Volatility Risk Premiums in Futures Markets: Investment Prices and Commercial Bank Performance

This dissertation is an in depth study of the measurement of pricing biases in futures options, and whether this bias is due to volatility risk premia, market overreaction to public information or information asymmetry. Futures options for thirteen different contracts are used. Additionally, the contracts are from three different marketplaces. Six hypotheses are tested. The first is whether implied option volatilities from the Black (1976) futures option model is the only significant determinant of the volatility processes of the underlying futures contracts. For this estimation, we use both a GARCH (1,1) model and the Partially Non-parametric model of Engle and Ng (1993). We find that implied option volatility is not the sole significant predictor for of conditional volatility for 10 of the thirteen contracts. For three of the contracts, the implied volatility is insignificant. Second, we test Stein\u27s (1989) hypothesis of market overreaction. We find that in general, the evidence tends to support the prediction of Stein\u27s hypothesis, though there are important exceptions. Third, we test Nandi\u27s hypothesis of asymmetric information in the market between traders. We test this by testing the significance of option contract volume on the volatility process. In general, the evidence tends to support Nandi\u27s hypothesis, though again, there are important exceptions. Fourth, we test the significance of the news response curves as outlined by Engle and Ng (1993). We find that there is little support in the shape and significance of the news response curves to support the presence of volatility risk premiums. Fifth, we test for differences in the structures of the estimated GARCH models between contracts and model. We find that American based interest-rate futures markets tend to be more highly reactive to innovations than the London (LIFFE) market. Sixth, we test for the exposure of major commercial banks dealing in futures to a volatility risk premium. While we find evidence that some banks are exposed to our volatility risk premium proxy, the contracts exhibiting significant coefficients generally do not match up with those contracts suspected of harboring volatility risk premiums under the previous tests. We conclude that there is little empirical support for the presence of a priced volatility risk premium amongst futures and futures options. The presence of pricing biases in such markets seems better explained as being due to information asymmetry or overreaction to news

Variability in the Firing of Nerve Impulses in Eccentric Cells of the Limulus Eye

Thesis is concerned with the source and characteristics of variability in the discharge of impulses by neurons. The neuron in which variability was studied is the eccentric cell in the compound eye of the horseshoe crab, Limulus polyphemus. In Part I a theory is presented which accounts for the variability in the response of an eccentric cell to light. The main idea of this theory is that the source of randomness in the impulse rate is noise in the generator potential. Another essential aspect of the theory is the view that the process which codes the generator potential into the impulse rate may be treated as a linear filter. These ideas lead directly to Fourier analysis of the fluctuations of the generator potential and fluctuations of the impulse rate. Experimental verification of theoretical predictions was obtained by measurement of the fluctuations and calculation of their variance spectrum. The variance spectrum (or power spectrum) of the impulse rate is shown to be the filtered variance spectrum of the generator potential. Another verification of the theory is the finding that in many cells the signal-to-noise ratio is constant for responses to sinusoidally modulated light, at all modulation frequencies. Inhibition from neighboring eccentric cells will have an effect on the variability of firing of a given eccentric cell. The effects of inhibition are discussed in Part II. The reduction in the average impulse rate which is caused by inhibition decreases the variance of the impulse rate. However, this reduction of the average impulse rate increases the coefficient of variation of the impulse rate. Inhibitory synaptic noise adds to the low frequency portion of the variance spectrum of the impulse rate. This occurs because of the Ill slow time course of the inhibitory synaptic potentials. As a consequence, inhibition decreases the signal-to-noise ratio for low frequency modulated stimuli. The net effect of inhibition is to increase the coefficient of variation of the impulse rate. This effect is predicted by the linear model of the eccentric cell. The same qualitative effect is predicted by other theories of neuronal variability, although its importance is stressed here for the first time

Effect of various mixing devices and patterns on flocculation kinetics in water treatment

