Portfolio Budget Research Articles

Управление изменениями организационной модели бюджетирования российского банка при внедрении гибких подходов к управлению ИТ-проектами

The research project described in this article is intended to identify the requirements for the target organizational budgeting model of a company implementing agile approach in managing IT projects and to develop recommendations concerning these requirements. To collect data relevant for the research an interview and a questionnaire were conducted among the key participants of processes of managing project portfolio, and also some materials from meetings inside the company were used. The most significant results of this project ready to be applied in other companies are:
 •• the activity-based costs allocation model, which allows to improve the project planning quality and to increase the benefits estimation objectiveness;
 •• the open access integrated IS model providing the transparency of project portfolio budgeting process and possibilities for cascading the metrics of strategic goals achievement set in Balanced Scorecards and increments delivered by agile-teams.

A BAYESIAN-BASED MODEL FOR ALLOCATING CONTINGENCY TO A PORTFOLIO OF CORRELATED CONSTRUCTION PROJECTS

Despite the availability of various probabilistic and non-probabilistic methods for determining budget contingency, still many large capital projects are suffering from cost overrun. Furthermore, most of the effort has been concentrated on calculation of contingency for a single project rather than a group of projects. This paper introduces a new Bayesian-based model for allocating contingency budget to a portfolio of correlated construction projects. The proposed model enables an owner agency to define the individual project confidence level for contingency calculation taking into account the portfolio budget and the desired portfolio confidence level. The model recognizes the correlation between each pair of projects in the portfolio and calculates the required increase in budget in such a way to ensure adequate budgets with respect to individual projects and the portfolio. Using the information from newly completed projects, the Bayesian technique can be used to update the model parameters periodically so that more accurate contingency budget can be established for the portfolio. A numerical example is presented to show the application of the model on a portfolio of transit projects. The proposed model can be employed as an effective tool for the owner agencies in charge of funding a group of projects every year.

Project Portfolio Selection: A Newsvendor Approach

ABSTRACTWe consider the problem of balancing the penalties associated with budgetary slack (being underbudget) and cost overruns in the project portfolio selection problem by addressing randomness in project costs and making individual project budgets decision variables. Setting the budget for a single project is shown to be analogous to the newsvendor problem. For related versions of the project portfolio selection problem we provide optimal and heuristic procedures. Numerical experiments are used to test the procedures and provide managerial guidelines. We show project budgets should be set so that each project in the portfolio has the same probability of running over budget, it is better to have a larger number of projects with less than ideal funding compared to a smaller number of projects with ideal funding, and substantial opportunities to select more projects with a higher expected profit are available if an aggregate portfolio budget is used.

A probabilistic portfolio budget allocation problem with CPI index under risk

The portfolio budget allocation plays an important role in making appropriate decisions in management systems. Budget allocation is also crucial when the nature of an organization is based on projects like construction organizations. The proposed model, in this paper, considers portfolio budget allocation when there is an uncertainty associated with input/output parameters. A probabilistic model based on project cost performance index (CPI) is then proposed where risky conditions are considered for each project and are solved using a recent robust optimization technique. The resulted nonlinear optimization problem is handled using CVX as a comprehensive decision support framework for solving cone programming problems. The implementation of the proposed model has been verified using various kinds of test problems and the results are finally discussed.

The Impact of Currency Exposure on Institutional Investment Performance: The Good, the Bad, and the Ugly

Institutional investor portfolios typically hold a significant allocation of foreign currency denominated assets. Very often at least some of this currency exposure has been viewed as bad or unwanted. On the other hand, recent studies have concluded that currency is itself an asset class that offers investors favorable risk-adjusted returns that could benefit a typical portfolio of stocks and bonds. There are two basic types of currency management mandates. In a currency hedging mandate (currency overlay), investors strive to manage (usually meaning reduce) the risk associated with the foreign currency exposure in their international assets. With an absolute return mandate (currency alpha), investors seek to earn a positive return subject to acceptable risk levels. The existing literature analyses these two basic types of currency management mandates separately. In this study, we investigate their impact on institutional investment performance simultaneously. We find that both absolute return and currency hedging mandates can have a positive impact on the portfolio risk/return characteristics. Absolute return mandates have the potential to increase the portfolio return with little impact on volatility. Risk reduction mandates tend to reduce portfolio volatility with little impact on returns. Due to the safe haven status of the U.S. Dollar, higher hedge ratios provide diversification for US dollar based investors when needed most, namely in periods of negative equity returns. Combining both currency hedging and absolute return mandates improves overall investment performance while allowing managers to stay within their portfolio risk budget.

Inverse portfolio problem with mean-deviation model

A Markowitz-type portfolio selection problem is to minimize a deviation measure of portfolio rate of return subject to constraints on portfolio budget and on desired expected return. In this context, the inverse portfolio problem is finding a deviation measure by observing the optimal mean-deviation portfolio that an investor holds. Necessary and sufficient conditions for the existence of such a deviation measure are established. It is shown that if the deviation measure exists, it can be chosen in the form of a mixed CVaR-deviation, and in the case of n risky assets available for investment (to form a portfolio), it is determined by a combination of (n+1) CVaR-deviations. In the later case, an algorithm for constructing the deviation measure is presented, and if the number of CVaR-deviations is constrained, an approximate mixed CVaR-deviation is offered as well. The solution of the inverse portfolio problem may not be unique, and the investor can opt for the most conservative one, which has a simple closed-form representation.

