Engineering sustainable solutions program : critical literacies for engineers portfolio

Purpose While a number of universities in Australia have embraced concepts such as project/problem‐based learning and design of innovative learning environments for engineering education, there has been a lack of national guidance on including sustainability as a “critical literacy” into all engineering streams. This paper was presented at the 2004 International Conference on Engineering Education in Sustainable Development (EESD) in Barcelona, Spain, outlining a current initiative that is seeking to address the “critical literacy” dilemma. Design/methodology/approach The paper presents the positive steps taken by Australia's peak engineering body, the Institution of Engineers Australia (EA), in considering accreditation requirements for university engineering courses and its responsibility to ensure the inclusion of sustainability education material. It then describes a current initiative called the “Engineering Sustainable Solutions Program – Critical Literacies for Engineers Portfolio” (ESSP‐CL), which is being developed by The Natural Edge Project (TNEP) in partnership with EA and Unesco. Findings Content for the module was gathered from around the world, drawing on research from the publication The Natural Advantage of Nations: Business Opportunities, Innovation, and Governance in the Twenty‐first Century. Parts of the first draft of the ESSP‐CL have been trialled at Griffith University, Queensland, Australia with first year environmental engineering students, in May 2004. Further trials are now proceeding with a number of other universities and organisations nationally and internationally. Practical implications It is intended that ESSP‐CL will be a valuable resource to universities, professional development activities or other education facilities nationally and internationally. Originality/value This paper fulfils an identified information/resources need.

The impact of taxes on optimal portfolio choice : an Australian study

Taxes are an important component of investing that is commonly overlooked in both the literature and in practice. For example, many understand that taxes will reduce an investment’s return, but less understood is the risk-sharing nature of taxes that also reduces the investment’s risk. This thesis examines how taxes affect the optimal asset allocation and asset location decision in an Australian environment. It advances the model of Horan & Al Zaman (2008), improving the method by which the present value of tax liabilities are calculated, by using an after-tax risk-free discount rate, and incorporating any new or reduced tax liabilities generated into its expected risk and return estimates. The asset allocation problem is examined for a range of different scenarios using Australian parameters, including different risk aversion levels, personal marginal tax rates, investment horizons, borrowing premiums, high or low inflation environments, and different starting cost bases. The findings support the Horan & Al Zaman (2008) conclusion that equities should be held in the taxable account. In fact, these findings are strengthened with most of the efficient frontier maximising equity holdings in the taxable account instead of only half. Furthermore, these findings transfer to the Australian case, where it is found that taxed Australian investors should always invest into equities first through the taxable account before investing in super. However, untaxed Australian investors should invest their equity first through superannuation. With borrowings allowed in the taxable account (no borrowing premium), Australian taxed investors should hold 100% of the superannuation account in the risk-free asset, while undertaking leverage in the taxable account to achieve the desired risk-return. Introducing a borrowing premium decreases the likelihood of holding 100% of super in the risk-free asset for taxable investors. The findings also suggest that the higher the marginal tax rate, the higher the borrowing premium in order to overcome this effect. Finally, as the investor’s marginal tax rate increases, the overall allocation to equities should increase due to the increased risk and return sharing caused by taxation, and in order to achieve the same risk/return level as the lower taxation level, the investor must take on more equity exposure. The investment horizon has a minimal impact on the optimal allocation decision in the absence of factors such as mean reversion and human capital.

Return distribution predictability and its implications for portfolio selection

The inquiries to return predictability are traditionally limited to conditional mean, while literature on portfolio selection is replete with moment-based analysis with up to the fourth moment being considered. This paper develops a distribution-based framework for both return prediction and portfolio selection. More specifically, a time-varying return distribution is modeled through quantile regressions and copulas, using quantile regressions to extract information in marginal distributions and copulas to capture dependence structure. A preference function which captures higher moments is proposed for portfolio selection. An empirical application highlights the additional information provided by the distributional approach which cannot be captured by the traditional moment-based methods.

Portfolio review

The portfolio can be loosely defined as a collection or collation of achievements, artefacts, creative works or examples of competencies, usually for the purpose of demonstrating a person’s capabilities in a specific field of endeavour. People make and share their portfolios for many reasons: social or cultural recognition, employment, accreditation, and educational qualification. It is this latter purpose that this chapter addresses; the creation and use of a portfolio for educational development and certification.

