This study investigates the daily co-movements in commodity prices over period 2006–2020 using a novel approach based on time-varying Gerber correlation. The statistic is computed considering set of probabilities estimated via non-traditional models that give structure to measure. results indicate there are several across commodities, these change time, and they tendentially positive. Condition...

We propose a new method for multivariate forecasting which combines Dynamic Factor and multivariate GARCH models. We call the model Dynamic Factor GARCH, as the information contained in large macroeconomic or financial datasets is captured by a few dynamic common factors, which we assume being conditionally heteroskedastic. After describing the estimation of the model, we present simulation res...

Motivated by the security of the nonlinear filter generator, the concept of correlation was previously extended to the conditional correlation, that studied the linear correlation of the inputs conditioned on a given (short) output pattern of some specific nonlinear function. Based on the conditional correlations, conditional correlation attacks were shown to be successful and efficient against...

The paper aims to analyze the contagion effect coming from developed stock markets of US and Germany emerging CEE Romania, Czech Republic, Hungary, Poland using daily data for period April 2005–April 2021. also captures level integration these by analyzing volatility spillover phenomenon. quantification consisted an empirical analysis based on DCC-GARCH (Dynamic Conditional Correlation) model. ...

The estimation of a large covariance matrix is challenging when the dimension p relative to sample size n. Common approaches deal with challenge have been based on thresholding or shrinkage methods in estimating matrices. However, many applications (e.g., regression, forecast combination, portfolio selection), what we need not but its inverse (the precision matrix). In this paper introduce meth...

BACKGROUND The time stratified case cross-over approach is a popular alternative to conventional time series regression for analysing associations between time series of environmental exposures (air pollution, weather) and counts of health outcomes. These are almost always analyzed using conditional logistic regression on data expanded to case-control (case crossover) format, but this has some ...

Financial liberalisation has offered global investors with new investment opportunities via international portfolio diversification. Proper investment planning as well as portfolio diversification and rebalancing require low correlations between the assets under consideration. In general, correlations between countries have increased during the global financial crisis due to contagion, interdep...

This paper examines the intertemporal relation between expected return and risk for 30 stocks in the Dow Jones Industrial Average. The mean-reverting dynamic conditional correlation model of Engle (2002) is used to estimate a stock’s conditional covariance with the market and test whether the conditional covariance predicts time-variation in the stock’s expected return. The risk-aversion coeffi...