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.

Alcohol expectancy changes over a 12-week cognitive–behavioral therapy program are predictive of treatment success

This study examines if outcome expectancies (perceived consequences of engaging in certain behavior) and self- efficacy expectancies (confidence in personal capacity to regulate behavior) contribute to treatment outcome for alcohol dependence. Few clinical studies have examined these constructs. The Drinking Expectancy Profile (DEP), a psychometric measure of alcohol expectancy and drinking refusal selfefficacy, was administered to 298 alcohol-dependent patients (207 males) at assessment and on completion of a 12-week cognitive–behavioral therapy alcohol abstinence program. Baseline measures of expectancy and self-efficacy were not strong predictors of outcome. However, for the 164 patients who completed treatment, all alcohol expectancy and self-efficacy factors of the DEP showed change over time. The DEP scores approximated community norms at the end of treatment. Discriminant analysis indicated that change in social pressure drinking refusal self-efficacy, sexual enhancement expectancies, and assertion expectancies successfully discriminated those who successfully completed treatment from those who did not. Future research should examine the basis of expectancies related to social functioning as a possible mechanism of treatment response and a means to enhance treatment outcome.

The mediating effects of the time structure on the relationships between time management behaviour, job satisfaction and psychological wellbeing

This article examined the relationship between time structure and Macan's process model of time management. This study proposed that time structure—‘appraisal of effective time usage’—would be a more parsimonious mediator than perceived control over time in the relationship between time management behaviours and outcome variables, such as job satisfaction and psychological well-being. Alternative structure models were compared using a sample of 111 university students. Model 1 tested Macan's process model of time management with perceived control over time as the mediator. Model 2 replaced perceived control over time by the construct of time structure. Model 3 examined the possibility of perceived control over time and time structure as being parallel mediators of the relationships between time management and outcomes. Results of this study showed that Model 1 and Model 2 fitted the data equally well. On the other hand, the mediated effects were small and partial in both models. This pattern of results calls for reassessment of the process model.

Rural activity spaces and transport disadvantage : qualitative analysis of quantitative models integrating time and space

Current knowledge about the relationship between transport disadvantage and activity space size is limited to urban areas, and as a result, very little is known to date about this link in a rural context. In addition, although research has identified transport disadvantaged groups based on their size of activity spaces, these studies have, however, not empirically explained such differences and the result is often a poor identification of the problems facing disadvantaged groups. Research has shown that transport disadvantage varies over time. The static nature of analysis using the activity space concept in previous research studies has lacked the ability to identify transport disadvantage in time. Activity space is a dynamic concept; and therefore possesses a great potential in capturing temporal variations in behaviour and access opportunities. This research derives measures of the size and fullness of activity spaces for 157 individuals for weekdays, weekends, and for a week using weekly activity-travel diary data from three case study areas located in rural Northern Ireland. Four focus groups were also conducted in order to triangulate the quantitative findings and to explain the differences between different socio-spatial groups. The findings of this research show that despite having a smaller sized activity space, individuals were not disadvantaged because they were able to access their required activities locally. Car-ownership was found to be an important life line in rural areas. Temporal disaggregation of the data reveals that this is true only on weekends due to a lack of public transport services. In addition, despite activity spaces being at a similar size, the fullness of activity spaces of low-income individuals was found to be significantly lower compared to their high-income counterparts. Focus group data shows that financial constraint, poor connections both between public transport services and between transport routes and opportunities forced individuals to participate in activities located along the main transport corridors.

