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Author: Cornelis A. Los
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
There are three crucial mathematical system concepts in Finance, which are either being confused or misapplied - uncertainty, complexity and rank. First, the concept of epistemic uncertainty is sufficient for modeling and the concept of probability is unnecessary. This is illustrated by quot;Galton's Error,quot; and the under-repesentation of systematic risk by American mutual funds. These funds use simple unidirectional projection (quot;regressionquot;) to compute Sharpe's beta for fund selection. There are at least five equivalent ways of representing the measured model uncertainty and a new and an improved risk categorization for mutual funds is presented. Second, the concept of (linear) system complexity is usually dealt with by presuming a model rank, as the Cowles Foundation erroneously prescribed in the early 1950s, and superimposing that model rank on the data, when a model is estimated. But the model rank does not have to be presumed: it can be identified from the data and all corresponding (Grassmanian) coefficients can be computed by CLS Projections. This is illustrated by the identification of the model rank of simple financial risk systems in six Asian countries, in particular in Taiwan. Third, often it is thought that Markowitz' portfolio optimization and exact and complete cash flow accounting are incompatible because of the non-existence, or empirical instability of the information matrix. The problem is caused by the rank constraints imposed by the portfolio accounting identities. But these rank constraints also provide the solution, since they form exact selectors of the portfolio allocations, which are found by simple tensor algebra. This will be illustrated by the optimization of an Asian multi-currency stock investment portfolio.
Author: Cornelis A. Los
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
There are three crucial mathematical system concepts in Finance, which are either being confused or misapplied - uncertainty, complexity and rank. First, the concept of epistemic uncertainty is sufficient for modeling and the concept of probability is unnecessary. This is illustrated by quot;Galton's Error,quot; and the under-repesentation of systematic risk by American mutual funds. These funds use simple unidirectional projection (quot;regressionquot;) to compute Sharpe's beta for fund selection. There are at least five equivalent ways of representing the measured model uncertainty and a new and an improved risk categorization for mutual funds is presented. Second, the concept of (linear) system complexity is usually dealt with by presuming a model rank, as the Cowles Foundation erroneously prescribed in the early 1950s, and superimposing that model rank on the data, when a model is estimated. But the model rank does not have to be presumed: it can be identified from the data and all corresponding (Grassmanian) coefficients can be computed by CLS Projections. This is illustrated by the identification of the model rank of simple financial risk systems in six Asian countries, in particular in Taiwan. Third, often it is thought that Markowitz' portfolio optimization and exact and complete cash flow accounting are incompatible because of the non-existence, or empirical instability of the information matrix. The problem is caused by the rank constraints imposed by the portfolio accounting identities. But these rank constraints also provide the solution, since they form exact selectors of the portfolio allocations, which are found by simple tensor algebra. This will be illustrated by the optimization of an Asian multi-currency stock investment portfolio.
Author: Christian Hugo Hoffmann
Publisher: Springer
ISBN: 3658200324
Category : Business & Economics
Languages : en
Pages : 377
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Book Description
Christian Hugo Hoffmann undermines the citadel of risk assessment and management, arguing that classical probability theory is not an adequate foundation for modeling systemic and extreme risk in complex financial systems. He proposes a new class of models which focus on the knowledge dimension by precisely describing market participants’ own positions and their propensity to react to outside changes. The author closes his thesis by a synthetical reflection on methods and elaborates on the meaning of decision-making competency in a risk management context in banking. By choosing this poly-dimensional approach, the purpose of his work is to explore shortcomings of risk management approaches of financial institutions and to point out how they might be overcome.
Author: Tomasz Zaleskiewicz
Publisher: Springer Nature
ISBN: 3030455009
Category : Psychology
Languages : en
Pages : 367
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Book Description
This book reviews the latest research from psychology, neuroscience, and behavioral economics evaluating how people make financial choices in real-life circumstances. The volume is divided into three sections investigating financial decision making at the level of the brain, the level of an individual decision maker, and the level of the society, concluding with a discussion of the implications for further research. Among the topics discussed: Neural and hormonal bases of financial decision making Personality, cognitive abilities, emotions, and financial decisions Aging and financial decision making Coping methods for making financial choices under uncertainty Stock market crashes and market bubbles Psychological perspectives on borrowing, paying taxes, gambling, and charitable giving Psychological Perspectives on Financial Decision Making is a useful reference for researchers both in and outside of psychology, including decision-making experts, consumer psychologists, and behavioral economists.
