Estimating and forecasting generalized fractional Long memory stochastic volatility models

In recent years fractionally differenced processes have received a great deal of attention due to its flexibility in financial applications with long memory. This paper considers a class of models generated by Gegenbauer polynomials, incorporating the long memory in stochastic volatility (SV) components in order to develop the General Long Memory SV (GLMSV) model. We examine the statistical properties of the new model, suggest using the spectral likelihood estimation for long memory processes, and investigate the finite sample properties via Monte Carlo experiments. We apply the model to three exchange rate return series. Overall, the results of the out-of-sample forecasts show the adequacy of the new GLMSV model.

Volatility spillovers in EMU sovereign bond markets

We analyse volatility spillovers in EMU sovereign bond markets. First, we examine the unconditional patterns during the full sample (April 1999-January 2014) using a measure recently proposed by Diebold and Yılmaz (2012). Second, we make use of a dynamic analysis to evaluate net directional volatility spillovers for each of the eleven countries under study, and to determine whether core and peripheral markets present differences. Finally, we apply a panel analysis to empirically investigate the determinants of net directional spillovers of this kind.

Real exchange rate volatility, financial crises and nominal exchange regimes

This paper examines the sources of real exchange rate (RER) volatility in eighty countries around the world, during the period 1970 to 2011. Our main goal is to explore the role of nominal exchange rate regimes and financial crises in explaining the RER volatility. To that end, we employ two complementary procedures that consist in detecting structural breaks in the RER series and decomposing volatility into its permanent and transitory components. The results confirm that exchange rate volatility does increase with the global financial crises and detect the existence of an inverse relationship between the degree of flexibility in the exchange rate regime and RER volatility using a de facto exchange rate classification.

Modelling and testing volatility spillovers in oil and financial markets for USA, UK and China

The primary purpose of the paper is to analyze the conditional correlations, conditional covariances, and co-volatility spillovers between international crude oil and associated financial markets. The paper investigates co-volatility spillovers (namely, the delayed effect of a returns shock in one physical or financial asset on the subsequent volatility or co-volatility in another physical or financial asset) between the oil and financial markets. The oil industry has four major regions, namely North Sea, USA, Middle East, and South-East Asia. Associated with these regions are two major financial centers, namely UK and USA. For these reasons, the data to be used are the returns on alternative crude oil markets, returns on crude oil derivatives, specifically futures, and stock index returns in UK and USA. The paper will also analyze the Chinese financial markets, where the data are more recent. The empirical analysis will be based on the diagonal BEKK model, from which the conditional covariances will be used for testing co-volatility spillovers, and policy recommendations. Based on these results, dynamic hedging strategies will be suggested to analyze market fluctuations in crude oil prices and associated financial markets.

Testing co-volatility spillovers for natural gas spot, futures and ETF spot using dynamic conditional covariances

There is substantial empirical evidence that energy and financial markets are closely connected. As one of the most widely-used energy resources worldwide, natural gas has a large daily trading volume. In order to hedge the risk of natural gas spot markets, a large number of hedging strategies can be used, especially with the rapid development of natural gas derivatives markets. These hedging instruments include natural gas futures and options, as well as Exchange Traded Fund (ETF) prices that are related to natural gas stock prices. The volatility spillover effect is the delayed effect of a returns shock in one physical, biological or financial asset on the subsequent volatility or co-volatility of another physical, biological or financial asset. Investigating volatility spillovers within and across energy and financial markets is a crucial aspect of constructing optimal dynamic hedging strategies. The paper tests and calculates spillover effects among natural gas spot, futures and ETF markets using the multivariate conditional volatility diagonal BEKK model. The data used include natural gas spot and futures returns data from two major international natural gas derivatives markets, namely NYMEX (USA) and ICE (UK), as well as ETF data of natural gas companies from the stock markets in the USA and UK. The empirical results show that there are significant spillover effects in natural gas spot, futures and ETF markets for both USA and UK. Such a result suggests that both natural gas futures and ETF products within and beyond the country might be considered when constructing optimal dynamic hedging strategies for natural gas spot prices.

Volatility spillovers for spot, futures, and ETF prices in energy and agriculture

The agricultural and energy industries are closely related, both biologically and financially. The paper discusses the relationship and the interactions on price and volatility, with special focus on the covolatility spillover effects for these two industries. The interaction and covolatility spillovers or the delayed effect of a returns shock in one asset on the subsequent volatility or covolatility in another asset, between the energy and agricultural industries is the primary emphasis of the paper. Although there has already been significant research on biofuel and biofuel-related crops, much of the previous research has sought to find a relationship among commodity prices. Only a few published papers have been concerned with volatility spillovers. However, it must be emphasized that there have been numerous technical errors in the theoretical and empirical research, which needs to be corrected. The paper not only considers futures prices as a widely-used hedging instrument, but also takes an interesting new hedging instrument, ETF, into account. ETF is regarded as index futures when investors manage their portfolios, so it is possible to calculate an optimal dynamic hedging ratio. This is a very useful and interesting application for the estimation and testing of volatility spillovers. In the empirical analysis, multivariate conditional volatility diagonal BEKK models are estimated for comparing patterns of covolatility spillovers. The paper provides a new way of analyzing and describing the patterns of covolatility spillovers, which should be useful for the future empirical analysis of estimating and testing covolatility spillover effects.

