A Team of Continuous-Action Learning Automata for Noise-Tolerant Learning of Half-Spaces

Learning automata are adaptive decision making devices that are found useful in a variety of machine learning and pattern recognition applications. Although most learning automata methods deal with the case of finitely many actions for the automaton, there are also models of continuous-action-set learning automata (CALA). A team of such CALA can be useful in stochastic optimization problems where one has access only to noise-corrupted values of the objective function. In this paper, we present a novel formulation for noise-tolerant learning of linear classifiers using a CALA team. We consider the general case of nonuniform noise, where the probability that the class label of an example is wrong may be a function of the feature vector of the example. The objective is to learn the underlying separating hyperplane given only such noisy examples. We present an algorithm employing a team of CALA and prove, under some conditions on the class conditional densities, that the algorithm achieves noise-tolerant learning as long as the probability of wrong label for any example is less than 0.5. We also present some empirical results to illustrate the effectiveness of the algorithm.

An extragenic suppressor of prp24-1 defines genetic interaction between PRP24 and PRP21 gene products of Saccharomyces cerevisiae

The temperature-sensitive prp24-1 mutation defines a gene product required for the first step in pre-mRNA splicing. PRP24 is probably a component of the U6 snRNP particle. We have applied genetic reversion analysis to identify proteins that interact with PRP24. Spontaneous revertants of the temperature-sensitive (ts) prp24-1 phenotype were analyzed for those that are due to extragenic suppression. We then extended our analysis to screen for suppressors that confer a distinct conditional phenotype. We have identified a temperature-sensitive extragenic suppressor, which was shown by genetic complementation analysis to be allelic to prp21-1. This suppressor, prp21-2, accumulates pre-mRNA at the non-permissive temperature, a phenotype similar to that of prp21-1. prp21-2 completely suppresses the splicing defect and restores in vivo levels of the U6 snRNA in the prp24-1 strain. Genetic analysis of the suppressor showed that prp21-2 is not a bypass suppressor of prp24-1. The suppression of prp24-1 by prp21-2 is gene specific and also allele specific with respect to both the loci. Genetic interactions with other components of the pre-spliceosome have also been studied. Our results indicate an interaction between PRP21, a component of the U2 snRNP, and PRP24, a component of the U6 snRNP. These results substantiate other data showing U2-U6 snRNA interactions.

Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture

The extent to which low-frequency (minor allele frequency (MAF) between 1-5%) and rare (MAF conditional loss of En1 results in low bone mass, probably as a consequence of high bone turnover. We also identified a novel low-frequency non-coding variant with large effects on BMD near WNT16 (rs148771817(T), MAF = 1.2%, replication effect size = +0.41 s.d., Pmeta = 1 x 10(-11)). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population.

Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

Analyzing information flow in brain networks with nonparametric Granger causality

Multielectrode neurophysiological recording and high-resolution neuroimaging generate multivariate data that are the basis for understanding the patterns of neural interactions. How to extract directions of information flow in brain networks from these data remains a key challenge. Research over the last few years has identified Granger causality as a statistically principled technique to furnish this capability. The estimation of Granger causality currently requires autoregressive modeling of neural data. Here, we propose a nonparametric approach based on widely used Fourier and wavelet transforms to estimate both pairwise and conditional measures of Granger causality, eliminating the need of explicit autoregressive data modeling. We demonstrate the effectiveness of this approach by applying it to synthetic data generated by network models with known connectivity and to local field potentials recorded from monkeys performing a sensorimotor task.

Testing against changing correlation

A test for time-varying correlation is developed within the framework of a dynamic conditional score (DCS) model for both Gaussian and Student t-distributions. The test may be interpreted as a Lagrange multiplier test and modified to allow for the estimation of models for time-varying volatility in the individual series. Unlike standard moment-based tests, the score-based test statistic includes information on the level of correlation under the null hypothesis and local power arguments indicate the benefits of doing so. A simulation study shows that the performance of the score-based test is strong relative to existing tests across a range of data generating processes. An application to the Hong Kong and South Korean equity markets shows that the new test reveals changes in correlation that are not detected by the standard moment-based test.

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.

