Sensitivity Analysis of the Risk of Forecasting for Autoregressive Time Series with Missing Values

2000 Mathematics Subject Classification: 62M20, 62M10, 62-07.

An autoregressive conditional filtering process to remove intraday seasonal volatility and its application to testing the noisy rational expectations model

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

Radiative forcing of natural forest disturbances

Forest disturbances are major sources of carbon dioxide to the atmosphere, and therefore impact global climate. Biogeophysical attributes, such as surface albedo (reflectivity), further control the climate-regulating properties of forests. Using both tower-based and remotely sensed data sets, we show that natural disturbances from wildfire, beetle outbreaks, and hurricane wind throw can significantly alter surface albedo, and the associated radiative forcing either offsets or enhances the CO2 forcing caused by reducing ecosystem carbon sequestration over multiple years. In the examined cases, the radiative forcing from albedo change is on the same order of magnitude as the CO2 forcing. The net radiative forcing resulting from these two factors leads to a local heating effect in a hurricane-damaged mangrove forest in the subtropics, and a cooling effect following wildfire and mountain pine beetle attack in boreal forests with winter snow. Although natural forest disturbances currently represent less than half of gross forest cover loss, that area will probably increase in the future under climate change, making it imperative to represent these processes accurately in global climate models.

An Autoregressive Conditional Filtering Process to remove Intraday Seasonal Volatility and its Application to Testing the Noisy Rational Expectations Model

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

Bayesian estimation in generalized autoregressive conditional heteroskedasticity models

Esta tesis doctoral nace con el propósito de entender, analizar y sobre todo modelizar el comportamiento estadístico de las series financieras. En este sentido, se puede afirmar que los modelos que mejor recogen las especiales características de estas series son los modelos de heterocedasticidad condicionada en tiempo discreto,si los intervalos de tiempo en los que se recogen los datos lo permiten, y en tiempo continuo si tenemos datos diarios o datos intradía. Con esta finalidad, en esta tesis se proponen distintos estimadores bayesianos para la estimación de los parámetros de los modelos GARCH en tiempo discreto (Bollerslev (1986)) y COGARCH en tiempo continuo (Kluppelberg et al. (2004)). En el capítulo 1 se introducen las características de las series financieras y se presentan los modelos ARCH, GARCH y COGARCH, así como sus principales propiedades. Mandelbrot (1963) destacó que las series financieras no presentan estacionariedad y que sus incrementos no presentan autocorrelación, aunque sus cuadrados sí están correlacionados. Señaló también que la volatilidad que presentan no es constante y que aparecen clusters de volatilidad. Observó la falta de normalidad de las series financieras, debida principalmente a su comportamiento leptocúrtico, y también destacó los efectos estacionales que presentan las series, analizando como se ven afectadas por la época del año o el día de la semana. Posteriormente Black (1976) completó la lista de características especiales incluyendo los denominados leverage effects relacionados con como las fluctuaciones positivas y negativas de los precios de los activos afectan a la volatilidad de las series de forma distinta.

Optimal selection of autoregressive model coefficients for early damage detectability with an application to wind turbine blades

Piotr Omenzetter and Simon Hoell's work within the Lloyd's Register Foundation Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd’s Register Foundation. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research.

Optimal selection of autoregressive model coefficients for early damage detectability with an application to wind turbine blades

Piotr Omenzetter and Simon Hoell's work within the Lloyd's Register Foundation Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd’s Register Foundation. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research.

White-nose syndrome initiates a cascade of physiologic disturbances in the hibernating bat host

Acknowledgments This project was financially supported by the US Geological Survey through a cooperative agreement with the University of Wisconsin – Madison. We are indebted to Dave and Jennifer Redell and Paul White from the Wisconsin Department of Natural Resources for collecting the animals used to complete this study and for assisting with data collection. We thank Melissa Behr for assistance with necropsies and NWHC Animal Care Staff for their help with set-up and maintenance of animals. We thank Lobke Vaanholt and Catherine Hambly (University of Aberdeen, Scotland) for their expertise and coordination in the analyses of the DLW blood samples. Funds were used for direct project costs only. Use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the US Government.

Climate-driven shifts in species' distributions may exacerbate the impacts of storm disturbances on North-east Atlantic kelp forests

Physical disturbance through wave action is a major determinant of kelp forest structure. The North-east Atlantic storm season of 2013–14 was unusually severe; the south coast of the UK was subjected to 6 of the 12 most intense storms recorded in the past 5 years. Inshore significant wave heights and periods exceeded 7 m and 13 s with two storms classified as ‘1-in-30 year’ events. We examined the impacts of the storm season on kelp canopies at three study sites. Monospecific canopies comprising Laminaria hyperborea were unaffected by storm disturbance. However, at one study site a mixed canopy comprising Laminaria ochroleuca, Saccharina latissima and L. hyperborea was significantly altered by the storms, due to decreased abundances of the former two species. Quantification of freshly severed stipes suggested that the ‘warm water’ kelp L. ochroleuca was more susceptible to storm damage than L. hyperborea. Overall, kelp canopies were highly resistant to storm disturbance because of the low vulnerability of L. hyperborea to intense wave action. However, if climate-driven shifts in kelp species distributions result in more mixed canopies, as predicted, then resistance to storm disturbance may be eroded.

