106 resultados para volatility spillover
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This article details the second, successful pilot of the Promoting Adult Resilience (PAR) program in the human-services departments of a local government organization. The PAR program is a strengths-based resilience building program that integrates Interpersonal and CBT perspectives and this pilot use a shorter, 7-week version of the program. Pre, post and follow-up measures on PAR participants from a resource-sector company were compared with a non-intervention matched comparison group. Post-test, PAR participants reported greater self-efficacy, more family satisfaction, greater f\work-life fit and balance and less negative family to work spillover than the comparison group. At the 6-month follow-up, these gains were maintained to a lesser degree, although work-life balance was strengthened, and negative spillover in both directions reduced. Participants also reported greater optimism for the future, greater work satisfaction and promisingly for human service workers, exhaustion was reduced and more vigour, important for human services as burnout, exhaustion is part of this is a serious work hazard
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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.
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In this paper, we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new double smooth transition conditional correlation (DSTCC) GARCH model extends the smooth transition conditional correlation (STCC) GARCH model of Silvennoinen and Teräsvirta (2005) by including another variable according to which the correlations change smoothly between states of constant correlations. A Lagrange multiplier test is derived to test the constancy of correlations against the DSTCC-GARCH model, and another one to test for another transition in the STCC-GARCH framework. In addition, other specification tests, with the aim of aiding the model building procedure, are considered. Analytical expressions for the test statistics and the required derivatives are provided. Applying the model to the stock and bond futures data, we discover that the correlation pattern between them has dramatically changed around the turn of the century. The model is also applied to a selection of world stock indices, and we find evidence for an increasing degree of integration in the capital markets.
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This study employs a pairs trading investment strategy on daily commodity futures returns. The study reveals that pairs trading in similarly related commodity futures earns statistically significant excess returns with commensurate volatility. The excess returns from pairs trading in commodity futures are unrelated to conventional market risk factors and they are not associated with classic contrarian investing. The evidence of pairs trading reflect compensation to arbitrageurs for enforcing the law of one price in similarly related market efficiency.
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The annual income return for rural property is based on two major factors being commodity prices and production yields. Commodity prices paid to rural producers can vary depending on the agricultural policies of their respective countries. Free trade countries, such as Australia and New Zealand are subject to the volatility of the world commodity markets to a greater extent than those farmers in protected or subsidised markets. In countries where rural production is protected or subsidised the annual income received by rural producers has been relatively stable. However, the high cost of agricultural protection is now being questioned, particularly in relation to the increasing economic costs of government services such as health, education and housing. When combined with the agricultural production limitations of climate, topography, chemical residues and disease issues, the impact of commodity prices on rural property income is crucial in the ability of rural producers to enter into or expand their holdings in agricultural land. These problems are then reflected in the volatility of the rural land capital returns and the investment performance of this property class. This paper will address the total and capital return performance of a major agricultural area and compare these returns on the basis of both location of land and land use. The comparison will be used to determine if location or actual land use has a greater influence on rural property capital returns. This performance analysis is based on over 35,000 rural sales transactions. These transactions cover all market based rural property transactions in New South Wales, Australia for the period January 1990 to December 2008. Correlation analysis and investment performance analysis has also been carried out to determine the possible relationships between location and land use and subsequent changes in rural land capital values.
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In the Superannuation/Pension industry ordinary investors entrust their retirement savings to the trustees of the superannuation plan. Investors rely on the trustees to ensure ethical business and risk management practices are implemented to protect their retirement savings. Governance practices ensure the monitoring of ethical risk management (Drennan, 2004). The Australian superannuation industry presents a unique scenario. Legislation requires employers to contribute a minimum of 9% of the employees wage to retirement savings. However, there are no legislated governance standards, although there are standards of recommended governance practices. In this paper, we examine the level of voluntary adoption of governance practices by the trustees of Australian public sector and industry superannuation funds. We also assess whether superannuation governance practices are associated with performance and volatility/riskiness of returns. Survey results show that the majority of superannuation plans adopt recommended governance practices supporting the concept of ethical management of the member’s retirement savings. The examination of governance principles that impact returns and risk show that board size and regular review of conflicts are positively associated with return. Superannuation plans with higher volatility in returns meet more frequently.
