Diagnostic Tests Based on Quantile Residuals for Nonlinear Time Series Models

This thesis studies quantile residuals and uses different methodologies to develop test statistics that are applicable in evaluating linear and nonlinear time series models based on continuous distributions. Models based on mixtures of distributions are of special interest because it turns out that for those models traditional residuals, often referred to as Pearson's residuals, are not appropriate. As such models have become more and more popular in practice, especially with financial time series data there is a need for reliable diagnostic tools that can be used to evaluate them. The aim of the thesis is to show how such diagnostic tools can be obtained and used in model evaluation. The quantile residuals considered here are defined in such a way that, when the model is correctly specified and its parameters are consistently estimated, they are approximately independent with standard normal distribution. All the tests derived in the thesis are pure significance type tests and are theoretically sound in that they properly take the uncertainty caused by parameter estimation into account. -- In Chapter 2 a general framework based on the likelihood function and smooth functions of univariate quantile residuals is derived that can be used to obtain misspecification tests for various purposes. Three easy-to-use tests aimed at detecting non-normality, autocorrelation, and conditional heteroscedasticity in quantile residuals are formulated. It also turns out that these tests can be interpreted as Lagrange Multiplier or score tests so that they are asymptotically optimal against local alternatives. Chapter 3 extends the concept of quantile residuals to multivariate models. The framework of Chapter 2 is generalized and tests aimed at detecting non-normality, serial correlation, and conditional heteroscedasticity in multivariate quantile residuals are derived based on it. Score test interpretations are obtained for the serial correlation and conditional heteroscedasticity tests and in a rather restricted special case for the normality test. In Chapter 4 the tests are constructed using the empirical distribution function of quantile residuals. So-called Khmaladze s martingale transformation is applied in order to eliminate the uncertainty caused by parameter estimation. Various test statistics are considered so that critical bounds for histogram type plots as well as Quantile-Quantile and Probability-Probability type plots of quantile residuals are obtained. Chapters 2, 3, and 4 contain simulations and empirical examples which illustrate the finite sample size and power properties of the derived tests and also how the tests and related graphical tools based on residuals are applied in practice.

Japanese Video Game Localization : A Case Study of Sony's Sairen Series

This thesis is a comparative case study in Japanese video game localization for the video games Sairen, Sairen 2 and Sairen Nyûtoransurêshon, and English-language localized versions of the same games as published in Scandinavia and Australia/New Zealand. All games are developed by Sony Computer Entertainment Inc. and published exclusively for Playstation2 and Playstation3 consoles. The fictional world of the Sairen games draws much influence from Japanese history, as well as from popular and contemporary culture, and in doing so caters mainly to a Japanese audience. For localization, i.e. the adaptation of a product to make it accessible to users outside the original market it was intended for in the first place, this is a challenging issue. Video games are media of entertainment, and therefore localization practice must preserve the games’ effects on the players’ emotions. Further, video games are digital products that are comprised of a multitude of distinct elements, some of which are part of the game world, while others regulate the connection between the player as part of the real world and the game as digital medium. As a result, video game localization is also a practice that has to cope with the technical restrictions that are inherent to the medium. The main theory used throughout the thesis is Anthony Pym’s framework for localization studies that considers the user of the localized product as a defining part of the localization process. This concept presupposes that localization is an adaptation that is performed to make a product better suited for use during a specific reception situation. Pym also addresses the factor that certain products may resist distribution into certain reception situations because of their content, and that certain aspects of localization aim to reduce this resistance through significant alterations of the original product. While Pym developed his ideas with mainly regular software in mind, they can also be adapted well to study video games from a localization angle. Since modern video games are highly complex entities that often switch between interactive and non-interactive modes, Pym’s ideas are adapted throughout the thesis to suit the particular elements being studied. Instances analyzed in this thesis include menu screens, video clips, in-game action and websites. The main research questions focus on how the games’ rules influence localization, and how the games’ fictional domain influences localization. Because there are so many peculiarities inherent to the medium of the video game, other theories are introduced as well to complement the research at hand. These include Lawrence Venuti’s discussions of foreiginizing and domesticating translation methods for literary translation, and Jesper Juul’s definition of games. Additionally, knowledge gathered from interviews with video game localization professionals in Japan during September and October 2009 is also utilized for this study. Apart from answering the aforementioned research questions, one of this thesis’ aims is to enrich the still rather small field of game localization studies, and the study of Japanese video games in particular, one of Japan’s most successful cultural exports.