Simultaneous implementation of the Bachelor, Masters and PhD degrees in nursing in the Universidad Jaume I. Castellón de la Plana, Spain

We present an experience in Nursing Education, accredited and implemented under the Spanish University System Reform in a Public University (Jaume I, Castellón) which had no previous nursing studies. The academics offered included all three educational levels (Bachelor, Master's and Doctorate), with an integrated theoretical-practical-clinical teaching methodology for the Bachelor Degree, competence acquisition in research in the Master's degree, and a doctorate formed by lines of research in the field of Nursing. Studies are accredited by the National Agency for Quality Assessment, which were authorized by the Spanish Ministry of Education and implanted between 2009 and 2011.

Simultaneous synthesis of heat exchanger networks with pressure recovery: optimal integration between heat and work

The optimal integration between heat and work may significantly reduce the energy demand and consequently the process cost. This paper introduces a new mathematical model for the simultaneous synthesis of heat exchanger networks (HENs) in which the pressure levels of the process streams can be adjusted to enhance the heat integration. A superstructure is proposed for the HEN design with pressure recovery, developed via generalized disjunctive programming (GDP) and mixed-integer nonlinear programming (MINLP) formulation. The process conditions (stream temperature and pressure) must be optimized. Furthermore, the approach allows for coupling of the turbines and compressors and selection of the turbines and valves to minimize the total annualized cost, which consists of the operational and capital expenses. The model is tested for its applicability in three case studies, including a cryogenic application. The results indicate that the energy integration reduces the quantity of utilities required, thus decreasing the overall cost.

Impact of simultaneous pancreas-kidney transplantation: patients' perspectives

Background: Few qualitative studies of simultaneous pancreas-kidney transplantation (SPK Tx) have been published. The aims of this study were to explore from the perspective of patients, the experience of living with diabetes mellitus type 1 (T1DM), suffering from complications, and undergoing SPK Tx with good outcome; and to determine the impact of SPK Tx on patients and their social and cultural environment. Methods: We performed a focused ethnographic study. Twenty patients were interviewed. Data were analyzed using content analysis and constant comparison following the method proposed by Miles and Huberman. Results: A functioning SPK Tx allowed renal replacement therapy and insulin to be discontinued. To describe their new situation, patients used words and phrases such as "miracle", "being reborn" or "coming back to life". Although the complications of T1DM, its surgery and treatment, and associated psychological problems did not disappear after SPK Tx, these were minimized when compared with the pretransplantation situation. Conclusion: For patients, SPK Tx represents a recovery of their health and autonomy despite remaining problems associated with the complications of T1DM and SPK Tx. The understanding of patients' existential framework and their experience of disease are key factors for planning new intervention and improvement strategies.

Simultaneous synthesis of work exchange networks with heat integration

The optimal integration of work and its interaction with heat can represent large energy savings in industrial plants. This paper introduces a new optimization model for the simultaneous synthesis of work exchange networks (WENs), with heat integration for the optimal pressure recovery of process gaseous streams. The proposed approach for the WEN synthesis is analogous to the well-known problem of synthesis of heat exchanger networks (HENs). Thus, there is work exchange between high-pressure (HP) and low-pressure (LP) streams, achieved by pressure manipulation equipment running on common axes. The model allows the use of several units of single-shaft-turbine-compressor (SSTC), as well as stand-alone compressors, turbines and valves. Helper motors and generators are used to respond to any demand and excess of energy. Moreover, between the WEN stages the streams are sent to the HEN to promote thermal recovery, aiming to enhance the work integration. A multi-stage superstructure is proposed to represent the process. The WEN superstructure is optimized in a mixed-integer nonlinear programming (MINLP) formulation and solved with the GAMS software, with the goal of minimizing the total annualized cost. Three examples are conducted to verify the accuracy of the proposed method. In all case studies, the heat integration between WEN stages is essential to improve the pressure recovery, and to reduce the total costs involved in the process.

