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...

This chapter reviews recent research adopting methods from statistical physics in theoretical or empirical work in economics and finance. The bulk of what has recently become known as 'econophysics' in broader circles draws its motivation from observed scaling laws in financial markets and the...

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...

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 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...

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...

This paper estimates a simple univariate model of expectation or opinion formation in continuous time adapting a 'canonical' stochastic model of collective opinion dynamics (Weidlich and Haag, 1983; Lux, 1995, 2007). This framework is applied to a selected data set on survey-based expectations from...

The economics profession appears to have been unaware of the long build-up to the current worldwide financial crisis and to have significantly underestimated its dimensions once it started to unfold. In our view, this lack of understanding is due to a misallocation of research efforts in...

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...

A Monte Carlo (MC) experiment is conducted to study the forecasting performance of a variety of volatility models under alternative data generating processes (DGPs). The models included in the MC study are the (Fractionally Integrated) Generalized Autoregressive Conditional Heteroskedasticity...