Budget‐constrained portfolio trades using multiobjective optimization

AbstractA decision support process using many‐objective optimization, high‐performance computing, and advanced visualization is applied to gain comprehensive insight into multistakeholder portfolio budgeting trades. The key tradeoffs among nondominated portfolio budget solutions are systematically identified and examined with respect to different stakeholder viewpoints. The approach is illustrated using a portfolio of 14 U.S. Air Force satellite development programs using budget data taken from the 2010 Future Year Development Plan [http://www.saffm.hq.af.mil/budget/, last accessed April 20, 2011]. Practical lessons learned in applying the approach are discussed. ©2012 Wiley Periodicals, Inc. Syst Eng 15

Risk Management and Portfolio Budgeting Based on ARMA-GARCH Non-Gaussian Multivariate Model

In this work, we propose an ARMA(1,1)-GARCH(1,1) model with standard classical tempered stable (CTS) innovations for historical daily returns of 29 selected stocks. The non-Gaussian nature of the innovations captures the fat-tail property observed in data. The dependency between different assets is modeled by a student’s t copula. We fit the data and estimate the parameters of the model and perform statistical goodness-of-fit tests for fitted parameters. Based on the multivariate model consisting of standard CTS marginals and student’s t copula, we construct ARMA-GARCH Monte-Carlo paths for daily returns of each single stock. Daily VaR is computed for an equally weighted portfolio, and for a time span of 250 trading days, the model is being backtested. It is shown that in comparison with the Gaussian model, the proposed CTS-t copula offers more realistic estimation for the portfolio risk. Moreover we study the portfolio selection problem. We compute the marginal VaR and Component VaR of single stocks for the VaR optimized portfolio. We consider an active portfolio budgeting method, where we change the portfolio composition according to marginal VaR measurements. We show that the resulting portfolio converges to the VaR minimized portfolio in the 29 dimensional space of portfolio weight vectors. We perform a return to VaR ratio, performance test, to realize the ”costs” of this risk reduction action in terms of potential return suppression. Little transaction costs due to limited and relatively small position modification in portfolio, presents an efficient management scenario for pension funds and other investment organization, where relative changes in investment positions are restricted.

A New Approach for Contingency Determination in a Portfolio of Construction Projects

In this paper, a new approach for contingency determination in a portfolio of construction projects is proposed. The model proposed helps an agency find the level of confidence needed for individual projects to ensure that the portfolio budget will meet the minimum level of confidence based on available funding and the agency’s policy goals. The promise of this model is to protect a portfolio of projects against cost overrun by adjusting their original budgets. A Bayesian approach is employed to update the model on regular intervals. As more information becomes available in the future, the required adjustment in portfolio budget will be reduced, because the accuracy of estimating the contingency is improved. The proposed model is an effective tool for the agencies/owners to develop contingency budgets.

The Relative Efficiency of Beta Estimates

When estimation of beta is based on the Capital Asset Pricing Model the standard recommendation is to use five years of monthly data and a value-weighted index. Given the importance of the beta estimate obtained for financial decisions, such as those involved in portfolio management, capital budgeting, and performance evaluation, there is surprisingly little research evidence in support of this recommendation. The objective of this paper is to address this shortcoming. For this purpose the relative efficiency of beta estimates which result from using different data frequencies, time periods, and indexes is examined. It is found that five years of monthly data and an equal-weighted index, as opposed to the commonly recommended value-weighted index, provides the most efficient estimate.

A Simulation-Based Decision Support System for Managing Information Technology Project Portfolios

The complicatedness in conducting software development derives from the probabilistic assessment of future conditions or unclear requirements and project implications. Information technology project portfolio management is more complex and presents program managers with the challenge of dynamic decision-making in the context of target revisions and project selection (continuation of active projects at various budgeting levels, termination of other active projects and launching new projects). The authors propose a simulation-based decision support system for managing information technology project portfolios. At each control (decision) point, this data support system enables ’optimizing’ each project planning subject to alternative determinations of time and cost chance constraints, and evaluating the up-to-date chance of alternative project selections being within the project portfolio budget. These ’optimizations’ and evaluations are provided by a stochastic procedure based on Monte Carlo simulations. In contrast with deterministic procedures that are highly inadequate since they mostly provide erroneous results, the stochastic procedure is appropriate since it analyses a higher level of information and provides more accurate results. The proposed system enables the program manager to decipher highly complex simulation results and make decisions based on up-to-date data. It can be easily implemented even by non-experts.

Portfolio Budgeting in the Australian Portfolios‐Principles and Practice

In the mid‐eighties Australia implemented a budgeting system that is similar in its principles to the U.S. PAYGO rule and the now defunct Policy and Expenditure Management System of Canada. Termed as portfolio budgeting, it seeks to encourage greater ministerial participation (a ministry comprising a number of related departments) in the portfolio budget process. It obligates portfolio ministers to offer offsetting savings for funding new policies. Ministers have to thereby set new policy priorities so that only the most deserving new policies obtain funding through the savings identified. Additionally, portfolio budgeting requires ministers to prioritize their ongoing programs so that budget allocation to these programs reflects ministerial priorities. The article examines the practice of portfolio budgeting in the Australian portfolios in light of these objectives. The article suggests that portfolio budgeting has caused greater ministerial involvement in budgetary management. However, there has been little significant change in budget decision making at the portfolio level. The state of play of portfolio budgeting at the national budget process (cabinet and the Department of Finance) offered little incentive to portfolios to provide offsetting savings for new policy proposals. And, the appropriation structure and the organizational and political dynamics impeded ministers from allocating and reallocating their budgets (operating expenditure or running costs) for ongoing programs along ministerial priorities.