Download or read book Uncertainty and Expectation written by Gerald Ashley and published by John Wiley & Sons. This book was released on 2005-08-05 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this entertaining and thoughtful book, Gerald Ashley sets out to explain what trading is, and lays out a modus operandi for being a trader and investor. He draws upon market anecdotes and examples from the past, seeking to debunk many myths surrounding financial markets, and to try and make the reader understand the real processes, risks and rewards that drive investment. In particular he examines ideas in market and individual investor behaviour, and questions the usefulness of many of todays standard investment techniques including benchmarks, charts, analysts and 'gurus'. He also lays out simple precepts for understanding investment risk and suggests ideas for managing your investments in today's markets.
Download or read book Post Keynesian Economics written by T. Palley and published by Springer. This book was released on 1996-06-19 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an important and original statement of Post Keynesian macroeconomic theory, focusing on the significance of privately created inside debts and income distribution for the determination of economic activity. The material is presented in a clear and accessible format
Download or read book Nonlinear Expectations and Stochastic Calculus under Uncertainty written by Shige Peng and published by Springer Nature. This book was released on 2019-09-09 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is focused on the recent developments on problems of probability model uncertainty by using the notion of nonlinear expectations and, in particular, sublinear expectations. It provides a gentle coverage of the theory of nonlinear expectations and related stochastic analysis. Many notions and results, for example, G-normal distribution, G-Brownian motion, G-Martingale representation theorem, and related stochastic calculus are first introduced or obtained by the author. This book is based on Shige Peng’s lecture notes for a series of lectures given at summer schools and universities worldwide. It starts with basic definitions of nonlinear expectations and their relation to coherent measures of risk, law of large numbers and central limit theorems under nonlinear expectations, and develops into stochastic integral and stochastic calculus under G-expectations. It ends with recent research topic on G-Martingale representation theorem and G-stochastic integral for locally integrable processes. With exercises to practice at the end of each chapter, this book can be used as a graduate textbook for students in probability theory and mathematical finance. Each chapter also concludes with a section Notes and Comments, which gives history and further references on the material covered in that chapter. Researchers and graduate students interested in probability theory and mathematical finance will find this book very useful.
Download or read book Term Expectation and Uncertainty in Human Decision Behavior written by Jerry D. Tate and published by . This book was released on 1964 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Probability and Statistics written by Michael J. Evans and published by Macmillan. This book was released on 2004 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlike traditional introductory math/stat textbooks, Probability and Statistics: The Science of Uncertainty brings a modern flavor based on incorporating the computer to the course and an integrated approach to inference. From the start the book integrates simulations into its theoretical coverage, and emphasizes the use of computer-powered computation throughout.* Math and science majors with just one year of calculus can use this text and experience a refreshing blend of applications and theory that goes beyond merely mastering the technicalities. They'll get a thorough grounding in probability theory, and go beyond that to the theory of statistical inference and its applications. An integrated approach to inference is presented that includes the frequency approach as well as Bayesian methodology. Bayesian inference is developed as a logical extension of likelihood methods. A separate chapter is devoted to the important topic of model checking and this is applied in the context of the standard applied statistical techniques. Examples of data analyses using real-world data are presented throughout the text. A final chapter introduces a number of the most important stochastic process models using elementary methods. *Note: An appendix in the book contains Minitab code for more involved computations. The code can be used by students as templates for their own calculations. If a software package like Minitab is used with the course then no programming is required by the students.
Download or read book Understanding Uncertainty written by Dennis V. Lindley and published by John Wiley & Sons. This book was released on 2013-12-16 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "...a reference for everyone who is interested in knowing and handling uncertainty." —Journal of Applied Statistics The critically acclaimed First Edition of Understanding Uncertainty provided a study of uncertainty addressed to scholars in all fields, showing that uncertainty could be measured by probability, and that probability obeyed three basic rules that enabled uncertainty to be handled sensibly in everyday life. These ideas were extended to embrace the scientific method and to show how decisions, containing an uncertain element, could be rationally made. Featuring new material, the Revised Edition remains the go-to guide for uncertainty and decision making, providing further applications at an accessible level including: A critical study of transitivity, a basic concept in probability A discussion of how the failure of the financial sector to use the proper approach to uncertainty may have contributed to the recent recession A consideration of betting, showing that a bookmaker's odds are not expressions of probability Applications of the book’s thesis to statistics A demonstration that some techniques currently popular in statistics, like significance tests, may be unsound, even seriously misleading, because they violate the rules of probability Understanding Uncertainty, Revised Edition is ideal for students studying probability or statistics and for anyone interested in one of the most fascinating and vibrant fields of study in contemporary science and mathematics.
