Parameterizing Unconditional Skewness in Models for Financial Time Series

In this paper we consider the third-moment structure of a class of time series models. It is often argued that the marginal distribution of financial time series such as returns is skewed. Therefore it is of importance to know what properties a model should possess if it is to accommodate unconditional skewness. We consider modeling the unconditional mean and variance using models that respond nonlinearly or asymmetrically to shocks. We investigate the implications of these models on the third-moment structure of the marginal distribution as well as conditions under which the unconditional distribution exhibits skewness and nonzero third-order autocovariance structure. In this respect, an asymmetric or nonlinear specification of the conditional mean is found to be of greater importance than the properties of the conditional variance. Several examples are discussed and, whenever possible, explicit analytical expressions provided for all third-order moments and cross-moments. Finally, we introduce a new tool, the shock impact curve, for investigating the impact of shocks on the conditional mean squared error of return series.

Modelling the impact of traffic incidents on travel time reliability

Traffic incidents are recognised as one of the key sources of non-recurrent congestion that often leads to reduction in travel time reliability (TTR), a key metric of roadway performance. A method is proposed here to quantify the impacts of traffic incidents on TTR on freeways. The method uses historical data to establish recurrent speed profiles and identifies non-recurrent congestion based on their negative impacts on speeds. The locations and times of incidents are used to identify incidents among non-recurrent congestion events. Buffer time is employed to measure TTR. Extra buffer time is defined as the extra delay caused by traffic incidents. This reliability measure indicates how much extra travel time is required by travellers to arrive at their destination on time with 95% certainty in the case of an incident, over and above the travel time that would have been required under recurrent conditions. An extra buffer time index (EBTI) is defined as the ratio of extra buffer time to recurrent travel time, with zero being the best case (no delay). A Tobit model is used to identify and quantify factors that affect EBTI using a selected freeway segment in the Southeast Queensland, Australia network. Both fixed and random parameter Tobit specifications are tested. The estimation results reveal that models with random parameters offer a superior statistical fit for all types of incidents, suggesting the presence of unobserved heterogeneity across segments. What factors influence EBTI depends on the type of incident. In addition, changes in TTR as a result of traffic incidents are related to the characteristics of the incidents (multiple vehicles involved, incident duration, major incidents, etc.) and traffic characteristics.

A novel approach to 6-DOF adaptive trajectory tracking control of an AUV in the presence of parameter uncertainties

In this paper, the trajectory tracking control of an autonomous underwater vehicle (AUVs) in six-degrees-of-freedom (6-DOFs) is addressed. It is assumed that the system parameters are unknown and the vehicle is underactuated. An adaptive controller is proposed, based on Lyapunov׳s direct method and the back-stepping technique, which interestingly guarantees robustness against parameter uncertainties. The desired trajectory can be any sufficiently smooth bounded curve parameterized by time even if consist of straight line. In contrast with the majority of research in this field, the likelihood of actuators׳ saturation is considered and another adaptive controller is designed to overcome this problem, in which control signals are bounded using saturation functions. The nonlinear adaptive control scheme yields asymptotic convergence of the vehicle to the reference trajectory, in the presence of parametric uncertainties. The stability of the presented control laws is proved in the sense of Lyapunov theory and Barbalat׳s lemma. Efficiency of presented controller using saturation functions is verified through comparing numerical simulations of both controllers.

Effects of increasing neuromuscular electrical stimulation current intensity on cortical sensorimotor network activation: A time domain fNIRS study

Neuroimaging studies have shown neuromuscular electrical stimulation (NMES)-evoked movements activate regions of the cortical sensorimotor network, including the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), and secondary somatosensory area (S2), as well as regions of the prefrontal cortex (PFC) known to be involved in pain processing. The aim of this study, on nine healthy subjects, was to compare the cortical network activation profile and pain ratings during NMES of the right forearm wrist extensor muscles at increasing current intensities up to and slightly over the individual maximal tolerated intensity (MTI), and with reference to voluntary (VOL) wrist extension movements. By exploiting the capability of the multi-channel time domain functional near-infrared spectroscopy technique to relate depth information to the photon time-of-flight, the cortical and superficial oxygenated (O₂Hb) and deoxygenated (HHb) hemoglobin concentrations were estimated. The O₂Hb and HHb maps obtained using the General Linear Model (NIRS-SPM) analysis method, showed that the VOL and NMES-evoked movements significantly increased activation (i.e., increase in O₂Hb and corresponding decrease in HHb) in the cortical layer of the contralateral sensorimotor network (SMC, PMC/SMA, and S2). However, the level and area of contralateral sensorimotor network (including PFC) activation was significantly greater for NMES than VOL. Furthermore, there was greater bilateral sensorimotor network activation with the high NMES current intensities which corresponded with increased pain ratings. In conclusion, our findings suggest that greater bilateral sensorimotor network activation profile with high NMES current intensities could be in part attributable to increased attentional/pain processing and to increased bilateral sensorimotor integration in these cortical regions.