Simultaneous environmental and economic process synthesis of Isobutane Alkylation

This multidisciplinary study concerns the optimal design of processes with a view to both maximizing profit and minimizing environmental impacts. This can be achieved by a combination of traditional chemical process design methods, measurements of environmental impacts and advanced mathematical optimization techniques. More to the point, this paper presents a hybrid simulation-multiobjective optimization approach that at once optimizes the production cost and minimizes the associated environmental impacts of isobutane alkylation. This approach has also made it possible to obtain the flowsheet configurations and process variables that are needed to manufacture isooctane in a way that satisfies the above-stated double aim. The problem is formulated as a Generalized Disjunctive Programming problem and solved using state-of-the-art logic-based algorithms. It is shown, starting from existing alternatives for the process, that it is possible to systematically generate a superstructure that includes alternatives not previously considered. The optimal solution, in the form a Pareto curve, includes different structural alternatives from which the most suitable design can be selected. To evaluate the environmental impact, Life Cycle Assessment based on two different indicators is employed: Ecoindicator 99 and Global Warming Potential.

Forecasting Elections with High Volatility

This article uses data from the social survey Allbus 1998 to introduce a method of forecasting elections in a context of electoral volatility. The approach models the processes of change in electoral behaviour, exploring patterns in order to model the volatility expressed by voters. The forecast is based on the matrix of transition probabilities, following the logic of Markov chains. The power of the matrix, and the use of the mover-stayer model, is debated for alternative forecasts. As an example of high volatility, the model uses data from the German general election of 1998. The unification of two German states in 1990 caused the incorporation of around 15 million new voters from East Germany who had limited familiarity and no direct experience of the political culture in West Germany. Under these circumstances, voters were expected to show high volatility.

The Goodness of Simultaneous Fits in ISIS

In a previous work, we introduced a tool for analyzing multiple datasets simultaneously, which has been implemented into ISIS. This tool was used to fit many spectra of X-ray binaries. However, the large number of degrees of freedom and individual datasets raise an issue about a good measure for a simultaneous fit quality. We present three ways to check the goodness of these fits: we investigate the goodness of each fit in all datasets, we define a combined goodness exploiting the logical structure of a simultaneous fit, and we stack the fit residuals of all datasets to detect weak features. These tools are applied to all RXTE-spectra from GRO 1008−57, revealing calibration features that are not detected significantly in any single spectrum. Stacking the residuals from the best-fit model for the Vela X-1 and XTE J1859+083 data evidences fluorescent emission lines that would have gone undetected otherwise.

Predictors and Consequences of Simultaneous Alcohol and Cannabis Use in Adolescents

Background/Aims: The simultaneous use of alcohol and cannabis is common among adolescents, but has been little studied. In this study, we examine predictors and consequences of this behavior in a population-based sample of high school students. Method: Self-reports were obtained from students in Quebec (Canada) followed throughout high school (N=6589). Logistic regressions were used to test the association between individual, family, and peerrelated predictors in grades 7–8 and simultaneous alcohol and cannabis use in grade 10, as well as between simultaneous alcohol and cannabis use in grade 10 and experiencing 3 or more substance-related problems of various types (legal, physical, etc.) in grade 11. Results: Most predictors in grades 7–8 were associated with simultaneous alcohol and cannabis use in grade 10. Only variables reflecting early-onset substance use involvement — alcohol intoxication, cannabis use, and drug use by close friend(s) — remained predictive in a multivariate model. Simultaneous alcohol and cannabis use was associated with increased substance-related problems in grade 11, above and beyond baseline problems and the concurrent use of the two substances in separate episodes in grade 10. Conclusions: Simultaneous alcohol and cannabis use 1) is anticipated by multiple psychosocial risk factors which come together with individual and peer substance use in early high school and 2) is independently predictive of subsequent substance-related problems. Providing adolescents with adequate information regarding the potential harm of simultaneous use may be a useful prevention strategy.

Predictors and Consequences of Simultaneous Alcohol and Cannabis Use in Adolescents

Background/Aims: The simultaneous use of alcohol and cannabis is common among adolescents, but has been little studied. In this study, we examine predictors and consequences of this behavior in a population-based sample of high school students. Method: Self-reports were obtained from students in Quebec (Canada) followed throughout high school (N=6589). Logistic regressions were used to test the association between individual, family, and peerrelated predictors in grades 7–8 and simultaneous alcohol and cannabis use in grade 10, as well as between simultaneous alcohol and cannabis use in grade 10 and experiencing 3 or more substance-related problems of various types (legal, physical, etc.) in grade 11. Results: Most predictors in grades 7–8 were associated with simultaneous alcohol and cannabis use in grade 10. Only variables reflecting early-onset substance use involvement — alcohol intoxication, cannabis use, and drug use by close friend(s) — remained predictive in a multivariate model. Simultaneous alcohol and cannabis use was associated with increased substance-related problems in grade 11, above and beyond baseline problems and the concurrent use of the two substances in separate episodes in grade 10. Conclusions: Simultaneous alcohol and cannabis use 1) is anticipated by multiple psychosocial risk factors which come together with individual and peer substance use in early high school and 2) is independently predictive of subsequent substance-related problems. Providing adolescents with adequate information regarding the potential harm of simultaneous use may be a useful prevention strategy.