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The most salient feature of security returns is uncertainty. The purpose of the book is to provide systematically a quantitative method for analyzing return and risk of a portfolio investment in different kinds of uncertainty and present the ways for striking a balance between investment return and risk such that an optimal portfolio can be obtained. In classical portfolio theory, security returns were assumed to be random variables, and probability theory was the main mathematical tool for handling uncertainty in the past. However, the world is complex and uncertainty is varied. Randomness is not the only type of uncertainty in reality, especially when human factors are included. Security market, one of the most complex markets in the world, contains almost all kinds of uncertainty. The security returns are sensitive to various factors including economic, social, political and very importantly, people’s psychological factors. Therefore, other than strict probability method, scholars have proposed some other approaches including imprecise probability, possibility, and interval set methods, etc., to deal with uncertainty in portfolio selection since 1990s. In this book, we want to add to the tools existing in science some new and unorthodox approaches for analyzing uncertainty of portfolio returns. When security returns are fuzzy, we use credibility which has self-duality property as the basic measure and employ credibility theory to help make selection decision such that the decision result will be consistent with the laws of contradiction and excluded middle. Being aware that one tool is not enough for solving complex practical problems, we further employ uncertain measure and uncertainty theory to help select an optimal portfolio when security returns behave neither randomly nor fuzzily.

Portfolio management --- Probabilities --- Uncertainty --- Finance --- Engineering & Applied Sciences --- Business & Economics --- Computer Science --- Investment & Speculation --- Mathematical models --- Mathematical models. --- Probability --- Statistical inference --- Computer science. --- Artificial intelligence. --- Computational intelligence. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Computational Intelligence. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Informatics --- Science --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Engineering. --- Artificial Intelligence. --- Construction --- Industrial arts --- Technology

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The most salient feature of security returns is uncertainty. The purpose of the book is to provide systematically a quantitative method for analyzing return and risk of a portfolio investment in different kinds of uncertainty and present the ways for striking a balance between investment return and risk such that an optimal portfolio can be obtained. In classical portfolio theory, security returns were assumed to be random variables, and probability theory was the main mathematical tool for handling uncertainty in the past. However, the world is complex and uncertainty is varied. Randomness is not the only type of uncertainty in reality, especially when human factors are included. Security market, one of the most complex markets in the world, contains almost all kinds of uncertainty. The security returns are sensitive to various factors including economic, social, political and very importantly, people's psychological factors. Therefore, other than strict probability method, scholars have proposed some other approaches including imprecise probability, possibility, and interval set methods, etc., to deal with uncertainty in portfolio selection since 1990s. In this book, we want to add to the tools existing in science some new and unorthodox approaches for analyzing uncertainty of portfolio returns. When security returns are fuzzy, we use credibility which has self-duality property as the basic measure and employ credibility theory to help make selection decision such that the decision result will be consistent with the laws of contradiction and excluded middle. Being aware that one tool is not enough for solving complex practical problems, we further employ uncertain measure and uncertainty theory to help select an optimal portfolio when security returns behave neither randomly nor fuzzily.

Artificial intelligence. Robotics. Simulation. Graphics --- neuronale netwerken --- fuzzy logic --- cybernetica --- KI (kunstmatige intelligentie)

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This volume provides a complete record of presentations made at Industrial Engineering, Management Science and Applications 2015 (ICIMSA 2015), and provides the reader with a snapshot of current knowledge and state-of-the-art results in industrial engineering, management science and applications. The goal of ICIMSA is to provide an excellent international forum for researchers and practitioners from both academia and industry to share cutting-edge developments in the field, and to exchange and distribute the latest research and theories from the international community. The conference is held every year, making it an ideal platform for people to share their views and experiences in industrial engineering, management science and applications related fields.

Industrial economics --- Operational research. Game theory --- Mathematical statistics --- Applied physical engineering --- Planning (firm) --- Physical distribution --- Computer science --- Programming --- Computer. Automation --- MIS (management informatie systeem) --- facility management --- besluitvorming --- computers --- mathematische modellen --- speltheorie --- econometrie --- operationeel onderzoek --- informatica management --- industriële marketing --- ingenieurswetenschappen --- computerkunde

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With the rapid development and drastic change of the world economy, "Digital Finance", "Internet Finance", "Science and Technology Finance" have become new hotspots, which also represent the future trend of economy development in the era of big data. Enterprises are facing more uncertainty, opportunities coexist with challenges. There are more possibilities for economic development and enterprise management to accelerate the integration of cutting-edge research results, to deepen hot topics discussion and to promote opinion exchanges among academic and business circles. The Sixth International Conference on Economic and Business Management (FEBM2021) was successfully held online on October 16-17, 2021, and aimed to provide a platform for researchers, engineers, academics as well as industry professionals from all over the world to present their latest research findings and development activities in economic and business management. These proceedings include 51 accepted articles selected from 94 submissions.

Finance --- Industrial management