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Author: Colin Andrew Small Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
Models are often formulated to aid in decision-making. However, the details included or excluded are often determined with minimal examination of the effects. There is a tendency to make models more complex than merited. Yet, decision makers’ risk preferences are often ignored without considering the effect on recommendations. Additionally, modelers do not always understand the difference between preferences toward deterministic outcomes and risk preferences or the impact of modeling conflicting risk and deterministic preferences together in a single component. In this paper, I investigate the relationship between complexity and accuracy, using COVID-19 forecasting as a case study. I find our simple model is comparable in accuracy to highly publicized models, generating among the best-calibrated forecasts. This may be surprising, given the complexity of many high-profile models supported by large teams. However, it is consistent with research suggesting simple models perform very well in a variety of settings. Although utility functions are a fundamental component of decision analysis, they can assume many forms. For small decisions, the choice might not change the decision. But it can greatly affect recommendations for large decisions. There are qualitative recommendations on which functional form to use. But there is no quantitative recommendation relating size of uncertainties to choice of utility function. By maximizing error in certain equivalents when using different utility functions, this paper provides guidance into when to use different utility functions. Although decision makers should be approximately risk neutral for small problems, they are often “risk averse.” Rabin and Thaler showed utility functions modeling small-scale risk aversion result in absurd risk aversion for large uncertainties. They explain small-scale risk aversion is due to loss aversion, where pain from losses exceeds benefit from gains. But preferences for deterministic losses and gains is a deterministic preference and is not equivalent to risk preference. They argue loss aversion caused the observed behavior, yet modelled deterministic and risk preferences in a single factor. In this paper, I show modeling risk and deterministic preference separately can resolve Rabin’s Paradox, underscoring the need to explicitly model both when deterministic preferences can influence decision making or conflict with risk preferences
Author: Colin Andrew Small Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
Models are often formulated to aid in decision-making. However, the details included or excluded are often determined with minimal examination of the effects. There is a tendency to make models more complex than merited. Yet, decision makers’ risk preferences are often ignored without considering the effect on recommendations. Additionally, modelers do not always understand the difference between preferences toward deterministic outcomes and risk preferences or the impact of modeling conflicting risk and deterministic preferences together in a single component. In this paper, I investigate the relationship between complexity and accuracy, using COVID-19 forecasting as a case study. I find our simple model is comparable in accuracy to highly publicized models, generating among the best-calibrated forecasts. This may be surprising, given the complexity of many high-profile models supported by large teams. However, it is consistent with research suggesting simple models perform very well in a variety of settings. Although utility functions are a fundamental component of decision analysis, they can assume many forms. For small decisions, the choice might not change the decision. But it can greatly affect recommendations for large decisions. There are qualitative recommendations on which functional form to use. But there is no quantitative recommendation relating size of uncertainties to choice of utility function. By maximizing error in certain equivalents when using different utility functions, this paper provides guidance into when to use different utility functions. Although decision makers should be approximately risk neutral for small problems, they are often “risk averse.” Rabin and Thaler showed utility functions modeling small-scale risk aversion result in absurd risk aversion for large uncertainties. They explain small-scale risk aversion is due to loss aversion, where pain from losses exceeds benefit from gains. But preferences for deterministic losses and gains is a deterministic preference and is not equivalent to risk preference. They argue loss aversion caused the observed behavior, yet modelled deterministic and risk preferences in a single factor. In this paper, I show modeling risk and deterministic preference separately can resolve Rabin’s Paradox, underscoring the need to explicitly model both when deterministic preferences can influence decision making or conflict with risk preferences
Author: Leonard C. MacLean Publisher: World Scientific ISBN: 9814417351 Category : Business & Economics Languages : en Pages : 941
Book Description
This handbook in two parts covers key topics of the theory of financial decision making. Some of the papers discuss real applications or case studies as well. There are a number of new papers that have never been published before especially in Part II.Part I is concerned with Decision Making Under Uncertainty. This includes subsections on Arbitrage, Utility Theory, Risk Aversion and Static Portfolio Theory, and Stochastic Dominance. Part II is concerned with Dynamic Modeling that is the transition for static decision making to multiperiod decision making. The analysis starts with Risk Measures and then discusses Dynamic Portfolio Theory, Tactical Asset Allocation and Asset-Liability Management Using Utility and Goal Based Consumption-Investment Decision Models.A comprehensive set of problems both computational and review and mind expanding with many unsolved problems are in an accompanying problems book. The handbook plus the book of problems form a very strong set of materials for PhD and Masters courses both as the main or as supplementary text in finance theory, financial decision making and portfolio theory. For researchers, it is a valuable resource being an up to date treatment of topics in the classic books on these topics by Johnathan Ingersoll in 1988, and William Ziemba and Raymond Vickson in 1975 (updated 2 nd edition published in 2006).
