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.

Dynamic contrast-enhanced magnetic resonance imaging as a biomarker for the pharmacological response of PTK787/ZK 222584, an inhibitor of the vascular endothelial growth factor receptor tyrosine kinases, in patients with advanced colorectal cancer and liver metastases: Results from two phase I studies

Purpose: PTK787/ZK 222584 (PTK/ZK), an orally active inhibitor of vascular endothelial growth factor (VEGF) receptor tyrosine kinases, inhibits VEGF-mediated angiogenesis. The pharmacodynamic effects of PTK/ZK were evaluated by assessing changes in contrast-enhancement parameters of metastatic liver lesions using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in patients with advanced colorectal cancer treated in two ongoing, dose-escalating phase I studies. Patients and Methods: Twenty-six patients had DCE-MRI performed at baseline, day 2, and at the end of each 28-day cycle. Doses of oral PTK/ZK ranged from 50 to 2000 mg once daily. Tumor permeability and vascularity were assessed by calculating the bidirectional transfer constant (Ki). The percentage of baseline Ki (% of baseline Ki) at each time point was compared with pharmacokinetic and clinical end points. Results: A significant negative correlation exists between the % of baseline Ki and increase in PTK/ZK oral dose and plasma levels (P = .01 for oral dose; P = .0001 for area under the plasma concentration curve at day 2). Patients with a best response of stable disease had a significantly greater reduction in Ki at both day 2 and at the end of cycle 1 compared with progressors (mean difference in % of baseline Ki, 47%, P = .004%; and 51%, P = .006; respectively). The difference in % of baseline Ki remained statistically significant after adjusting for baseline WHO performance status. Conclusion: These findings should help to define a biologically active dose of PTK/ZK. These results suggest that DCE-MRI may be a useful biomarker for defining the pharmacological response and dose of angiogenesis inhibitiors, such as PTK/ZK, for further clinical development. © 2003 by American Society of Clinical Oncology.

Re-think, Re-generate, Re-envisage fashionable sun-safe apparel

Design is a way of thinking and working that systematically can create immense societal change. In particular, fashion design is one of the most progressively forward-looking creative and commercial generators that can envisage and initiate meaningful visual and social transformation. If we look back in time at the authority of fashion, many trends have significantly induced visual norms aligning glamour and health with tanned skin - numerous examples exist, including Vogue magazine proclaiming (front-cover) that ‘The 1929 girl must be tanned’. Indeed, in a contemporary landscape, fashion trends continue to re-generate apparel that, in-the-main, has limited design resolution connected to sun safety, and surprisingly many designers elect to ignore this vital and potentially lucrative market segment. In a context with soaring skin cancer rates, how can this powerful design medium of fashion make a positive difference to sun protection; what is the untapped potential for young design talent to connect with the health sector for skin cancer prevention; and, how can fashion designers be swayed to design and produce fashionable sun-safe apparel, that address pertinent issues including heat build up, comfort and transformability? Through a case study approach, examining emergent fashion designers, this paper will propose that astute and novel avenues exist for fashion to re-think sun protective apparel, including: generation of crucial design standards for sun-safe apparel, exploration of co-branding opportunities, advancement of fashion forecasting to connect modesty of body coverage to fashion trends and alignment of the market segment to re-envisage a critical mass for fashionable sun-safe apparel.

Exploring plant genomes by RNA-induced gene silencing

The nucleotide sequences of several animal, plant and bacterial genomes are now known, but the functions of many of the proteins that they are predicted to encode remain unclear. RNA interference is a gene-silencing technology that is being used successfully to investigate gene function in several organisms - for example, Caenorhabditis elegans. We discuss here that RNA-induced gene silencing approaches are also likely to be effective for investigating plant gene function in a high-throughput, genome-wide manner.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

A Bayesian regression approach to assess uncertainty in pollutant wash-off modelling

Due to knowledge gaps in relation to urban stormwater quality processes, an in-depth understanding of model uncertainty can enhance decision making. Uncertainty in stormwater quality models can originate from a range of sources such as the complexity of urban rainfall-runoff-stormwater pollutant processes and the paucity of observed data. Unfortunately, studies relating to epistemic uncertainty, which arises from the simplification of reality are limited and often deemed mostly unquantifiable. This paper presents a statistical modelling framework for ascertaining epistemic uncertainty associated with pollutant wash-off under a regression modelling paradigm using Ordinary Least Squares Regression (OLSR) and Weighted Least Squares Regression (WLSR) methods with a Bayesian/Gibbs sampling statistical approach. The study results confirmed that WLSR assuming probability distributed data provides more realistic uncertainty estimates of the observed and predicted wash-off values compared to OLSR modelling. It was also noted that the Bayesian/Gibbs sampling approach is superior compared to the most commonly adopted classical statistical and deterministic approaches commonly used in water quality modelling. The study outcomes confirmed that the predication error associated with wash-off replication is relatively higher due to limited data availability. The uncertainty analysis also highlighted the variability of the wash-off modelling coefficient k as a function of complex physical processes, which is primarily influenced by surface characteristics and rainfall intensity.

