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This study attempts to conduct a comparative analysis between dynamic and static asset allocation to achieve the long-term target return on asset liability management (ALM). This study conducts asset allocation using the ex ante expected rate of return through the outlook of future economic indicators because past economic indicators or realized rate of returns which are used as input data for expected rate of returns in the \"building block\" method, most adopted by domestic pension funds, does not fully reflect the future economic situation. Vector autoregression is used to estimate and forecast long-term interest rates. Furthermore, it is applied to gross domestic product and consumer price index estimation because it is widely used in financial time series data. Based on asset allocation simulations, this study derived the following insights: first, economic indicator filtering and upper-lower bound computation is needed to reduce the expected return volatility. Second, to reach the ALM goal, more stocks should be allocated than low-yielding assets. Finally, dynamic asset allocation which has been mirroring economic changes actively has a higher annual yield and risk-adjusted return than static asset allocation.

This study attempts to conduct a comparative analysis between dynamic and static asset allocation to achieve the long-term target return on asset liability management (ALM). This study conducts asset allocation using the ex ante expected rate of return through the outlook of future economic indicators because past economic indicators or realized rate of returns which are used as input data for expected rate of returns in the “building block” method, most adopted by domestic pension funds, does not fully reflect the future economic situation. Vector autoregression is used to estimate and forecast long-term interest rates. Furthermore, it is applied to gross domestic product and consumer price index estimation because it is widely used in financial time series data. Based on asset allocation simulations, this study derived the following insights: first, economic indicator filtering and upper-lower bound computation is needed to reduce the expected return volatility. Second, to reach theALMgoal, more stocks should be allocated than low-yielding assets. Finally, dynamic asset allocation which has been mirroring economic changes actively has a higher annual yield and risk-adjusted return than static asset allocation.

In this paper we examine the impact of asset allocation strategies on the investment performance of life insurers in the U.S. We are especially interested in comparing the effects of active portfolio management to the effects of passive holding strategies. We define three novel quantitative indices of static/dynamic strategies to represent important dimensions of the active/passive spectrum of investment strategies. The indices are computed from portfolio allocations reported in the firms' annual statement data. Using cluster analysis, we partition the population of life insurers into three groups, characterised by generally having static (passive), dynamic (active) and mixed asset allocation strategies, respectively. There are major differences among the three clusters in terms of risk profile, size and other factors. We model investment performance and allocations among the major holdings of bonds, stocks, cash and mortgages explicitly as simultaneously interacting phenomena. In order to isolate the effect of allocation strategies from the confounding effects of other risks, we imbed a spectrum of enterprise risks, treated as exogenous or predetermined, within the model framework of endogenously interacting performance and asset allocation variables. The strategy indicators are also exogenous variables. We find that the most active cluster enjoys the greatest relative performance, even controlling for allocations among asset classes.

Purpose The purpose of this paper is to investigate whether asset allocation across various industries listed on the Ghana Stock Exchange (GSE) varies across different monetary policy states. Design/methodology/approach This paper adopts the Markov Chain technique to split monetary policy into three different states. The authors further adopt the Markowitz portfolio optimization technique to find the minimum variance and optimum portfolio for the industries listed on the GSE. Findings The finding reveals a dynamic asset allocation, which varies the industry’s weight mix across the various monetary policy states enhance excess returns compared to the static asset allocation. Specifically, the authors find risk-return trade-off among industries listed on the GSE. Financial and Food and Beverage industries portfolios record high returns relative to the Government of Ghana 91-day Treasury bill. The Food and Beverage portfolio is the only portfolio that records relatively high excess returns across all the monetary policy states. The authors also find that, during expansionary state (high monetary policy rates) of the monetary policy, investors are to allocate about 69 and 30 percent of their investment into food and beverages and financials, respectively. Corner solution is found in the transient state where 100 percent of wealth is allocated to financial to obtain the optimum portfolio. The optimum portfolio in the contraction state assigns 52 percent to financials and 42 percent to manufacturing. In summary, the result supports the dependence of investors’ asset allocation decisions on monetary policy. Practical implications Therefore, the authors propose an investment strategy which is dynamic and takes into consideration the monetary policy states rather than static asset allocation which maintains the same industry weight mix over the investment period. Social implications In sum, the authors interpret the result as support for the dependence of investors’ asset allocation decisions on monetary policy. In Ghana, an increase in the monetary policy appears to support industries listed on the equity market. The result also gives knowledge about investors’ asset allocation decisions on the GSE, which is practical balanced source of information for investors’ risk and return choices. For a prudent monetary policy framework, the monetary policy committee should monitor industries listed on the GSE. The result from the analysis has also an implication for investors, portfolio managers and fund managers to consider the state of the monetary policy in Ghana when making investment decisions. Originality/value The study differs from earlier research on asset allocation by breaking new grounds on two levels. First of all, based on the notion that different industries have different exposures to monetary policy states, the authors extend the portfolios by grouping the equities listed on the GSE into their industrial sectors. Second, the authors examine how investors’ optimal portfolio allocation may change depending on the state of monetary policy.

