Re-examining the financial returns from New Zealand's SOE sector : re-examining privatisation

This paper considers the potential for profit within state-owned enterprises [SOEs] as part of the privatisation debate, through an examination of New Zealand’s SOE sector from 2006 to 2010, extending and comparing findings of an earlier study from 2001 to 2005.

Microscopic origin of non-Gaussian distributions of financial returns

In this paper we study the possible microscopic origin of heavy-tailed probability density distributions for the price variation of financial instruments. We extend the standard log-normal process to include another random component in the so-called stochastic volatility models. We study these models under an assumption, akin to the Born-Oppenheimer approximation, in which the volatility has already relaxed to its equilibrium distribution and acts as a background to the evolution of the price process. In this approximation, we show that all models of stochastic volatility should exhibit a scaling relation in the time lag of zero-drift modified log-returns. We verify that the Dow-Jones Industrial Average index indeed follows this scaling. We then focus on two popular stochastic volatility models, the Heston and Hull-White models. In particular, we show that in the Hull-White model the resulting probability distribution of log-returns in this approximation corresponds to the Tsallis (t-Student) distribution. The Tsallis parameters are given in terms of the microscopic stochastic volatility model. Finally, we show that the log-returns for 30 years Dow Jones index data is well fitted by a Tsallis distribution, obtaining the relevant parameters. (c) 2007 Elsevier B.V. All rights reserved.

Sensitivity of estimated financial returns on timber investments to data errors /

Includes appendix.

Operational expenditure costs for wave energy projects and impacts on financial returns

This paper examines 'availability' and the input metrics of operational expenditure (OPEX) for wave energy projects and reports on a case study which assesses the impact of these inputs on project profit returns. Case study simulations modelled a 75 MW wave energy project at two locations; the west coast of Ireland and the north coast of Portugal. Access and availability with respect to weather windows at both locations are discussed and their impact on energy output and wave farm operations is quantified. The input metrics used to calculate OPEX of wave energy projects are defined as well as the impact of OPEX on project net present value (NPV) and internal rate of return (IRR). Results indicate that access and resultant availability factors have a significant impact on case study results by reducing energy output and correspondingly financial returns. Furthermore, the technology maturity level designated for a project also impacts on availability factors and consequently energy output and NPV. Case study profits proved to be very sensitive to annual OPEX, especially if overhaul and replacement costs were accounted for. As a result of the impact of 'availability' on project profit returns. Feed-in tariffs will need to be tailored to the location in question as well as the device technology maturity level, with case study simulations indicating that high FIT will be required to support early stage WEC projects. (C) 2012 Elsevier Ltd. All rights reserved.

The risks and returns of new public management : political business

Purpose – This article aims to consider success in terms of the financial returns and risks of new public management (NPM) in state-owned enterprises (SOEs). Design/methodology/approach – Financial returns of New Zealand SOEs were examined through a review of their annual reports over a five-year period. Dimensions of risk were examined through interviews conducted in two phases over a two-year period with senior executives from 12 of the (then) 17 SOEs operating in New Zealand. Findings – Findings indicate the potential for SOEs to operate as profitable government investments, with clear support for positive financial returns under NPM. However, variations noted within individual SOEs also indicate that profitable and commercial operations may not be possible in all cases. An examination of the risks associated with SOEs’ operations reveals a number of dimensions of risk, encompassing financial, political (including regulatory), reputational, and public accountability aspects. Practical implications – There is a need for an enhanced awareness on the part of internal and external stakeholders (such as the government and general public) of the risks SOEs face in pursuing higher levels of profitability. Also required, is a more acute understanding on the part of internal and external stakeholders (e.g. government and the public) of the need for SOEs to manage the range of risks identified, given the potentially delicate balance between risk and return. Originality/value – While previous studies have considered the financial returns of SOEs, or the risks faced by the public sector in terms of accountability, few have addressed the two issues collectively in a single context.

Essays on the Modeling and Prediction of Volatility and Higher Moments of Stock Returns (summary section only)