Time as the critical factor in the investigation of the relationship between pollutant wash-off and rainfall characteristics

The approach adopted for investigating the relationship between rainfall characteristics and pollutant wash-off process is commonly based on the use of parameters which represent the entire rainfall event. This does not permit the investigation of the influence of rainfall characteristics on different sectors of the wash-off process such as first flush where there is a high pollutant wash-off load at the initial stage of the runoff event. This research study analysed the influence of rainfall characteristics on the pollutant wash-off process using two sets of innovative parameters by partitioning wash-off and rainfall characteristics. It was found that the initial 10% of the wash-off process is closely linked to runoff volume related rainfall parameters including rainfall depth and rainfall duration while the remaining part of the wash-off process is primarily influenced by kinetic energy related rainfall parameters, namely, rainfall intensity. These outcomes prove that different sectors of the wash-off process are influenced by different segments of a rainfall event.

The Impacts of Climate Change on Australia’s Food Production and Export

The global food system is undergoing unprecedented change. With population increases, demands for food globally will continue to rise at the same time that agricultural environments are compromised through urban encroachment, climate change and environmental degradation. Australia has long identified itself as an agricultural exporting nation—but what will its capacity be in feeding an increasing global population as it also comes to terms with extreme climatic events such as the floods, fires and droughts, and reduced water availability, experienced in recent decades? This chapter traces the history of Australian agricultural exports and evaluates its food production and export capacity against scientific predictions of climate change impacts. With the federal government forecasting declines in the production of wheat, beef, dairy and sugar, Australia’s key export commodities may well be compromised. Calls to produce more food using new technologies are likely to generate significant environmental problems. Yet, a radical reconfiguration of Australian agriculture which incorporates alternative approaches, such as agro-ecology, is rarely considered by government and industry.

Do prediction markets produce well-calibrated probability forecasts?

This article presents new theoretical and empirical evidence on the forecasting ability of prediction markets. We develop a model that predicts that the time until expiration of a prediction market should negatively affect the accuracy of prices as a forecasting tool in the direction of a ‘favourite/longshot bias’. That is, high-likelihood events are underpriced, and low-likelihood events are over-priced. We confirm this result using a large data set of prediction market transaction prices. Prediction markets are reasonably well calibrated when time to expiration is relatively short, but prices are significantly biased for events farther in the future. When time value of money is considered, the miscalibration can be exploited to earn excess returns only when the trader has a relatively low discount rate.

Sustainable Urban Water Environment : Climate, Pollution and Adaptation

"This multi-disciplinary book provides practical solutions for safeguarding the sustainability of the urban water environment. Firstly, the importance of the urban water environment is highlighted and the major problems urban water bodies face and strategies to safeguard the water environment are explored. Secondly, the diversity of pollutants entering the water environment through stormwater runoff are discussed and modelling approaches for factoring in climate change and future urban and transport scenarios are proposed. Thirdly, by linking the concepts of sustainable urban ecosystems and sustainable urban and transport development, capabilities of two urban sustainability assessment models are demonstrated."--publisher website

Energy Transformed : Building Capacity in the Engineering Profession in Australia

Global pressures of burgeoning population growth and consumption are threatening efforts to reduce negative environmental pressures associated with development such as atmospheric, land and water pollution. For example, the world’s population is now growing at over 70 million per year or 1 billion per decade (Brown, 2007), increasing from 3.5 billion in 1970, to 5 billion in 1990, to 7 billion by 2010 (United Nations, 2002). In 1990 only 13 percent of the global population lived in cities, while in 2007 more than half did. More than 60 percent of the global population lives within 100 kilometers of the coastline (World Resources Institute, 2005) and nearly all of the population growth hereon is forecast to happen in developing countries (Postel, 1999). Future levels of stress on the global environment are therefore likely to increase if current trends are used for forecasting, which is particularly challenging as scientists are already observing significant signs of degradation and failure in environmental systems. For example, the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC, 2007) provided an nequivocal link between climate change and current human activities, in particular: the burning of fossil fuels; deforestation and land clearing; the use of synthetic greenhouse gases; and decomposition of wastes from landfill. The UK Stern Review concluded that within our lifetime there is between a 77 to 99 percent chance (depending on the climate model used) of the global average temperature rising by more than 2 degrees Celsius (Stern, 2006), with a likely greenhouse gas concentration in the atmosphere of 550 parts per million (ppm) or more by around 2100.

