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ABSTRACTThis paper examines the optimal allocation each period of an internationally diversified portfolio from the different points of view of a UK and a US investor. We find that investor location affects optimal asset allocation. The presence of exchange rate risk causes the markets to appear not fully integrated and creates a preference for home assets. Domestic equity is the dominant asset in the optimal portfolio for both investors, but the US investor bears less risk than the UK investor, and holds less foreign equity – 20% compared with 25%. Survey evidence indicates actual shares are 6% and 18%, respectively, making the home‐bias puzzle more acute for US than UK investors. There would seem to be more potential gains from increased international diversification for the US than the UK investor.

ABSTRACTAn optimal asset allocation is crucial for nonlife insurance companies. The most previous studies focused on this topic use a mono‐objective technique optimization. This technique usually allows the maximization of shareholders' expected utility. As nonlife insurance company is a complex system, it has many stakeholders other than shareholders. So, the satisfaction of the shareholders' expected utility cannot lead usually to the satisfaction of other stakeholders' objectives. Therefore, the focus on utility maximization can be a destruction source of other objectives such as productivity, competitiveness and solvency. Our developed model integrates simulation approach with a multiobjective particle swarm optimization algorithm. This model insures an optimal asset allocation that maximizes, simultaneously, shareholders expected utility and technical efficiency of European nonlife insurance companies. The empirical application conducts a comparison between the attained results with multiobjective optimization technique and mono‐objective technique to search the optimal asset allocation for nonlife insurance companies. Our results show that the investment portfolio will be more diversified between most available investment assets. In addition, any decision maker should take account of different stakeholders' objectives. Accordingly, multiobjective optimization allows us to find the best asset allocation that maximizes simultaneously expected utility and technical efficiency of nonlife insurance companies. Copyright © 2013 John Wiley & Sons, Ltd.

Intro -- Preface -- Contents -- Theoretical Results -- Why Quantiles Are a Good Description of Volatility in Economics: A Pedagogical Explanation -- 1 Formulation of the Problem -- 2 Our Explanation -- References -- An Introduction to Stacking Regression for Economists -- 1 Introduction -- 2 Cross-Validation -- 3 Estimators -- 3.1 Lasso -- 3.2 Ridge Regression -- 3.3 Elastic Net -- 3.4 Support Vector Machine -- 3.5 Random Forest -- 3.6 Gradient Boosting -- 4 Stacking -- 5 An Empirical Example: Predicting Crime Rates -- References -- Economics of Reciprocity and Temptation -- 1 Formulation of the Problem -- 2 How to Make Traditional Models More Adequate: Empathy and Discounting -- 3 Reciprocity: What It Is and How It Can Be Explained -- 4 Temptation: What It Is and How It Can Be Explained -- References -- The Most Infamous Coronavirus Forecast -- 1 Outline of the Crisis -- 2 Term Confusion -- 3 The Panic Begins -- 4 SAGE Times -- 5 Not Cases -- 6 Conclusion -- References -- How to Efficiently Store Intermediate Results in Quantum Computing: Theoretical Explanation of the Current Algorithm -- 1 Formulation of the Problem -- 2 What Are Natural Symmetries? -- 3 Symmetries That Keep the Original Transformation Invariant -- 4 Main Result: T0 Is the Only Invariant Transformation -- References -- Decompositions in Quantum Mechanics-An Overview -- 1 Introduction -- 2 Direct Product Decompositions of Hilbert Spaces -- 3 Direct Product Decompositions in a General Setting -- 4 Questions -- 5 States -- 6 Observables -- 7 Dynamics -- References -- A First Look at Quantum Conditional Events for Economics -- 1 Introduction -- 2 Probability Logic -- 3 Conditional Probability Logic -- 4 Quantum Logic -- 5 Quantum Conditional Events (Quantum Implication) -- References -- Quantum-Like Modeling: Projection Postulate and Quantum Nonlocality -- 1 Introduction.

AbstractThis paper fills a fundamental gap in commodity price risk management and optimal portfolio selection literatures by contributing a thorough reflection on trading risk modeling with a dynamic asset allocation process and under the supposition of illiquid and adverse market settings. This paper analyzes, from a portfolio managers' perspective, the performance of liquidity adjusted risk modeling in obtaining efficient and coherent investable commodity portfolios under normal and adverse market conditions. As such, the author argues that liquidity risk associated with the uncertainty of liquidating multiple commodity assets over given holding periods is a key factor in formalizing and measuring overall trading risk and is thus an important component to model, particularly in the wake of the repercussions of the recent 2008 financial crisis. To this end, this article proposes a practical technique for the quantification of liquidity trading risk for large portfolios that consist of multiple commodity assets and whereby the holding periods are adjusted according to the specific needs of each trading portfolio. Specifically, the paper proposes a robust technique to commodity optimal portfolio selection, in a liquidity‐adjusted value‐at‐risk (L‐VaR) framework, and particularly from the perspective of large portfolios that have both long and short positions or portfolios that consist of merely pure long trading positions. Moreover, in this paper, the author develops a portfolio selection model and an optimization‐algorithm which allocates commodity assets by minimizing the L‐VaR subject to applying credible operational and financial constraints based on fundamental asset management considerations. The empirical optimization results indicate that this alternate L‐VaR technique can be regarded as a robust portfolio management tool and can have many uses and applications in real‐world asset management practices and predominantly for fund managers with large commodity portfolios.

"This review article describes recent literature on asset allocation, covering both static and dynamic models. The article focuses on the bond--stock decision and on the implications of return predictability. In the static setting, investors are assumed to be Bayesian, and the role of various prior beliefs and specifications of the likelihood are explored. In the dynamic setting, recursive utility is assumed, and attention is paid to obtaining analytical results when possible. Results under both full and limited-information assumptions are discussed"--National Bureau of Economic Research web site

"Countries differ in their governmental architectures and in the rules that describe the allocation of tasks, rights and duties across the various levels of government. In this paper, we present a short and selective survey of the development of the theory of optimal allocation of rights and duties along the vertical dimension in federations. We thereby first discuss the multiple trade-offs brought forward in the literature; these make that an ideal allocation of actual tasks across levels of government may be difficult, if not impossible, to attain. Then we turn to the consequences of a sub-optimal allocation of tasks and discuss spillover effects, strategic interactions between jurisdictions and intergovernmental competition. Throughout the review, we highlight paths in need of further research such that, in time, we will have a more solid ground for policy advice." (author's abstract)