Methodological and Empirical Advances in the Quantitative Analysis of Spontaneous Responses in Psychophysiological Time Series

The aim of the present study was to advance the methodology and use of time series analysis to quantify dynamic structures in psychophysiological processes and thereby to produce information on spontaneously coupled physiological responses and their behavioral and experiential correlates. Series of analyses using both simulated and empirical cardiac (IBI), electrodermal (EDA), and facial electromyographic (EMG) data indicated that, despite potential autocorrelated structures, smoothing increased the reliability of detecting response coupling from an interindividual distribution of intraindividual measures and that especially the measures of covariance produced accurate information on the extent of coupled responses. This methodology was applied to analyze spontaneously coupled IBI, EDA, and facial EMG responses and vagal activity in their relation to emotional experience and personality characteristics in a group of middle-aged men (n = 37) during the administration of the Rorschach testing protocol. The results revealed new characteristics in the relationship between phasic end-organ synchronization and vagal activity, on the one hand, and individual differences in emotional adjustment to novel situations on the other. Specifically, it appeared that the vagal system is intimately related to emotional and social responsivity. It was also found that the lack of spontaneously synchronized responses is related to decreased energetic arousal (e.g., depression, mood). These findings indicate that the present process analysis approach has many advantages for use in both experimental and applied research, and that it is a useful new paradigm in psychophysiological research. Keywords: Autonomic Nervous System; Emotion; Facial Electromyography; Individual Differences; Spontaneous Responses; Time Series Analysis; Vagal System

Pyhä Kolminaisuus vai pilven reunalla istuva partasuu? : Jumalakuva evankelisluterilaisissa ja ortodoksissa 1.–4.-luokan uskonnon oppikirjoissa 1970–80- ja 2000-luvuilla

A concept of god is a wholeness that an individual experiences as God. The Christian concept of god is based on triune God: Father, Son, and the Holy Spirit. The concept of god is examined in different kinds of contexts particularly between the 1940's and the 1970's. Many researches of school books have widely been made in Finland, but, however, only a few from the point of view of the concept of god. Considering this, the concept of god in the school books of Evangelical Lutheran and Orthodox religion from first to fourth grade in 1970–80 and 2000 is examined in this survey. Additionally, the concept of god in curricula between years 1970 and 2004 is studied. The perspective on the concept of god is the change in the course of time and denominational emphasis. As a first hypothesis, God the Father is represented in books in 21st century as a kind and loving figure. As a second hypothesis, the Trinity and the Holy Spirit get more space in Orthodox books comparing with the Lutheran books. Twelve school books of Evangelical Lutheran and Orthodox religion from first to fourth grade were used as a research material. The books were from four different series between the years 1978 and 2005. Teacher's guidebooks and student's exercise books were left outside of this survey. The research material was analyzed by using abductive content analysis and methodological triangulation. This study included both qualitative and quantitative aspects. The classification system which defined the classifying of concept of god from the research material was consisted of the basis of research material, former reseach, and subtext of used theories. The number of mentions in concept of god was higher in books from the 21st century. In Lutheran books, the change was seen as a growth of the category of God the Father. In Orthodox books, the trend was opposite: the category of Jesus the Son had grown. Differing from the presupposition, the features of loving God in new books had less emphasis than in older books in both churces. The mentions of the Holy Spirit and Trinity were marginal. In the Orthodox books, the categories were bigger, as it was presupposed. It could be seen, that the books confirmed the legalistic period of the concept of god on 3rd and 4th grades. The mentions of concept of god in curriculas have diminished and generalized. The diminution was seen most radically in the curriculum from the year 1994. The results tell something about social changes and views of innovation in curricula. In books the change was not perceived that bright. The idea of the concept of god getting shrank and decreased during the time can be refused.

