A comparison of Spillover Effects before, during and after the 2008 Financial Crisis

This paper applies graphical modelling to the S&P 500, Nikkei 225 and FTSE 100 stock market indices to trace the spillover of returns and volatility between these three major world stock market indices before, during and after the 2008 financial crisis. We find that the depth of market integration changed significantly between the pre-crisis period and the crisis and post- crisis period. Graphical models of both return and volatility spillovers are presented for each period. We conclude that graphical models are a useful tool in the analysis of multivariate time series where tracing the flow of causality is important.Volatility spillover; graphical modelling; financial crisis; causality

Extreme Value GARCH modelling with Bayesian Inference

Extreme value theory is widely used financial applications such as risk analysis, forecasting and pricing models. One of the major difficulties in the applications to finance and economics is that the assumption of independence of time series observations is generally not satisfied, so that the dependent extremes may not necessarily be in the domain of attraction of the classical generalised extreme value distribution. This study examines a conditional extreme value distribution with the added specification that the extreme values (maxima or minima) follows a conditional autoregressive heteroscedasticity process. The dependence has been modelled by allowing the location and scale parameters of the extreme distribution to vary with time. The resulting combined model, GEV-GARCH, is developed by implementing the GARCH volatility mechanism in these extreme value model parameters. Bayesian inference is used for the estimation of parameters and posterior inference is available through the Markov Chain Monte Carlo (MCMC) method. The model is firstly applied to relevant simulated data to verify model stability and reliability of the parameter estimation method. Then real stock returns are used to consider evidence for the appropriate application of the model. A comparison is made between the GEV-GARCH and traditional GARCH models. Both the GEV-GARCH and GARCH show similarity in the resulting conditional volatility estimates, however the GEV-GARCH model differs from GARCH in that it can capture and explain extreme quantiles better than the GARCH model because of more reliable extrapolation of the tail behaviour.Extreme value distribution, dependency, Bayesian, MCMC, Return quantile

Bayesian Extreme Value Mixture Modelling for Estimating VaR

A new extreme value mixture modelling approach for estimating Value-at-Risk (VaR) is proposed, overcoming the key issues of determining the threshold which defines the distribution tail and accounts for uncertainty due to threshold choice. A two-stage approach is adopted: volatility estimation followed by conditional extremal modelling of the independent innovations. Bayesian inference is used to account for all uncertainties and enables inclusion of expert prior information, potentially overcoming the inherent sparsity of extremal data. Simulations show the reliability and flexibility of the proposed mixture model, followed by VaR forecasting for capturing returns during the current financial crisis.Extreme values; Bayesian; Threshold estimation; Value-at-Risk

evmix: An R package for Extreme Value Mixture Modeling, Threshold Estimation and Boundary Corrected Kernel Density Estimation

evmix is an R package (R Core Team 2017) with two interlinked toolsets: i) for extreme value modeling and ii) kernel density estimation. A key issue in univariate extreme value modeling is the choice of threshold beyond which the asymptotically motivated extreme value models provide a suitable tail approximation. The package implements almost all existing extreme value mixture models, which permit objective threshold estimation and uncertainty quantification. Some traditional diagnostic plots for threshold choice are provided. Kernel density estimation with a range of kernels is provided, including cross-validation maximum likelihood inference for the bandwidth. A key contribution over existing kernel smoothing packages in R is that a wide range of boundary corrected kernel density estimators are implemented, which are designed for populations with bounded support. These non-parametric density estimators are also incorporated into the extreme value mixture model framework to describe the density below the threshold. The quartet of density, distribution, quantile and random number generation functions is provided along with parameter estimation by likelihood inference and standard model fit diagnostics, for both the mixture models and kernel density estimators. The key features of the mixture models and (boundary corrected) kernel density estimators are described and their implementation using the package demonstrated

Effectiveness of pads and enclosures as safety interventions on consumer trampolines

