Computational Methods for Risk Management in Economics and Finance

• Autore: Resta Marina
• Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute, 2020
• Descrizione fisica: 1 online resource (234 p.)
• Soggetto non controllato: admissible convex risk measures; auto-regressive; Big Data; capital allocation; capital market pricing model; cartography; conditional Value-at-Risk (CoVaR); convex programming; copula models; CoVaR; credit risk; current drawdown; data science; deep learning; efficient frontier; estimation error; financial markets; financial mathematics; financial regulation; fractional Kelly allocation; growth optimal portfolio; independence assumption; International Financial Reporting Standard 9; loss given default; Markowitz portfolio theory; multi-step ahead forecasts; non-stationarity; ordered probit; portfolio theory; quantile regression; quantitative risk management; random matrices; risk measure; risk-based portfolios; shrinkage; stock prices; structural models; systemic risk; systemic risk measures; target matrix; utility functions; value at risk; weighted logistic regression; Wishart model
• 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