Results 191 to 200 of about 31,329,977 (262)
Mathematical Finance, 2019 We provide sharp analytical upper and lower bounds for value‐at‐risk (VaR) and sharp bounds for expected shortfall (ES) of portfolios of any dimension subject to default risk.
R. Fontana, E. Luciano, P. Semeraro
semanticscholar +5 more sources
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Reduced Risk Information Seeking Model (RISK): A Meta-Analysis
Science communication, 2022This meta-analysis synthesizes research findings from 50 studies to assess the explanatory power of the reduced risk information seeking model (RISK).
Zhuling Liu, J. Yang, T. Feeley
semanticscholar +1 more source
, 2020
Business models and business model innovation—and particularly their opportunities—have been a popular topic recently, but we find the extant literature on the subject lacking.
Anne-Sophie Brillinger +3 more
semanticscholar +1 more source
Business models and business model innovation—and particularly their opportunities—have been a popular topic recently, but we find the extant literature on the subject lacking.
Anne-Sophie Brillinger +3 more
semanticscholar +1 more source
Robust risk measurement and model risk
Quantitative Finance, 2014Financial risk measurement relies on models of prices and other market variables, but models inevitably rely on imperfect assumptions and estimates, creating model risk. Moreover, optimization decisions, such as portfolio selection, amplify the effect of model error. In this work, we develop a framework for quantifying the impact of model error and for
P. Glasserman, Xingbo Xu
semanticscholar +2 more sources
Journal of Banking & Finance, 2014
The experience from the global financial crisis has raised serious concerns about the accuracy of standard risk measures as tools for the quantification of extreme downward risks. A key reason for this is that risk measures are subject to a model risk due, e.g. to specification and estimation uncertainty.
Boucher, Christophe +3 more
openaire +2 more sources
The experience from the global financial crisis has raised serious concerns about the accuracy of standard risk measures as tools for the quantification of extreme downward risks. A key reason for this is that risk measures are subject to a model risk due, e.g. to specification and estimation uncertainty.
Boucher, Christophe +3 more
openaire +2 more sources
The evolution of model risk management processes
Journal of Risk Management in Financial Institutions, 2019Model risk is a relatively new area that only recently separated from operational risk. This paper provides an overview of what needs to be done in model risk management versus the older concept of model validation.
M. Garro
semanticscholar +1 more source
The Journal of Risk Model Validation, 2008 Model risk as part of the operational risk is a serious problem for financial institutions. As the pricing of derivatives as well as the computation of the market or credit risk of an institution depend on statistical models the application of a wrong model can lead to a serious overor underestimation of the institution’s risk.
Sibbertsen, Philipp +2 more
openaire +2 more sources
COPING WITH LONG TERM MODEL RISK IN MARKET RISK MODELS
Proceedings of the 1st International Conference on Operations Research and Enterprise Systems, 2012The recent financial crisis has shown that most market risk models – even if they deliver sufficiently accurate risk figures over short time horizons – are not able to provide reliable forecasts for risk figures over longer time horizons like three, twelve or 36 months, which are the basis for both limit management and economic capital planning.
Spangler, Manuela, Werner, Ralf
openaire +2 more sources
Model Risk Measures: A Review and New Proposals on Risk Forecasting
Social Science Research Network, 2019In financial decisions, model risk has been recognized as an important source of uncertainty. The revision of the Basel II suggests that financial institutions quantify and manage their model risk.
Fernanda Muller, M. Righi
semanticscholar +1 more source
Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews
arXiv.orgThe advent of large language models has ushered in a new era of agentic systems, where artificial intelligence programs exhibit remarkable autonomous decision-making capabilities across diverse domains. This paper explores agentic system workflows in the
Izunna Okpala +2 more
semanticscholar +1 more source