We investigate the equivalence of dynamic and static asset allocations in the case where the price process of a risky asset is driven by a Poisson process. Under some mild conditions, we obtain a necessary and sufficient condition for the equivalence of dynamic and static asset allocations. In addition, we provide a simple sufficient condition for the equivalence.

In the Latin America and Caribbean (LAC) region, as in the rest of the world, reliable financial information is the cornerstone of a robust market economy and efficient public sector. This book presents both an analysis of the broader trends derived from the individual country-level studies produced under the Report on the Observance of Standards and Codes (ROSC) Accounting and Auditing (A&A) program and a synthesis of lessons learned from the Bank's experiences working with policy makers and other stakeholders to implement the ROSC A&A recommendations. This first chapter introduces the book by showing how sound A&A practices in the private and public sectors contribute to LAC development agenda, and by describing the regional economic context. It then presents three case studies of successful financial reporting and auditing reforms within LAC, showing how these reforms have benefited the countries. It describes drivers of reform that have led some countries to adopt global standards of good A&A practice and others to take a more conservative, wait and see approach. Finally, the chapter describes the objectives and methodology of this study, and the structure of the book.

The roots signify the origins and initial steps taken to build a coalition and the associated teething problems; the trunk represents efforts toward sustaining the organization s existence and growth; and the branches highlight the collective actions undertaken by the coalition in fulfillment of its aims and objectives. In preparing this book, and based on their unique experiences, Tanzania, Kenya, and Uganda respectively focus their chapters on the roots, trunk, and branches. To further the tree analogy, each country s chapter draws parallels or makes comparisons with what pertains in the other two countries, to show how they benefit from each other in an ongoing knowledge exchange. Chapter two (Putting Down Roots, Tanzania) has three main sections: an overview of the country context and health reform agenda; a discussion of the experiences of MSG-Pharma, Tanzania s multi-stakeholder body, in setting up a coalition, and lessons learned. These outline the reasons leading to the establishment of the multi-stakeholder group and describe how challenges met during its formation stages were overcome. Chapter three (growing a strong trunk, Kenya) provides insights into the approaches employed by Kenya s multi-stakeholder coalition, the Forum for Transparency and Accountability in Pharmaceutical Procurement (FoTAPP), in order to sustain the interest and commitment of key stakeholders. It presents a brief description of the Kenyan context in relation to the pharmaceutical sector, highlighting challenges in the sector, and the importance of a multi-stakeholder coalition amid other reform platforms. Chapter four (branching out and bearing fruits, Uganda) describes the opportunities, challenges, and rewards associated with designing and implementing a joint intervention in furtherance of the goals of the Medicines Transparency Alliance (MeTA), the coalition in Uganda. It also illustrates how the coalition has been Able to inform policy dialogue and reform efforts in the health sector.

This volume is an introduction to the theories and policies that affect economic growth and poverty. It is a compilation of lecture notes used in face-to-face and e-learning courses presented by the World Bank Institute's (WBI) Poverty Program during 2004-08. The volume is divided into three parts. Part one discusses basic concepts and measurement issues pertaining to poverty, national income, and economic growth. Part two deals with the macroeconomic policies that are critical for economic growth in the short term. It covers government enforced fiscal and exchange-rate policies and the roles of financial institutions, development assistance (or aid), debt relief, and trade policies. Part three covers the structural and sectoral policies that affect longer-term economic growth and poverty reduction. To underscore the impact of good governance and effective service delivery in growth and poverty reduction, separate chapters are devoted to institutional and technological development, education, health, labor, and land. The volume ends with a chapter that summarizes knowledge of growth theory, reviews the process of growth in 13 successful countries, and draws out implications for other developing countries. The authors hope that this chapter may be of help to policy makers in identifying the constraints to economic growth and development that may be unique to each country.

This chapter contains sections titled: Strategic Asset Allocation Without Hedge Funds Introducing Hedge Funds in the Asset Allocation How Much to Allocate to Hedge Funds? Hedge Funds as Portable Alpha Overlays Hedge Funds as Sources of Alternative Risk Exposure