Risk forecasting in (T)GARCH models with uncorrelated dependent innovations

(G)ARCH-type models are frequently used for the dynamic modelling and forecasting of risk attached to speculative asset returns. While the symmetric and conditionally Gaussian GARCH model has been generalized in a manifold of directions, model innovations are mostly presumed to stem from an underlying IID distribution. For a cross section of 18 stock market indices, we notice that (threshold) (T)GARCH-implied model innovations are likely at odds with the commonly held IID assumption. Two complementary strategies are pursued to evaluate the conditional distributions of consecutive TGARCH innovations, a non-parametric approach and a class of standardized copula distributions. Modelling higher order dependence patterns is found to improve standard TGARCH-implied conditional value-at-risk and expected shortfall out-of-sample forecasts that rely on the notion of IID innovations.     

Measures of risk associated to regulations compliance: a laboratory experiment on the use of common-pool resources

The present research examined the influence of different risk perspectives by the use of four different target persons (who could be affected: abstract person, self, specific person, and specific others) and of four different questionnaire answer formats (rating, open percentage, open, and closed frequency) on risk assessments. It was assumed that subjects use two different systems in terms of probabilistic reasoning: a distributional approach for abstract targets leading to higher risk estimates and a singular approach for specific targets leading to lower risk assessments. According to unrealistic optimism (UO) research (showing higher risk assessments for an abstract person than for self), the assumption was that risk assessments for a specific (named) target lead to lower risk assessments compared to an abstract target. Further, common quantitative answer formats for assessing risk were compared to explore differences in risk estimates. The hypotheses were tested using data of a sample of 512 students from a Bavarian university. The frequently confirmed finding of UO could be replicated with both rating scale and open frequency scale, which appeared to be more sensitive compared to the other used scales. However, UO disappeared when the comparison target was specific. Further, risk assessments for an abstract target were highest within every answer format and lowest for specific targets. Furthermore, results revealed that the type of answer format has a moderating effect on the extent of the influence of risk perspective on risk assessments. Overall, this study gives evidence that both the chosen scale and the risk perspective strongly influence risk assessments. Results aim to contribute to the research fields of quantitative assessment of perceived risk. They suggest that probabilistic reasoning in regard to risk not only underlies motivational or cognitive ego-defensive mechanisms but is rather presumably caused by the use of different systems of inferential strategies.     

Network topology of the interbank market

We provide an empirical analysis of the network structure of the Austrian interbank market based on Austrian Central Bank (OeNB) data. The interbank market is interpreted as a network where banks are nodes and the claims and liabilities between banks define the links. This allows us to apply methods from general network theory. We find that the degree distributions of the interbank network follow power laws. Given this result we discuss how the network structure affects the stability of the banking system with respect to the elimination of a node in the network, i.e. the default of a single bank. Further, the interbank liability network shows a community structure that exactly mirrors the regional and sectoral organization of the current Austrian banking system. The banking network has the typical structural features found in numerous other complex real-world networks: a low clustering coefficient and a short average path length. These empirical findings are in marked contrast to the network structures that have been assumed thus far in the theoretical economic and econo-physics literature.     

Why do people save in cash? Distrust,memories of banking crises,weak institutions and dollarization

The paper analyzes why households hold sizeable shares of their assets in cash at home rather than at banks – a phenomenon that is widespread in many economies but for which information is scarce. Using survey data from ten Central, Eastern and Southeastern European countries, I document the relevance of this behavior and show that cash preferences cannot be fully explained by whether people are banked or unbanked. The analysis reveals that a lack of trust in banks, memories of past banking crises and weak tax enforcement are important factors. Moreover, cash preferences are stronger in dollarized economies where a “safe” foreign currency serves as a store of value.