Background Trampolines continue to be a major source of childhood injury. Objective To examine available data on trampoline injuries in order to determine the effectiveness of padding and enclosures. Design Trampoline injuries from the NEISS database from 2002 to 2007 were reclassified into five cause-categories, to examine evidence for injury trends. Setting The ASTM trampoline standard recommendations for safety padding were upgraded in 1999 and enclosures were introduced in 1997. This is the first study to examine the impact of these changes. Patients The sampling frame comprises patients with NEISS product code 'consumer trampolines' (1233). A systematic sample of 360 patients each year is taken. Interventions The prominent interventions recommended by the ASTM are netting enclosures to prevent falling off and safety padding to cover frames and springs. Main outcome measures Proportion of injuries within each cause-category and trend estimates. Results There was no evidence for a decline within the injury cause-categories that should be prevented by these interventions from 2002 to 2007. Conclusions If these interventions were effective the associated injury causes would be in decline. Instead they remain close to half of all trampoline injuries with no significant change over the period of the study. Follow-up studies are proposed to determine the reasons. Given the number of injuries involved it is recommended that steps be taken to ensure these safety interventions or their equivalents are in place, work properly and remain effective for the life of consumer trampolines

An Exploratory Investigation of Some Statistical Summaries of Oximeter Oxygen Saturation Data from Preterm Babies

Aim. To explore the potential usefulness of the mean, standard deviation (SD), and coefficient of variation (CV = SD/mean) of oximeter oxygen saturations in the clinical care of preterm babies. Methods. This was an exploratory investigation involving 31 preterm babies at 36 weeks postmenstrual age. All babies were healthy, but two were considered to be clinically unstable and required greater attention. Each baby's oxygen saturations were recorded using an oximeter and summarized by the mean, SD, and CV. The potential usefulness of each measure was assessed by its ability to distinguish the two unstable babies from the others. This was achieved using box plots and hierarchical clustering together with the Calinski-Harabasz (CH) index to quantify clustering performance (higher CH index indicates stronger clustering outcome). Results. The box plots flagged both unstable babies as outliers and none of the other babies. Successful clustering of the stable and unstable babies was achieved using the CV (CH = 72.8) and SD (CH = 63.3) but not with the mean. Conclusion. Taking the box plots and clustering results together, it seems plausible that variability might be more effective than mean level for detecting instability in oxygen saturation in preterm babies and that the combination of variability and level through the CV might be even better

Forearm oxygenation and blood flow kinetics during a sustained contraction in multiple ability groups of rock climbers

Currently, the physiological mechanisms that allow elite level climbers to maintain intense isometric contractions for prolonged periods of time are unknown. Furthermore, it is unclear whether blood flow or muscle oxidative capacity best governs performance. This study aimed to determine the haemodynamic kinetics of 2 forearm flexor muscles in 3 ability groups of rock climbers. Thirty-eight male participants performed a sustained contraction at 40% of maximal voluntary contraction (MVC) until volitional fatigue. Oxygen saturation and blood flow was assessed using near infrared spectroscopy and Doppler ultrasound. Compared to control, intermediate, and advanced groups, the elite climbers had a significantly (P < 0.05) higher strength-to-weight ratio (MVC/N), de-oxygenated the flexor digitorum profundus significantly (P < 0.05) more (32, 34.3, and 42.8 vs. 63% O2, respectively), and at a greater rate (0.32, 0.27, and 0.34 vs. 0.77 O2%·s−1, respectively). Furthermore, elite climbers de-oxygenated the flexor carpi radialis significantly (P < 0.05) more and at a greater rate than the intermediate group (36.5 vs. 14.6% O2 and 0.43 vs. 0.1O2%·s−1, respectively). However, there were no significant differences in total forearm ∆ blood flow. An increased MVC/N is not associated with greater blood flow occlusion in elite climbers; therefore, oxidative capacity may be more important for governing performance

Reactor modelling and risk assessment

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