Anticipating Chinese Tourists Arrivals in Australia: A Time Series Analysis

Given the growing importance of the Chinese tourist market to Australia, an understanding of Chinese tourists' arrival patterns is essential to accurate forecasting of future arrivals. Drawing on 25 years of records (1991-2015), this study developed a time-series model of monthly arrivals of Chinese tourists in Australia. The model reflects the exponentially increasing trend and strong seasonality of arrivals. Excellent results from validation of the model's forecasts endorsed this time-series model's potential in the policy prescription and management practice of Australian tourism industries.

Overcoming the challenges of building heritage projects: Improvements to time, scope and cost performance

This research was undertaken to encompass and identify challenges and impact factors that affect the successful outcomes of heritage building projects, especially those related to finding major causes of delays and cost overruns across projects in all Australian states. This project determined and analysed the causes of such delays and programme issues emanating from the planning and execution phases, whilst also analysing the requirements for management of multiple stakeholder relationships and the influence of unforeseen technical factors. The research proposes "call for action" guidance and was validated by experienced experts in heritage building projects in Australia. The proposed guidance is designed to ensure that realistic cost targets and delivery timeframes are set in future heritage projects, and necessary interventions made at appropriate project stages to ensure decisions are made that will help to prevent overtime and cost overuns.

Real-time wide-area loading margin sensitivity (WALMS) in power systems

Loading margin sensitivity (LMS) has been widely used in applications in the realm of voltage stability assessment and control. Typically, LMS is derived based on system equilibrium equations near bifurcation and therefore requires full detailed system model and significant computation effort. Availability of phasor measurement units (PMUs) due to the recent development of wide-area monitoring system (WAMS) provides an alternative computation-friendly approach for calculating LMS. With such motivation, this work proposes measurement-based wide-area loading margin sensitivity (WALMS) in bulk power systems. The proposed sensitivity, with its simplicity, has great potential to be embedded in real-time applications. Moreover, the calculation of the WALMS is not limited to low voltage near bifurcation point. A case study on IEEE 39-bus system verifies the proposed sensitivity. Finally, a voltage control scenario demonstrates the potential application of the WALMS.

Art changing the world: one person at a time

Dr Michael Whelan from Autism Queensland talks about a mentoring program supporting young people to develop creative industries skills… Following the extreme social stresses of high school, a lot of young people on the autism spectrum retreat to their bedrooms and computers to hibernate for extended periods of time. Online gaming communities and digital media hubs often provide a more accessible forum for young adults on the autism spectrum to establish and maintain social connections. A recent study suggests that school leavers on the autism spectrum in Queensland spend an average of 9.5 hours per day (68 hours per week) engaged in solitary technology-based activities. While this astonishing figure has its foundations in the sobering fact that most of these young people have limited social networks and experience significant anxiety and depression, it also serves to illustrate the extraordinary skill sets that these extended hours of technological engagement can facilitate.

Real-time locating systems applications in construction

Real-time locating systems (RTLSs) are considered an effective way to identify and track the location of an object in both indoor and outdoor environments. Various RTLSs have been developed and made commercially available in recent years. Research into RTLSs in the construction sector is ubiquitous and results have been published in many construction-related academic journals over the past decade. A succinct and systematic review of current applications would help academics, researchers and industry practitioners in identifying existing research deficiencies and therefore future research directions. However, such a review is lacking to date. This paper provides a framework for understanding RTLS research and development in the construction literature over the last decade. The research opportunities and directions of construction RTLS are highlighted. Background information relating to construction RTLS trends, accuracy, deployment, cost, purposes, advantages and limitations is provided. Four major research gaps are identified and research opportunities and directions are highlighted.

