The valuation of long life mines : current issues and methodologies

The past decade has seen an increasing focus on the mining and extractive industries in Australia. The significant increases in both new mines, commodity prices and employment opportunities has lead to considerable discussion on the value of this industry and the contribution that the industry makes to exports, GDP and the public in general. This debate has resulted in the introduction of the Mineral Resources Rent Tax being introduced in 2012. An issue that follows from the introduction of these taxes is the current exposure of property valuers to mine and extractive industry valuations and the most appropriate method that should be employed for valuing long life mines for rating and taxing purposes, finance and accounting purposes. This paper will provide a detailed review of past and current valuation methods for long life mines and will highlight the current issues and problem facing valuers who are currently working in or intend to carry out valuation work in this industry.

Public Economics and the Assessment of Tourism Developments and Policies

Public economics covers both topics in welfare economic of social (as opposed to private) interest and aspects of public finance. This chapter considers the application of two methods of social economic evaluation of tourist developments, namely, social cost-benefit analysis and economic impact analysis. The role of social cost-benefit analysis in the assessment of tourism is illustrated by its application to the evaluation of inbound tourism. This is followed by a discussion of taxes on tourism and subsidies to promote it. The principle focus is on hotel room taxes. The analysis of taxes on tourism involves both public finance and welfare economics issues. The scope for and desirability of applying the user-pays principle to tourism is then examined.

Distance education and the application of academagogy : a case study

The education sector has dramatically changed in the past half decade. In a time of globalisation of education and tightening budgets, various paradigm shifts and challenges have rapidly changed learning and teaching. These include: meeting student expectation for more engaging, more interactive learning experiences, the increased focus to deliver content online, and the complexities of fast-changing technologies. Rising to these challenges and responding to them is a complex and multi-faceted task. This paper discusses educational theories and issues and explores current educational practices in the context of teaching undergraduate students via distance education in the university context. A case study applies a framework drawn from engineering education using the learner-centric concept of academagogy. Results showed that academagogy actively empowers students to build effective learning, and engages facilitators in meaningful teaching and delivery methods.

Use and usefulnss of PDSs in the financial planning context

Following considerable criticism of the complexity and lack of readability of product disclosure statements (PDSs), regulatory changes were introduced requiring shorter PDSs for certain investment products. This paper reports the findings of an online survey of financial planners regarding use of managed investment scheme (MIS) PDSs with clients, the perceived usefulness of PDSs as an information source, and their views on shorter PDSs. Our findings highlight major concerns about the usefulness of the PDS and disclosure reforms.

Simultaneous estimation of hunting pressure, harvest and hunter success rates using WinBUGS

The use of hierarchical Bayesian spatial models in the analysis of ecological data is increasingly prevalent. The implementation of these models has been heretofore limited to specifically written software that required extensive programming knowledge to create. The advent of WinBUGS provides access to Bayesian hierarchical models for those without the programming expertise to create their own models and allows for the more rapid implementation of new models and data analysis. This facility is demonstrated here using data collected by the Missouri Department of Conservation for the Missouri Turkey Hunting Survey of 1996. Three models are considered, the first uses the collected data to estimate the success rate for individual hunters at the county level and incorporates a conditional autoregressive (CAR) spatial effect. The second model builds upon the first by simultaneously estimating the success rate and harvest at the county level, while the third estimates the success rate and hunting pressure at the county level. These models are discussed in detail as well as their implementation in WinBUGS and the issues arising therein. Future areas of application for WinBUGS and the latest developments in WinBUGS are discussed as well.

Climate change and financial regulation : challenges for the financial sector post the Global Financial Crisis

Regulation has played a significant role in shaping the financial services sector in Australia over the past few decades. Regulatory changes have included the establishment of the Australian Prudential Regulation Authority (APRA), floating the Australian dollar, allowing foreign financial institutions to operate domestically, the introduction of the superannuation guarantee charge, and the removal of interest rate controls. As the economy emerges from the worst financial crisis since the great depression, a new force of change that is recognised as one of the most significant sources of risk and opportunity facing the business community in the foreseeable future is that of climate change. Climate change is expected to be a significant change agent in the financial services sector as extreme weather patterns, sea level rises, and atmospheric changes impact on asset values (both investment and lending), project finance, and risk products. The financial services industry will be particularly affected by these developments, both as a provider of financial products (capital, credit, investment, advice, and insurance), and also through its powerful influence on the economy in terms of capital allocation. In addition, industry constituents will be heavily impacted by government regulation in this area (reporting, emissions trading and environmental policies), with respect to their own business practices and also those of their clients. This study reports the results of interviews conducted with senior members of the finance sector working in the sustainability area to gauge their perceptions of the challenges facing the sector with respect to climate change. Our results confirm that that regulatory intervention will be critical to climate change response gaining traction and momentum. In particular, regulatory certainty will promote engagement, particularly in relation to the Carbon Pollution Reduction Scheme (CPRS), with other developments needed in terms of information disclosure, performance and remuneration, and incentive programs. Accordingly, the significant potential risks and opportunities that climate change presents to the sector, and the broader economy, will in part be managed/realised only if a swift and significant regulatory response is achieved.

