Profil
Mes achats
Découvrez plus de 300 000 ebooks aux formats pdf epub, audio en telechargement ou en lecture streaming. Nous vous avons sélectionné nos coups de cœur toutes categories confondues et mettons en avant l'actualité de la litterature française et internationale.
voir toutes les nouveautés
Nouveautés de la semaine
Recherche avancée
This open access volume explores the cutting edge of quantitative methods in agricultural risk management and insurance. Composed of insightful articles authored by field experts, focusing on innovation, recent advancements, and the use of technology and data sciences, it bridges the gap between theory and practice through empirical studies, concrete examples and case analyses.
Evolving challenges in risk management have called for the development of new, groundbreaking models. Beyond presenting the theoretical foundations of these models, this book discusses their real-world applications, providing tangible insights into how innovative modeling can elevate risk management strategies in the agricultural sector.
The latest risk management tools incorporate novel concepts such as index insurance, price index risk management frameworks and risk pools. The practical implications of these approaches are investigated, and their impact on contemporary agricultural risk mitigation and insurance practices is examined. Field experiences illustrate the implementation of these tools and their resulting outcomes.
Modern data analysis techniques in agricultural risk and insurance include machine learning, spatial analysis, text analysis, and deep learning. In addition to scrutinizing these ideas, the authors introduce an economic perspective towards risk, highlighting areas that have developed thanks to technological progress. Examples illustrate how these combined methodologies contribute to informed decision-making in agriculture, and their potential benefits and challenges are considered.
This carefully compiled volume will be a valuable reference for researchers, practitioners, and students intrigued by the dynamic intersection of agricultural risk management and insurance practices.
Les livres numériques peuvent être téléchargés depuis l'ebookstore Numilog ou directement depuis une tablette ou smartphone.
PDF : format reprenant la maquette originale du livre ; lecture recommandée sur ordinateur et tablette EPUB : format de texte repositionnable ; lecture sur tous supports (ordinateur, tablette, smartphone, liseuse)
DRM Adobe LCP
LCP DRM Adobe
Ce livre est protégé contre la rediffusion à la demande de l'éditeur (DRM).
La solution LCP apporte un accès simplifié au livre : une clé d'activation associée à votre compte client permet d'ouvrir immédiatement votre livre numérique.
Les livres numériques distribués avec la solution LCP peuvent être lus sur :
La solution Adobe consiste à associer un fichier à un identifiant personnel (Adobe ID). Une fois votre appareil de lecture activé avec cet identifiant, vous pouvez ouvrir le livre avec une application compatible.
Les livres numériques distribués avec la solution Adobe peuvent être lus sur :
mobile-and-tablet Pour vérifier la compatibilité avec vos appareils,consultez la page d'aide
Hirbod Assa is a prominent researcher in the field of InsurTech and risk management with a focus on parametric risk transfer tools. Hirbod serves as a director at Model Library, a consulting firm specializing in risk management. Additionally he was a founding team and quantitative researcher at Edge Technologies, working on innovative risk management solutions. His academic career includes ten years at the universities of Essex, Kent, and Liverpool, focusing on commodity and systematic risk management by leveraging insurance risk capacity. Hirbod played a key role in the development of price index insurance for agricultural commodities at Stable Group Ltd, an achievement recognized by the University of Liverpool in their 2021 REF impact case submissions. He worked on machine learning projects with renowned banks such as Lloyds and MUFG. Hirbod holds a Ph.D. in financial mathematics from the University of Montreal and a Ph.D. in economics from Concordia University.
Peng Liu is a Lecturer in the School of Mathematics, Statistics and Actuarial Science, University of Essex since 2020. He received PhD in Probability and Statistics in Nankai University in 2015. Since then, he did postdoc in the University of Lausanne and University of Waterloo for two years respectively. His research focuses on Quantitative Risk Management, Actuarial Science, and Extreme Value Theory.
Simon (Meng) Wang is the Chief Technology Officer at Stable Group Limited, a London-based leading InsurTech firm specializing in supply chain parametric insurance. With a strong foundation in mathematical sciences and financial mathematics, Simon has extensive experience in developing advanced machine learning algorithms and quantitative models for risk management and financial derivatives. His innovative work includes the creation of automated systems for real-time hedging in incomplete markets and comprehensive risk simulation tools. Simon has also contributed to several notable publications in the field, focusing on cross-hedging, stochastic models, and agricultural goods pricing.
Restez informé(e) des événements et promotions ebook
Paiements sécurisés