Hard Custom, Hard Dance : Social Organisation, (Un)Differentiation and Notions of Power in a Tabiteuean Community, Southern Kiribati

Hard Custom, Hard Dance: Social Organisation, (Un)Differentiation and Notions of Power in a Tabiteuean Community, Southern Kiribati is an ethnographic study of a village community. This work analyses social organisation on the island of Tabiteuea in the Micronesian state of Kiribati, examining the intertwining of hierarchical and egalitarian traits, meanwhile bringing a new perspective to scholarly discussions of social differentiation by introducing the concept of undifferentiation to describe non-hierarchical social forms and practices. Particular attention is paid to local ideas concerning symbolic power, abstractly understood as the potency for social reproduction, but also examined in one of its forms; authority understood as the right to speak. The workings of social differentiation and undifferentiation in the village are specifically studied in two contexts connected by local notions of power: the meetinghouse institution (te maneaba) and traditional dancing (te mwaie). This dissertation is based on 11 months of anthropological fieldwork in 1999‒2000 in Kiribati and Fiji, with an emphasis on participant observation and the collection of oral tradition (narratives and songs). The questions are approached through three distinct but interrelated topics: (i) A key narrative of the community ‒ the story of an ancestor without descendants ‒ is presented and discussed, along with other narratives. (ii) The Kiribati meetinghouse institution, te maneaba, is considered in terms of oral tradition as well as present-day practices and customs. (iii) Kiribati dancing (te mwaie) is examined through a discussion of competing dance groups, followed by an extended case study of four dance events. In the course of this work the community of close to four hundred inhabitants is depicted as constructed primarily of clans and households, but also of churches, work co-operatives and dance groups, but also as a significant and valued social unit in itself, and a part of the wider island district. In these partly cross-cutting and overlapping social matrices, people are alternatingly organised by the distinct values and logic of differentiation and undifferentiation. At different levels of social integration and in different modes of social and discursive practice, there are heightened moments of differentiation, followed by active undifferentiation. The central notions concerning power and authority to emerge are, firstly, that in order to be valued and utilised, power needs to be controlled. Secondly, power is not allowed to centralize in the hands of one person or group for any long period of time. Thirdly, out of the permanent reach of people, power/authority is always, on the one hand, left outside the factual community and, on the other, vested in community, the social whole. Several forms of differentiation and undifferentiation emerge, but these appear to be systematically related. Social differentiation building on typically Austronesian complementary differences (such as male:female, elder:younger, autochtonous:allotochtonous) is valued, even if eventually restricted, whereas differentiation based on non-complementary differences (such as monetary wealth or level of education) is generally resisted, and/or is subsumed by the complementary distinctions. The concomitant forms of undifferentiation are likewise hierarchically organised. On the level of the society as a whole, undifferentiation means circumscribing and ultimately withholding social hierarchy. Potential hierarchy is both based on a combination of valued complementary differences between social groups and individuals, but also limited by virtue of the undoing of these differences; for example, in the dissolution of seniority (elder-younger) and gender (male-female) into sameness. Like the suspension of hierarchy, undifferentiation as transformation requires the recognition of pre-existing difference and does not mean devaluing the difference. This form of undifferentiation is ultimately encompassed by the first one, as the processes of the differentiation, whether transformed or not, are always halted. Finally, undifferentiation can mean the prevention of non-complementary differences between social groups or individuals. This form of undifferentiation, like the differentiation it works on, takes place on a lower level of societal ideology, as both the differences and their prevention are always encompassed by the complementary differences and their undoing. It is concluded that Southern Kiribati society be seen as a combination of a severely limited and decentralised hierarchy (differentiation) and of a tightly conditional and contextual (intra-category) equality (undifferentiation), and that it is distinctly characterised by an enduring tension between these contradicting social forms and cultural notions. With reference to the local notion of hardness used to characterise custom on this particular island as well as dance in general, it is argued in this work that in this Tabiteuean community some forms of differentiation are valued though strictly delimited or even undone, whereas other forms of differentiation are a perceived as a threat to community, necessitating pre-emptive imposition of undifferentiation. Power, though sought after and displayed - particularly in dancing - must always remain controlled.

Neighborhood Shopkeepers in Contemporary South Korea: Household, Work, and Locality

