This dissertation contains applications of agent-based financial market models and nonlinear econometric methods in financial economics. The first part deals with the analysis of the effectiveness of currency transaction taxes within financial market models with traders with heterogeneous...

High-frequency financial data are characterized by a set of ubiquitous statistical properties that prevail with surprising uniformity. While these 'stylized facts' have been well-known for decades, attempts at their behavioral explanation have remained scarce. However, recently a new branch of...

We use weekly survey data on short-term and medium-term sentiment of German investors in order to study the causal relationship between investors' mood and subsequent stock price changes. In contrast to extant literature for other countries, a tri-variate vector autoregression for short-run...

Based on a classical financial market model different model variants known from the literature are discussed and analyzed, each focussing on modeling financial markets as a nonlinear dynamic system by introducing the formation of (heterogeneous) beliefs about future asset prices into the model...

Simulations of agent-based models have shown that the stylized facts (unit-root, fat tails and volatility clustering) of financial markets have a possible explanation in the interactions among agents. However, the complexity, originating from the presence of non-linearity and interactions, often...

Maximum likelihood estimation of discretely observed diffusion processes is mostly hampered by the lack of a closed form solution of the transient density. It has recently been argued that a most generic remedy to this problem is the numerical solution of the pertinent Fokker-Planck (FP) or...