Revising the Program Portfolio: Elevating Academic Program Performance and Strategic Alignment

At many institutions, program review is an underproductive exercise. Review of existing programs is often a check-the-box formality, with inconsistent criteria and little connection to institutional priorities or funding considerations. Decisions about where to concentrate resources across the portfolio can be highly politicized. This report profiles how academic planning exemplars use program review as a strategic tool, integrating data on academic quality, student demand, and resource utilization to improve the economics of challenged programs and prioritize programs for investment and expansion.

Impact investing: portfolio company selection in Latin America

O documento analisa como investidores de impacto selecionar suas companhias de portfólio na América Latina e que critérios são avaliados no processo. Uma vez que praticamente ne-nhuma pesquisa sobre isso foi con conduzidos até à data, e desde que o modelo de processo de seleção aplicados em capital de risco não é dissemelhantes, foi adotado essa abordagem. Os resultados revelam que os investidores de impacto originar e avaliar negócios de uma for-ma semelhante a capitalistas de risco , mas que alguns critérios são ajustados e outros adicio-nados a fim de refletir o duplo objectivo de investimento de impacto. Os investidores de im-pacto podem originar ofertas passivamente, mas eles preferem procurar empreendimentos sociais de forma proativa: contatos pessoais, o acesso a redes e eventos do setor são cruciais neste contexto. Impacto Investidores considerando um investimento em pesquisa para a Amé-rica Latina inteira, empreendedores sociais honestos e confiáveis comprometidos com impacto social; empreendimentos sociais elegíveis devem ser rentáveis com potencial de escalabilidade; o produto deve ter um impacto social, ou seja, criar valor para o consumidor individual e para a comunidade em geral; tamanho do mercado e crescimento do mercado são fatores externos cruciais; e as características de negócio dependem de atitude de risco do investidor e as perspectivas de uma saída bem sucedida, tanto em termos financeiros e sociais. Os investi-dores de impacto também estão dispostos a dar apoio não financeiro antes de um investimen-to, se um empreendimento social, mostra alto potencial para atingir o seu objectivo dual.

Insider trading, investment, and liquidity: a welfare analysis

We compare competitive equilibrium outcomes with and without trading by a privately infonned "monopolistic" insider, in a model with real investment portfolio choices ex ante, and noise trading generated by aggregate uncertainty regarding other agents' intertemporal consumption preferences. The welfare implications of insider trading for the ex ante expected utilities of outsiders are analyzed. The role of interim infonnation revelation due to insider trading, in improving the risk-sharing among outsiders with stochastic liquidity needs, is examined in detaiL

Asymmetric preferences in investment decisions in the Brazilian financial market

The main objective of this article is to test the hypothesis that utility preferences that incorporate asymmetric reactions between gains and losses generate better results than the classic Von Neumann-Morgenstern utility functions in the Brazilian market. The asymmetric behavior can be computed through the introduction of a disappointment (or loss) aversion coefficient in the classical expected utility function, which increases the impact of losses against gains. The results generated by both traditional and loss aversion utility functions are compared with real data from the Brazilian market regarding stock market participation in the investment portfolio of pension funds and individual investors.

The Effects of Credit Risk on Dynamic Portfolio Management: A New Computational Approach

The study investigates the role of credit risk in a continuous time stochastic asset allocation model, since the traditional dynamic framework does not provide credit risk flexibility. The general model of the study extends the traditional dynamic efficiency framework by explicitly deriving the optimal value function for the infinite horizon stochastic control problem via a weighted volatility measure of market and credit risk. The model's optimal strategy was then compared to that obtained from a benchmark Markowitz-type dynamic optimization framework to determine which specification adequately reflects the optimal terminal investment returns and strategy under credit and market risks. The paper shows that an investor's optimal terminal return is lower than typically indicated under the traditional mean-variance framework during periods of elevated credit risk. Hence I conclude that, while the traditional dynamic mean-variance approach may indicate the ideal, in the presence of credit-risk it does not accurately reflect the observed optimal returns, terminal wealth and portfolio selection strategies.