This is an ethnographic study of the lived worlds of the keepers of small shops in a residential neighborhood in Seoul, South Korea. It outlines, discusses, and analyses the categories and conceptualizations of South Korean capitalism at the level of households, neighborhoods, and Korean society. These cultural categories were investigated through the neighborhood shopkeepers practices of work and reciprocal interaction as well as through the shopkeepers articulations of their lived experience. In South Korea, the keepers of small businesses have continued to be a large occupational category despite of societal and economic changes, occupying approximately one fourth of the population in active work force. In spite of that, these people, their livelihoods and their cultural and social worlds have rarely been in the focus of social science inquiry. The ethnographic field research for this study was conducted during a 14-month period between November 1998 and December 1999 and in three subsequent short visits to Korea and to the research neighborhood. The fieldwork was conducted during the aftermath of the Asian currency crisis, colloquially termed at the time as the IMF crisis, which highlighted the social and cultural circumstances of small businesskeeper in a specific way. The livelihoods of small-scale entrepreneurs became even more precarious than before; self-employment became an involuntary choice for many middle-class salaried employees who were laid off; and the cultural categories and concepts of society and economy South Korean capitalism were articulated more sharply than before. This study begins with an overview of the contemporary setting, the Korean society under the socially and economically painful outcomes of the economic crisis, and continues with an overview of relevant literature. After introducing the research area and the informants, I discuss the Korean notion of neighborhood, which incorporates both the notions of culturally valued Koreanness and deficiency in the sense of modernity and development. This study further analyses the ways in which the businesskeepers appropriate and reproduce the Korean ideas of men s and women s gender roles and spheres of work. As the appropriation of children s labor is conditional to intergenerational family trajectories which aim not to reproduce parents occupational status but to gain entry to salaried occupations via educational credentials, the work of a married couple is the most common organization of work in small businesses, to which the Korean ideas of family and kin continuity are not applied. While the lack of generational businesskeeping succession suggests that the proprietors mainly subscribe to the notions of familial status that emanate from the practices of the white-collar middle class, the cases of certain women shopkeepers show that their proprietorship and the ensuing economic standing in the family prompts and invites inversed interpretations and uses of common cultural notions of gender. After discussing and analyzing the concept of money and the cultural categorization of leisure and work, topics that emerged as very significant in the lived world of the shopkeepers, this study charts and analyses the categories of identification which the shopkeepers employ for their cultural and social locations and identities. Particular attention is paid to the idea of ordinary people (seomin), which shopkeepers are commonly considered to be most representative of, and which also sums up the ambivalence of neighborhood shopkeepers as a social category: they are not committed to familial reproduction and continuity of the business but aspire non-entrepreneurial careers for their children, while they occupy a significant position in the elaborations of culturally valued notions and ideologies defining Koreanness such as warmheartedness and sociability.

Essays on the Modeling and Prediction of Volatility and Higher Moments of Stock Returns (summary section only)

One of the most fundamental and widely accepted ideas in finance is that investors are compensated through higher returns for taking on non-diversifiable risk. Hence the quantification, modeling and prediction of risk have been, and still are one of the most prolific research areas in financial economics. It was recognized early on that there are predictable patterns in the variance of speculative prices. Later research has shown that there may also be systematic variation in the skewness and kurtosis of financial returns. Lacking in the literature so far, is an out-of-sample forecast evaluation of the potential benefits of these new more complicated models with time-varying higher moments. Such an evaluation is the topic of this dissertation. Essay 1 investigates the forecast performance of the GARCH (1,1) model when estimated with 9 different error distributions on Standard and Poor’s 500 Index Future returns. By utilizing the theory of realized variance to construct an appropriate ex post measure of variance from intra-day data it is shown that allowing for a leptokurtic error distribution leads to significant improvements in variance forecasts compared to using the normal distribution. This result holds for daily, weekly as well as monthly forecast horizons. It is also found that allowing for skewness and time variation in the higher moments of the distribution does not further improve forecasts. In Essay 2, by using 20 years of daily Standard and Poor 500 index returns, it is found that density forecasts are much improved by allowing for constant excess kurtosis but not improved by allowing for skewness. By allowing the kurtosis and skewness to be time varying the density forecasts are not further improved but on the contrary made slightly worse. In Essay 3 a new model incorporating conditional variance, skewness and kurtosis based on the Normal Inverse Gaussian (NIG) distribution is proposed. The new model and two previously used NIG models are evaluated by their Value at Risk (VaR) forecasts on a long series of daily Standard and Poor’s 500 returns. The results show that only the new model produces satisfactory VaR forecasts for both 1% and 5% VaR Taken together the results of the thesis show that kurtosis appears not to exhibit predictable time variation, whereas there is found some predictability in the skewness. However, the dynamic properties of the skewness are not completely captured by any of the models.

Intraday Dynamics of International Equity Markets

The increased availability of high frequency data sets have led to important new insights in understanding of financial markets. The use of high frequency data is interesting and persuasive, since it can reveal new information that cannot be seen in lower data aggregation. This dissertation explores some of the many important issues connected with the use, analysis and application of high frequency data. These include the effects of intraday seasonal, the behaviour of time varying volatility, the information content of various market data, and the issue of inter market linkages utilizing high frequency 5 minute observations from major European and the U.S stock indices, namely DAX30 of Germany, CAC40 of France, SMI of Switzerland, FTSE100 of the UK and SP500 of the U.S. The first essay in the dissertation shows that there are remarkable similarities in the intraday behaviour of conditional volatility across European equity markets. Moreover, the U.S macroeconomic news announcements have significant cross border effect on both, European equity returns and volatilities. The second essay reports substantial intraday return and volatility linkages across European stock indices of the UK and Germany. This relationship appears virtually unchanged by the presence or absence of the U.S stock market. However, the return correlation among the U.K and German markets rises significantly following the U.S stock market opening, which could largely be described as a contemporaneous effect. The third essay sheds light on market microstructure issues in which traders and market makers learn from watching market data, and it is this learning process that leads to price adjustments. This study concludes that trading volume plays an important role in explaining international return and volatility transmissions. The examination concerning asymmetry reveals that the impact of the positive volume changes is larger on foreign stock market volatility than the negative changes. The fourth and the final essay documents number of regularities in the pattern of intraday return volatility, trading volume and bid-ask spreads. This study also reports a contemporaneous and positive relationship between the intraday return volatility, bid ask spread and unexpected trading volume. These results verify the role of trading volume and bid ask quotes as proxies for information arrival in producing contemporaneous and subsequent intraday return volatility. Moreover, asymmetric effect of trading volume on conditional volatility is also confirmed. Overall, this dissertation explores the role of information in explaining the intraday return and volatility dynamics in international stock markets. The process through which the information is incorporated in stock prices is central to all information-based models. The intraday data facilitates the investigation that how information gets incorporated into security prices as a result of the trading behavior of informed and uninformed traders. Thus high frequency data appears critical in enhancing our understanding of intraday behavior of various stock markets’ variables as it has important implications for market participants, regulators and academic researchers.

