We generalize the score test for time-varying copula parameters proposed by [Abegaz & Naik-Nimbalkar, 2008] to a setting where more than one-parametric copulas can be tested for time variation in at least one parameter. In a next step we model the daily log returns of the Commerzbank stock using...

In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The approach adopted here is based on the decomposition of the covariances into correlations and standard deviations. The time-varying conditional correlations change smoothly between two...

Liechtenstein's economy has been heavily affected by the international economic downturn during the financial crisis. Additionally to the deep world recession, Liechtenstein's financial sector was challenged by the Zumwinkel-Affair (data of thousands of tax evaders were sold to several...

Asset-backed securitisation (ABS) is an asset funding technique that involves the issuance of structured claims on the cash flow performance of a designated pool of underlying receivables. Efficient risk management and asset allocation in this growing segment of fixed income markets requires...

We examine time-varying stock market comovements in Central Europe employing the asymmetric dynamic conditional correlation multivariate GARCH model. Using daily data from 2001 to 2011, we find that the correlations among stock markets in Central Europe and between Central Europe vis-a-vis the...

This study proposes a novel framework for the joint modelling of commodity forward curves. Its key contribution is twofold. First, dynamic correlation models are applied in this context as part of the modelling scheme. Second, we introduce a family of dynamic conditional correlation models based...

This paper concerns the distributional assumptions made on stock returns in the myopic loss aversion (MLA) proposed explanation to the equity premium puzzle. While Benartzi and Thaler (1995) assume temporal independence in these returns, we introduce a more realistic assumption incorporating...

This paper considers simultaneous modelling of seasonality, slowly changing un- conditional variance and conditional heteroskedasticity in high-frequency fiancial returns. A new approach, called a seasonal SEMIGARCH model, is proposed to perform this by introducing multiplicative seasonal and...

This paper investigates the use of price intensities to estimate volatilities based on high-frequency data. We interpret the conditional probability for the occurence of a price event within a certain time horizon as a risk measure which allows us to obtain an estimator of the conditional...

In this paper we present an exact maximum likelihood treatment forthe estimation of a Stochastic Volatility in Mean(SVM) model based on Monte Carlo simulation methods. The SVM modelincorporates the unobserved volatility as anexplanatory variable in the mean equation. The same extension...