2 edition of On portfolio modelling in multiple criteria situations under uncertainty found in the catalog.
On portfolio modelling in multiple criteria situations under uncertainty
Alan P. Muhlemann
by Manchester Business School, Centre for Business Research in Manchester
Written in English
|Statement||by A.P. Muhlemann, A.G.Lockett and A.E. Gear.|
|Series||Working paper series -- 31.|
|Contributions||Gear, Tony., Lockett, Alan Geoffrey.|
|The Physical Object|
|Number of Pages||21|
Selecting a renewable energy source portfolio is an uncertain multi-criteria decision-making (MCDM) problem. In particular, it involves searching for the best portfolio of renewable energy that meets the decision maker’s preferences by considering and leveraging conflicting criteria such as technical, environmental, societal, and economic. To tackle such complex problems, this paper proposes an efficient method, called multi-segment . Risk-Management Models Based on the Portfolio Theory Using Historical Data under Uncertainty: /ch This chapter considers various types of risk-management models based on the portfolio theory under some social uncertainty .
57 Velasquez and Hester: An Analysis of Multi-Criteria Decision Making Methods IJOR Vol. 10, No. 2, () Multi-Attribute Utility Theory (MAUT) Literature Review Multi-Attribute Utility Theory (see Fishburn, ; Keeney, . bundle of a project portfolio may over- or under-estimate the value of managerial flexibility and then propose a revised valuation model of project portfolio under uncertainty. The DCF model is the most widely used method in the valuation of projects, firms, or assets that are expected to earn a stream of cash flow over time.
d. in a situation of uncertainty. The analysis of a complex decision situation by constructing a mathematical model of the situation and then performing a large number of iterations in order to determine the probability distribution of outcomes is called Which of the following is a way to deal with decision making under uncertainty? a. realms of decision-making under either: (a) Certainty, where each action is known to lead invariably to a specific outcome. (b) Risk, where each action leads to one of a set of possible specific outcomes, each outcome occurring with a known probability. (c) Uncertainty, where actions may lead to a set of.
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There have been many models for portfolio selection, but most do not explicitly include uncertainty and multiple objectives. This paper presents an approach that includes these aspects using a form of stochastic integer programming with recourse.
The method involves the use of a time‐based decision tree structure called a “project tree.”Cited by: Portfolio Modeling in Multiple-Criteria Situations Under Uncertainty Article in Decision Sciences 9(4) - June with 4 Reads How we measure 'reads'.
PORTFOLIO MODELING IN MULTIPLE‐CRITERIA SITUATIONS UNDER UNCERTAINTY Muhlemann, Alan Paul; Lockett, Alan Geoffrey; Gear, Anthony Edward There have been many models for portfolio selection, but most do not explicitly include uncertainty and multiple objectives.
This paper presents an approach that includes these aspects using a form of stochastic integer programming with recourse. Abstract Harrington and Fischer discuss some of the limitations of a model presented by Muhlemann, Lockett, and Gear for the portfolio selection problem in multiple-criteria situations under.
This paper discusses a portfolio investment with options in such a kind of situation. Treating the stock index price as an uncertain variable, we build an uncertain mean-chance portfolio model based on uncertainty theory and provide the equivalent form of the by: 1. LIFETIME PORTFOLIO SELECTION UNDER UNCERTAINTY: THE CONTINUOUS-TIME CASE Robert C.
I Introduction M OST models of portfolio selection have been one-period models. I examine the combined problem of optimal portfolio selec- tion and consumption rules for an individual in a continuous-time model where his income is. Publisher Summary. This chapter discusses models and methods in multiple objectives decision making.
Multicriteria decision making (MCDM) is a world of concepts, approaches, models, and methods to help the decision makers to describe, evaluate, sort, rank, select, or objects, candidates, products, projects, etc.
on the basis of an evaluation expressed by scores, values. The first step is to assess your portfolio with the current situation in mind. Start off by evaluating the projects in your company’s project portfolio and deciding where plans may need to change.