Modeling and Forecasting Implied Volatility: Implications for Trading, Pricing, and Risk Management

Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.

Modeling Nonlinearities and Asymmetries in Asset Pricing

Financial time series tend to behave in a manner that is not directly drawn from a normal distribution. Asymmetries and nonlinearities are usually seen and these characteristics need to be taken into account. To make forecasts and predictions of future return and risk is rather complicated. The existing models for predicting risk are of help to a certain degree, but the complexity in financial time series data makes it difficult. The introduction of nonlinearities and asymmetries for the purpose of better models and forecasts regarding both mean and variance is supported by the essays in this dissertation. Linear and nonlinear models are consequently introduced in this dissertation. The advantages of nonlinear models are that they can take into account asymmetries. Asymmetric patterns usually mean that large negative returns appear more often than positive returns of the same magnitude. This goes hand in hand with the fact that negative returns are associated with higher risk than in the case where positive returns of the same magnitude are observed. The reason why these models are of high importance lies in the ability to make the best possible estimations and predictions of future returns and for predicting risk.

Perceived Value of Mobile Service Use and its Consequences

The thesis is positioned in the services marketing field. Previous mobile service research has identified perceived value or relative advantage as a stable predictor of use of services. However, a more detailed view of what customers value in mobile services is needed for marketing diverse types of mobile content and attracting committed customers. The direct relationships between multidimensional value and loyalty constructs have received limited attention in the previous literature, although a multidimensional view is needed for differentiating services. This thesis studies how perceived value of mobile service use affects customer commitment, repurchase intentions, word-of-mouth and willingness to pay. The doctoral thesis consists of three journal articles and one working paper. The four papers have different sub-aims and comprise individual empirical studies. Mixed methods including both personal interviews and survey data collected from end-users of different types of mobile content services are used. The conceptual mobile perceived value model that results from the first explorative empirical study supports a six- dimensional value view. The six dimensions are further categorized into two higher order constructs: content-related perceived value (emotional, social, convenience and monetary value) and context-related (epistemic and conditional value) perceived value. Structural equation modeling is used in the other three studies to validate this framework by analyzing the relationships between context- and content-related value, and how the individual perceived value dimensions affect commitment and behavioral outcomes. Analyzing the direct relationships revealed differences in the effect of perceived value dimensions between information and entertainment mobile service user groups, between effects on commitment, repurchase intentions and word-of-mouth intentions, as well as between effects on commitment to the provider and to the mobile channel as such. This thesis contributes to earlier perceived value literature by structuring the value dimensions into two groups. Most importantly, the thesis contributes to the value and loyalty literature by increasing understanding of how the different dimensions of perceived value directly affect commitment and post-purchase intentions. The results have implications for further theory development in the electronic services field using multidimensional latent constructs, and practical implications for enhancing commitment to content provider and for differentiated marketing strategies in the mobile field. The general conclusion of this thesis is that differentiated value-based marketing of mobile services is essential for attracting committed customers who will use the same providers’ content also in the future. Minna Pihlström is associated with the Centre for Relationship Marketing and Service Management (CERS) at Hanken.

An Empirical Comparison of Linear and Nonlinear Volatility Models for Nordic Stock Returns

This paper examines how volatility in financial markets can preferable be modeled. The examination investigates how good the models for the volatility, both linear and nonlinear, are in absorbing skewness and kurtosis. The examination is done on the Nordic stock markets, including Finland, Sweden, Norway and Denmark. Different linear and nonlinear models are applied, and the results indicates that a linear model can almost always be used for modeling the series under investigation, even though nonlinear models performs slightly better in some cases. These results indicate that the markets under study are exposed to asymmetric patterns only to a certain degree. Negative shocks generally have a more prominent effect on the markets, but these effects are not really strong. However, in terms of absorbing skewness and kurtosis, nonlinear models outperform linear ones.