Author: J.K. Sengupta
Publisher: Springer Science & Business Media
ISBN: 3642701639
Category : Business & Economics
Languages : en
Pages : 295
Book Description
Understanding the stochastic enviornment is as much important to the manager as to the economist. From production and marketing to financial management, a manager has to assess various costs imposed by uncertainty. The economist analyzes the role of incomplete and too often imperfect information structures on the optimal decisions made by a firm. The need for understanding the role of uncertainty in quantitative decision models, both in economics and management science provide the basic motivation of this monograph. The stochastic environment is analyzed here in terms of the following specific models of optimization: linear and quadratic models, linear programming, control theory and dynamic programming. Uncertainty is introduced here through the para meters, the constraints, and the objective function and its impact evaluated. Specifically recent developments in applied research are emphasized, so that they can help the decision-maker arrive at a solution which has some desirable charac teristics like robustness, stability and cautiousness. Mathematical treatment is kept at a fairly elementary level and applied as pects are emphasized much more than theory. Moreover, an attempt is made to in corporate the economic theory of uncertainty into the stochastic theory of opera tions research. Methods of optimal decision rules illustrated he re are applicable in three broad areas: (a) applied economic models in resource allocation and economic planning, (b) operations research models involving portfolio analysis and stochastic linear programming and (c) systems science models in stochastic control and adaptive behavior.
Optimal Decisions Under Uncertainty
Author: J.K. Sengupta
Publisher: Springer Science & Business Media
ISBN: 3642701639
Category : Business & Economics
Languages : en
Pages : 295
Book Description
Understanding the stochastic enviornment is as much important to the manager as to the economist. From production and marketing to financial management, a manager has to assess various costs imposed by uncertainty. The economist analyzes the role of incomplete and too often imperfect information structures on the optimal decisions made by a firm. The need for understanding the role of uncertainty in quantitative decision models, both in economics and management science provide the basic motivation of this monograph. The stochastic environment is analyzed here in terms of the following specific models of optimization: linear and quadratic models, linear programming, control theory and dynamic programming. Uncertainty is introduced here through the para meters, the constraints, and the objective function and its impact evaluated. Specifically recent developments in applied research are emphasized, so that they can help the decision-maker arrive at a solution which has some desirable charac teristics like robustness, stability and cautiousness. Mathematical treatment is kept at a fairly elementary level and applied as pects are emphasized much more than theory. Moreover, an attempt is made to in corporate the economic theory of uncertainty into the stochastic theory of opera tions research. Methods of optimal decision rules illustrated he re are applicable in three broad areas: (a) applied economic models in resource allocation and economic planning, (b) operations research models involving portfolio analysis and stochastic linear programming and (c) systems science models in stochastic control and adaptive behavior.
Publisher: Springer Science & Business Media
ISBN: 3642701639
Category : Business & Economics
Languages : en
Pages : 295
Book Description
Understanding the stochastic enviornment is as much important to the manager as to the economist. From production and marketing to financial management, a manager has to assess various costs imposed by uncertainty. The economist analyzes the role of incomplete and too often imperfect information structures on the optimal decisions made by a firm. The need for understanding the role of uncertainty in quantitative decision models, both in economics and management science provide the basic motivation of this monograph. The stochastic environment is analyzed here in terms of the following specific models of optimization: linear and quadratic models, linear programming, control theory and dynamic programming. Uncertainty is introduced here through the para meters, the constraints, and the objective function and its impact evaluated. Specifically recent developments in applied research are emphasized, so that they can help the decision-maker arrive at a solution which has some desirable charac teristics like robustness, stability and cautiousness. Mathematical treatment is kept at a fairly elementary level and applied as pects are emphasized much more than theory. Moreover, an attempt is made to in corporate the economic theory of uncertainty into the stochastic theory of opera tions research. Methods of optimal decision rules illustrated he re are applicable in three broad areas: (a) applied economic models in resource allocation and economic planning, (b) operations research models involving portfolio analysis and stochastic linear programming and (c) systems science models in stochastic control and adaptive behavior.
Optimisation of Production Under Uncertainty
Author: Svend Rasmussen
Publisher: Springer Science & Business Media
ISBN: 3642216862
Category : Business & Economics
Languages : en
Pages : 83
Book Description
The book provides a short review of the classical approach to planning and decision making under uncertainty. It further explains the concept of state-contingent goods, and it extends earlier work on the state-contingent approach to describing production under uncertainty to the problems involved in optimising production under uncertainty.
Publisher: Springer Science & Business Media
ISBN: 3642216862
Category : Business & Economics
Languages : en
Pages : 83
Book Description
The book provides a short review of the classical approach to planning and decision making under uncertainty. It further explains the concept of state-contingent goods, and it extends earlier work on the state-contingent approach to describing production under uncertainty to the problems involved in optimising production under uncertainty.