This research was designed to investigate the effects of different mixing variables on flocculation kinetics of kaolinite clay suspension at both warm and cold water temperatures (23°C and 5°C) using alum and ferric nitrate under a number of physico-chemical conditions. The following work was performed during this experimental study: (1) G versus rpm curves for different impellers were developed using calculated power based on measured torque. The torque was measured by a rotating torque meter using a photographic technique. (2) The effects of impeller geometry, rapid mixing intensity and pattern, concentration of coagulant dosing solution, coagulant injection pattern, and slow mixing intensity and pattern on flocculation efficiency were investigated in a bench scale batch reactor at both warm and cold water temperatures with metal coagulants;All the experiments were performed in a batch reactor with 18-L liquid working volume inside a walk-in constant temperature room using five impeller geometries. The primary particles were kaolinite and they were flocculated using alum and ferric nitrate (Fe(NO[subscript]3)[subscript]3.9 H[subscript]2 O].;The paddle type mesh impeller performed significantly better than the turbine type impellers (2-blade and A 310) under all conditions tested. All the paddle type impellers (mesh, modified stake, and 2-blade stack) performed almost identically under the conditions tested. Both rapid mixing intensity and pattern had a remarkable impact on flocculation kinetics. An optimum G-value was obtained for each set of conditions. The low intensity, longer duration, rapid mix pattern outperformed the high intensity, short duration, rapid mix pattern in almost all the conditions studied;Slow injection, dilute dosing solution and multi port injection proved more beneficial than the pulse injection, concentrated dosing solution, and the single port injection respectively. There was an optimum slow mix G for each set of experimental conditions when constant G-slow mixing was adopted. Reducing the slow mix G as flocculation progressed resulted in higher flocculation index as flocculation progressed and better settled water turbidity due to less danger of floc breakup. All the mixing variables tested in this study demonstrated a more pronounced effect on flocculation kinetics at cold temperature than at warm temperature

Essays on the nonlinear and nonstochastic nature of stock market data

The nature and structure of stock-market price dynamics is an area of ongoing and rigourous scientific debate. For almost three decades, most emphasis has been given on upholding the concepts of Market Efficiency and rational investment behaviour. Such an approach has favoured the development of numerous linear and nonlinear models mainly of stochastic foundations. Advances in mathematics have shown that nonlinear deterministic processes i.e. "chaos" can produce sequences that appear random to linear statistical techniques. Till recently, investment finance has been a science based on linearity and stochasticity. Hence it is important that studies of Market Efficiency include investigations of chaotic determinism and power laws. As far as chaos is concerned, there are rather mixed or inconclusive research results, prone with controversy. This inconclusiveness is attributed to two things: the nature of stock market time series, which are highly volatile and contaminated with a substantial amount of noise of largely unknown structure, and the lack of appropriate robust statistical testing procedures. In order to overcome such difficulties, within this thesis it is shown empirically and for the first time how one can combine novel techniques from recent chaotic and signal analysis literature, under a univariate time series analysis framework. Three basic methodologies are investigated: Recurrence analysis, Surrogate Data and Wavelet transforms. Recurrence Analysis is used to reveal qualitative and quantitative evidence of nonlinearity and nonstochasticity for a number of stock markets. It is then demonstrated how Surrogate Data, under a statistical hypothesis testing framework, can be simulated to provide similar evidence. Finally, it is shown how wavelet transforms can be applied in order to reveal various salient features of the market data and provide a platform for nonparametric regression and denoising. The results indicate that without the invocation of any parametric model-based assumptions, one can easily deduce that there is more to linearity and stochastic randomness in the data. Moreover, substantial evidence of recurrent patterns and aperiodicities is discovered which can be attributed to chaotic dynamics. These results are therefore very consistent with existing research indicating some types of nonlinear dependence in financial data. Concluding, the value of this thesis lies in its contribution to the overall evidence on Market Efficiency and chaotic determinism in financial markets. The main implication here is that the theory of equilibrium pricing in financial markets may need reconsideration in order to accommodate for the structures revealed

Population dynamics in voles: characterization and modelling of global spatio-temporal patterns