Climate-driven shifts in species' distributions may exacerbate the impacts of storm disturbances on North-east Atlantic kelp forests

Physical disturbance through wave action is a major determinant of kelp forest structure. The North-east Atlantic storm season of 2013–14 was unusually severe; the south coast of the UK was subjected to 6 of the 12 most intense storms recorded in the past 5 years. Inshore significant wave heights and periods exceeded 7 m and 13 s with two storms classified as ‘1-in-30 year’ events. We examined the impacts of the storm season on kelp canopies at three study sites. Monospecific canopies comprising Laminaria hyperborea were unaffected by storm disturbance. However, at one study site a mixed canopy comprising Laminaria ochroleuca, Saccharina latissima and L. hyperborea was significantly altered by the storms, due to decreased abundances of the former two species. Quantification of freshly severed stipes suggested that the ‘warm water’ kelp L. ochroleuca was more susceptible to storm damage than L. hyperborea. Overall, kelp canopies were highly resistant to storm disturbance because of the low vulnerability of L. hyperborea to intense wave action. However, if climate-driven shifts in kelp species distributions result in more mixed canopies, as predicted, then resistance to storm disturbance may be eroded.

BAP Guidelines on the Management of Weight Gain, Metabolic Disturbances and Cardiovascular Risk Associated With Psychosis and Antipsychotic Drug Treatment

Excess deaths from cardiovascular disease are a major contributor to the significant reduction in life expectancy experienced by people with schizophrenia. Important risk factors in this are smoking, alcohol misuse, excessive weight gain and diabetes. Weight gain also reinforces service users’ negative views of themselves and is a factor in poor adherence with treatment. Monitoring of relevant physical health risk factors is frequently inadequate, as is provision of interventions to modify these. These guidelines review issues surrounding monitoring of physical health risk factors and make recommendations about an appropriate approach. Overweight and obesity, partly driven by antipsychotic drug treatment, are important factors contributing to the development of diabetes and cardiovascular disease in people with schizophrenia. There have been clinical trials of many interventions for people experiencing weight gain when taking antipsychotic medications but there is a lack of clear consensus regarding which may be appropriate in usual clinical practice. These guidelines review these trials and make recommendations regarding appropriate interventions. Interventions for smoking and alcohol misuse are reviewed, but more briefly as these are similar to those recommended for the general population. The management of impaired fasting glycaemia and impaired glucose tolerance (‘pre-diabetes’), diabetes and other cardiovascular risks, such as dyslipidaemia, are also reviewed with respect to other currently available guidelines. These guidelines were compiled following a consensus meeting of experts involved in various aspects of these problems. They reviewed key areas of evidence and their clinical implications. Wider issues relating to primary care/secondary care interfaces are discussed but cannot be resolved within guidelines such as these.

Sleep disturbances and nightmares in a patient treated with prazosin

DIFFERENTIATION OF ARBOREAL VEGETATION IN THREE SECTORS OF A FOREST FRAGMENT RELATED TO ITS HISTORICAL DISTURBANCES

Forest fragmentation is one of the main causes of biodiversity loss, directly affecting the ecological processes. This study aimed to evaluate tree diversity, structure, and composition parameters in three sectors of a forest fragment with distinct disturbance records. The arboreal vegetation was evaluated in twenty-four 10 × 10 m plots, sampling a total of 1,228 living individuals. We calculated Shanon’s diversity index, Pielou’s equability, and jackknife estimators of first and second orders. The sampled individuals were distributed in diameter classes and the importance value (VI) was calculated for each species. It was made a Detrended Correspondence Analysis (DCA) to verify whether there were significant distinctions between the sectors. It was noticed that the sector where there was clear cutting and vegetation burning in a recent past had higher abundance and richness but also the worst equability. That corresponds to the effects of perturbation as confirmed by the tree diameters and the presence of species of greater importance value. The sector that had no record of disturbance, situated in a location with greater variety of microenvironments, presented diversity, structure, and composition consistent with a no disturbance scenario. The other sector, which did not have clear cutting, was subjected to cattle trampling presented ecological parameters consistent with the absence of major disturbances. On the other hand, this third sector had the smallest environmental diversity, which puts this last sector in an intermediate situation.

Self-exciting threshold binomial autoregressive processes

We introduce a new class of integer-valued self-exciting threshold models, which is based on the binomial autoregressive model of order one as introduced by McKenzie (Water Resour Bull 21:645–650, 1985. doi:10.1111/j.1752-1688.1985. tb05379.x). Basic probabilistic and statistical properties of this class of models are discussed. Moreover, parameter estimation and forecasting are addressed. Finally, the performance of these models is illustrated through a simulation study and an empirical application to a set of measle cases in Germany.