Technical Reports Awareness Circular : TRAC.
Optimal Fiscal Adjustment under Uncertainty
Author: Rossen Rozenov
Publisher: International Monetary Fund
ISBN: 1475561385
Category : Business & Economics
Languages : en
Pages : 51
Book Description
The paper offers a non-probabilistic framework for representation of uncertainty in the context of a simple linear-quadratic model of fiscal adjustment. Instead of treating model disturbances as random variables with known probability distributions, it is only assumed that they belong to some pre-specified compact set. Such an approach is appropriate when the decision maker does not have enough information to form probabilistic beliefs or when considerations for robustness are important. Solution of the model in the minimax sense when disturbance sets are ellipsoids is obtained and the application of the method is illustrated using the example of Portugal.
Publisher: International Monetary Fund
ISBN: 1475561385
Category : Business & Economics
Languages : en
Pages : 51
Book Description
The paper offers a non-probabilistic framework for representation of uncertainty in the context of a simple linear-quadratic model of fiscal adjustment. Instead of treating model disturbances as random variables with known probability distributions, it is only assumed that they belong to some pre-specified compact set. Such an approach is appropriate when the decision maker does not have enough information to form probabilistic beliefs or when considerations for robustness are important. Solution of the model in the minimax sense when disturbance sets are ellipsoids is obtained and the application of the method is illustrated using the example of Portugal.
Mathematical Methods in Risk Theory
Author: Hans Bühlmann
Publisher: Springer Science & Business Media
ISBN: 3540307117
Category : Mathematics
Languages : en
Pages : 218
Book Description
From the reviews: "The huge literature in risk theory has been carefully selected and supplemented by personal contributions of the author, many of which appear here for the first time. The result is a systematic and very readable book, which takes into account the most recent developments of the field. It will be of great interest to the actuary as well as to the statistician . . ." -- Math. Reviews Vol. 43
Publisher: Springer Science & Business Media
ISBN: 3540307117
Category : Mathematics
Languages : en
Pages : 218
Book Description
From the reviews: "The huge literature in risk theory has been carefully selected and supplemented by personal contributions of the author, many of which appear here for the first time. The result is a systematic and very readable book, which takes into account the most recent developments of the field. It will be of great interest to the actuary as well as to the statistician . . ." -- Math. Reviews Vol. 43
Economic and Financial Decisions under Risk
Author: Louis Eeckhoudt
Publisher: Princeton University Press
ISBN: 1400829216
Category : Business & Economics
Languages : en
Pages : 245
Book Description
An understanding of risk and how to deal with it is an essential part of modern economics. Whether liability litigation for pharmaceutical firms or an individual's having insufficient wealth to retire, risk is something that can be recognized, quantified, analyzed, treated--and incorporated into our decision-making processes. This book represents a concise summary of basic multiperiod decision-making under risk. Its detailed coverage of a broad range of topics is ideally suited for use in advanced undergraduate and introductory graduate courses either as a self-contained text, or the introductory chapters combined with a selection of later chapters can represent core reading in courses on macroeconomics, insurance, portfolio choice, or asset pricing. The authors start with the fundamentals of risk measurement and risk aversion. They then apply these concepts to insurance decisions and portfolio choice in a one-period model. After examining these decisions in their one-period setting, they devote most of the book to a multiperiod context, which adds the long-term perspective most risk management analyses require. Each chapter concludes with a discussion of the relevant literature and a set of problems. The book presents a thoroughly accessible introduction to risk, bridging the gap between the traditionally separate economics and finance literatures.
Publisher: Princeton University Press
ISBN: 1400829216
Category : Business & Economics
Languages : en
Pages : 245
Book Description
An understanding of risk and how to deal with it is an essential part of modern economics. Whether liability litigation for pharmaceutical firms or an individual's having insufficient wealth to retire, risk is something that can be recognized, quantified, analyzed, treated--and incorporated into our decision-making processes. This book represents a concise summary of basic multiperiod decision-making under risk. Its detailed coverage of a broad range of topics is ideally suited for use in advanced undergraduate and introductory graduate courses either as a self-contained text, or the introductory chapters combined with a selection of later chapters can represent core reading in courses on macroeconomics, insurance, portfolio choice, or asset pricing. The authors start with the fundamentals of risk measurement and risk aversion. They then apply these concepts to insurance decisions and portfolio choice in a one-period model. After examining these decisions in their one-period setting, they devote most of the book to a multiperiod context, which adds the long-term perspective most risk management analyses require. Each chapter concludes with a discussion of the relevant literature and a set of problems. The book presents a thoroughly accessible introduction to risk, bridging the gap between the traditionally separate economics and finance literatures.