One of the most fundamental and widely accepted ideas in finance is that investors are compensated through higher returns for taking on non-diversifiable risk. Hence the quantification, modeling and prediction of risk have been, and still are one of the most prolific research areas in financial economics. It was recognized early on that there are predictable patterns in the variance of speculative prices. Later research has shown that there may also be systematic variation in the skewness and kurtosis of financial returns. Lacking in the literature so far, is an out-of-sample forecast evaluation of the potential benefits of these new more complicated models with time-varying higher moments. Such an evaluation is the topic of this dissertation. Essay 1 investigates the forecast performance of the GARCH (1,1) model when estimated with 9 different error distributions on Standard and Poor’s 500 Index Future returns. By utilizing the theory of realized variance to construct an appropriate ex post measure of variance from intra-day data it is shown that allowing for a leptokurtic error distribution leads to significant improvements in variance forecasts compared to using the normal distribution. This result holds for daily, weekly as well as monthly forecast horizons. It is also found that allowing for skewness and time variation in the higher moments of the distribution does not further improve forecasts. In Essay 2, by using 20 years of daily Standard and Poor 500 index returns, it is found that density forecasts are much improved by allowing for constant excess kurtosis but not improved by allowing for skewness. By allowing the kurtosis and skewness to be time varying the density forecasts are not further improved but on the contrary made slightly worse. In Essay 3 a new model incorporating conditional variance, skewness and kurtosis based on the Normal Inverse Gaussian (NIG) distribution is proposed. The new model and two previously used NIG models are evaluated by their Value at Risk (VaR) forecasts on a long series of daily Standard and Poor’s 500 returns. The results show that only the new model produces satisfactory VaR forecasts for both 1% and 5% VaR Taken together the results of the thesis show that kurtosis appears not to exhibit predictable time variation, whereas there is found some predictability in the skewness. However, the dynamic properties of the skewness are not completely captured by any of the models.

Jumps in the Volatility of Financial Markets.

Recent work suggests that the conditional variance of financial returns may exhibit sudden jumps. This paper extends a non-parametric procedure to detect discontinuities in otherwise continuous functions of a random variable developed by Delgado and Hidalgo (1996) to higher conditional moments, in particular the conditional variance. Simulation results show that the procedure provides reasonable estimates of the number and location of jumps. This procedure detects several jumps in the conditional variance of daily returns on the S&P 500 index.

Using benchmarking to improve the financial and social sustainability of commercial goat meat, cashmere and mohair farms in Australia

Production and financial benchmarking was undertaken with commercially motivated mohair, cashmere and goat meat farmers in Australia. There were large differences in animal and fleece production and financial returns between the best and worst performing farms. Farmers and industry groups reported that the process and results were helpful and resulted in them changing management practices. Benchmarking demonstrated that there is substantial scope to increase productivity and profitability through improved genetic selection and improved management of pastures, breeding flocks and in kid survival and growth.

Financial and economic performance of long-rotation hardwood plantation investments in Queensland, Australia

In Queensland, Australia, there is presently a high level of interest in long-rotation hardwood plantation investments for sawlog production, despite the consensus in Australian literature that such investments are not financially viable. Continuing genetics, silviculture and processing research, and increasing awareness about the ecosystem services generated by plantations, are anticipated to make future plantings profitable and socio-economically desirable in many parts of Queensland. Financial and economic models of hardwood plantations in Queensland are developed to test this hypothesis. The economic model accounts for carbon sequestration, salinity amelioration and other ecosystem service values of hardwood plantations. A carbon model estimates the value of carbon sequestered, while salinity and other ecosystem service values are estimated by the benefit transfer method. Where high growth rates (20-25 m(3) ha(-1) year(-1)) are achievable, long-rotation hardwood plantations are profitable in Queensland Hardwood Regions 1, 3 and 7 when rural land values are less than $2300/ha. Under optimistic assumptions, hardwood plantations growing at a rate of 15 in 3 ha-1 year 1 are financially viable in Hardwood Regions 2, 4 and 8, provided land values are less than $1600/ha. The major implication of the economic analysis is that long-rotation hardwood plantation forestry is socio-economically justified in most Hardwood Regions, even though financial returns from timber production may be negative. (c) 2003 Elsevier B.V. All rights reserved.

E-business adoption in construction : international review on impediments

The adoption of e-business by the Australian construction industry lags other service and product industries. It is assumed that slow adoption rate does not reflect the maturity of the technology but is due to adoption impediments peculiar to the nature of construction. This chapter examines impediments to the uptake of e-business nationally and internationally. A systematic and extensive literature search of impediments (also referred to as obstacles, impediments or hindrances) to adoption has been undertaken and the findings discussed in this chapter. This review included more that 200 documents and these have been published in a searchable database as part of a larger research initiative funded by the Cooperative Research Centre for Construction Innovation. The influence of levels of e-business maturity seen in other sectors such as retail, tourism and manufacturing was also captured and a number of major impediments were identified some including: privacy, trust, uncertainty of financial returns, lack of reliable measurement, fraud, lack of support and system maintenance. A total of 23 impediments were assessed in terms of impact to organisational type and size across reviewed documents. With this information it was possible to develop a reference framework for measuring maturity levels and readiness to uptake e-business in construction. Results have also shown that impediments to e-business adoption work differently according to organisational type and culture. Areas of training and people development need to be addressed. This would include a more sensitive approach to the nature of construction organisations, especially to those small and medium enterprises. Raising levels of awareness and creating trust for on-line collaboration are other aspects that need attention, which current studies confirm as lacking. An empirical study within construction, to validate these findings, forms the subsequent phase of this research.

