We study the well-known multiplicative Lognormal cascade process in which the multiplication of Gaussian and Lognormally distributed random variables yields time series with intermittent bursts of activity. Due to the non-stationarity of this process and the combinatorial nature of such a...

We study the well-known multiplicative Lognormal cascade process in which the multiplication of Gaussian and Lognormally distributed random variables yields time series with intermittent bursts of activity. Due to the non-stationarity of this process and the combinatorial nature of such a...

We use weekly survey data on short-term and medium-term sentiment of German investors to estimate the parameters of a stochastic model of opinion dynamics. The bivariate nature of our data set also allows us to explore the interaction between the two hypothesized opinion formation processes,...

We examine the performance of volatility models that incorporate features such as long (short) memory, regime-switching and multifractality along with two competing distributional assumptions of the error component, i.e. Normal vs Student-t. Our precise contribution is twofold. First, we...

In this paper we consider daily financial data from various sources (stock market indices, foreign exchange rates and bonds) and analyze their multi-scaling properties by estimating the parameters of a Markov-switching multifractal model (MSM) with Lognormal volatility components. In order to...

We consider the current bipartite graph of German corporate boards and identify a small core of directors who are highly central in the entire network while being densely connected among themselves. To identify the core, we compare the actual number of board memberships to a random benchmark,...

Models with heterogeneous interacting agents explain macro phenomena through interactions at the micro level. We propose genetic algorithms as a model for individual expectations to explain aggregate market phenomena. The model explains all stylized facts observed in aggregate price fluctuations...

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...

This paper develops a methodology for estimating the parameters of dynamic opinion or expectation formation processes with social interactions. We study a simple stochastic framework of a collective process of opinion formation by a group of agents who face a binary decision problem. The...