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

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.

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.

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?

Essays on Stock Option Compensation and the Role of Incentives and Risk (summary section only)

Managerial pay-for-performance sensitivity has increased rapidly around the world. Early empirical research showed that pay-for-performance sensitivity resulting from stock ownership and stock options appeared to be quite low during the 1970s and early 1980s in the U.S. However, recent empirical research from the U.S. shows an enormous increase in pay-for-performance sensitivity. The global trend has also reached Finland, where stock options have become a major ingredient of executive compensation. The fact that stock options seem to be an appealing form of remuneration from a theoretical point of view combined with the observation that the use of this compensation form has increased significantly during the recent years, implies that research on the dynamics of stock option compensation is highly relevant for the academic community, as well as for practitioners and regulators. The research questions of the thesis are analyzed in four separate essays. The first essay examines whether stock option compensation practices of Finnish firms are consistent with predictions from principal-agent theory. The second essay explores one of the major puzzles in the compensation literature by studying determinants of stock option contract design. In theory, optimal contract design should vary according to firm characteristics. However, in the U.S., variation in contract design seems to be surprisingly low, a phenomenon generally attributed to tax and accounting considerations. In Finland, however, firms are not subject to stringent contracting restrictions, and the variation in contract design tends, in fact, to be quite substantial. The third essay studies the impact of price- and risk incentives arising from stock option compensation on firm investment. In addition, the essay explores one of the most debated questions in the literature, in particular, the relation between incentives and firm performance. Finally, several strands of literature in both economics and corporate finance hypothesize that economic uncertainty is related to corporate decision-making. Previous research has shown that risk tends to slow down firm investment. In the fourth essay, it is hypothesized that firm risk slows down growth from a more universal perspective. Consistent with this view, it is shown that risk not only tends to slow down firm investment, but also employment growth. Moreover, the essay explores whether the nature of firms’ compensation policies, in particular, whether firms make use of stock option compensation, affects the relation between risk and firm growth. In summary, the four essays contribute to the current understanding of stock options as a form of equity incentives, and how incentives and risk affect corporate decision-making. By this, the thesis promotes the knowledge related to the modern theory of the firm.

Bootstrap and Fast Double Bootstrap Tests of Cointegration Rank with Financial Time Series

The likelihood ratio test of cointegration rank is the most widely used test for cointegration. Many studies have shown that its finite sample distribution is not well approximated by the limiting distribution. The article introduces and evaluates by Monte Carlo simulation experiments bootstrap and fast double bootstrap (FDB) algorithms for the likelihood ratio test. It finds that the performance of the bootstrap test is very good. The more sophisticated FDB produces a further improvement in cases where the performance of the asymptotic test is very unsatisfactory and the ordinary bootstrap does not work as well as it might. Furthermore, the Monte Carlo simulations provide a number of guidelines on when the bootstrap and FDB tests can be expected to work well. Finally, the tests are applied to US interest rates and international stock prices series. It is found that the asymptotic test tends to overestimate the cointegration rank, while the bootstrap and FDB tests choose the correct cointegration rank.

The Power of Bootstrap Tests of Cointegration Rank with Financial Time Series

Bootstrap likelihood ratio tests of cointegration rank are commonly used because they tend to have rejection probabilities that are closer to the nominal level than the rejection probabilities of the correspond- ing asymptotic tests. The e¤ect of bootstrapping the test on its power is largely unknown. We show that a new computationally inexpensive procedure can be applied to the estimation of the power function of the bootstrap test of cointegration rank. The bootstrap test is found to have a power function close to that of the level-adjusted asymp- totic test. The bootstrap test estimates the level-adjusted power of the asymptotic test highly accurately. The bootstrap test may have low power to reject the null hypothesis of cointegration rank zero, or underestimate the cointegration rank. An empirical application to Euribor interest rates is provided as an illustration of the findings.