Cover Image
Read Now

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...

Full description

Bibliographic Details
Main Author: Resta, Marina
Format: eBook
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2020
Subjects:
Copula Models
Quantile Regression
Growth Optimal Portfolio
Multi-step Ahead Forecasts
Quantitative Risk Management
Data Science
Utility Functions
Admissible Convex Risk Measures
Covar
Deep Learning
Structural Models
International Financial Reporting Standard 9
Cartography
Credit Risk
Financial Mathematics
Target Matrix
Random Matrices
Risk Measure
Risk-based Portfolios
Value At Risk
Wishart Model
Convex Programming
Systemic Risk
Shrinkage
Financial Regulation
Efficient Frontier
Fractional Kelly Allocation
Non-stationarity
Weighted Logistic Regression
Loss Given Default
Systemic Risk Measures
Big Data
Estimation Error
Markowitz Portfolio Theory
Portfolio Theory
Financial Markets
Conditional Value-at-risk (covar)
Ordered Probit
Independence Assumption
Auto-regressive
Capital Allocation
Capital Market Pricing Model
Current Drawdown
Stock Prices
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
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.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by-nc-nd/4.0/
Physical Description:1 electronic resource (234 p.)
ISBN:9783039284986
9783039284993
books978-3-03928-499-3

Similar Items