Population fluctuations of rodents have always aroused human interest due to their importance in ecosystems and human welfare. However, their scientific study became especially relevant in the late 19th and early 20th centuries when Robert Collet and Charles S. Elton described periodic eruptions of lemmings and voles. Since then, hundreds of theoretical, experimental, and field works have provided a basis for understanding the mechanisms underlying the different population fluctuations observed in nature. However, the generality of these mechanisms across different species and geographic areas remains one of the greatest unknowns in ecology; posing a problem for understanding natural ecosystems, as well as for managing species and their effects on human welfare. This dissertation takes advantage of the vast amount of data and knowledge on vole population dynamics to test the existence of general demographic mechanisms, as well as to identify predictors of events such as plagues to better understand and manage these species. This dissertation compiles nearly 70 years of capture-mark-recapture data from 17 trapping areas with weekly, biweekly and monthly sampling frequency from five populations of four vole species in North America and Europe (M. agrestis = 4 sampling areas or spatiotemporal replicates, M. ochrogaster = 4, M. pennsylvanicus = 5 and M. townsendii = 4); being to date the largest database of rodent demographic data with high temporal resolution (monthly resolution or higher). Subsequently, this dissertation analyses whether part of the inter-annual fluctuations is produced by common demographic mechanisms in different species and geographic areas (e.g. similar variations in survival, reproduction or migration). But to do so, it first overcomes one of the main obstacles in the study of population dynamics of rodents and many other species, the relatively low number of observations to make models sufficiently complex and informative to understand population dynamics. Specifically, this thesis proposes an extension of traditional capture-mark-recapture models, using regularization techniques widely used in different fields of statistics such as in the calculation of random effects, in order to estimate demographic parameters under conditions of relatively low data availability. With this new analysis tool, whose usefulness goes far beyond the study of rodent demography (e.g. elusive species or species with low densities such as some endangered species), this dissertation estimates the abundances and vital rates of the four vole species in the 17 sampling areas at a fine enough temporal scale to study biological models that allow an adequate understanding of their population dynamics. This dissertation uses these estimated demographic parameters to evaluate the existence of common general patterns. The results show not only the existence of such common demographic mechanisms, but also suggest their great relevance; reopening an interesting debate on the relative importance of common and specific factors in the origin of population fluctuations. Furthermore, by testing predictions of the most accepted hypotheses in the scientific community, it showed that feeding and social interactions are more likely underlying these common demographic patterns. Finally, the dissertation shows how theoretical knowledge about population dynamics can be used to solve or mitigate a human welfare problem, such as vole outbreaks. Specifically, this dissertation identifies an early warning signal capable of predicting outbreaks of the common vole (M. arvalis) one year in advance in Castilla y León (Spain). This predictor facilitates farmers and regional government to take preventive measures to mitigate the impact of vole outbreaks in crop fields. Complementarily, this dissertation proposes an approach to solve an important but little discussed problem in applied ecology, which is that erroneous predictions entail costs for users. This dissertation proposes an approach to measure the usefulness of predictors in decision making by considering their hit and error rate (statistical aspect) as well as the expenses, effectiveness, and indirect effects of the treatment to be applied based on the predictions (management aspect). This last contribution aims that scientific researches proposing predictive models explicitly indicate their usefulness for each potential user; which can enhance and improve its use in applied ecology. In general, this dissertation focuses on vole population dynamics from a basic, theoretical, and applied ecology point of view. On the one hand, it provides fundamental theoretical knowledge to understand the generalities of vole population dynamics, as well as vole outbreaks in Mediterranean environments. On the other hand, it provides diverse conceptual and analytical approaches with great multidisciplinary utility. All this together makes the present dissertation an important key piece in future research in various fields of science.Las fluctuaciones poblacionales de roedores han despertado siempre el interés humano debido a su importancia en los ecosistemas y en el bienestar humano. Sin embargo, su estudio científico empezó a ser especialmente relevante a finales del siglo XIX y principios del XX cuando Robert Collet y Charles S. Elton describieron las erupciones periódicas de lemmings y topillos. Desde entonces, cientos de trabajos teóricos, experimentales y de campo han proporcionado una base para entender los mecanismos que subyacen a las diferentes fluctuaciones poblacionales observadas en la naturaleza. Sin embargo, la generalidad de estos mecanismos a lo largo de las diferentes especies y áreas geográficas sigue siendo una de las mayores incógnitas de la ecología; lo que supone un problema para comprender los ecosistemas naturales, así como para gestionar las especies y sus efectos en el bienestar humano. Esta tesis aprovecha la amplia cantidad de datos y conocimientos sobre las dinámicas poblacionales de topillos para testar la existencia de mecanismos demográficos generales, así como