Out of time: The moral temporality of sex, crime and taboo

This paper discusses the relationship between law and morality. Morality does not necessarily coincide with the law, but it contributes to it. An act may be legal but nevertheless considered to be immoral in a particular society. For example, the use of pornography may be considered by many to be immoral. Nevertheless, the sale and distribution of non-violent, non-child related, sexually explicit material is legal (or regulated) in many jurisdictions. Many laws are informed by, and even created by, morality. This paper examines the historical influence of morality on the law and on society in general. It aims to develop a theoretical framework for examining legal moralism and the social construction of morality and crime as well as the relationship between sex, desire and taboo. Here, we refer to the moral temporality of sex and taboo, which examines the way in which moral judgments about sex and what is considered taboo change over time, and the kinds of justifications that are employed in support of changing moralities. It unpacks the way in which abstract and highly tenuous concepts such as ‘‘desire’’, ‘‘art’’ and ‘‘entertainment’’ may be ‘‘out of time’’ with morality, and how morality shapes laws over time, fabricating justifications from within socially constructed communities of practice. This theoretical framework maps the way in which these concepts have become temporally dominated by heteronormative structures such as the family, marriage, reproduction, and longevity. It is argued that the logic of these structures is inexorably tied to the heterosexual life-path, charting individual lives and relationships through explicit phases of childhood, adolescence and adulthood that, in the twenty-first century, delimit the boundaries of taboo surrounding sex more than any other time in history.

The impact of nonlinear exposure risk relationships on seasonal time series data: modelling danish neonatal birth anthropometric data

Background Birth weight and length have seasonal fluctuations. Previous analyses of birth weight by latitude effects identified seemingly contradictory results, showing both 6 and 12 monthly periodicities in weight. The aims of this paper are twofold: (a) to explore seasonal patterns in a large, Danish Medical Birth Register, and (b) to explore models based on seasonal exposures and a non-linear exposure-risk relationship. Methods Birth weight and birth lengths on over 1.5 million Danish singleton, live births were examined for seasonality. We modelled seasonal patterns based on linear, U- and J-shaped exposure-risk relationships. We then added an extra layer of complexity by modelling weighted population-based exposure patterns. Results The Danish data showed clear seasonal fluctuations for both birth weight and birth length. A bimodal model best fits the data, however the amplitude of the 6 and 12 month peaks changed over time. In the modelling exercises, U- and J-shaped exposure-risk relationships generate time series with both 6 and 12 month periodicities. Changing the weightings of the population exposure risks result in unexpected properties. A J-shaped exposure-risk relationship with a diminishing population exposure over time fitted the observed seasonal pattern in the Danish birth weight data. Conclusion In keeping with many other studies, Danish birth anthropometric data show complex and shifting seasonal patterns. We speculate that annual periodicities with non-linear exposure-risk models may underlie these findings. Understanding the nature of seasonal fluctuations can help generate candidate exposures.

Analyzing real-time video microscopy : the dynamics and geometry of vesicles and tubules in endocytosis

With the advent of live cell imaging microscopy, new types of mathematical analyses and measurements are possible. Many of the real-time movies of cellular processes are visually very compelling, but elementary analysis of changes over time of quantities such as surface area and volume often show that there is more to the data than meets the eye. This unit outlines a geometric modeling methodology and applies it to tubulation of vesicles during endocytosis. Using these principles, it has been possible to build better qualitative and quantitative understandings of the systems observed, as well as to make predictions about quantities such as ligand or solute concentration, vesicle pH, and membrane trafficked. The purpose is to outline a methodology for analyzing real-time movies that has led to a greater appreciation of the changes that are occurring during the time frame of the real-time video microscopy and how additional quantitative measurements allow for further hypotheses to be generated and tested.

A continuous time model for election timing

We consider a continuous time model for election timing in a Majoritarian Parliamentary System where the government maintains a constitutional right to call an early election. Our model is based on the two-party-preferred data that measure the popularity of the government and the opposition over time. We describe the poll process by a Stochastic Differential Equation (SDE) and use a martingale approach to derive a Partial Differential Equation (PDE) for the government’s expected remaining life in office. A comparison is made between a three-year and a four-year maximum term and we also provide the exercise boundary for calling an election. Impacts on changes in parameters in the SDE, the probability of winning the election and maximum terms on the call exercise boundaries are discussed and analysed. An application of our model to the Australian Federal Election for House of Representatives is also given.