Consider every initiative in the pipeline and look at any dependencies that exist between the various projects. model, which is the workhorse of modern economics. We’ll consider the foundations of this model, and then use it to develop basic properties of preference and choice in the presence of uncertainty: measures of risk aversion, rankings of uncertain prospects, and comparative statics of choice under uncertainty.
A situation of uncertainty arises when there can be more than one possible consequences of selecting any course of action. In terms of the payoff matrix, if the decision-maker selects A 1, his payoff can be X 11, X 12, X 13, etc., depending upon which state of nature S 1, S 2, S 3, etc., is going to occur.
Harrington and Fischer 12) discuss some of the limitations of a model presented by Muhlemaiin, Lockett, and Gear (81 tor the portfolio selection problem in multiple-criteria situations under uncertainty. They go on to propose integer goal programming and simulation as an alternative solution procedure.
Decision Making Under Uncertainty Theory And Application. Welcome,you are looking at books for reading, the Decision Making Under Uncertainty Theory And Application, you will able to read or download in Pdf or ePub books and notice some of author may have lock the live reading for some of ore it need a FREE signup process to obtain the book.
Portfolio Selection under Model Uncertainty 3 only partial moment information of underlying probability measure is available. For example, El Ghaoui, Oks, and Oustry  considered a portfolio selection problem that minimizes worst-case value-at.
Fang et al. [ 35] proposed a portfolio rebalancing model with transaction costs based on fuzzy decision theory considering three criteria: return, risk, and liquidity.
The main focus of this paper is to propose a mean-entropy-skewness portfolio selection framework with transaction cost having returns in the form of uncertain variables.
This book is a tour de force for its systematic treatment of the latest advances in decision making and planning under uncertainty. The detailed discussion on modeling issues and computational efficiency within real-world applications makes it invaluable for students and practitioners alike.
Adiel Teixeira de Almeida-Filho, Diogo Ferreira de Lima Silva, Luciano Ferreira, Financial modelling with multiple criteria decision making: A systematic literature review, Journal of the Operational Research Society, /, (), (). Portfolio Selection with Parameter and Model Uncertainty: A Multi-Prior Approach Abstract In this paper, we extend the mean-variance portfolio model where expected returns are ob-tained using maximum likelihood estimation to explicitly account for uncertainty about the estimated expected returns.
The conventional portfolio selection models are generally obtained by probability theory based on precise historical data. However, in real situation, there are many input parameters in the securities, such as market forces of supply and demand, political factors and company performance, which are associated with non-statistical uncertainty and.
Our article is closely related to several papers in the literature on portfolio decisions that are robust to model uncertainty or incorporate aversion to ambiguity.
7 Goldfarb and Iyengar (), Halldórsson and Tütüncü (), and Tütüncü and Koenig () develop algorithms for solving max-min saddle-point problems numerically and. In a world under uncertainty, the beliefs for the information underlie the behavioral style of portfolio decisions in portfolio management.
In this work, we use the copula-based ordered modular averages (OMAs) in the calculation of the mean and variance of the assets’ returns for portfolio selection to capture the beliefs of the investors and.
Spatial conservation planning under uncertainty: adapting to climate change risks using modern portfolio theory 22 July | Ecological Applications, Vol. 29, No. 7 Reducing wall-clock time for the computation of all efficient extreme points in multiple objective linear programming.Portfolio optimization under model uncertainty and BSDE games Bernt Øksendal Department of Mathematics, Center of Mathematics for Applications (CMA), University of Oslo, P.O.
BoxBlindern, N Oslo, Norway ; Norwegian School of Economics and Business Administration, Helleve N Bergen, Norway Correspondence oksendal.International Portfolio Allocation under Model Uncertainty face model uncertainty in the sense that they surround the true probability distribution with use ambiguity aversion based on recursive multiple priors.
In particular, Epstein and Miao () develop a two-country continuos-time dynamic general equilibrium model.