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In this paper we propose a new measure for systemic risk: the Financial Risk Meter (FRM). This measure is based on the … parameters over the 100 largest US publicly traded financial institutions. We demonstrate the suitability of this risk measure by … comparing the proposed FRM to other measures for systemic risk, such as VIX, SRISK and Google Trends. We find that mutual …
Persistent link: https://www.econbiz.de/10011598919
Risiko verbinden ließe, wenn man nur die Finanzprodukte entsprechend gestaltete, hat sich diese Wahnvorstellung … Risikos angesprochen. -- pricing kernels ; risk aversion ; risk neutral density …
Persistent link: https://www.econbiz.de/10003893128
Persistent link: https://www.econbiz.de/10013411139
Persistent link: https://www.econbiz.de/10012500180
quantile and expectile estimation, a platform for risk assessment is provided. ES and implications for tail events under … different distributional scenarios are investigated, particularly we discuss the implications of increased tail risk for mixture … can be successfully estimated on a daily basis using a one-year time horizon across different risk levels. …
Persistent link: https://www.econbiz.de/10011349502
We propose a semiparametric measure to estimate systemic interconnectedness across financial institutions based on tail-driven spill-over effects in a ultra-high dimensional framework. Methodologically, we employ a variable selection technique in a time series setting in the context of a...
Persistent link: https://www.econbiz.de/10010428185
aspects. More precisely, our framework captures the risk propagation and dynamics in terms of a quantile (or expectile …) autoregression involving network effects quantified through an adjacency matrix. To reflect the nature and risk content of systemic … risk, the construction of the adjacency matrix is suggested to include tail event covariates. The model is evaluated using …
Persistent link: https://www.econbiz.de/10011598923
This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of...
Persistent link: https://www.econbiz.de/10003633940
Graphical data representation is an important tool for model selection in bankruptcy analysis since the problem is highly non-linear and its numerical representation is much less transparent. In classical rating models a convenient representation of ratings in a closed form is possible reducing...
Persistent link: https://www.econbiz.de/10003324316
This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of...
Persistent link: https://www.econbiz.de/10003608864