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Red light cameras (RLCs) have been used in a number of US cities to yield a demonstrable reduction in red light violations; however, evaluating their impact on safety (crashes) has been relatively more difficult. Accurately estimating the safety impacts of RLCs is challenging for several reasons. First, many safety related factors are uncontrolled and/or confounded during the periods of observation. Second, “spillover” effects caused by drivers reacting to non-RLC equipped intersections and approaches can make the selection of comparison sites difficult. Third, sites selected for RLC installation may not be selected randomly, and as a result may suffer from the regression to the mean bias. Finally, crash severity and resulting costs need to be considered in order to fully understand the safety impacts of RLCs. Recognizing these challenges, a study was conducted to estimate the safety impacts of RLCs on traffic crashes at signalized intersections in the cities of Phoenix and Scottsdale, Arizona. Twenty-four RLC equipped intersections in both cities are examined in detail and conclusions are drawn. Four different evaluation methodologies were employed to cope with the technical challenges described in this paper and to assess the sensitivity of results based on analytical assumptions. The evaluation results indicated that both Phoenix and Scottsdale are operating cost-effective installations of RLCs: however, the variability in RLC effectiveness within jurisdictions is larger in Phoenix. Consistent with findings in other regions, angle and left-turn crashes are reduced in general, while rear-end crashes tend to increase as a result of RLCs.
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It is increasingly understood that learning and thus innovation often occurs via highly interactive, iterative, network-based processes. Simultaneously, economic development policy is increasingly focused on small and medium-sized enterprises (SMEs) as a means of generating growth, creating a clear research issue in terms of the roles and interactions of government policy, universities, and other sources of knowledge, SMEs, and the creation and dissemination of innovation. This paper analyses the contribution of a range of actors in an SME innovation creation and dissemination framework, reviewing the role of various institutions therein, exploring the contribution of cross-locality networks, and identifying the mechanisms required to operationalise such a framework. Bivariate and multivariate (regression) techniques are employed to investigate both innovation and growth outcomes in relation to these structures; data are derived from the survey responses of over 450 SMEs in the UK. Results are complex and dependent upon the nature of institutions involved, the type of knowledge sought, and the spatial level of the linkages in place but overall highlight the value of cross-locality networks, network governance structures, and certain spillover effects from universities. In general, we find less support for the factors predicting SME growth outcomes than is the case for innovation. Finally, we outline an agenda for further research in the area.
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The influence of biogenic particle formation on climate is a well recognised phenomenon. To understand the mechanisms underlying the biogenic particle formation, determining the chemical composition of the new particles and therefore the species that drive the particle production is of utmost importance. Due to the very small amount of mass involved, indirect approaches are frequently used to infer the composition. We present here the results of such an indirect approach by simultaneously measuring volatile and hygroscopic properties of newly formed particles in a forest environment. It is shown that the particles are composed of both sulphates and organics, with the amount of sulphate component strongly depending on the available gas-phase sulphuric acid, and the organic components having the same volatility and hygroscopicity as photooxidation products of a monoterpene such as α-pinene. Our findings agree with a two-step process through nucleation and cluster formation followed by simultaneous growth by condensation of sulphates and organics that take the particles to climatically relevant sizes.
