Risk and Decision Analysis
The journal Risk and Decision Analysis (RDA) emphasizes a theoretical and practical interdisciplinary and comprehensive vision of Risk: its definition, its measurements, its analysis, its manifestations and reconcile their contradictions and their differences. RDA considers for publication research papers that contribute to a greater appreciation of risks and uncertainties in their many definitions, their modeling (mathematical or otherwise), their empirical and data analysis, their pricing and their management. Application of risk modeling and decision analysis to general and risk engineering, economic and financial systems, operational and networked systems in industry, in services, in control, regulatory and compliance systems etc. are emphasized. For example, financial market risks, eco-risks and urban systems, insurance, energy, safety and security, healthcare, environment, and related areas are emphasized for the purpose to provide an integrative vision of risks and uncertainty how to confront their manifestations. The intent of RDA is to provide to academic and practitioners, a platform to better integrate and interpret risks and their manifestations in a comprehensive manner.
RDA's focus is scientific, based on mathematical and systematic approaches to risk (statistics, probability theory, data science), Bayesian statistics and (automatic, machine) learning, stochastic modeling, stochastic and optimal control. At the same time it is “educational”, having set “an educational corner” to introduce and clarify complex risk related issues and problems. These problems include for example issues such as VIX and Fear; Risk and Uncertainty (ambiguity), the risks of “financialization”, environmental and extreme risks, managerial approaches, etc. Empirical analysis and data analytic approaches to assess and support theoretical results based on interesting methodologies is an important element of RDA’s mission.
The journal Risk and Decision Analysis (RDA) emphasizes a theoretical and practical interdisciplinary and comprehensive vision of Risk: its definition, its measurements, its analysis, its manifestations and reconcile their contradictions and their differences. RDA considers for publication research papers that contribute to a greater appreciation of risks and uncertainties in their many definitions, their modeling (mathematical or otherwise), their empirical and data analysis, their pricing and their management. Application of risk modeling and decision analysis to general and risk engineering, economic and financial systems, operational and networked systems in industry, in services, in control, regulatory and compliance systems etc. are emphasized. For example, financial market risks, eco-risks and urban systems, insurance, energy, safety and security, healthcare, environment, and related areas are emphasized for the purpose to provide an integrative vision of risks and uncertainty how to confront their manifestations. The intent of RDA is to provide to academic and practitioners, a platform to better integrate and interpret risks and their manifestations in a comprehensive manner.
RDA's focus is scientific, based on mathematical and systematic approaches to risk (statistics, probability theory, data science), Bayesian statistics and (automatic, machine) learning, stochastic modeling, stochastic and optimal control. At the same time it is “educational”, having set “an educational corner” to introduce and clarify complex risk related issues and problems. These problems include for example issues such as VIX and Fear; Risk and Uncertainty (ambiguity), the risks of “financialization”, environmental and extreme risks, managerial approaches, etc. Empirical analysis and data analytic approaches to assess and support theoretical results based on interesting methodologies is an important element of RDA’s mission.
| George Papanicolaou | Stanford University, USA |
| Chantal Delabarre | Toulouse, France |
| Stefano Barone | University of Palermo, Italy |
| Sergio Bianchi | "Sapienza” University of Rome, Italy |
| Metin Cakanyildirim | University of Texas at Dallas, USA |
| Robert Cooper | Florida Atlantic University, USA |
| Michel Crouhy | IXIS Securities, France |
| Alexandre Dolgui | IMT Atlantique, France |
| Raphael Douady | Université Paris 1 Panthéon Sorbonne, France |
| Tyrone Duncan | University of Kansas, USA |
| Dan Galai | The Hebrew University of Jerusalem, Israel |
| Helyette Geman | University of London, UK |
| Hyeng Keun Koo | Ajou University Business School, Republic Of Korea |
| Steven Kou | Columbia University, USA |
| Jean-Michel Lasry | University Paris IX-Dauphine, France |
| John Liu | The Hong Kong Polytechnic, Hong Kong |
| Alexander Melnikov | University of Alberta, Canada |
| Shmuel Oren | University of California at Berkeley, USA |
| Bozenna Pasik-Duncan | University of Kansas, USA |
| Elisabeth Pate-Cornell | Stanford University, USA |
| Stylianos Perrakis | Concordia University, Canada |
| Sumit Sarkar | University of Texas at Dallas, USA |
| Suresh P. Sethi | University of Texas at Dallas, USA |
| Ronnie Sircar | Princeton University, USA |
| Lorne Switzer | Concordia University, Canada |
| Mina Teicher | Bar-Ilan University, Israel |
| Kwok-Leung Tsui | City University of Hong Kong, Hong Kong |
| Paul Zipkin | Duke University, USA |