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"PORTFOLIO RISK"
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Modeling of Project Portfolio Risk Evolution and Response under the Influence of Interactions
Due to dynamic changes in both internal and external environments, the risk evolution of the project portfolio (PP) becomes extremely complicated, thereby increasing the difficulties of effective risk response. In particular, the real-time influence of risk interactions on the evolution of project portfolio risk (PPR) often goes unnoticed. Meanwhile, risk contagiousness is completely ignored in risk response. To tackle this challenge, this study proposes a PPR evolution and response (PPRER) model by improving the Barrat–Barthelemy–Vespignani (BBV) model and by introducing the evolutionary dynamics method into the PPR response research. The feasibility and applicability of the proposed model are verified through a numerical illustration. Computational results demonstrate that the proposed model can simulate the evolution process of PPRs under the influence of their interactions and give a snapshot of the real-time interactive relationship between PPRs. Based on the obtained results, decision-makers can take effective risk responses by identifying critical strategy intrusion nodes at any time in the evolution process.
Journal Article
Shedding New Light on Project Portfolio Risk Management
This paper constitutes an innovative attempt to analyse the risks and negative phenomena dependencies within a project portfolio. Based on the available literature, the risks and negative phenomena (that is, the problems with the availability of resources, interpersonal conflicts, irregularities in the portfolio balance, etc.) specific to a project portfolio were identified. Theoretical constructs were then used to connect the identified risks with the negative phenomena. Structural equations were used to confirm the existence and quality of these constructs, as well as models describing connections between phenomena. The determination of the structural equations also provided a setting in which statistical methods (χ2, RMSEA and CFI) could be used to investigate the level of fit of the constructs and models to the empirical data.
Journal Article
How to Construct a Lower Risk FOF Based on Correlation Network? The Method of Principal Component Risk Parity Asset Allocation
In order to build a low-risk Fund of Funds (FOF), from the perspective of correlation, the principal component factor is used to improve the traditional risk parity model. Principal component analysis is used to decompose the underlying assets and generate unrelated principal component factors, and then the authors can construct a principal component risk parity portfolio. The proposed empirical results based on China’s mutual fund market show that the performance of principal component risk parity portfolio (PCRPP) is better than that of equal weight portfolio (EWP) and traditional risk parity portfolio (RPP). That is to say, not only the PCRPP in this paper has much lower risk than EWP and RPP, but also slightly better than EWP and RPP in terms of average return. Moreover, the study of dividing the underlying assets shows that the PCRPP in this paper is not sensitive to the underlying assets. The PCRPP in this paper is better than EWP and RPP for both the better performing funds and the worse performing funds. In addition, the empirical results on dynamic portfolio adjustments show that it is not appropriate to adjust asset allocation too frequently when the expected rate of return is calculated using the arithmetic mean.
Journal Article
Alternative decision-making models for financial portfolio management : emerging research and opportunities
\"This book focuses on the application of the methods organized in statistical physics, fuzzy logic, neuro nets and combinatorial stochastic processes which have been proven useful in analyzing complex evolving systems. It explores real data cases that provide upper level students and investment professionals with the concepts and tools they need to make intelligent decisions under risk\"-- Provided by publisher.
Book
Worst-Case Value-At-Risk and Robust Portfolio Optimization: A Conic Programming Approach
Classical formulations of the portfolio optimization problem, such as mean-variance or Value-at-Risk (VaR) approaches, can result in a portfolio extremely sensitive to errors in the data, such as mean and covariance matrix of the returns. In this paper we propose a way to alleviate this problem in a tractable manner. We assume that the distribution of returns is partially known, in the sense that only bounds on the mean and covariance matrix are available. We define the worst-case Value-at-Risk as the largest VaR attainable, given the partial information on the returns' distribution. We consider the problem of computing and optimizing the worst-case VaR, and we show that these problems can be cast as semidefinite programs. We extend our approach to various other partial information on the distribution, including uncertainty in factor models, support constraints, and relative entropy information.
Journal Article
The principles of alternative investments management : a study of the global market
\"The purpose of this book is to present the principles of alternative investments in management. The individual chapters provide a detailed analysis of various classes of alternative investments on the financial market. Despite many different definitions of alternative investments, it can be assumed that a classical approach to alternative investments includes hedge funds, fund of funds (FOF), managed accounts, structured products and private equity/venture capital. Alternative investment in keeping with this broad definition is the subject of consideration here. The theoretical part of each chapter is meant to collect, systematize and deepen readers' understanding of a given investment category, while the practical part of each focuses on an analysis of the current state of development of alternative investments on the global market and outlines the prospects of future market development.\" -- Back cover.
Book
Family ownership and acquisition behavior in publicly-traded companies
Much of the literature on corporate acquisitions has focused on managerial incentives for making acquisitions but has underemphasized the role played by the social context of major shareholders. This study of Fortune 1000 firms argues that the priorities and risk preferences of family owners can have important implications not only for the volume but also for the diversifying nature of their acquisitions. Agency and family business perspectives are used to derive expectations concerning the acquisitions behavior of family owners. Consistent with both perspectives, and owners' desire to reduce business risk, we find that family ownership is inversely related to the number and dollar volume of acquisitions. However, whereas agency theorists differ about how ownership concentration influences whether acquisitions are diversified, the family firm literature is more definitive. The latter suggests that given family owners' desire to retain control of their firms for offspring, their wealth must remain concentrated. Hence they can most easily reduce the risk of their wealth portfolio by diversifying the business—that is, through diversifying acquisitions. Consistent with this logic, we found the propensity to make diversifying acquisitions to increase with the level of family ownership.
Journal Article