Computational Methods for Risk Management in Economics and Finance

• Autore: Resta Marina
• Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute, 2020
• Descrizione fisica: 1 electronic resource (234 p.)
• Soggetto non controllato: 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
• Sommario/riassunto: 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.
• Titolo autorizzato: Computational Methods for Risk Management in Economics and Finance
• ISBN: 3-03928-499-1
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910404091803321
• Lo trovi qui: Univ. Federico II