Handbook of the Economics of Risk and Uncertainty
Author: Mark Machina
Publisher: Newnes
ISBN: 0444536868
Category : Business & Economics
Languages : en
Pages : 897
Book Description
The need to understand the theories and applications of economic and finance risk has been clear to everyone since the financial crisis, and this collection of original essays proffers broad, high-level explanations of risk and uncertainty. The economics of risk and uncertainty is unlike most branches of economics in spanning from the individual decision-maker to the market (and indeed, social decisions), and ranging from purely theoretical analysis through individual experimentation, empirical analysis, and applied and policy decisions. It also has close and sometimes conflicting relationships with theoretical and applied statistics, and psychology. The aim of this volume is to provide an overview of diverse aspects of this field, ranging from classical and foundational work through current developments. - Presents coherent summaries of risk and uncertainty that inform major areas in economics and finance - Divides coverage between theoretical, empirical, and experimental findings - Makes the economics of risk and uncertainty accessible to scholars in fields outside economics
Publisher: Newnes
ISBN: 0444536868
Category : Business & Economics
Languages : en
Pages : 897
Book Description
The need to understand the theories and applications of economic and finance risk has been clear to everyone since the financial crisis, and this collection of original essays proffers broad, high-level explanations of risk and uncertainty. The economics of risk and uncertainty is unlike most branches of economics in spanning from the individual decision-maker to the market (and indeed, social decisions), and ranging from purely theoretical analysis through individual experimentation, empirical analysis, and applied and policy decisions. It also has close and sometimes conflicting relationships with theoretical and applied statistics, and psychology. The aim of this volume is to provide an overview of diverse aspects of this field, ranging from classical and foundational work through current developments. - Presents coherent summaries of risk and uncertainty that inform major areas in economics and finance - Divides coverage between theoretical, empirical, and experimental findings - Makes the economics of risk and uncertainty accessible to scholars in fields outside economics
Macroeconomic Prospects for a Small Oil Exporting Country
Author: O. Bjerkholt
Publisher: Springer Science & Business Media
ISBN: 9400951272
Category : Business & Economics
Languages : en
Pages : 318
Book Description
Publisher: Springer Science & Business Media
ISBN: 9400951272
Category : Business & Economics
Languages : en
Pages : 318
Book Description
Optimal Control, Expectations and Uncertainty
Author: Sean Holly
Publisher: Cambridge University Press
ISBN: 0521264448
Category : Business & Economics
Languages : en
Pages : 258
Book Description
An examination of how the rational expectations revolution and game theory have enhanced the understanding of how an economy functions.
Publisher: Cambridge University Press
ISBN: 0521264448
Category : Business & Economics
Languages : en
Pages : 258
Book Description
An examination of how the rational expectations revolution and game theory have enhanced the understanding of how an economy functions.
Robust Discrete Optimization and Its Applications
Author: Panos Kouvelis
Publisher: Springer Science & Business Media
ISBN: 1475726201
Category : Mathematics
Languages : en
Pages : 373
Book Description
This book deals with decision making in environments of significant data un certainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness ap proach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. The main motivating factors for a decision maker to use the robustness approach are: • It does not ignore uncertainty and takes a proactive step in response to the fact that forecasted values of uncertain parameters will not occur in most environments; • It applies to decisions of unique, non-repetitive nature, which are common in many fast and dynamically changing environments; • It accounts for the risk averse nature of decision makers; and • It recognizes that even though decision environments are fraught with data uncertainties, decisions are evaluated ex post with the realized data. For all of the above reasons, robust decisions are dear to the heart of opera tional decision makers. This book takes a giant first step in presenting decision support tools and solution methods for generating robust decisions in a variety of interesting application environments. Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making.
Publisher: Springer Science & Business Media
ISBN: 1475726201
Category : Mathematics
Languages : en
Pages : 373
Book Description
This book deals with decision making in environments of significant data un certainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness ap proach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. The main motivating factors for a decision maker to use the robustness approach are: • It does not ignore uncertainty and takes a proactive step in response to the fact that forecasted values of uncertain parameters will not occur in most environments; • It applies to decisions of unique, non-repetitive nature, which are common in many fast and dynamically changing environments; • It accounts for the risk averse nature of decision makers; and • It recognizes that even though decision environments are fraught with data uncertainties, decisions are evaluated ex post with the realized data. For all of the above reasons, robust decisions are dear to the heart of opera tional decision makers. This book takes a giant first step in presenting decision support tools and solution methods for generating robust decisions in a variety of interesting application environments. Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making.