			Home About us Contact

Portfolio Selection (portfolio + selection)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	80%

Distribution within Business, Economics, Finance and Accounting

General & Introductory Economics	25%
General & Introductory Finance & Investments	16%

Terms modified by Portfolio Selection

portfolio selection problem

Selected Abstracts

BEHAVIORAL PORTFOLIO SELECTION IN CONTINUOUS TIME

MATHEMATICAL FINANCE, Issue 3 2008
Hanqing Jin
This paper formulates and studies a general continuous-time behavioral portfolio selection model under Kahneman and Tversky's (cumulative) prospect theory, featuring S-shaped utility (value) functions and probability distortions. Unlike the conventional expected utility maximization model, such a behavioral model could be easily mis-formulated (a.k.a. ill-posed) if its different components do not coordinate well with each other. Certain classes of an ill-posed model are identified. A systematic approach, which is fundamentally different from the ones employed for the utility model, is developed to solve a well-posed model, assuming a complete market and general Itô processes for asset prices. The optimal terminal wealth positions, derived in fairly explicit forms, possess surprisingly simple structure reminiscent of a gambling policy betting on a good state of the world while accepting a fixed, known loss in case of a bad one. An example with a two-piece CRRA utility is presented to illustrate the general results obtained, and is solved completely for all admissible parameters. The effect of the behavioral criterion on the risky allocations is finally discussed. [source]

CONTINUOUS-TIME MEAN-VARIANCE PORTFOLIO SELECTION WITH BANKRUPTCY PROHIBITION

MATHEMATICAL FINANCE, Issue 2 2005
Tomasz R. Bielecki
A continuous-time mean-variance portfolio selection problem is studied where all the market coefficients are random and the wealth process under any admissible trading strategy is not allowed to be below zero at any time. The trading strategy under consideration is defined in terms of the dollar amounts, rather than the proportions of wealth, allocated in individual stocks. The problem is completely solved using a decomposition approach. Specifically, a (constrained) variance minimizing problem is formulated and its feasibility is characterized. Then, after a system of equations for two Lagrange multipliers is solved, variance minimizing portfolios are derived as the replicating portfolios of some contingent claims, and the variance minimizing frontier is obtained. Finally, the efficient frontier is identified as an appropriate portion of the variance minimizing frontier after the monotonicity of the minimum variance on the expected terminal wealth over this portion is proved and all the efficient portfolios are found. In the special case where the market coefficients are deterministic, efficient portfolios are explicitly expressed as feedback of the current wealth, and the efficient frontier is represented by parameterized equations. Our results indicate that the efficient policy for a mean-variance investor is simply to purchase a European put option that is chosen, according to his or her risk preferences, from a particular class of options. [source]

Optimal Dynamic Portfolio Selection: Multiperiod Mean-Variance Formulation

MATHEMATICAL FINANCE, Issue 3 2000
Duan Li
The mean-variance formulation by Markowitz in the 1950s paved a foundation for modern portfolio selection analysis in a single period. This paper considers an analytical optimal solution to the mean-variance formulation in multiperiod portfolio selection. Specifically, analytical optimal portfolio policy and analytical expression of the mean-variance efficient frontier are derived in this paper for the multiperiod mean-variance formulation. An efficient algorithm is also proposed for finding an optimal portfolio policy to maximize a utility function of the expected value and the variance of the terminal wealth. [source]

Markowitz's "Portfolio Selection": A Fifty-Year Retrospective

THE JOURNAL OF FINANCE, Issue 3 2002
Mark Rubinstein
First page of article [source]

Disinflation, Real Income Uncertainty and the Demand for Consumer Durables in a Mean,Variance Model of Portfolio Selection

THE MANCHESTER SCHOOL, Issue 2 2001
Jakob B. MadsenArticle first published online: 16 DEC 200
Survey evidence indicates that consumers only expect to be fractionally compensated by the real income reduction of inflation. Incorporating this evidence into a mean,variance model of portfolio selection, this paper shows that demand for durables is a negative function of expected inflation and income uncertainty. Using quarterly data for the USA and annual panel data for the OECD countries, empirical evidence shows that demand for durables is significantly adversely affected by inflation and income uncertainty, and that the recent disinflation has resulted in a significant increase in demand for durables. [source]