Foreign Direct Investment Relations between Myanmar and ASEAN

Myanmar highly appreciates foreign direct investment (FDI) as a key solution reducing the development gap with leading ASEAN countries. Accordingly, it is welcomed by the government. Myanmar's Foreign Investment Law was enacted in 1988 soon after the adoption of a market-oriented economic system to boost the flow of FDI into the country. Foreign investors positively responded to these measures in the early years and FDI inflow into Myanmar gradually increased during the period from 1989 to 1996. However, after 1997, FDI inflow was dramatically reduced and markedly declined until 2004. In 2005, FDI inflow increased at an unprecedented rate and reached the highest level in the country's history. However, this growth was not sustainable in the subsequent years, as it declined again and turned stagnant at the previous level. In terms of source regions, ASEAN is a major investor in Myanmar, which investment is significantly exceeds the combined investment of other regions of the world. Among top ten countries, Thailand's investment alone is significantly more than combined total investments of the other nine countries. Next to Thailand in terms of investments in Myanmar are Singapore and Malaysia among ASEAN, at second and third places, respectively. The combined total FDI inflows into the power and oil and gas sector represent about 65 percent of the total investment. There are many opportunities for foreign investment in other sectors, which are not, yet exploited. ASEAN countries will certainly be source countries of Myanmar FDI in the future, and Myanmar should expand to other Asian countries like Japan, India, China, Korea, and Hong Kong where its FDI portfolio is concerned. To effectively attract FDI into the country, Myanmar needs to minimize the effect of policy while opening and encouraging other potential sectors of FDI to foreign investors in ASEAN and Asian countries.

Disclosure of proxy voting information by Australian managed investment schemes

The US Securities and Exchange Commission requires registered management investment companies to disclose how they vote proxies relating to portfolio securities they hold. The primary purpose of this rule is to enable fund investors to monitor the role of institutional shareholders in the corporate governance practices of public companies. In Australia, despite reform proposals, there are no regulations requiring institutional investors to report proxy voting procedures and practices. There is little evidence of voluntary disclosure of proxy voting by Australian managed investment schemes in equities, indicating that there are costs involved in such disclosure.

Real estate research needs of the plan sponsor community:what do the plan sponsor real estate investment managers want to know?

This article reports the results of a web-based survey of real estate portfolio managers in the pension fund industry. The study focused on ascertaining the real estate research interests of the respondents as well as whether or not research funding should be allocated to various research topics. Performance measures of real estate assets and portfolios, microeconomic factors affecting real estate and the role of real estate in a mixed-asset portfolio were the top three real estate research interests. There was some variation by the type and size of fund providing evidence that segmentation is important within the money management industry. Respondents were also queried on more focused research subtopics and additional questions in the survey focused on satisfaction with existing real estate benchmarks, and perceptions of the usefulness of published research. Findings should be used to guide research practitioners and academics as to the most important research interests of plan sponsor real estate investment managers.

Genetic algorithms and investment strategies: A global perspective

The profitability of momentum portfolios in the equity markets is derived from the continuation of stock returns over medium time horizons. The empirical evidence of momentum, however, is significantly different across markets around the world. The purpose of this dissertation is to: (1) help global investors determine the optimal selection and holding periods for momentum portfolios, (2) evaluate the profitability of the optimized momentum portfolios in different time periods and market states, (3) assess the investment strategy profits after considering transaction costs, and (4) interpret momentum returns within the framework of prior studies on investors’ behavior. Improving on the traditional practice of selecting arbitrary selection and holding periods, a genetic algorithm (GA) is employed. The GA performs a thorough and structured search to capture the return continuations and reversals patterns of momentum portfolios. Three portfolio formation methods are used: price momentum, earnings momentum, and earnings and price momentum and a non-linear optimization procedure (GA). The focus is on common equity of the U.S. and a select number of countries, including Australia, France, Germany, Japan, the Netherlands, Sweden, Switzerland and the United Kingdom. The findings suggest that the evolutionary algorithm increases the annualized profits of the U.S. momentum portfolios. However, the difference in mean returns is statistically significant only in certain cases. In addition, after considering transaction costs, both price and earnings and price momentum portfolios do not appear to generate abnormal returns. Positive risk-adjusted returns net of trading costs are documented solely during “up” markets for a portfolio long in prior winners only. The results on the international momentum effects indicate that the GA improves the momentum returns by 2 to 5% on an annual basis. In addition, the relation between momentum returns and exchange rate appreciation/depreciation is examined. The currency appreciation does not appear to influence significantly momentum profits. Further, the influence of the market state on momentum returns is not uniform across the countries considered. The implications of the above findings are discussed with a focus on the practical aspects of momentum investing, both in the U.S. and globally.

