Die folgenden Links führen aus den jeweiligen lokalen Bibliotheken zum Volltext:
Alternativ können Sie versuchen, selbst über Ihren lokalen Bibliothekskatalog auf das gewünschte Dokument zuzugreifen.
Bei Zugriffsproblemen kontaktieren Sie uns gern.
36 Ergebnisse
Sortierung:
In: Wiley Handbooks in Financial Engineering and Econometrics
In: Wiley online library
"A companion book to Fundamental Aspects of Operational Risk Modeling and Insurance Analytics: A Handbook of Operational Risk (2014), this book covers key mathematical and statistical aspects of the quantitative modelling of heavy tailed loss processes in operational risk and insurance settings. This book can add value to the industry by providing clear and detailed coverage of modelling for heavy tailed operational risk losses from both a rigorous mathematical as well as a statistical perspective. Few books cover the range of details provided both the mathematical and statistical features of such models, directly targeting practitioners. The book focuses on providing a sound understanding of how one would mathematically and statistically model, estimate, simulate and validate heavy tailed loss process models in operational risk. Coverage includes advanced topics on risk modelling in high consequence low frequency loss processes. This features splice loss models and motivation for heavy tailed risk processes models. The key aspects of extreme value theory and their development in loss distributional approach modelling is considered. Classification and understanding of different classes of heavy tailed risk process models is discussed, this leads into topics on heavy tailed closed form loss distributional approach models and flexible heavy tailed risk models such as a-stable and tempered stable models. The remainder of the chapters covers advanced topics on risk measures and asymptotics for heavy tailed compound process models. The finishing chapter covers advanced topics including forming links between actuarial compound process recursions and monte carlo numerical solutions for capital and risk measure estimations"--
SSRN
SSRN
Working paper
In: Andréasson, J.G., Shevchenko, P.V. A bias-corrected Least-Squares Monte Carlo for solving multi-period utility models. European Actuarial Journal (2021). https://doi.org/10.1007/s13385-021-00288-9
SSRN
Working paper
SSRN
Working paper
SSRN
Working paper
"A companion book to Fundamental Aspects of Operational Risk Modeling and Insurance Analytics: A Handbook of Operational Risk (2014), this book covers key mathematical and statistical aspects of the quantitative modelling of heavy tailed loss processes in operational risk and insurance settings. This book can add value to the industry by providing clear and detailed coverage of modelling for heavy tailed operational risk losses from both a rigorous mathematical as well as a statistical perspective. Few books cover the range of details provided both the mathematical and statistical features of such models, directly targeting practitioners. The book focuses on providing a sound understanding of how one would mathematically and statistically model, estimate, simulate and validate heavy tailed loss process models in operational risk. Coverage includes advanced topics on risk modelling in high consequence low frequency loss processes. This features splice loss models and motivation for heavy tailed risk processes models. The key aspects of extreme value theory and their development in loss distributional approach modelling is considered. Classification and understanding of different classes of heavy tailed risk process models is discussed, this leads into topics on heavy tailed closed form loss distributional approach models and flexible heavy tailed risk models such as a-stable and tempered stable models. The remainder of the chapters covers advanced topics on risk measures and asymptotics for heavy tailed compound process models. The finishing chapter covers advanced topics including forming links between actuarial compound process recursions and monte carlo numerical solutions for capital and risk measure estimations"--
In: European actuarial journal
ISSN: 2190-9741
AbstractIn this paper we develop a model to find optimal decisions in retirement with respect to the consumption, risky asset allocation, access to annuities, reverse mortgage and the option to scale housing in the presence of a means-tested public pension. To solve the corresponding high-dimensional optimal stochastic control problem, we use the Least-Squares Monte Carlo simulation method. The model is applied in the context of the Australian retirement system. Few retirees in Australia utilise financial products in retirement, such as annuities or reverse mortgages. Since the government-provided means-tested Age Pension in Australia is an indirect annuity stream which is typically higher than the consumption floor, it can be argued that this could be the reason why many Australians do not annuitise. In addition, in Australia where assets allocated to the family home are not included in the means tests of Age Pension, the incentive to over-allocate wealth into housing assets is high. This raises the question whether a retiree is really better off over-allocating into the family home, while accessing home equity later on either via downsizing housing or by taking out a reverse mortgage. Our findings confirm that means-tested pension crowds out voluntary annuitisation in retirement, and that annuitisation is optimal sooner rather than later once retired. We find that it is never optimal to downscale housing when the means-tested pension and a reverse mortgage are available; only when there is no other way to access equity then downsizing is the only option.
In: European actuarial journal, Band 12, Heft 1, S. 349-379
ISSN: 2190-9741
In: Journal of economic dynamics & control, Band 157, S. 104759
ISSN: 0165-1889
In: Journal of Economic Dynamics and Control, Forthcoming
SSRN
In: Quantitative Finance 2021, https://doi.org/10.1080/14697688.2021.1950918
SSRN
SSRN
Working paper
In: A. Lichtenstern, P.V.Shevchenko, R. Zagst (2020). Optimal life-cycle consumption and investment decisions under age-dependent risk preferences. Mathematics and Financial Economics. DOI 10.1007/s11579-020-00276-9.
SSRN