Portfolio selection, diversification and fund-of-funds: a note

ACCOUNTING & FINANCE, Issue 2 2005
Simone Brands
G23 Abstract The present paper examines the performance and diversification properties of active Australian equity fund-of-funds (FoF). Simulation analysis is employed to examine portfolio performance as a function of the number of funds in the portfolio. The present paper finds that as the number of funds in an FoF portfolio increases, performance improves in a mean,variance setting; however, measures of skewness and kurtosis behave less favourably given an investor's preferences for the higher moments of the return distribution. The majority of diversification benefits are realized when a portfolio of approximately 6 active equity funds are included in the FoF portfolio. [source]

Portfolio selection on the Madrid Exchange: a compromise programming model

INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, Issue 1 2003
E. Ballestero
As a contribution to portfolio selection analysis, we develop a compromise programming approach to the investor's utility optimum on the Madrid Online Market. This approach derives from linkages between utility functions under incomplete information, Yu's compromise set, and certain biased sets of portfolios on the efficient frontier. These linkages rely on recent theorems in multi,criteria literature, which allow us to approximate the investor's utility optimum between bounds which are determined either by linear programming models or graphic techniques. Returns on 104 stocks are computed from capital gains and cash,flows, including dividends and rights offerings, over the period 1992,1997. The first step consists in normalizing the mean,variance efficient frontier, which is defined in terms of two indexes, profitability and safety. In the second step, interactive dialogues to elicit the investor's preferences for profitability and safety are described. In the third step, the utility optimum for each particular investor who pursues a buy,&,hold policy is bounded on the efficient frontier. From this step, a number of portfolios close to the investor's utility optimum are obtained. In the fourth step, compromise programming is used again to select one ,satisficing' portfolio from the set already bounded for each investor. This step is new with respect to previous papers in which compromise/utility models are employed. Computing processes are detailed in tables and figures which also display the numerical results. Extensions to active management policies are suggested. [source]

A simulation-optimization framework for research and development pipeline management

AICHE JOURNAL, Issue 10 2001
Dharmashankar Subramanian
The Research and Development Pipeline management problem has far-reaching economic implications for new-product-development-driven industries, such as pharmaceutical, biotechnology and agrochemical industries. Effective decision-making is required with respect to portfolio selection and project task scheduling in the face of significant uncertainty and an ever-constrained resource pool. The here-and-now stochastic optimization problem inherent to the management of an R&D Pipeline is described in its most general form, as well as a computing architecture, Sim-Opt, that combines mathematical programming and discrete event system simulation to assess the uncertainty and control the risk present in the pipeline. The R&D Pipeline management problem is viewed in Sim-Opt as the control problem of a performance-oriented, resource-constrained, stochastic, discrete-event, dynamic system. The concept of time lines is used to study multiple unique realizations of the controlled evolution of the discrete-event pipeline system. Four approaches using various degrees of rigor were investigated for the optimization module in Sim-Opt, and their relative performance is explored through an industrially motivated case study. Methods are presented to efficiently integrate information across the time lines from this framework. This integration of information demonstrated in a case study was used to infer a creative operational policy for the corresponding here-and-now stochastic optimization problem. [source]

Optimal Dynamic Portfolio Selection: Multiperiod Mean-Variance Formulation

Project portfolio control and portfolio management performance in different contexts

PROJECT MANAGEMENT JOURNAL, Issue 3 2008
Ralf Müller
Abstract This article investigates the nature and relationship of project portfolio control techniques and portfolio management performance, and how this relationship is moderated by situational idiosyncrasies of internal and external dynamics, industries, governance types, and geographic location. A worldwide questionnaire with 242 responses was used, of which 136 high-performing responses were filtered out for quantitative analysis of best practices. Three portfolio control factors were identified: portfolio selection, portfolio reporting, and decision-making style. Two measures for portfolio management performance were identified: achievement of desired portfolio results and achievement of project and program purpose. The results indicate that different portfolio control mechanisms are associated with different performance measures. A contingency model was developed, including moderating effects by contextual variables. [source]

Disinflation, Real Income Uncertainty and the Demand for Consumer Durables in a Mean,Variance Model of Portfolio Selection

