Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization The finance industry is seeing increased interest in new risk measures and techniques for portfolio optimization when parameters of the model are uncertain. This groundbreaking book extends traditional approaches of risk measurement and portfolio optimization by combining distributional models with risk or performance measures into one framework. Throughout these pages, the expert authors explain the fundamentals of probability metrics, outline new approaches to portfolio optimization, and discuss a variety of essential risk measures. Using numerous examples, they illustrate a range of applications to optimal portfolio choice and risk theory, as well as applications to the area of computational finance that may be useful to financial engineers. They also clearly show how stochastic models, risk assessment, and optimization are essential to mastering risk, uncertainty, and performance measurement. Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization provides quantitative portfolio managers (including hedge fund managers), financial engineers, consultants, and academic researchers with answers to the key question of which risk measure is best for any given problem.
A Probability Metrics Approach to Financial Risk Measures relates the field of probability metrics and risk measures to one another and applies them to finance for the first time. Helps to answer the question: which risk measure is best for a given problem? Finds new relations between existing classes of risk measures Describes applications in finance and extends them where possible Presents the theory of probability metrics in a more accessible form which would be appropriate for non-specialists in the field Applications include optimal portfolio choice, risk theory, and numerical methods in finance Topics requiring more mathematical rigor and detail are included in technical appendices to chapters
This book covers the method of metric distances and its application in probability theory and other fields. The method is fundamental in the study of limit theorems and generally in assessing the quality of approximations to a given probabilistic model. The method of metric distances is developed to study stability problems and reduces to the selection of an ideal or the most appropriate metric for the problem under consideration and a comparison of probability metrics. After describing the basic structure of probability metrics and providing an analysis of the topologies in the space of probability measures generated by different types of probability metrics, the authors study stability problems by providing a characterization of the ideal metrics for a given problem and investigating the main relationships between different types of probability metrics. The presentation is provided in a general form, although specific cases are considered as they arise in the process of finding supplementary bounds or in applications to important special cases. Svetlozar T. Rachev is the Frey Family Foundation Chair of Quantitative Finance, Department of Applied Mathematics and Statistics, SUNY-Stony Brook and Chief Scientist of Finanlytica, USA. Lev B. Klebanov is a Professor in the Department of Probability and Mathematical Statistics, Charles University, Prague, Czech Republic. Stoyan V. Stoyanov is a Professor at EDHEC Business School and Head of Research, EDHEC-Risk Institute—Asia (Singapore). Frank J. Fabozzi is a Professor at EDHEC Business School. (USA)
An analysis of Douglas McGregors seminal 1960 book, this resource reveals how McGregor sought to find out what makes a good manager by evaluating different management approaches, their assumptions about human behavior, and effects they had. --
A critical analysis of Argyris’s Integrating The Individual and the Organization, which forms part of a series of essays and books considering how organisations should be run. The essay explores the lack of congruence between the needs and expectations of individual employees and the organisations that employ them. The impact of the work depends heavily on reasoning skills. Chris Argyris used strong, well-structured arguments to make his point. His reasoning has strong implications for solving a problem that many organizations experience: disengaged and disloyal employees. Grounding his argument in studies on human nature, Argyris highlighted that demands of greater independence, an expansion of interests, and re-orientation of goals usually accompany maturation, which is at odds with higher control stemming from formal organisations. This frustration, he contends, is detrimental to productivity, increases the chance of failure and causes conflict.
US psychologist Abraham H. Maslow’s A Theory of Human Motivation is a classic of psychological research that helped change the field for good. Like many field-changing thinkers, Maslow was not just a talented researcher, he was also a creative thinker – able to see things from a new perspective and show them in a different light. At a time when psychology was dominated by two major schools of thought, Maslow was able to forge a new, third paradigm, that remains influential today. Sigmund Freud’s psychoanalysis had developed the idea of understanding the mind through dialogue between patient and analyst. The behaviorism of Ivan Pavlov and John Watson had focused on comprehending the mind through behaviors that could be measured, trained, and changed. Maslow, however, generated new ideas, forging what he called “positive” or “humanistic psychology”. His argument was that humans are psychologically motivated by a series of hierarchical needs, starting with the most essential first. Maslow thought it important for the advancement of psychology to identify, group and rank these needs in terms of priority. His belief in the value of this third way was important in leading those who studied psychology to redefine the discipline, and so see it in new ways.