Modeling Asymmetries in Financial Data with Multiplicative Error Models

This thesis addresses modeling of financial time series, especially stock market returns and daily price ranges. Modeling data of this kind can be approached with so-called multiplicative error models (MEM). These models nest several well known time series models such as GARCH, ACD and CARR models. They are able to capture many well established features of financial time series including volatility clustering and leptokurtosis. In contrast to these phenomena, different kinds of asymmetries have received relatively little attention in the existing literature. In this thesis asymmetries arise from various sources. They are observed in both conditional and unconditional distributions, for variables with non-negative values and for variables that have values on the real line. In the multivariate context asymmetries can be observed in the marginal distributions as well as in the relationships of the variables modeled. New methods for all these cases are proposed. Chapter 2 considers GARCH models and modeling of returns of two stock market indices. The chapter introduces the so-called generalized hyperbolic (GH) GARCH model to account for asymmetries in both conditional and unconditional distribution. In particular, two special cases of the GARCH-GH model which describe the data most accurately are proposed. They are found to improve the fit of the model when compared to symmetric GARCH models. The advantages of accounting for asymmetries are also observed through Value-at-Risk applications. Both theoretical and empirical contributions are provided in Chapter 3 of the thesis. In this chapter the so-called mixture conditional autoregressive range (MCARR) model is introduced, examined and applied to daily price ranges of the Hang Seng Index. The conditions for the strict and weak stationarity of the model as well as an expression for the autocorrelation function are obtained by writing the MCARR model as a first order autoregressive process with random coefficients. The chapter also introduces inverse gamma (IG) distribution to CARR models. The advantages of CARR-IG and MCARR-IG specifications over conventional CARR models are found in the empirical application both in- and out-of-sample. Chapter 4 discusses the simultaneous modeling of absolute returns and daily price ranges. In this part of the thesis a vector multiplicative error model (VMEM) with asymmetric Gumbel copula is found to provide substantial benefits over the existing VMEM models based on elliptical copulas. The proposed specification is able to capture the highly asymmetric dependence of the modeled variables thereby improving the performance of the model considerably. The economic significance of the results obtained is established when the information content of the volatility forecasts derived is examined.

Improving GPS time series for geodynamic studies

Accurate and stable time series of geodetic parameters can be used to help in understanding the dynamic Earth and its response to global change. The Global Positioning System, GPS, has proven to be invaluable in modern geodynamic studies. In Fennoscandia the first GPS networks were set up in 1993. These networks form the basis of the national reference frames in the area, but they also provide long and important time series for crustal deformation studies. These time series can be used, for example, to better constrain the ice history of the last ice age and the Earth s structure, via existing glacial isostatic adjustment models. To improve the accuracy and stability of the GPS time series, the possible nuisance parameters and error sources need to be minimized. We have analysed GPS time series to study two phenomena. First, we study the refraction in the neutral atmosphere of the GPS signal, and, second, we study the surface loading of the crust by environmental factors, namely the non-tidal Baltic Sea, atmospheric load and varying continental water reservoirs. We studied the atmospheric effects on the GPS time series by comparing the standard method to slant delays derived from a regional numerical weather model. We have presented a method for correcting the atmospheric delays at the observational level. The results show that both standard atmosphere modelling and the atmospheric delays derived from a numerical weather model by ray-tracing provide a stable solution. The advantage of the latter is that the number of unknowns used in the computation decreases and thus, the computation may become faster and more robust. The computation can also be done with any processing software that allows the atmospheric correction to be turned off. The crustal deformation due to loading was computed by convolving Green s functions with surface load data, that is to say, global hydrology models, global numerical weather models and a local model for the Baltic Sea. The result was that the loading factors can be seen in the GPS coordinate time series. Reducing the computed deformation from the vertical time series of GPS coordinates reduces the scatter of the time series; however, the long term trends are not influenced. We show that global hydrology models and the local sea surface can explain up to 30% of the GPS time series variation. On the other hand atmospheric loading admittance in the GPS time series is low, and different hydrological surface load models could not be validated in the present study. In order to be used for GPS corrections in the future, both atmospheric loading and hydrological models need further analysis and improvements.