Preparing for portfolio careers in Australian music : setting a research agenda

In the twenty-first century, Australian musicians increasingly maintain ‘portfolio’ careers, in which they combine diverse employment arrangements and activities. Often, these incorporate industry sectors outside of music. This career pattern is widespread but not well understood, largely because of the limitations of existing research. The lack of knowledge about musicians’ work and careers means that Australia currently may not provide appropriate and effective policy, funding, initial training and continuing career support across the diverse music sector. This article discusses existing research relating to the careers and skilling needs of musicians in Australia, and outlines a targeted agenda for further research that has the potential to inform stronger alignment between the requirements of building sustainable music careers and musicians’ education and training.

Embedded tax liabilities and portfolio choice

his study presents an improved method of dealing with embedded tax liabilities in portfolio choice. We argue that using a risk-free discount rate is appropriate for calculating the present value of future tax liabilities. Supportive of recent research, our results found a taxation-induced preference of holding equities over bonds, and a location preference of holding equities in the taxable account and bonds in retirement accounts. These important findings contrast with traditional investment advice which suggests a greater capacity for risk in retirement accounts.

Contributing factors to optimal project portfolio selection

A modified Delphi approach has been applied in this study to investigate best practice and to determine the factors that contribute to optimal selection of projects. There are various standards and practices that some may recognise as representing best practice in this area. Many of these have similar characteristics and this study has found no single best practice. The study identified the factors that contribute to the optimal selection of projects as: culture, process, knowledge of the business, knowledge of the work, education, experience, governance, risk awareness, selection of players, preconceptions, and time pressures. All these factors were found to be significant; to be appropriate to public sector organisations, private sector organisations and government owned corporations; and to have a strong linkage to research on strategic decision making. These factors can be consolidated into two underlying factors of organisation culture and leadership.

Does board gender diversity have a financial impact? Evidence using stock portfolio performance.

There is growing regulatory pressure on firms worldwide to address the under-representation of women in senior positions. Regulators have taken a variety of approaches to the issue. We investigate a jurisdiction that has issued recommendations and disclosure requirements, rather than implementing quotas. Much of the rhetoric surrounding gender diversity centres on whether diversity has a financial impact. In this paper we take an aggregate (market-level) approach and compare the performance of portfolios of firms with gender diverse boards to those without. We also investigate whether having multiple women on the board is linked to performance, and if there is a within-industry effect. Overall, we do not find evidence of an association between diversity and performance. We find some weak evidence of a negative correlation between having multiple women on the board and performance, but that in some industries diversity is positively correlated with performance.

Volatility timing : how best to forecast portfolio exposures

This paper investigates how best to forecast optimal portfolio weights in the context of a volatility timing strategy. It measures the economic value of a number of methods for forming optimal portfolios on the basis of realized volatility. These include the traditional econometric approach of forming portfolios from forecasts of the covariance matrix, and a novel method, where a time series of optimal portfolio weights are constructed from observed realized volatility and directly forecast. The approach proposed here of directly forecasting portfolio weights shows a great deal of merit. Resulting portfolios are of equivalent economic benefit to a number of competing approaches and are more stable across time. These findings have obvious implications for the manner in which volatility timing is undertaken in a portfolio allocation context.

Portfolio selection using artificial intelligence

The application of artificial intelligence in finance is relatively new area of research. This project employed artificial neural networks (ANNs) that use both fundamental and technical inputs to predict future prices of widely held Australian stocks and use these predicted prices for stock portfolio selection over a long investment horizon. The research involved the creation and testing of a large number of possible network configurations and draws conclusions about ANN architectures and their overall suitability for the purpose of stock portfolio selection.

Has portfolio theory got any principles?

Recently, Portfolio Theory (PT) has been proposed for Information Retrieval. However, under non-trivial conditions PT violates the original Probability Ranking Principle (PRP). In this poster, we shall explore whether PT upholds a different ranking principle based on Quantum Theory, i.e. the Quantum Probability Ranking Principle (QPRP), and examine the relationship between this new model and the new ranking principle. We make a significant contribution to the theoretical development of PT and show that under certain circumstances PT upholds the QPRP, and thus guarantees an optimal ranking according to the QPRP. A practical implication of this finding is that the parameters of PT can be automatically estimated via the QPRP, instead of resorting to extensive parameter tuning.

Selecting volatility forecasting models for portfolio allocation purposes

Techniques for evaluating and selecting multivariate volatility forecasts are not yet understood as well as their univariate counterparts. This paper considers the ability of different loss functions to discriminate between a set of competing forecasting models which are subsequently applied in a portfolio allocation context. It is found that a likelihood-based loss function outperforms its competitors, including those based on the given portfolio application. This result indicates that considering the particular application of forecasts is not necessarily the most effective basis on which to select models.