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Recent studies have detected a dominant accumulation mode (~100 nm) in the Sea Spray Aerosol (SSA) number distribution. There is evidence to suggest that particles in this mode are composed primarily of organics. To investigate this hypothesis we conducted experiments on NaCl, artificial SSA and natural SSA particles with a Volatility-Hygroscopicity-Tandem-Differential-Mobility-Analyser (VH-TDMA). NaCl particles were atomiser generated and a bubble generator was constructed to produce artificial and natural SSA particles. Natural seawater samples for use in the bubble generator were collected from biologically active, terrestrially-affected coastal water in Moreton Bay, Australia. Differences in the VH-TDMA-measured volatility curves of artificial and natural SSA particles were used to investigate and quantify the organic fraction of natural SSA particles. Hygroscopic Growth Factor (HGF) data, also obtained by the VH-TDMA, were used to confirm the conclusions drawn from the volatility data. Both datasets indicated that the organic fraction of our natural SSA particles evaporated in the VH-TDMA over the temperature range 170–200°C. The organic volume fraction for 71–77 nm natural SSA particles was 8±6%. Organic volume fraction did not vary significantly with varying water residence time (40 secs to 24 hrs) in the bubble generator or SSA particle diameter in the range 38–173 nm. At room temperature we measured shape- and Kelvin-corrected HGF at 90% RH of 2.46±0.02 for NaCl, 2.35±0.02 for artifical SSA and 2.26±0.02 for natural SSA particles. Overall, these results suggest that the natural accumulation mode SSA particles produced in these experiments contained only a minor organic fraction, which had little effect on hygroscopic growth. Our measurement of 8±6% is an order of magnitude below two previous measurements of the organic fraction in SSA particles of comparable sizes. We stress that our results were obtained using coastal seawater and they can’t necessarily be applied on a regional or global ocean scale. Nevertheless, considering the order of magnitude discrepancy between this and previous studies, further research with independent measurement techniques and a variety of different seawaters is required to better quantify how much organic material is present in accumulation mode SSA.
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A 4 week intensive measurement campaign was conducted in March–April 2007 at Agnes Water, a remote coastal site on the east coast of Australia. A Volatility-Hygroscopicity-Tandem Differential Mobility Analyser (VH-TDMA) was used to investigate changes in the hygroscopic properties of ambient particles as volatile components were progressively evaporated. Nine out of 18 VH-TDMA volatility scans detected internally mixed multi-component particles in the nucleation and Aitken modes in clean marine air. Evaporation of a volatile, organic-like component in the VH-TDMA caused significant increases in particle hygroscopicity. In 3 scans the increase in hygroscopicity was so large it was explained by an increase in the absolute volume of water uptake by the particle residuals, and not merely an increase in their relative hygroscopicity. This indicates the presence of organic components that were suppressing the hygroscopic growth of mixed particles on the timescale of humidification in the VH-TDMA (6.5 secs). This observation was supported by ZSR calculations for one scan, which showed that the measured growth factors of mixed particles were up to 18% below those predicted assuming independent water uptake of the individual particle components. The observed suppression of water uptake could be due to a reduced rate of hygroscopic growth caused by the presence of organic films or organic-inorganic interactions in solution droplets that had a negative effect on hygroscopicity.
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Short-term traffic flow data is characterized by rapid and dramatic fluctuations. It reflects the nature of the frequent congestion in the lane, which shows a strong nonlinear feature. Traffic state estimation based on the data gained by electronic sensors is critical for much intelligent traffic management and the traffic control. In this paper, a solution to freeway traffic estimation in Beijing is proposed using a particle filter, based on macroscopic traffic flow model, which estimates both traffic density and speed.Particle filter is a nonlinear prediction method, which has obvious advantages for traffic flows prediction. However, with the increase of sampling period, the volatility of the traffic state curve will be much dramatic. Therefore, the prediction accuracy will be affected and difficulty of forecasting is raised. In this paper, particle filter model is applied to estimate the short-term traffic flow. Numerical study is conducted based on the Beijing freeway data with the sampling period of 2 min. The relatively high accuracy of the results indicates the superiority of the proposed model.
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Globally, teaching has become more complex and more challenging over recent years, with new and increased demands being placed on teachers by students, their families, governments and wider society. Teachers work with more diverse communities in times characterised by volatility, uncertainty and moral ambiguity. Societal, political, economic and cultural shifts have transformed the contexts in which teachers work and have redefined the ways in which teachers interact with students. This qualitative study uses phenomenographic methods to explore the nature of pedagogic teacherstudent interactions. The data analysis reveals five qualitatively different ways in which teachers experience pedagogic engagements with students. The resultant categories of description ranged from information providing, with teachers viewed as transmitters of a body of knowledge through to mentoring in which teachers were perceived as significant others in the lives of students with their influence extending beyond the walls of the classroom and beyond the years of schooling. The paper concludes by arguing that if teachers are to prepare students for the challenges and opportunities in changing times, teacher education programs need to consider ways to facilitate the development of mentoring capacities in new teachers.