Exotic superfluid states of ultra-cold Fermi gases

This is a study of ultra-cold Fermi gases in different systems. This thesis is focused on exotic superfluid states, for an example on the three component Fermi gas and the FFLO phase in optical lattices. In the two-components case, superfluidity is studied mainly in the case of the spin population imbalanced Fermi gases and the phase diagrams are calculated from the mean-field theory. Different methods to detect different phases in optical lattices are suggested. In the three-component case, we studied also the uniform gas and harmonically trapped system. In this case, the BCS theory is generalized to three-component gases. It is also discussed how to achieve the conditions to get an SU(3)-symmetric Hamiltonian in optical lattices. The thesis is divided in chapters as follows: Chapter 1 is an introduction to the field of cold quantum gases. In chapter 2 optical lattices and their experimental characteristics are discussed. Chapter 3 deals with two-components Fermi gases in optical lattices and the paired states in lattices. In chapter 4 three-component Fermi gases with and without a harmonic trap are explored, and the pairing mechanisms are studied. In this chapter, we also discuss three-component Fermi gases in optical lattices. Chapter 5 devoted to the higher order correlations, and what they can tell about the paired states. Chapter 6 concludes the thesis.

Growing Flowers in the Frost: Civic Activity, Citizenship and Gender in Russia

This study analyzes civic activity, citizenship and their gendered manifestations in contemporary Russia. It is based on a case study conducted in the city of Tver , located in the vicinity of Moscow, during 2001-2005. The data consists of interviews with civic activists and municipal and regional authorities; observations of civic organizations; and a quantitative survey conducted among local civic groups. The theoretical and methodological framework of the study draws upon a micro perspective on organization, discourse analysis, gender and citizenship theories and Pierre Bourdieu s theory of fields and capital. This study develops theoretical understanding of the characteristics and logic of civic organization in Russia. It shows that social class centrally structures the field of civic activity. Organizations can be seen as a vehicle of the educated class to advocate their interests, help themselves and seek both social and individual-level change. The study also argues that civic organizations founded during the post-Soviet era are often an institutionalized form of informal social networks. Networks, which were a central element of everyday interaction in Soviet society, are a resource and often the only resource available that can be made use of in contemporary organizational activities. The study argues that gender operates as a key structuring principle in the Russian socio-political community. Civic activity is often discursively associated with femininity and institutional politics with masculinity. Women tend to participate more than men in civic organizations, while men dominate the formal political domain. The study shows that civic organizations are important loci of communality. This communality, however, differs from the communality envisioned in the communitarian and social capital debates in the West. It is selective communality , as it is restricted to the members of the organizations and does not create generalized reciprocity and trust. Civic organizations tend to build upon and reproduce the traditional Russian organizational form of circles , kruzhki. Along with the analysis of civic activities, the study also examines the redefinition of the role and functions of the state. The authorities interviewed in this study understand civic organizations as serving those goals and interests determined by the authorities, instead of viewing them as sites of citizens self-organization around interests and problems citizens themselves deem important, or as a counterforce to the state. By contrast, civic activists understand the core of organizational activity to be advocacy of their interests and rights, tackling social problems, the pursuit of wider social change and self-help. Co-operation between authorities and organizations tends to be personified and based upon unequal, hierarchical patron-client arrangements, which inhibits the development of democratic governance. The study will be published in Routledge Contemporary Russia and Eastern Europe Series later this year.

Studies on Binary Time Series Models with Applications to Empirical Macroeconomics and Finance

This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.

What do hydrological time series tell about climate change?

Yhteenveto: Mitä hydrologiset mallit kertovat ilmaston muutoksesta?