Time dependency of molecular rate estimates and systematic overestimation of recent divergence times

Studies of molecular evolutionary rates have yielded a wide range of rate estimates for various genes and taxa. Recent studies based on population-level and pedigree data have produced remarkably high estimates of mutation rate, which strongly contrast with substitution rates inferred in phylogenetic (species-level) studies. Using Bayesian analysis with a relaxed-clock model, we estimated rates for three groups of mitochondrial data: avian protein-coding genes, primate protein-coding genes, and primate d-loop sequences. In all three cases, we found a measurable transition between the high, short-term (<1–2 Myr) mutation rate and the low, long-term substitution rate. The relationship between the age of the calibration and the rate of change can be described by a vertically translated exponential decay curve, which may be used for correcting molecular date estimates. The phylogenetic substitution rates in mitochondria are approximately 0.5% per million years for avian protein-coding sequences and 1.5% per million years for primate protein-coding and d-loop sequences. Further analyses showed that purifying selection offers the most convincing explanation for the observed relationship between the estimated rate and the depth of the calibration. We rule out the possibility that it is a spurious result arising from sequence errors, and find it unlikely that the apparent decline in rates over time is caused by mutational saturation. Using a rate curve estimated from the d-loop data, several dates for last common ancestors were calculated: modern humans and Neandertals (354 ka; 222–705 ka), Neandertals (108 ka; 70–156 ka), and modern humans (76 ka; 47–110 ka). If the rate curve for a particular taxonomic group can be accurately estimated, it can be a useful tool for correcting divergence date estimates by taking the rate decay into account. Our results show that it is invalid to extrapolate molecular rates of change across different evolutionary timescales, which has important consequences for studies of populations, domestication, conservation genetics, and human evolution.

Capping computation time and storage requirements for appearance-based localization with CAT-SLAM

Appearance-based localization is increasingly used for loop closure detection in metric SLAM systems. Since it relies only upon the appearance-based similarity between images from two locations, it can perform loop closure regardless of accumulated metric error. However, the computation time and memory requirements of current appearance-based methods scale linearly not only with the size of the environment but also with the operation time of the platform. These properties impose severe restrictions on longterm autonomy for mobile robots, as loop closure performance will inevitably degrade with increased operation time. We present a set of improvements to the appearance-based SLAM algorithm CAT-SLAM to constrain computation scaling and memory usage with minimal degradation in performance over time. The appearance-based comparison stage is accelerated by exploiting properties of the particle observation update, and nodes in the continuous trajectory map are removed according to minimal information loss criteria. We demonstrate constant time and space loop closure detection in a large urban environment with recall performance exceeding FAB-MAP by a factor of 3 at 100% precision, and investigate the minimum computational and memory requirements for maintaining mapping performance.

Clinical performance of a new silicone hydrogel contact lens over 6 months of extended wear

Purpose: Silicone hydrogel contact lenses (CLs) are becoming increasingly popular for daily wear (DW), extended wear (EW) and continuous wear (CW), due to their higher oxygen transmissibility compared to hydrogel CLs. The aim of this study was to investigate the clinical and subjective performance of asmofilcon A (Menicon Co., Ltd), a new surface treated silicone hydrogel CL, during 6-night EW over 6 months (M). Methods: A prospective, randomised, single-masked, monadic study was conducted. N=60 experienced DW soft CL wearers were randomly assigned to wear either asmofilcon A (test: Dk=129, water content (WC)=40%, Nanogloss surface treatment) or senofilcon A (control: Dk=103, WC=38%, PVP internal wetting agent, Vistakon, Johnson & Johnson Vision Care) CLs bilaterally for 6 M on an EW basis. A PHMB-preserved solution (Menicon Co., Ltd) was dispensed for CL care. Evaluations were conducted at CL delivery and after 1 week (W), 4 W, 3 M and 6 M of EW. At each visit, a range of objective and subjective clinical performance measures were assessed. Results: N=50 subjects (83%) successfully completed the study, with the majority of discontinuations due to loss to follow-up (n=3) or moving away/travel (n=5). N=2 subjects experienced adverse events; n=1 unilateral red eye with asmofilcon A and n=1 asymptomatic infiltrate with senofilcon A. There were no significant differences in high or low contrast distance visual acuity (HCDVA or LCDVA) between asmofilcon A and senofilcon A; however, LCDVA decreased significantly over time with both CL types (p<0.05). The two CL types did not vary significantly with respect to any of the objective and subjective measures assessed (p>0.05); CL fitting characteristics and CL surface measurements were very similar and mean bulbar and limbal redness measures were always less than grade 1.0. Superior palpebral conjunctival injection showed a statistically, but not clinically, significant increase over time with both CL types (p<0.05). Corneal staining did not vary significantly between asmofilcon A and senofilcon A (p>0.05), with low median gradings of less than 0.5 observed for all areas assessed. There were no solution-related staining reactions observed with either CL type. The asmofilcon A and senofilcon A CLs were both rated highly with respect to overall comfort, with medians of 14 or 15 hours of comfortable lens wearing time per day reported at each of the study visits (p>0.05). Conclusions: Over 6 months of EW, the asmofilcon A and senofilcon A CLs performed in a similar manner with respect to visual acuity, ocular health and CL performance measures. Some changes over time were observed with both CL types, including reduced LCDVA and increased superior palpebral injection, which warrant further investigation in longer-term EW studies. Asmofilcon A appeared to be equivalent in performance to senofilcon A.