A comprehensive portfolio construction under stochastic environment

Prior research has established that idiosyncratic volatility of the securities prices exhibits a positive trend. This trend and other factors have made the merits of investment diversification and portfolio construction more compelling. ^ A new optimization technique, a greedy algorithm, is proposed to optimize the weights of assets in a portfolio. The main benefits of using this algorithm are to: (a) increase the efficiency of the portfolio optimization process, (b) implement large-scale optimizations, and (c) improve the resulting optimal weights. In addition, the technique utilizes a novel approach in the construction of a time-varying covariance matrix. This involves the application of a modified integrated dynamic conditional correlation GARCH (IDCC - GARCH) model to account for the dynamics of the conditional covariance matrices that are employed. ^ The stochastic aspects of the expected return of the securities are integrated into the technique through Monte Carlo simulations. Instead of representing the expected returns as deterministic values, they are assigned simulated values based on their historical measures. The time-series of the securities are fitted into a probability distribution that matches the time-series characteristics using the Anderson-Darling goodness-of-fit criterion. Simulated and actual data sets are used to further generalize the results. Employing the S&P500 securities as the base, 2000 simulated data sets are created using Monte Carlo simulation. In addition, the Russell 1000 securities are used to generate 50 sample data sets. ^ The results indicate an increase in risk-return performance. Choosing the Value-at-Risk (VaR) as the criterion and the Crystal Ball portfolio optimizer, a commercial product currently available on the market, as the comparison for benchmarking, the new greedy technique clearly outperforms others using a sample of the S&P500 and the Russell 1000 securities. The resulting improvements in performance are consistent among five securities selection methods (maximum, minimum, random, absolute minimum, and absolute maximum) and three covariance structures (unconditional, orthogonal GARCH, and integrated dynamic conditional GARCH). ^

A decision support framework for infrastructure maintenance investment decision-making

Infrastructure management agencies are facing multiple challenges, including aging infrastructure, reduction in capacity of existing infrastructure, and availability of limited funds. Therefore, decision makers are required to think innovatively and develop inventive ways of using available funds. Maintenance investment decisions are generally made based on physical condition only. It is important to understand that spending money on public infrastructure is synonymous with spending money on people themselves. This also requires consideration of decision parameters, in addition to physical condition, such as strategic importance, socioeconomic contribution and infrastructure utilization. Consideration of multiple decision parameters for infrastructure maintenance investments can be beneficial in case of limited funding. Given this motivation, this dissertation presents a prototype decision support framework to evaluate trade-off, among competing infrastructures, that are candidates for infrastructure maintenance, repair and rehabilitation investments. Decision parameters' performances measured through various factors are combined to determine the integrated state of an infrastructure using Multi-Attribute Utility Theory (MAUT). The integrated state, cost and benefit estimates of probable maintenance actions are utilized alongside expert opinion to develop transition probability and reward matrices for each probable maintenance action for a particular candidate infrastructure. These matrices are then used as an input to the Markov Decision Process (MDP) for the finite-stage dynamic programming model to perform project (candidate)-level analysis to determine optimized maintenance strategies based on reward maximization. The outcomes of project (candidate)-level analysis are then utilized to perform network-level analysis taking the portfolio management approach to determine a suitable portfolio under budgetary constraints. The major decision support outcomes of the prototype framework include performance trend curves, decision logic maps, and a network-level maintenance investment plan for the upcoming years. The framework has been implemented with a set of bridges considered as a network with the assistance of the Pima County DOT, AZ. It is expected that the concept of this prototype framework can help infrastructure management agencies better manage their available funds for maintenance.