Author: Tamar Kugler Publisher: Springer Science & Business Media ISBN: 038777131X Category : Business & Economics Languages : en Pages : 364
Book Description
This text examines new research at the interface of operations research, behavioral and cognitive sciences, and decision analysis. From the cognitive behaviorist who collects empirical evidence as to how people make decisions to the engineer and economist who are the consumers of such understanding, the reader encounters the familiar Traveling Salesman Problem and Prisoner's dilemma, how agricultural decisions are made in Argentina's Pampas region, and some social goals that come into play as an element of rational decision-making. In these 14 self-contained chapters, broad topics covered include the integration of decision analysis and behavioral models, innovations in behavioral models, exploring descriptive behavior models, and experimental studies.
Author: Danny Samson Publisher: CRC Press ISBN: 9780256061628 Category : Business & Economics Languages : en Pages : 1536
Book Description
This text focuses on how decision analysis can be used to support the managerial decision process. It supports professors and students in the classroom with extensive case studies and problem sets, and with Arborist software and documentation.
Author: J. Geweke Publisher: Springer Science & Business Media ISBN: 9780792319047 Category : Business & Economics Languages : en Pages : 282
Book Description
As desired, the infonnation demand correspondence is single valued at equilibrium prices. Hence no planner is needed to assign infonnation allocations to individuals. Proposition 4. For any given infonnation price system p E . P (F *), almost every a E A demands a unique combined infonnation structure (although traders may be indifferent among partial infonnation sales from different information allocations, etc. ). In particular, the aggregate excess demand correspondence for net combined infonnation trades is a continuous function. Proof Uniqueness fails only if an agent can obtain the same expected utility from two or more net combined infonnation allocations. If this happens, appropriate slight perturbations of personal probability vectors destroy the equality unless the utility functions and wealth allocations were independent across states. Yet, when utilities and wealths don't depend on states in S, no infonnation to distinguish the states is desired, so that the demand for such infonnation structures must equal zero. To show the second claim, recall that if the correspondence is single valued for almost every agent, then its integral is also single valued. Finally, note that an upper hemicontinuous (by Proposition 2) correspondence which is single valued everywhere is, in fact, a continuous function. [] REFERENCES Allen, Beth (1986a). "The Demand for (Differentiated) Infonnation"; Review of Economic Studies. 53. (311-323). Allen, Beth (1986b). "General Equilibrium with Infonnation Sales"; Theory and Decision. 21. (1-33). Allen, Beth (1990). "Infonnation as an Economic Commodity"; American Economic Review. 80. (268-273).