Barriers to e-business adoption in construction: international literature review

The adoption of e-business by the Australian construction industry lags other service and product industries. It is assumed that slow adoption rate does not reflect the maturity of the technology but is due to adoption barriers peculiar to the nature of construction. This paper examines impediments to the uptake of e-business nationally and internationally. A systematic and extensive literature search of barriers (also referred to as obstacles, impediments or hindrances) to adoption has been undertaken and the findings discussed in this paper. This review included more that 200 documents and these have been published in a searchable database as part of a larger research initiative funded by the Cooperative Research Centre for Construction Innovation. The influence of levels of e-business maturity seen in other sectors such as retail, tourism and manufacturing was also captured and a number of major barriers were identified some including: privacy, trust, uncertainty of financial returns, lack of reliable measurement, fraud, lack of support and system maintenance. A total of 23 barriers were assessed in terms of impact to organisational type and size across reviewed documents. With this information it was possible to develop a reference framework for measuring maturity levels and readiness to uptake e-business in construction. Results have also shown that barriers to e-business adoption work differently according to organisational type and culture. Areas of training and people development need to be addressed. This would include a more sensitive approach to the nature of construction organisations, especially to those small and medium enterprises. Raising levels of awareness and creating trust for on-line collaboration are other aspects that need attention, which current studies confirm as lacking. An empirical study within construction, to validate these findings, forms the subsequent phase of this research.

Forecasting time-varying value-at-risk

In this thesis we are interested in financial risk and the instrument we want to use is Value-at-Risk (VaR). VaR is the maximum loss over a given period of time at a given confidence level. Many definitions of VaR exist and some will be introduced throughout this thesis. There two main ways to measure risk and VaR: through volatility and through percentiles. Large volatility in financial returns implies greater probability of large losses, but also larger probability of large profits. Percentiles describe tail behaviour. The estimation of VaR is a complex task. It is important to know the main characteristics of financial data to choose the best model. The existing literature is very wide, maybe controversial, but helpful in drawing a picture of the problem. It is commonly recognised that financial data are characterised by heavy tails, time-varying volatility, asymmetric response to bad and good news, and skewness. Ignoring any of these features can lead to underestimating VaR with a possible ultimate consequence being the default of the protagonist (firm, bank or investor). In recent years, skewness has attracted special attention. An open problem is the detection and modelling of time-varying skewness. Is skewness constant or there is some significant variability which in turn can affect the estimation of VaR? This thesis aims to answer this question and to open the way to a new approach to model simultaneously time-varying volatility (conditional variance) and skewness. The new tools are modifications of the Generalised Lambda Distributions (GLDs). They are four-parameter distributions, which allow the first four moments to be modelled nearly independently: in particular we are interested in what we will call para-moments, i.e., mean, variance, skewness and kurtosis. The GLDs will be used in two different ways. Firstly, semi-parametrically, we consider a moving window to estimate the parameters and calculate the percentiles of the GLDs. Secondly, parametrically, we attempt to extend the GLDs to include time-varying dependence in the parameters. We used the local linear regression to estimate semi-parametrically conditional mean and conditional variance. The method is not efficient enough to capture all the dependence structure in the three indices —ASX 200, S&P 500 and FT 30—, however it provides an idea of the DGP underlying the process and helps choosing a good technique to model the data. We find that GLDs suggest that moments up to the fourth order do not always exist, there existence appears to vary over time. This is a very important finding, considering that past papers (see for example Bali et al., 2008; Hashmi and Tay, 2007; Lanne and Pentti, 2007) modelled time-varying skewness, implicitly assuming the existence of the third moment. However, the GLDs suggest that mean, variance, skewness and in general the conditional distribution vary over time, as already suggested by the existing literature. The GLDs give good results in estimating VaR on three real indices, ASX 200, S&P 500 and FT 30, with results very similar to the results provided by historical simulation.

The importance of environmental issues and costs in Life Cycle Cost Analysis (LCCA) for highway projects

Sustainability has been increasingly recognised as an integral part of highway infrastructure development. In practice however, the fact that financial return is still a project’s top priority for many, environmental aspects tend to be overlooked or considered as a burden, as they add to project costs. Sustainability and its implications have a far-reaching effect on each project over time. Therefore, with highway infrastructure’s long-term life span and huge capital demand, the consideration of environmental cost/ benefit issues is more crucial in life-cycle cost analysis (LCCA). To date, there is little in existing literature studies on viable estimation methods for environmental costs. This situation presents the potential for focused studies on environmental costs and issues in the context of life-cycle cost analysis. This paper discusses a research project which aims to integrate the environmental cost elements and issues into a conceptual framework for life cycle costing analysis for highway projects. Cost elements and issues concerning the environment were first identified through literature. Through questionnaires, these environmental cost elements will be validated by practitioners before their consolidation into the extension of existing and worked models of life-cycle costing analysis (LCCA). A holistic decision support framework is being developed to assist highway infrastructure stakeholders to evaluate their investment decision. This will generate financial returns while maximising environmental benefits and sustainability outcome.