A nutrition and physical activity intervention for family child care homes

Background Family child care homes (FCCHs) provide child care to 1.9 million children in the U.S., but many do not meet established child care standards for healthy eating and physical activity. Purpose To determine the effects of a community-based train-the-trainer intervention on FCCHs policies and practices related to healthy eating and physical activity. Design Quasi-experimental design with replication in three independent cohorts of FCCHs. Setting/participants Registered FCCHs from 15 counties across Kansas participated in the Healthy Kansas Kids (HKK) program. Resource and referral agencies (RRAs) in each county recruited and enrolled between five and 15 child care providers in their service delivery area to participate in the program. The number of registered FCCHs participating in HKK in Years 1 (2006-2007); 2 (2007-2008); and 3 (2008-2009) of the program were 85, 64, and 87, respectively. A stratified random sample of registered FCCHs operating in Kansas (n=297) served as a normative comparison group. Interventions Child care trainers from each RRA completed a series of train-the-trainer workshops related to promotion of healthy eating and physical activity. FCCHs were subsequently guided through a four-step iterative process consisting of (1) self-evaluation; (2) goal setting; (3) developing an action plan; and (4) evaluating progress toward meeting goals. FCCHs also received U. S. Department of Agriculture resources related to healthy eating and physical activity. Main outcome measures Nutrition and Physical Activity Self-Assessment for Child Care (NAP SACC) self-assessment instrument (NAP SACC-SA). Analyses of outcome measures were conducted between 2008 and 2010. Results Healthy Kansas Kids FCCHs exhibited significant improvements in healthy eating (Delta=6.9%-7.1%) and physical activity (Delta=15.4%-19.2%) scores (p<0.05). Within each cohort, pre-intervention scores were not significantly different from the state average, whereas post-intervention scores were significantly higher than the state average. Conclusions Community-based train-the-trainer interventions to promote healthy eating and physical activity in FCCHs are feasible, sustainable, and effective.

Multi-utility finance : a problematic case

This paper treats one particular version of the multi-utility strategy as experienced by the Hyder Group. We examine some aspectw of the company's financial performance and consider the implications.

Corporate governance and securities class actions

This study investigates the governance attributes of firms that have been subject to securities class actions (SCAs). There has been a recent sizable increase in the number of firms subject to SCAs in Australia. We examine a sample of firms that have been subject to SCAs due to disclosure breaches and match the firms by industry and size to a control sample. First, we examine the compliance culture of the SCA firms via the frequency of Australian Securities Exchange (ASX)queries of the firm and find that the frequency of ASX queries is positively associated with the occurrence of a SCA. Secondly, we provide evidence that SCA firms exhibit weaker levels of corporate governance than the matched control sample. In addition, we contribute to the understanding of firms subject to SCAs and their corporate governance attributes. Our results suggest the presence of a nomination committee may be associated with higher agency costs and that the influence of CEO duality may reduce the effectiveness of a nomination committee.

Australian stock indexes and the four-factor model

Stock indexes are passive 'value-weighted' portfolios and should not have alphas which are significantly different from zero. If an index produces an insignificant alphan, then significant alphas for equity funds using this index can be attributed solely to manager performance. However, recent literature sugests that US Stock indexes can demonstrate significant alphas, which ultimately raise questions regarding equity fund manager performance in both the US and abroad. in this paper, we employ the Carhart four-factor model and newly available Asian-Pacific risk factors to generate alphas and risk factor loadings for eight Australian stock indexes from January 2004 to December 2012. We ifnd that the initial full sample period analysis does not provide indication of significant alphas in the indexes examined. However, by carrying out 36-month rolling regressions, we discover at least four significant alphas in seven of the eight indexes and factor loading variability. As previously reported in the US, this paper confirms similar issues with the four-factor model using Australian stock indexes and performance benchmarking. In effectively measuring Australian equity fund manager performance, it is therefore essential to evaluate a fund's alpha and risk factors relative to the alpha and risk factors of the appropriate benchmark index.

