ORCID Profile
0000-0003-3092-2500
Current Organisations
University of Bremen
,
University of Technology Sydney
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Publisher: Infopro Digital Services Limited
Date: 12-2014
Publisher: Elsevier BV
Date: 2012
DOI: 10.2139/SSRN.2182295
Publisher: Walter de Gruyter GmbH
Date: 20-12-2019
Abstract: This paper investigates dependence among insurance claims arising from different lines of business (LoBs). Using bivariate and multivariate portfolios of losses from different LoBs, we analyse the ability of various copulas in conjunction with skewed generalised hyperbolic (GH) marginals to capture the dependence structure between in idual insurance risks forming an aggregate risk of the loss portfolio. The general form skewed GH distribution is shown to provide the best fit to univariate loss data. When modelling dependency between LoBs using one-parameter and mixture copula models, we favour models that are capable of generating upper tail dependence, that is, when several LoBs have a strong tendency to exhibit extreme losses simultaneously. We compare the selected models in their ability to quantify risks of multivariate portfolios. By performing an extensive investigation of the in- and out-of-s le Value-at-Risk (VaR) forecasts by analysing VaR exceptions (i.e. observations of realised portfolio value that are greater than the estimated VaR), we demonstrate that the selected models allow to reliably quantify portfolio risk. Our results provide valuable insights with regards to the nature of dependence and fulfils one of the primary objectives of the general insurance providers aiming at assessing total risk of an aggregate portfolio of losses when LoBs are correlated.
Publisher: AIP Publishing
Date: 18-07-2022
DOI: 10.1063/5.0103026
Publisher: Elsevier BV
Date: 2020
Publisher: MDPI AG
Date: 06-2016
Publisher: Informa UK Limited
Date: 28-11-2014
Publisher: SAGE Publications
Date: 20-10-2014
Abstract: We investigate the coexistence of momentum and contrarian strategies in the Australian equity market from 1992 to 2011. We show that contrarian strategies prevail in the short-term investment horizon while momentum strategies dominate in the intermediate- and long-term horizons. However, only short-term contrarian strategies significantly outperform the simple buy-and-hold strategy of investing in the market index over the same period. Further examination of these strategies shows that the Australian mining sector undermines the performance of momentum while enhancing performance of contrarian strategies. Lastly, using both parametric and non-parametric approaches, we show that these strategies’ returns are persistent anomalies and not completely explained by standard return-generating models.
Publisher: AIP Publishing
Date: 23-03-2020
DOI: 10.1063/1.5143190
Abstract: DFTB+ is a versatile community developed open source software package offering fast and efficient methods for carrying out atomistic quantum mechanical simulations. By implementing various methods approximating density functional theory (DFT), such as the density functional based tight binding (DFTB) and the extended tight binding method, it enables simulations of large systems and long timescales with reasonable accuracy while being considerably faster for typical simulations than the respective ab initio methods. Based on the DFTB framework, it additionally offers approximated versions of various DFT extensions including hybrid functionals, time dependent formalism for treating excited systems, electron transport using non-equilibrium Green’s functions, and many more. DFTB+ can be used as a user-friendly standalone application in addition to being embedded into other software packages as a library or acting as a calculation-server accessed by socket communication. We give an overview of the recently developed capabilities of the DFTB+ code, demonstrating with a few use case ex les, discuss the strengths and weaknesses of the various features, and also discuss on-going developments and possible future perspectives.
Publisher: Elsevier BV
Date: 03-2019
Publisher: Elsevier BV
Date: 09-2011
Publisher: Wiley
Date: 21-06-2020
Publisher: Elsevier BV
Date: 11-2012
Publisher: Informa UK Limited
Date: 19-08-2015
Publisher: Elsevier BV
Date: 2017
Publisher: Elsevier BV
Date: 07-2019
No related grants have been discovered for Vitali Alexeev.