Time evolution of graphene growth on SiC as a function of annealing temperature

We followed by X-ray Photoelectron Spectroscopy (XPS) the time evolution of graphene layers obtained by annealing 3C SiC(111)/Si(111) crystals at different temperatures. The intensity of the carbon signal provides a quantification of the graphene thickness as a function of the annealing time, which follows a power law with exponent 0.5. We show that a kinetic model, based on a bottom-up growth mechanism, provides a full explanation to the evolution of the graphene thickness as a function of time, allowing to calculate the effective activation energy of the process and the energy barriers, in excellent agreement with previous theoretical results. Our study provides a complete and exhaustive picture of Si diffusion into the SiC matrix, establishing the conditions for a perfect control of the graphene growth by Si sublimation.

The impact of a streamlined funding application process on application time: Two cross-sectional surveys of Australian researchers

Objective: To examine if streamlining a medical research funding application process saved time for applicants. Design: Cross-sectional surveys before and after the streamlining. Setting: The National Health and Medical Research Council (NHMRC) of Australia. Participants: Researchers who submitted one or more NHMRC Project Grant applications in 2012 or 2014. Main outcome measures: Average researcher time spent preparing an application and the total time for all applications in working days. Results: The average time per application increased from 34 working days before streamlining (95% CI 33 to 35) to 38 working days after streamlining (95% CI 37 to 39; mean difference 4 days, bootstrap p value <0.001). The estimated total time spent by all researchers on applications after streamlining was 614 working years, a 67-year increase from before streamlining. Conclusions: Streamlined applications were shorter but took longer to prepare on average. Researchers may be allocating a fixed amount of time to preparing funding applications based on their expected return, or may be increasing their time in response to increased competition. Many potentially productive years of researcher time are still being lost to preparing failed applications.

Individual difference predictors of change in career adaptability over time

Career adaptability is a psychosocial construct that reflects individuals' resources for managing career tasks and challenges. This study investigated the effects of demographic characteristics and three sets of individual difference variables (Big Five personality traits, core self-evaluations, and temporal focus) on changes over time in career adaptability and its dimensions (concern, control, curiosity, and confidence). Data came from 659 full-time employees in Australia who participated in two measurement waves six months apart. Results showed that age and future temporal focus predicted change in overall career adaptability. In addition, age, education, extraversion, neuroticism, openness to experience, core self-evaluations, and future temporal focus differentially predicted change over time in one or more of the four career adaptability dimensions. While the lagged effects found in this study were generally small, the findings suggest that certain individual difference characteristics predispose employees to experience change in career adaptability over time.

Older job seekers' job search intensity: The interplay of proactive personality, age and occupational future time perspective

Long-term unemployment of older people can have severe consequences for individuals, communities and ultimately economies, and is therefore a serious concern in countries with an ageing population. However, the interplay of chronological age and other individual difference characteristics in predicting older job seekers' job search is so far not well understood. This study investigated relationships among age, proactive personality, occupational future time perspective (FTP) and job search intensity of 182 job seekers between 43 and 77 years in Australia. Results were mostly consistent with expectations based on a combination of socio-emotional selectivity theory and the notion of compensatory psychological resources. Proactive personality was positively related to job search intensity and age was negatively related to job search intensity. Age moderated the relationship between proactive personality and job search intensity, such that the relationship was stronger at higher compared to lower ages. One dimension of occupational FTP (perceived remaining time left in the occupational context) mediated this moderating effect, but not the overall relationship between age and job search intensity. Implications for future research, including the interplay of occupational FTP and proactive personality, and some tentative practical implications are discussed.

Stepping into my shoes: Generativity as a mediator of the relationship between business owners' age and family succession

The authors investigated generativity – the concern in establishing and guiding the next generation – as a mediator of the relationship between family business owners' age and succession in family businesses. Data came from 155 family business owners in Germany from different industries between the ages of 26 and 83 years. Results showed that age was positively related to generativity, and that generativity, in turn, positively influenced an objective measure of family succession. Generativity fully mediated the positive relationship between age and family succession. The findings suggest that generativity is an important psycho-social construct for understanding ageing, careers and succession in family business settings.