The use of fundamentalist traders in the stock market models is problematic since fundamental values in the real world are unknown. Yet, in the literature to date, fundamentalists are often required to replicate key stylized facts. The authors present an agent-based model of the stock market in...

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...

In dynamic financial markets the stochastic supply of risky assets has a significant informational role. Contrary to static models, where it acts as “noise,” in dynamic markets stochastic supply contains information about risk premiums. Acquiring private dividend information helps investors...

The paper studies the emergence of contrarian behavior in information networks in an asset pricing market. Financial traders coordinate on similar behavior, but have heterogeneous price expectations and are influenced by friends. According to a popular belief, they are prone to herding. However,...

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...

This paper examines the main drawbacks of technical analysis. Although this is widely used by practitioners, from an academic perspective it can only be seen as a form of "voodoo finance". In particular, it runs into the following pitfalls: Subjectivity; Doubtful assumptions; Unjustified...

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 propose a simple agent-based computational model in which speculators' trading behavior may cause bubbles and crashes, excess volatility, serially uncorrelated returns, fat-tailed return distributions and volatility clustering, thereby replicating five important stylized facts of stock...

We propose a parsimonious agent-based model of a financial market at the intra-day time scale that is able to jointly reproduce many of the empirically validated stylised facts. These include properties related to returns (leptokurtosis, absence of linear autocorrelation, volatility clustering),...

Recent survey evidence suggests that investors form beliefs about future stock returns by predominantly extrapolating their own experience: They overweight returns they have personally experienced while underweighting returns from earlier years and consequently expect high (low) stock market...