. Using Monte Carlo...

Using the Heterogeneous Agent Model framework, we incorporate an extension based on Prospect Theory into a popular agent-based asset pricing model. The extension covers the phenomenon of loss aversion manifested in risk aversion and asymmetric treatment of gains and losses. Using Monte Carlo...

We propose an empirically motivated financial market model in which speculators rely on trend-following, contrarian and fundamental trading rules to determine their orders. Speculators' probabilistic rule-selection behavior - the only type of randomness in our model - depends on past and future...

Within the seminal asset-pricing model by Brock and Hommes (1998), heterogeneous boundedly rational agents choose between a fixed number of expectation rules to forecast asset prices. However, agents' heterogeneity is limited in the sense that they typically switch between a representative...

We develop a simple agent-based financial market model in which heterogeneous speculators apply technical and fundamental analysis to trade in two different stock markets. Speculators’ strategy/market selections are repeated at each time step and depend on predisposition effects, herding...

We designed four observational learning experiments to identify the key channels that, along with Bayes-rational inferences, drive herd behavior. In Experiment 1, unobserved, whose actions remain private, learn from the public actions made in turn by subjects endowed with private signals of...

Due to data limitations and the absence of testable, model-based predictions, theory and evidence on herd behavior are only loosely connected. This paper contributes towards closing this gap in the herding literature. We use numerical simulations of a herd model to derive new, theory-based...