Genetic Algorithms and Investment Strategies: A Global Perspective

The profitability of momentum portfolios in the equity markets is derived from the continuation of stock returns over medium time horizons. The empirical evidence of momentum, however, is significantly different across markets around the world. The purpose of this dissertation is to: 1) help global investors determine the optimal selection and holding periods for momentum portfolios, 2) evaluate the profitability of the optimized momentum portfolios in different time periods and market states, 3) assess the investment strategy profits after considering transaction costs, and 4) interpret momentum returns within the framework of prior studies on investors’ behavior. Improving on the traditional practice of selecting arbitrary selection and holding periods, a genetic algorithm (GA) is employed. The GA performs a thorough and structured search to capture the return continuations and reversals patterns of momentum portfolios. Three portfolio formation methods are used: price momentum, earnings momentum, and earnings and price momentum and a non-linear optimization procedure (GA). The focus is on common equity of the U.S. and a select number of countries, including Australia, France, Germany, Japan, the Netherlands, Sweden, Switzerland and the United Kingdom. The findings suggest that the evolutionary algorithm increases the annualized profits of the U.S. momentum portfolios. However, the difference in mean returns is statistically significant only in certain cases. In addition, after considering transaction costs, both price and earnings and price momentum portfolios do not appear to generate abnormal returns. Positive risk-adjusted returns net of trading costs are documented solely during “up” markets for a portfolio long in prior winners only. The results on the international momentum effects indicate that the GA improves the momentum returns by 2 to 5% on an annual basis. In addition, the relation between momentum returns and exchange rate appreciation/depreciation is examined. The currency appreciation does not appear to influence significantly momentum profits. Further, the influence of the market state on momentum returns is not uniform across the countries considered. The implications of the above findings are discussed with a focus on the practical aspects of momentum investing, both in the U.S. and globally.

A Comprehensive Portfolio Construction Under Stochastic Environment

Prior research has established that idiosyncratic volatility of the securities prices exhibits a positive trend. This trend and other factors have made the merits of investment diversification and portfolio construction more compelling. A new optimization technique, a greedy algorithm, is proposed to optimize the weights of assets in a portfolio. The main benefits of using this algorithm are to: a) increase the efficiency of the portfolio optimization process, b) implement large-scale optimizations, and c) improve the resulting optimal weights. In addition, the technique utilizes a novel approach in the construction of a time-varying covariance matrix. This involves the application of a modified integrated dynamic conditional correlation GARCH (IDCC - GARCH) model to account for the dynamics of the conditional covariance matrices that are employed. The stochastic aspects of the expected return of the securities are integrated into the technique through Monte Carlo simulations. Instead of representing the expected returns as deterministic values, they are assigned simulated values based on their historical measures. The time-series of the securities are fitted into a probability distribution that matches the time-series characteristics using the Anderson-Darling goodness-of-fit criterion. Simulated and actual data sets are used to further generalize the results. Employing the S&P500 securities as the base, 2000 simulated data sets are created using Monte Carlo simulation. In addition, the Russell 1000 securities are used to generate 50 sample data sets. The results indicate an increase in risk-return performance. Choosing the Value-at-Risk (VaR) as the criterion and the Crystal Ball portfolio optimizer, a commercial product currently available on the market, as the comparison for benchmarking, the new greedy technique clearly outperforms others using a sample of the S&P500 and the Russell 1000 securities. The resulting improvements in performance are consistent among five securities selection methods (maximum, minimum, random, absolute minimum, and absolute maximum) and three covariance structures (unconditional, orthogonal GARCH, and integrated dynamic conditional GARCH).

Household portfolio allocation, risk attitudes and credit constraints : evidence from the eurozone

Mestrado em Economia Monetária e Financeira

Financial distress, financial constraint and investment decision: Evidence from Brazil

This paper analyses the presence of financial constraint in the investment decisions of 367 Brazilian firms from 1997 to 2004, using a Bayesian econometric model with group-varying parameters. The motivation for this paper is the use of clustering techniques to group firms in a totally endogenous form. In order to classify the firms we used a hybrid clustering method, that is, hierarchical and non-hierarchical clustering techniques jointly. To estimate the parameters a Bayesian approach was considered. Prior distributions were assumed for the parameters, classifying the model in random or fixed effects. Ordinate predictive density criterion was used to select the model providing a better prediction. We tested thirty models and the better prediction considers the presence of 2 groups in the sample, assuming the fixed effect model with a Student t distribution with 20 degrees of freedom for the error. The results indicate robustness in the identification of financial constraint when the firms are classified by the clustering techniques. (C) 2010 Elsevier B.V. All rights reserved.