We investigate the predictability of both volatility and volume for a large sample of Japanese stocks. The particular emphasis of this paper is on assessing the performance of long memory time series models in comparison to their short-memory counterparts. Since long memory models should have a...

Multi-fractal processes have recently been proposed as a new formalism for modelling the time series of returns in finance. The major attraction of these processes is their ability to generate various degrees of long memory in different powers of returns - a feature that has been found in...

We investigate the predictability of both volatility and volume for a large sample of Japanese stocks. The particular emphasis of this paper is on assessing the performance of long memory time series models in comparison to their short-memory counterparts. Since long memory models should have a...

Multifractal processes have recently been proposed as a new formalism for modelling the time series of returns in insurance. The major attraction of these processes is their ability to generate various degrees of long memory in different powers of returns - a feature that has been found 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...

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 explore the issue of estimating a simple agent-based model of price formation in an asset market using the approach of Alfarano et al. (2008) as an example. Since we are able to derive various moment conditions for this model, we can apply generalized method of moments (GMM) estimation. We...

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...