Spatiotemporal analysis of indigenous and imported dengue fever cases in Guangdong province, China

Background Dengue fever has been a major public health concern in China since it re-emerged in Guangdong province in 1978. This study aimed to explore spatiotemporal characteristics of dengue fever cases for both indigenous and imported cases during recent years in Guangdong province, so as to identify high-risk areas of the province and thereby help plan resource allocation for dengue interventions. Methods Notifiable cases of dengue fever were collected from all 123 counties of Guangdong province from 2005 to 2010. Descriptive temporal and spatial analysis were conducted, including plotting of seasonal distribution of cases, and creating choropleth maps of cumulative incidence by county. The space-time scan statistic was used to determine space-time clusters of dengue fever cases at the county level, and a geographical information system was used to visualize the location of the clusters. Analysis were stratified by imported and indigenous origin. Results 1658 dengue fever cases were recorded in Guangdong province during the study period, including 94 imported cases and 1564 indigenous cases. Both imported and indigenous cases occurred more frequently in autumn. The areas affected by the indigenous and imported cases presented a geographically expanding trend over the study period. The results showed that the most likely cluster of imported cases (relative risk = 7.52, p < 0.001) and indigenous cases (relative risk = 153.56, p < 0.001) occurred in the Pearl River Delta Area; while a secondary cluster of indigenous cases occurred in one district of the Chao Shan Area (relative risk = 471.25, p < 0.001). Conclusions This study demonstrated that the geographic range of imported and indigenous dengue fever cases has expanded over recent years, and cases were significantly clustered in two heavily urbanised areas of Guangdong province. This provides the foundation for further investigation of risk factors and interventions in these high-risk areas.

A nationwide web-based automated system for early outbreak detection and rapid response in China

Timely reporting, effective analyses and rapid distribution of surveillance data can assist in detecting the aberration of disease occurrence and further facilitate a timely response. In China, a new nationwide web-based automated system for outbreak detection and rapid response was developed in 2008. The China Infectious Disease Automated-alert and Response System (CIDARS) was developed by the Chinese Center for Disease Control and Prevention based on the surveillance data from the existing electronic National Notifiable Infectious Diseases Reporting Information System (NIDRIS) started in 2004. NIDRIS greatly improved the timeliness and completeness of data reporting with real time reporting information via the Internet. CIDARS further facilitates the data analysis, aberration detection, signal dissemination, signal response and information communication needed by public health departments across the country. In CIDARS, three aberration detection methods are used to detect the unusual occurrence of 28 notifiable infectious diseases at the county level and to transmit that information either in real-time or on a daily basis. The Internet, computers and mobile phones are used to accomplish rapid signal generation and dissemination, timely reporting and reviewing of the signal response results. CIDARS has been used nationwide since 2008; all Centers for Disease Control and Prevention (CDC) in China at the county, prefecture, provincial and national levels are involved in the system. It assists with early outbreak detection at the local level and prompts reporting of unusual disease occurrences or potential outbreaks to CDCs throughout the country.

Shari'ah supervision, corporate governance and performance: Conventional vs. Islamic banks

The performance and accountability of boards of directors and effectiveness of governance mechanisms continue to be a matter of concern. Focusing on differences between conventional banks and Islamic banks, we examine the effect of (i) Shari-ah supervision boards, (ii) board structure and (iii) CEO-power on performance during the period 2005-2011. We find Shari'ah supervision boards positively impact on Islamic banks' performance when they perform a supervisory role, but the impact is negligible when they have only an advisory role. The effect of board structure (Board size and board independence) and CEO power (CEO-chair duality and internally recruited CEO) on the performance of Islamic banks is overall negative. Our findings provide support for the positive contribution of Shari'ah supervision boards overall negative. Our findings provide support for the positive contribution of Shari'ah supervision boards overall negative. Our findings provide support for the positive contribution of Shari'ah supervision boards but also emphasize the need for enforcement and regulatory mechanism for them to be more effective.

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.

Modeling and Forecasting Implied Volatility: Implications for Trading, Pricing, and Risk Management

Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.