Download or read book Principles of Uncertainty written by Joseph B. Kadane and published by CRC Press. This book was released on 2020-11-25 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the first edition: Principles of Uncertainty is a profound and mesmerising book on the foundations and principles of subjectivist or behaviouristic Bayesian analysis. ... the book is a pleasure to read. And highly recommended for teaching as it can be used at many different levels. ... A must-read for sure!—Christian Robert, CHANCE It's a lovely book, one that I hope will be widely adopted as a course textbook. —Michael Jordan, University of California, Berkeley, USA Like the prize-winning first edition, Principles of Uncertainty, Second Edition is an accessible, comprehensive text on the theory of Bayesian Statistics written in an appealing, inviting style, and packed with interesting examples. It presents an introduction to the subjective Bayesian approach which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods. This new edition has been updated throughout and features new material on Nonparametric Bayesian Methods, the Dirichlet distribution, a simple proof of the central limit theorem, and new problems. Key Features: First edition won the 2011 DeGroot Prize Well-written introduction to theory of Bayesian statistics Each of the introductory chapters begins by introducing one new concept or assumption Uses "just-in-time mathematics"—the introduction to mathematical ideas just before they are applied
Download or read book Uncertainty written by Millett Granger Morgan and published by Cambridge University Press. This book was released on 1990 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: A risk analysis textbook which is intended as a basic text for students as well as a reference for practitioners and researchers. It provides a basis for policy analysis and draws upon a variety of case studies.
Download or read book Optimal Control Expectations and Uncertainty written by Sean Holly and published by Cambridge University Press. This book was released on 1989-07-20 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: An examination of how the rational expectations revolution and game theory have enhanced the understanding of how an economy functions.
Download or read book Uncertainty Expectations and Asset Price Dynamics written by Fredj Jawadi and published by Springer. This book was released on 2018-11-30 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written in honor of Emeritus Professor Georges Prat (University of Paris Nanterre, France), this book includes contributions from eminent authors on a range of topics that are of interest to researchers and graduates, as well as investors and portfolio managers. The topics discussed include the effects of information and transaction costs on informational and allocative market efficiency, bubbles and stock price dynamics, paradox of rational expectations and the principle of limited information, uncertainty and expectation hypotheses, oil price dynamics, and nonlinearity in asset price dynamics.
Download or read book Uncertainty Expectations and Financial Instability written by Eric Barthalon and published by Columbia University Press. This book was released on 2014-11-11 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Eric Barthalon applies the neglected theory of psychological time and memory decay of Nobel PrizeÐwinning economist Maurice Allais (1911Ð2010) to model investorsÕ psychology in the present context of recurrent financial crises. Shaped by the behavior of the demand for money during episodes of hyperinflation, AllaisÕs theory proves economic agents perceive the flow of clocksÕ time and forget the past at a context-dependent pace: rapidly in the presence of persistent and accelerating inflation and slowly in the event of the opposite situation. Barthalon recasts AllaisÕs work as a general theory of ÒexpectationsÓ under uncertainty, closing the gap between economic theory and investorsÕ behavior. Barthalon extends AllaisÕs theory to the field of financial instability, demonstrating its relevance to nominal interest rates in a variety of empirical scenarios and the positive nonlinear feedback that exists between asset price inflation and the demand for risky assets. Reviewing the works of the leading protagonists in the expectations controversy, Barthalon exposes the limitations of adaptive and rational expectations models and, by means of the perceived risk of loss, calls attention to the speculative bubbles that lacked the positive displacement discussed in KindlebergerÕs model of financial crises. He ultimately extrapolates Allaisian theory into a pragmatic approach to investor behavior and the natural instability of financial markets. He concludes with the policy implications for governments and regulators. Balanced and coherent, this book will be invaluable to researchers working in macreconomics, financial economics, behavioral finance, decision theory, and the history of economic thought.
Download or read book Risk Uncertainty and Profit written by Frank H. Knight and published by Cosimo, Inc.. This book was released on 2006-11-01 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Scalable Uncertainty Management written by Amol Deshpande and published by Springer Science & Business Media. This book was released on 2010-09-27 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Conference on Scalable Uncertainty Management, SUM 2010, held in Toulouse, France, in September 2010. The 26 revised full papers presented together with the abstracts of 2 invited talks and 6 “discussant” contributions were carefully reviewed and selected from 32 submissions. The papers cover all areas of managing substantial and complex kinds of uncertainty and inconsistency in data and knowledge, including applications in decision-support systems, negotiation technologies, semantic web applications, search engines, ontology systems, information retrieval, natural language processing, information extraction, image recognition, vision systems, text mining, and data mining, and consideration of issues such as provenance, trust, heterogeneity, and complexity of data and knowledge.