Author: Dragan Pamucar
Publisher: MDPI
ISBN: 3036515763
Category : Computers
Languages : en
Pages : 210
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Book Description
The dynamics of systems have proven to be very powerful tools in understanding the behavior of different natural phenomena throughout the last two centuries. However, the attributes of natural systems are observed to deviate from their classical states due to the effect of different types of uncertainties. Actually, randomness and impreciseness are the two major sources of uncertainties in natural systems. Randomness is modeled by different stochastic processes and impreciseness could be modeled by fuzzy sets, rough sets, Dempster–Shafer theory, etc.
Author: Desheng Dash Wu
Publisher: Springer Nature
ISBN: 3030521974
Category : Business & Economics
Languages : en
Pages : 144
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Book Description
COVID-19 has spread around the world, causing tremendous structural change, and severely affecting global supply chains and financial operations. As such there is a need for analytic tools help deal with the impact of the pandemic on the world’s economies; these tools are not panaceas and certainly won’t cure the problems faced, but they offer a means to aid governments, firms, and individuals in coping with specific problems. This book provides an overview of the COVID-19 pandemic and evaluates its effect on financial and supply chain operations. It then discusses epidemic modeling, presenting sources of quantitative and text data, and describing how models are used to illustrate the pandemic impact on supply chains, macroeconomic performance on financial operations. It highlights the specific experiences of the banking system, which offers predictions of the impact on the Swedish banking sector. Further, it examines models related to pandemic planning, such as evaluation of financial contagion, debt risk analysis, and health system efficiency performance, and addresses specific models of pandemic parameters. The book demonstrates various tools using available data on the ongoing COVID-19 pandemic. While it includes some citations, it focuses on describing the methods and explaining how they work, rather than on theory. The data sets and software presented were all selected on the basis of their widespread availability to any reader with computer links.
Author: Moshe Dror
Publisher: Springer Science & Business Media
ISBN: 9780792374633
Category : Business & Economics
Languages : en
Pages : 810
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Book Description
Writing in honour of Sid Yakowitz, 50 internationally known scholars have collectively contributed 30 papers on modelling uncertainty to this volume. These include papers with a theoretical emphasis and others that focus on applications.
Author: Frank H. Knight
Publisher: Cosimo, Inc.
ISBN: 1602060053
Category : Business & Economics
Languages : en
Pages : 401
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Book Description
A timeless classic of economic theory that remains fascinating and pertinent today, this is Frank Knight's famous explanation of why perfect competition cannot eliminate profits, the important differences between "risk" and "uncertainty," and the vital role of the entrepreneur in profitmaking. Based on Knight's PhD dissertation, this 1921 work, balancing theory with fact to come to stunning insights, is a distinct pleasure to read. FRANK H. KNIGHT (1885-1972) is considered by some the greatest American scholar of economics of the 20th century. An economics professor at the University of Chicago from 1927 until 1955, he was one of the founders of the Chicago school of economics, which influenced Milton Friedman and George Stigler.
Author: Van-Nam Huynh
Publisher: Springer Nature
ISBN: 3031467752
Category : Computers
Languages : en
Pages : 351
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Book Description
These two volumes constitute the proceedings of the 10th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2023, held in Kanazawa, Japan, during November 2-4, 2023. The 58 full papers presented were carefully reviewed and selected from 107 submissions. The papers deal with all aspects of research results, ideas, and experiences of application among researchers and practitioners involved with all aspects of uncertainty modelling and management.
Author: Mykel J. Kochenderfer
Publisher: MIT Press
ISBN: 0262331713
Category : Computers
Languages : en
Pages : 350
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Book Description
An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.
Author: Dan Braha
Publisher: Springer Nature
ISBN: 3030673189
Category : Mathematics
Languages : en
Pages : 446
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Book Description
The International Conference on Complex Systems (ICCS) offers a unique interdisciplinary venue for researchers from the physical and biological sciences, social sciences, psychology and cognitive science, engineering, medicine, human systems, and global systems. This proceedings volume gathers selected papers from the conference. The New England Complex Systems Institute (NECSI) has been instrumental in the development of complex systems science and its applications. NECSI pursues research, education, knowledge dissemination, and community development efforts around the world to promote the study of complex systems and its application for the benefit of society. NECSI hosts the International Conference on Complex Systems and publishes the NECSI Book.