Author: Edgardo Bucciarelli Publisher: Springer Nature ISBN: 3030382273 Category : Technology & Engineering Languages : en Pages : 334
Book Description
This book is based on the International Conference on Decision Economics (DECON 2019). Highlighting the fact that important decision-making takes place in a range of critical subject areas and research fields, including economics, finance, information systems, psychology, small and international business, management, operations, and production, the book focuses on analytics as an emerging synthesis of sophisticated methodology and large data systems used to guide economic decision-making in an increasingly complex business environment. DECON 2019 was organised by the University of Chieti-Pescara (Italy), the National Chengchi University of Taipei (Taiwan), and the University of Salamanca (Spain), and was held at the Escuela politécnica Superior de Ávila, Spain, from 26th to 28th June, 2019. Sponsored by IEEE Systems Man and Cybernetics Society, Spain Section Chapter, and IEEE Spain Section (Technical Co-Sponsor), IBM, Indra, Viewnext, Global Exchange, AEPIA-and-APPIA, with the funding supporting of the Junta de Castilla y León, Spain (ID: SA267P18-Project co-financed with FEDER funds)
Author: Bertrand Munier Publisher: Springer Science & Business Media ISBN: 9401722986 Category : Business & Economics Languages : en Pages : 443
Book Description
Models and Experiments in Risk and Rationality presents original contributions to the areas of individual choice, experimental economics, operations and analysis, multiple criteria decision making, market uncertainty, game theory and social choice. The papers, which were presented at the FUR VI conference, are arranged to appear in order of increasing complexity of the decision environment or social context in which they situate themselves. The first section `Psychological Aspects of Risk-Bearing', considers choice at the purely individual level and for the most part, free of any specific economic or social context. The second section examines individual choice within the classical expected utility approach while the third section works from a perspective that includes non-expected utility preferences over lotteries. Section four, `Multiple Criteria Decision-Making Under Uncertainty', considers the more specialized but crucial context of uncertain choice involving tradeoffs between competing criteria -- a field which is becoming of increasing importance in applied decision analysis. The final two sections examine uncertain choice in social or group contexts.
Author: Ralf Peter Wüstermann Publisher: ISBN: 9783832544416 Category : Languages : en Pages : 280
Book Description
During complex decisions processes, such as a direct investment in Brazil, the risk aversion of a decision maker influences if and to which extent a company invests directly in Brazil. Furthermore, the special economic situation of SMEs determines the degree of risk aversion of the decision makers. In the current state of scientific discussion, no model for risk aversion exists. Therefore it is not possible to explain scientifically the risk-averse decision-making behavior and the influence of the economic situation of decision makers to complex investment decisions. To answer the thesis, a model of risk aversion with the variables risk expectation, experience, information, intuition, risk preferences and risk perception is developed. This doctoral thesis also investigated the relationship between the variables. The variables of the model of risk aversion are verified with the example of the risk aversion decision-making behavior of decision makers in SMEs at a Brazilian direct investment.
Author: Mark J. Machina Publisher: Springer Science & Business Media ISBN: 1475745923 Category : Business & Economics Languages : en Pages : 373
Book Description
Beliefs, Interactions and Preferences in Decision Making mixes a selection of papers, presented at the Eighth Foundations and Applications of Utility and Risk Theory (`FUR VIII') conference in Mons, Belgium, together with a few solicited papers from well-known authors in the field. This book addresses some of the questions that have recently emerged in the research on decision-making and risk theory. In particular, authors have modeled more and more as interactions between the individual and the environment or between different individuals the emergence of beliefs as well as the specific type of information treatment traditionally called `rationality'. This book analyzes several cases of such an interaction and derives consequences for the future of decision theory and risk theory. In the last ten years, modeling beliefs has become a specific sub-field of decision making, particularly with respect to low probability events. Rational decision making has also been generalized in order to encompass, in new ways and in more general situations than it used to be fitted to, multiple dimensions in consequences. This book deals with some of the most conspicuous of these advances. It also addresses the difficult question to incorporate several of these recent advances simultaneously into one single decision model. And it offers perspectives about the future trends of modeling such complex decision questions. The volume is organized in three main blocks: The first block is the more `traditional' one. It deals with new extensions of the existing theory, as is always demanded by scientists in the field. A second block handles specific elements in the development of interactions between individuals and their environment, as defined in the most general sense. The last block confronts real-world problems in both financial and non-financial markets and decisions, and tries to show what kind of contributions can be brought to them by the type of research reported on here.
Author: Colin Andrew Small
Author: Colin Andrew Small
Author: Leonard C. MacLean
Author: Tamar Kugler
Author: Danny Samson
Author: J. Geweke
Author: Edgardo Bucciarelli
Author: Bertrand Munier
Author: Ralf Peter Wüstermann
Author: Mark J. Machina
Author: BUNN