para identificar predictores de eventos como las plagas que permitan entender y gestionar mejor estas especies. En primer lugar, esta tesis recopila casi 70 años de datos de captura-marcado-recaptura en 17 áreas de muestro con frecuencia de muestreo semanal, quincenal y mensual de cinco poblaciones de cuatro especies de topillos en Norteamérica y Europa (M. agrestis = 4 áreas de muestreo o réplicas espacio-temporales, M. ochrogaster = 4, M. pennsylvanicus = 5 y M. townsendii = 4); siendo hasta la fecha la mayor base de datos demográficos de roedores con alta resolución temporal (i.e., resolución mensual o mayor). Posteriormente, esta tesis analiza si parte de las fluctuaciones interanuales se producen por mecanismos demográficos comunes en diferentes especies y áreas geográficas (e.g. variaciones similares en la supervivencia, reproducción o migración). Pero para ello, antes supera uno de los principales obstáculos en el estudio de la dinámica poblacional de los roedores y de muchas otras especies, la relativa baja cantidad de observaciones para realizar modelos lo suficientemente complejos e informativos para entender las dinámicas poblacionales. En concreto, esta tesis propone una extensión de los modelos de captura-marcado-recaptura tradicionales, mediante el uso de técnicas de regularización ampliamente utilizadas en diferentes campos de la estadística como en el cálculo de los efectos aleatorios, y así poder estimar parámetros demográficos en condiciones de relativa baja disponibilidad de datos. Con esta nueva herramienta de análisis, cuya utilidad va mucho más allá del estudio de la demografía de roedores (e.g. especies esquivas o con bajas densidades como algunas en peligro de extinción), esta tesis estima las abundancias y tasas vitales de las cuatro especies de topillo en las 17 áreas de muestro a una escala temporal lo suficientemente fina como para poder estudiar modelos biológicos que permitan una adecuada comprensión de sus dinámicas poblacionales. Esta tesis utiliza esos parámetros demográficos estimados para evaluar la existencia de patrones generales comunes. Los resultados muestran no sólo la existencia de tales mecanismos demográficos comunes, sino que también sugieren su gran relevancia; reabriendo un interesante debate sobre la importancia relativa de los factores comunes y específicos en el origen de las fluctuaciones poblacionales. Además, esta tesis pone a prueba las predicciones de las hipótesis más aceptadas en la comunidad científica sobre los factores causales que subyacen a las variaciones demográficas (e.g. la alimentación, la depredación o las interacciones sociales). Los resultados sugieren que el alimento y las interacciones sociales podrían ser los factores causales detrás de las variaciones en las tasas vitales que producen los patrones comunes. Por último, la tesis muestra cómo el conocimiento teórico sobre la dinámica poblacional puede utilizarse para resolver o mitigar un problema de bienestar humano, como las plagas de topillos. En concreto, esta tesis identifica una señal de alerta temprana capaz de predecir las plagas de topillo campesino (M. arvalis) con un año de antelación en Castilla y León (España). Este predictor facilita que agricultores y gobierno regional tomen medidas preventivas para mitigar el impacto de las plagas de topillo en los campos de cultivo. Complementariamente, esta tesis propone un enfoque para solventar un problema importante pero poco discutido en ecología aplicada como es que las predicciones erróneas conllevan gastos para los usuarios. En particular, esta tesis propone un enfoque para medir la utilidad de un predictor en la toma de decisiones considerando la tasa de acierto y error (aspecto estadístico) y los costes, efectividad, y efectos indirectos del tratamiento que se aplicará en base a las predicciones (aspecto de gestión). Esta última contribución tiene como objetivo que las investigaciones científicas que proponen modelos predictivos indiquen explícitamente su utilidad para cada posible usuario; lo que puede potenciar y mejorar el uso de predictores en ecología aplicada. En general, esta tesis se centra en las dinámicas poblacionales de topillos desde un punto de vista de la ecología básica, teórica, y aplicada. Por un lado, proporciona un conocimiento teórico fundamental para entender las generalidades en las dinámicas poblacionales de topillos, así como de las plagas de topillos en ambientes mediterráneos. Por otro lado, proporciona diversos enfoques conceptuales y analíticos con una gran utilidad multidisciplinar. Todo esto junto hace que la presente tesis pueda ser una pieza importante clave en investigaciones futuras de diversos campos de la ciencia

On the Recognition of Emotion from Physiological Data

This work encompasses several objectives, but is primarily concerned with an experiment where 33 participants were shown 32 slides in order to create ‗weakly induced emotions‘. Recordings of the participants‘ physiological state were taken as well as a self report of their emotional state. We then used an assortment of classifiers to predict emotional state from the recorded physiological signals, a process known as Physiological Pattern Recognition (PPR). We investigated techniques for recording, processing and extracting features from six different physiological signals: Electrocardiogram (ECG), Blood Volume Pulse (BVP), Galvanic Skin Response (GSR), Electromyography (EMG), for the corrugator muscle, skin temperature for the finger and respiratory rate. Improvements to the state of PPR emotion detection were made by allowing for 9 different weakly induced emotional states to be detected at nearly 65% accuracy. This is an improvement in the number of states readily detectable. The work presents many investigations into numerical feature extraction from physiological signals and has a chapter dedicated to collating and trialing facial electromyography techniques. There is also a hardware device we created to collect participant self reported emotional states which showed several improvements to experimental procedure