An invasive grass shows colonization advantages over native grasses under conditions of low resource availability

Increased or fluctuating resources may facilitate opportunities for invasive exotic plants to dominate. This hypothesis does not, however, explain how invasive species succeed in regions characterized by low resource conditions or how these species persist in the lulls between high resource periods. We compare the growth of three co-occurring C4 perennial bunchgrasses under low resource conditions: an exotic grass, Eragrostis curvula (African lovegrass) and two native grasses, Themeda triandra and Eragrostis sororia. We grew each species over 12 weeks under low nutrients and three low water regimes differentiated by timing: continuous, pulsed, and mixed treatments (switched from continuous to pulsed and back to continuous). Over time, we measured germination rates, time to germination (first and second generations), height, root biomass, vegetative biomass, and reproductive biomass. Contrary to our expectations that the pulsed watering regime would favor the invader, water-supply treatments had little significant effect on plant growth. We did find inherent advantages in a suite of early colonization traits that likely favor African lovegrass over the natives including faster germination speed, earlier flowering times, faster growth rates and from 2 weeks onward it was taller. African lovegrass also showed similar growth allocation strategies to the native grasses in terms of biomass levels belowground, but produced more vegetative biomass than kangaroo grass. Overall our results suggest that even under low resource conditions invasive plant species like African lovegrass can grow similarly to native grasses, and for some key colonization traits, like germination rate, perform better than natives.

Prevalence of breast cancer treatment sequelae over 6 years of follow-up

Background: There is a need to better describe and understand the prevalence of breast cancer treatment-related adverse effects amenable to physical therapy and rehabilitative exercise. Prior studies have been limited to single issues and lacked long term follow-up. The Pulling Through Study provides data on prevalence of adverse effects in breast cancer survivors followed over six years. Methods: A population-based sample of Australian women (n=287) diagnosed with invasive, unilateral breast cancer was followed for a median of 6.6 years and prospectively assessed for treatment-related complications at 6, 12, 18 months, and 6 years post-diagnosis. Assessments included post-surgical complications, skin or tissue reaction to radiation therapy, upper-body symptoms, lymphedema, 10% weight gain, fatigue, and upper-quadrant function. The proportion of women with positive indication for each complication and one or more complication was estimated using all available data at each time point. Women were only considered to have a specific complication if they reported the highest two levels of the Likert scale for self-reported issues. Results: At six years post-diagnosis over 60% of women experienced one or more side effects amenable to rehabilitative intervention. The proportion of women experiencing 3 or more side effects decreased throughout follow-up, while the proportion experiencing no side effects remained stable around 40% from 12 months to six years. Weight gain was the only complication to increase in prevalence over time. Conclusion: These data support the development of a multi-disciplinary prospective surveillance approach for the purposes of managing and treating adverse effects in breast cancer survivors.

Traffic queue estimation for metered motorway on-ramps through use of loop detector time occupancies

The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is a vital input for dynamic queue management on metered on-ramps. Accurate and reliable queue information enables the management of on-ramp queue in an adaptive manner to the actual traffic queue size and thus minimises the adverse impacts of queue flush while increasing the benefit of ramp metering. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.

A Kalman filter based queue estimation algorithm using time occupancies for motorway on-ramps

The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is the most vital input for a dynamic queue management that can treat long queues on metered on-ramps more sophistically. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in the congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.