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Computational Methods for Risk Management in Economics and Finance

At present, computational methods have received considerable attention in economics and finance as an alternative to conventional analytical and numerical paradigms. This Special Issue brings together both theoretical and application-oriented contributions, with a focus on the use of computational t...

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Hovedforfatter: Resta, Marina
Format: Online
Sprog:engelsk
Udgivet: MDPI - Multidisciplinary Digital Publishing Institute 2021
Fag:
HG1-9999
growth optimal portfolio
Wishart model
conditional Value-at-Risk (CoVaR)
systemic risk
utility functions
current drawdown
risk measure
risk-based portfolios
capital market pricing model
systemic risk measures
Big Data
International Financial Reporting Standard 9
cartography
stock prices
copula models
CoVaR
quantitative risk management
auto-regressive
fractional Kelly allocation
independence assumption
deep learning
structural models
financial regulation
data science
efficient frontier
weighted logistic regression
estimation error
financial markets
capital allocation
multi-step ahead forecasts
target matrix
value at risk
random matrices
credit risk
portfolio theory
convex programming
admissible convex risk measures
non-stationarity
financial mathematics
quantile regression
Markowitz portfolio theory
shrinkage
loss given default
ordered probit
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Summary:At present, computational methods have received considerable attention in economics and finance as an alternative to conventional analytical and numerical paradigms. This Special Issue brings together both theoretical and application-oriented contributions, with a focus on the use of computational techniques in finance and economics. Examined topics span on issues at the center of the literature debate, with an eye not only on technical and theoretical aspects but also very practical cases.

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