Discerning the timing and cause of historical mortality events in modern Porites from the Great Barrier Reef

The life history strategies of massive Porites corals make them a valuable resource not only as key providers of reef structure, but also as recorders of past environmental change. Yet recent documented evidence of an unprecedented increase in the frequency of mortality in Porites warrants investigation into the history of mortality and associated drivers. To achieve this, both an accurate chronology and an understanding of the life history strategies of Porites are necessary. Sixty-two individual Uranium–Thorium (U–Th) dates from 50 dead massive Porites colonies from the central inshore region of the Great Barrier Reef (GBR) revealed the timing of mortality to have occurred predominantly over two main periods from 1989.2 ± 4.1 to 2001.4 ± 4.1, and from 2006.4 ± 1.8 to 2008.4 ± 2.2 A.D., with a small number of colonies dating earlier. Overall, the peak ages of mortality are significantly correlated with maximum sea-surface temperature anomalies. Despite potential sampling bias, the frequency of mortality increased dramatically post-1980. These observations are similar to the results reported for the Southern South China Sea. High resolution measurements of Sr/Ca and Mg/Ca obtained from a well preserved sample that died in 1994.6 ± 2.3 revealed that the time of death occurred at the peak of sea surface temperatures (SST) during the austral summer. In contrast, Sr/Ca and Mg/Ca analysis in two colonies dated to 2006.9 ± 3.0 and 2008.3 ± 2.0, suggest that both died after the austral winter. An increase in Sr/Ca ratios and the presence of low Mg-calcite cements (as determined by SEM and elemental ratio analysis) in one of the colonies was attributed to stressful conditions that may have persisted for some time prior to mortality. For both colonies, however, the timing of mortality coincides with the 4th and 6th largest flood events reported for the Burdekin River in the past 60 years, implying that factors associated with terrestrial runoff may have been responsible for mortality. Our results show that a combination of U–Th and elemental ratio geochemistry can potentially be used to precisely and accurately determine the timing and season of mortality in modern massive Porites corals. For reefs where long-term monitoring data are absent, the ability to reconstruct historical events in coral communities may prove useful to reef managers by providing some baseline knowledge on disturbance history and associated drivers.

Predicting movie ratings from audience behaviors

We propose a method of representing audience behavior through facial and body motions from a single video stream, and use these features to predict the rating for feature-length movies. This is a very challenging problem as: i) the movie viewing environment is dark and contains views of people at different scales and viewpoints; ii) the duration of feature-length movies is long (80-120 mins) so tracking people uninterrupted for this length of time is still an unsolved problem, and; iii) expressions and motions of audience members are subtle, short and sparse making labeling of activities unreliable. To circumvent these issues, we use an infrared illuminated test-bed to obtain a visually uniform input. We then utilize motion-history features which capture the subtle movements of a person within a pre-defined volume, and then form a group representation of the audience by a histogram of pair-wise correlations over a small-window of time. Using this group representation, we learn our movie rating classifier from crowd-sourced ratings collected by rottentomatoes.com and show our prediction capability on audiences from 30 movies across 250 subjects (> 50 hrs).

Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold

This paper employs a VAR-GARCH model to investigate the return links and volatility transmission between the S&P 500 and commodity price indices for energy, food, gold and beverages over the turbulent period from 2000 to 2011. Understanding the price behavior of commodity prices and the volatility transmission mechanism between these markets and the stock exchanges are crucial for each participant, including governments, traders, portfolio managers, consumers, and producers. For return and volatility spillover, the results show significant transmission among the S&P 500 and commodity markets. The past shocks and volatility of the S&P 500 strongly influenced the oil and gold markets. This study finds that the highest conditional correlations are between the S&P 500 and gold index and the S&P 500 and WTI index. We also analyze the optimal weights and hedge ratios for commodities/S&P 500 portfolio holdings using the estimates for each index. Overall, our findings illustrate several important implications for portfolio hedgers for making optimal portfolio allocations, engaging in risk management and forecasting future volatility in equity and commodity markets. © 2013 Elsevier B.V.