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 sentiment, medium-run sentiment and stock index returns allows to reject exogeneity of returns. Depending...

The purpose of this paper is to analyze in bivariate vector autoregression the relationship between feedback in stochastic systems, Granger causality and a measure of dissimilarity between ARMA models. In particular, we consider a bivariate vector autoregressive processes of order p (a bivariate VAR(p) process) and we prove if the distance between the univariate ARMA models implied by the VAR r...

Ploberger and Phillips (Econometrica, Vol. 71, pp. 627–673, 2003) proved a result that provides a bound on how close a fitted empirical model can get to the true model when the model is represented by a parameterized probability measure on a finite dimensional parameter space. The present note extends that result to cases where the parameter space is infinite dimensional. The results have impli...

This article focuses on the electricity industry and electricity consumption of population and industrial enterprises in Russia is analyzed. Economic factors that affect energy consumption are studied by the Vector Autoregression Analysis (VAR). The relationship between variables is defined by Granger test, and it also considers scenarios of reactions of electricity consumption on exogenous sho...

This paper studies the effect of uncertainty shocks on demand for business loans in individual euro area countries. The results Bayesian vector autoregression (VAR) model impulse response functions show that some countries overall loans, and particularly fixed-investment financing, respond significantly negatively to shock.

In this paper, the dynamic portfolio selection problem is considered. The Elman network is first designed to simulate the dynamic security behavior. Then, the dynamic covariance matrix is estimated by the cross-covariance matrices. Finally, the dynamic portfolio selection model is formulated. In addition, a numerical example is used to demonstrate the proposedmethod and compare with the vector ...

Vector Autoregression Models (VAR) are widely used by researchers to capture the linear interdependencies among multiple time series. We propose a novel method called Clustered VAR (CVAR) to identify components of the data generated by a mixture of K VAR processes. By applying a CVAR model to a consumer-level time series dataset on shopping behavior at a retailer, we segment consumers based on ...

In this paper we propose a strategy for forecasting the term structure of interest rates which may produce significant gains in predictive accuracy. The key idea is to use the restrictions implied by Affine Term Structure Models (ATSM) on a vector autoregression (VAR) as prior information rather than imposing them dogmatically. This allows to account for possible model misspecification. We appl...