Download or read book Keynes on Uncertainty and Tragic Happiness written by Anna M. Carabelli and published by Springer Nature. This book was released on 2021-07-23 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most economists who read the General Theory candidly admitted that they could not understand the theoretical apparatus and found it easy to recast it in traditional terms. This book provides a masterful guide to the generally unrecognized methodological revolution that supported the new theoretical concepts -- a veritable lodestone that complements and expands understanding on the treatment of the economic magnitudes appropriate to the ideal of generality in the social sciences, to the applicability of probability, to the formulation of decision-making under uncertainty, and the foundations of economic policy in interdependent economic systems. _Jan Kregel, Levy Economics Institute Anna Carabelli sets out Keynes’s understanding of economics as a way of thinking, encompassing method and morals, rather than as a doctrine. She does so with her customary admirable scholarship and also her willingness to take controversial positions. I commend the volume most highly to Keynes scholars as a drawing-together and development of the themes that Carabelli has pursued since the publication of her 1988 classic, On Keynes’s Method. Further Keynes’s approach was designed to be applied to different contexts, so I enthusiastically recommend the volume also as a foundation and guide for anyone open to such a ‘new way of reasoning in economics’ for the modern era. _Sheila Dow, University of Stirling This book examines the philosophy and methodology of Keynes, highlighting its novelty and how it presented a new form of economic reasoning. Exploring Keynes’s use of non-demonstrative logic, based on probability, commonalities are found in his economics, ethics, aesthetics, and international relations. Insights are provided into his reasoning and his approach to uncertainty, rationality, measurability of complex magnitudes, moral and rational dilemmas, and irreducible conflicts. This book investigates methodological continuity within Keynes’s work, in particular in relation to uncertainty, complexity, incommensurability, happiness and openness. It will be relevant to students and researchers interested in Keynes, probability, ambiguity, ethics and the history of economic thought.
Download or read book Uncertainty Quantification in Scientific Computing written by Andrew Dienstfrey and published by Springer. This book was released on 2012-08-11 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-proceedings of the 10th IFIP WG 2.5 Working Conference on Uncertainty Quantification in Scientific Computing, WoCoUQ 2011, held in Boulder, CO, USA, in August 2011. The 24 revised papers were carefully reviewed and selected from numerous submissions. They are organized in the following topical sections: UQ need: risk, policy, and decision making, UQ theory, UQ tools, UQ practice, and hot topics. The papers are followed by the records of the discussions between the participants and the speaker.
Download or read book Modelling Under Risk and Uncertainty written by Etienne de Rocquigny and published by John Wiley & Sons. This book was released on 2012-04-12 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modelling has permeated virtually all areas of industrial, environmental, economic, bio-medical or civil engineering: yet the use of models for decision-making raises a number of issues to which this book is dedicated: How uncertain is my model ? Is it truly valuable to support decision-making ? What kind of decision can be truly supported and how can I handle residual uncertainty ? How much refined should the mathematical description be, given the true data limitations ? Could the uncertainty be reduced through more data, increased modeling investment or computational budget ? Should it be reduced now or later ? How robust is the analysis or the computational methods involved ? Should / could those methods be more robust ? Does it make sense to handle uncertainty, risk, lack of knowledge, variability or errors altogether ? How reasonable is the choice of probabilistic modeling for rare events ? How rare are the events to be considered ? How far does it make sense to handle extreme events and elaborate confidence figures ? Can I take advantage of expert / phenomenological knowledge to tighten the probabilistic figures ? Are there connex domains that could provide models or inspiration for my problem ? Written by a leader at the crossroads of industry, academia and engineering, and based on decades of multi-disciplinary field experience, Modelling Under Risk and Uncertainty gives a self-consistent introduction to the methods involved by any type of modeling development acknowledging the inevitable uncertainty and associated risks. It goes beyond the “black-box” view that some analysts, modelers, risk experts or statisticians develop on the underlying phenomenology of the environmental or industrial processes, without valuing enough their physical properties and inner modelling potential nor challenging the practical plausibility of mathematical hypotheses; conversely it is also to attract environmental or engineering modellers to better handle model confidence issues through finer statistical and risk analysis material taking advantage of advanced scientific computing, to face new regulations departing from deterministic design or support robust decision-making. Modelling Under Risk and Uncertainty: Addresses a concern of growing interest for large industries, environmentalists or analysts: robust modeling for decision-making in complex systems. Gives new insights into the peculiar mathematical and computational challenges generated by recent industrial safety or environmental control analysis for rare events. Implements decision theory choices differentiating or aggregating the dimensions of risk/aleatory and epistemic uncertainty through a consistent multi-disciplinary set of statistical estimation, physical modelling, robust computation and risk analysis. Provides an original review of the advanced inverse probabilistic approaches for model identification, calibration or data assimilation, key to digest fast-growing multi-physical data acquisition. Illustrated with one favourite pedagogical example crossing natural risk, engineering and economics, developed throughout the book to facilitate the reading and understanding. Supports Master/PhD-level course as well as advanced tutorials for professional training Analysts and researchers in numerical modeling, applied statistics, scientific computing, reliability, advanced engineering, natural risk or environmental science will benefit from this book.
Download or read book Scalable Uncertainty Management written by Jesse Davis and published by Springer Nature. This book was released on 2020-09-16 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th International Conference on Scalable Uncertainty Management, SUM 2020, which was held in Bozen-Bolzano, Italy, in September 2020. The 12 full, 7 short papers presented in this volume were carefully reviewed and selected from 30 submissions. Besides that, the book also contains 2 abstracts of invited talks, 2 tutorial papers, and 2 PhD track papers. The conference aims to gather researchers with a common interest in managing and analyzing imperfect information from a wide range of fields, such as artificial intelligence and machine learning, databases, information retrieval and data mining, the semantic web and risk analysis. Due to the Corona pandemic SUM 2020 was held as an virtual event.