A new class of coherent risk measures based on p -norms and their applications

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 1 2007
Zhiping Chen
Abstract To exercise better control on the lower tail of the loss distribution and to easily describe the investor's risk attitude, a new class of coherent risk measures is proposed in this paper by taking the minimization of p -norms of lower losses with respect to some reference point. We demonstrate that the new risk measure has satisfactory mathematical properties such as convexity, continuity with respect to parameters included in its definition, the relations between two new risk measures are also examined. The application of the new risk measures for optimal portfolio selection is illustrated by using trade data from the Chinese stock markets. Empirical results not only support our theoretical conclusions, but also show the practicability of the portfolio selection model with our new risk measures. Copyright © 2006 John Wiley & Sons, Ltd. [source]

Identification of a spatially efficient portfolio of priority conservation sites in marine and estuarine areas of Florida

AQUATIC CONSERVATION: MARINE AND FRESHWATER ECOSYSTEMS, Issue 4 2009
Laura Geselbracht
Abstract 1.A systematic conservation planning approach using benthic habitat and imperilled species data along with the site prioritization algorithm, MARXAN, was used to identify a spatially efficient portfolio of marine and estuarine sites around Florida with high biodiversity value. 2.Ensuring the persistence of an adequate geographic representation of conservation targets in a particular area is a key goal of conservation. In this context, development and testing of different approaches to spatially-explicit marine conservation planning remains an important priority. 3.This detailed case study serves as a test of existing approaches while also demonstrating some novel ways in which current methods can be tailored to fit the complexities of marine planning. 4.The paper reports on investigations of the influence of varying several algorithm inputs on resulting portfolio scenarios including the conservation targets (species observations, habitat distribution, etc.) included, conservation target goals, and socio-economic factors. 5.This study concluded that engaging stakeholders in the development of a site prioritization framework is a valuable strategy for identifying broadly accepted selection criteria; universal target representation approaches are more expedient to use as algorithm inputs, but may fall short in capturing the impact of historic exploitation patterns for some conservation targets; socio-economic factors are best considered subsequent to the identification of priority conservation sites when biodiversity value is the primary driver of site selection; and the influence of surrogate targets on portfolio selection should be thoroughly investigated to ensure unintended effects are avoided. 6.The priority sites identified in this analysis can be used to guide allocation of limited conservation and management resources. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Risk Measurement and Investment Myopia in Hedge Fund Management,

ASIA-PACIFIC JOURNAL OF FINANCIAL STUDIES, Issue 1 2009
Xun Li
Abstract Lo (2001) surveys the literature on risk management for hedge funds, and recommends a dynamic and transparent risk measurement for the evolutionary hedge fund industry by citing Albert Einstein's comments. This study is to explore the feasibility and advantages of adopting a dynamic absolute-deviation risk measurement in hedge fund management. It does not only provide an optimal asset allocation strategy both analytically and numerically in a dynamic mean-absolute deviation (DMAD) setting for hedge fund managers, but also contributes to mitigation of potential investment myopia problems in their risk-taking behaviors. It sheds light on risk management and investor-fund manager agency conflicts in the hedge fund industry and adds to the literature on portfolio selection and optimal asset allocation. [source]

THE SYSTEMATIC RISK OF DEBT: AUSTRALIAN EVIDENCE,

AUSTRALIAN ECONOMIC PAPERS, Issue 1 2005
KEVIN DAVISArticle first published online: 21 FEB 200
This paper examines systematic risk (betas) of Australian government debt securities for the period 1979,2004 and makes three contributions to academic research and practical debate. First, the empirical work provides direct evidence on the systematic risk of government debt, and provides a benchmark for estimating the systematic risk of corporate debt which is relevant for cost of capital estimation and for optimal portfolio selection by asset managers such as superannuation funds. Second, analysis of reasons for non-zero (and time varying) betas for fixed income securities aids understanding of the primary sources of systematic risk. Third, the results cast light on the appropriate choice of maturity of risk free interest rate for use in the Capital Asset Pricing Model and have implications for the current applicability of historical estimates of the market risk premium. Debt betas are found to be, on average, significantly positive and (as expected) closely related, cross sectionally, to duration. They are, however, subject to significant time series variation, and over the past few years the pre-existing positive correlation between bond and stock returns appears to have vanished. [source]