Elio Canestrelli

Elio Canestrelli is a Senior Researcher in the Department of Economics at Ca' Foscari University of Venice, specializing in mathematical methods applied to economics, actuarial science, and financial sciences (SSD SECS-S/06). His academic career spans over four decades with continuous research contributions from 1973 through 2019.

Canestrelli's research focuses on the intersection of financial mathematics, stochastic programming, and portfolio optimization. His work demonstrates a consistent trajectory exploring quantitative approaches to financial decision-making, with particular emphasis on risk management, tracking error models, and multistage stochastic optimization problems. His research methodology often combines theoretical mathematical frameworks with practical applications in financial markets and port management systems.

Analysis of his publication history reveals a dual research focus: financial mathematics (particularly portfolio optimization under uncertainty) and urban/port traffic management systems. His work on downside risk protection, volatility modeling, and ship traffic optimization in Venice demonstrates applied research addressing both theoretical financial problems and practical urban challenges. The chronological progression shows an evolution from foundational work in stochastic processes to sophisticated multistage optimization models.

Canestrelli has served on the editorial board of Mathematical Methods in Economics and Finance, contributing to academic discourse in quantitative finance. His collaborative work spans multiple institutions and demonstrates interdisciplinary approaches to complex decision problems.

His research includes significant contributions to Venice port management systems, particularly through the development of the MANTA project (Modello di Analisi del Traffico Acqueo), which applied GIS technology to water traffic analysis in Venice's historic city center. This work represents the practical application of his mathematical expertise to local urban challenges.