A critical analysis of Argyris’s Integrating The Individual and the Organization, which forms part of a series of essays and books considering how organisations should be run. The essay explores the lack of congruence between the needs and expectations of individual employees and the organisations that employ them. The impact of the work depends heavily on reasoning skills. Chris Argyris used strong, well-structured arguments to make his point. His reasoning has strong implications for solving a problem that many organizations experience: disengaged and disloyal employees. Grounding his argument in studies on human nature, Argyris highlighted that demands of greater independence, an expansion of interests, and re-orientation of goals usually accompany maturation, which is at odds with higher control stemming from formal organisations. This frustration, he contends, is detrimental to productivity, increases the chance of failure and causes conflict.
US psychologist Abraham Maslow's A Theory of Human Motivation is a classic of psychological research that helped change the field for good. Like many field-changing thinkers, Maslow was not just a talented researcher, he was also a creative thinker - able to see things from a new perspective and show them in a different light. At a time when psychology was dominated by two major schools of thought, Maslow was able to forge a new, third paradigm, that remains influential today. Sigmund Freud's psychoanalysis had developed the idea of understanding the mind through dialogue between patient and analyst. The behaviorism of Ivan Pavlov and John Watson had focused on comprehending the mind through behaviors that could be measured, trained, and changed. Maslow, however, generated new ideas, forging what he called "positive" or "humanistic psychology". His argument was that humans are psychologically motivated by a series of hierarchical needs, starting with the most essential first. Maslow thought it important for the advancement of psychology to identify, group and rank these needs in terms of priority. HIs belief in the value of this third way was important in leading those who studied psychology to redefine the discipline, and so see it in new ways."--Provided by publisher.
An analysis of Douglas McGregors seminal 1960 book, this resource reveals how McGregor sought to find out what makes a good manager by evaluating different management approaches, their assumptions about human behavior, and effects they had. --
This book covers the method of metric distances and its application in probability theory and other fields. The method is fundamental in the study of limit theorems and generally in assessing the quality of approximations to a given probabilistic model. The method of metric distances is developed to study stability problems and reduces to the selection of an ideal or the most appropriate metric for the problem under consideration and a comparison of probability metrics. After describing the basic structure of probability metrics and providing an analysis of the topologies in the space of probability measures generated by different types of probability metrics, the authors study stability problems by providing a characterization of the ideal metrics for a given problem and investigating the main relationships between different types of probability metrics. The presentation is provided in a general form, although specific cases are considered as they arise in the process of finding supplementary bounds or in applications to important special cases. Svetlozar T. Rachev is the Frey Family Foundation Chair of Quantitative Finance, Department of Applied Mathematics and Statistics, SUNY-Stony Brook and Chief Scientist of Finanlytica, USA. Lev B. Klebanov is a Professor in the Department of Probability and Mathematical Statistics, Charles University, Prague, Czech Republic. Stoyan V. Stoyanov is a Professor at EDHEC Business School and Head of Research, EDHEC-Risk Institute—Asia (Singapore). Frank J. Fabozzi is a Professor at EDHEC Business School. (USA)
A Probability Metrics Approach to Financial Risk Measures relates the field of probability metrics and risk measures to one another and applies them to finance for the first time. Helps to answer the question: which risk measure is best for a given problem? Finds new relations between existing classes of risk measures Describes applications in finance and extends them where possible Presents the theory of probability metrics in a more accessible form which would be appropriate for non-specialists in the field Applications include optimal portfolio choice, risk theory, and numerical methods in finance Topics requiring more mathematical rigor and detail are included in technical appendices to chapters
Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization The finance industry is seeing increased interest in new risk measures and techniques for portfolio optimization when parameters of the model are uncertain. This groundbreaking book extends traditional approaches of risk measurement and portfolio optimization by combining distributional models with risk or performance measures into one framework. Throughout these pages, the expert authors explain the fundamentals of probability metrics, outline new approaches to portfolio optimization, and discuss a variety of essential risk measures. Using numerous examples, they illustrate a range of applications to optimal portfolio choice and risk theory, as well as applications to the area of computational finance that may be useful to financial engineers. They also clearly show how stochastic models, risk assessment, and optimization are essential to mastering risk, uncertainty, and performance measurement. Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization provides quantitative portfolio managers (including hedge fund managers), financial engineers, consultants, and academic researchers with answers to the key question of which risk measure is best for any given problem.
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