Do airlines always suffer from crashes?

We examine the impact of aviation disasters on the stock prices of the crash airlines and their rival airlines. Results show that the crash airlines experience deeper negative abnormal returns as the degree of fatality increases. The stock prices of the rival airlines also suffer in large-scale disasters but benefit from the disasters when the fatality is minor.

The relationship between the determinants of rental housing satisfaction and considering moving in Finland

Purpose The purpose of this paper is to discuss the relation between dissatisfaction with housing conditions and considering moving among residents of Finnish rental multifamily buildings. The paper examines physical attributes, socioeconomic factors, and subjective opinions related to housing conditions and satisfaction with housing. Design/methodology/approach Logistic regression analysis is used to examine survey data to analyse which factors contribute to dissatisfaction with the housing unit and the apartment building and whether dissatisfaction is related to consideration of moving. Findings The findings indicate that dissatisfaction with the building and individual housing unit are associated with greater probability of considering moving. Satisfaction with kitchen, living room, storage, and building age are the most important indicators of satisfaction with the housing unit, and satisfaction with living room, bathroom, storage, and building age are associated with satisfaction with the apartment building. These are the areas in which landlords could invest in renovations to increase satisfaction in an attempt to reduce turnover. Research limitations/implications The study is conducted with Finnish data only. The sample is not a representative sample of the Finnish population. A longitudinal study would be needed to determine whether dissatisfied residents indending to move actually change residence. Originality/value This study is the first of its kind in the Finnish housing market. It tests a general model that has been suggested to be customized to local conditions. In addition, much of the research on this topic is more than 20 years old. Examination of the model under current housing and socioeconomic conditions is necessary to determine if relationships have changed over time.

Matkalla suomalaiseksi ja hoiva-alan ammattilaiseksi? : Venäläis- ja virolaistaustaisten naisten ja suomalaisuuden kohtaamiset kuulumista rakentamassa

The research examines the process by which a sense of belonging to Finnish society is constructed among women of Russian and Estonian background who are multiply marginalised in Finnish society. It does so by analysing the encounters between their nationality and 'being Finnis'. Attention is focused on the question of what kind of "journey" they take after moving to Finland, how a sense of belonging is constructed especially along the paths followed in education and at work, and what kind of agency is available to them. The thesis is connected with post-colonial research and also draws from studies on citizenship and nationality as well as the social structures of interaction, when analysing careers. As the educational system forms the most central context of the research, the work is also focused on educational sociology. The research methodology includes life history and a narrative approach. The raw data is from thematic interviews concerning the life experiences of women of immigrant backgrounds. They were studying in Finland to be practical nurses or to complete Bachelor of Social Service degree. According to the study, the women had been encountered as alien, strange, and carrying a shade of "otherness". The experience of inclusion in Finnish communities and society turned out to be conditional, an inclusion based on the notion of a citizen worker, which is defined by national needs. The person from abroad is placed in the position of someone who fills gaps in the services of the welfare state. The choice of education in the care sector and the overall necessity of obtaining Finnish education turned out to be socially directed. Gendered structures of education and working life were found to act as a frame in which the decisions of the immigrant women were made. Although national education policy emphasis as an orientation to global labour markets, the immigrant student is placed above all in the position of an object to be made suitable for the Finnish labour market. Citizenship, a goal of education, requires consent to being "socialised" into Finnish society as well as learning to be Finnish. One s only option to negotiate appearing suitable as a member is to construct oneself into someone who adopts Finnish and Western cultural values, values which favour individuality. However, Finnish education is a resource to Finnishness. Finnish education enables a sense of being Finnish, and empowers the job applicant for example, and in addition to providing cultural, human and social capital strengthen inclusion as well. The study confirms the view that the encounter of an immigrant is still characterised by its colonial nature. It shows that encounters with Finns and Finnish society place the person of immigrant background, even one receiving a Finnish education, in the position of "the other". The journey as an immigrant continues. The immigrant has access only to certain predefined subject positions, which limits agency. When categorised as an immigrant, one becomes a per-son who is different and "other", while the sense of belonging as a member of Finnish society without conditions appears to be somewhat unreachable. Yet, new arrivals are capable of acting change. An immigrant woman can challenge the positions offered to her and present herself as strong. Her life story has often included struggle, and she has the fortitude strength to change her circumstances. Key words: life story, post-colonial encounter, nationality, citizenship, the career of immi-grant, position, agency

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.

Problems and Algorithms for Sequence Segmentations

The analysis of sequential data is required in many diverse areas such as telecommunications, stock market analysis, and bioinformatics. A basic problem related to the analysis of sequential data is the sequence segmentation problem. A sequence segmentation is a partition of the sequence into a number of non-overlapping segments that cover all data points, such that each segment is as homogeneous as possible. This problem can be solved optimally using a standard dynamic programming algorithm. In the first part of the thesis, we present a new approximation algorithm for the sequence segmentation problem. This algorithm has smaller running time than the optimal dynamic programming algorithm, while it has bounded approximation ratio. The basic idea is to divide the input sequence into subsequences, solve the problem optimally in each subsequence, and then appropriately combine the solutions to the subproblems into one final solution. In the second part of the thesis, we study alternative segmentation models that are devised to better fit the data. More specifically, we focus on clustered segmentations and segmentations with rearrangements. While in the standard segmentation of a multidimensional sequence all dimensions share the same segment boundaries, in a clustered segmentation the multidimensional sequence is segmented in such a way that dimensions are allowed to form clusters. Each cluster of dimensions is then segmented separately. We formally define the problem of clustered segmentations and we experimentally show that segmenting sequences using this segmentation model, leads to solutions with smaller error for the same model cost. Segmentation with rearrangements is a novel variation to the segmentation problem: in addition to partitioning the sequence we also seek to apply a limited amount of reordering, so that the overall representation error is minimized. We formulate the problem of segmentation with rearrangements and we show that it is an NP-hard problem to solve or even to approximate. We devise effective algorithms for the proposed problem, combining ideas from dynamic programming and outlier detection algorithms in sequences. In the final part of the thesis, we discuss the problem of aggregating results of segmentation algorithms on the same set of data points. In this case, we are interested in producing a partitioning of the data that agrees as much as possible with the input partitions. We show that this problem can be solved optimally in polynomial time using dynamic programming. Furthermore, we show that not all data points are candidates for segment boundaries in the optimal solution.

The economic consequences of financial reporting on Twitter

The use of social media has spread into many different areas including marketing, customer service, and corporate disclosure. However, our understanding of the timely effect of financial reporting information on Twitter is still limited. In this paper, we propose to examine the timely effect of financial reporting information on Twitter in Australian context, as reflect in the stock market trading. We aim to find out whether the level of information asymmetry within the stock market will be reduced, after the introduction of Twitter and the use of Twitter for financial reporting purpose

The economic consequences of corporate financial reporting on Twitter

The use of social media has spread into many different areas including marketing, customer service, and corporate disclosure. However, our understanding of the timely effect of financial reporting information on Twitter is still limited. In this paper, we examine the timely effect of financial reporting information on Twitter in the Australian context, as reflected in the follow-up stock market reaction. With the use of event methodology and comparative setting, we find that financial reporting disclosure on Twitter reduces the information asymmetry level. This is evidenced by reduction of bid-ask spread and increase of share trading volume. The results of this study imply that financial reporting disclosure on social media assists the dissemination of information and the stock market response to this information

Immigrant Associations in the Metropolitan Area of Finland : Forms of Mobilisation, Participation and Representation

This study examines the role of immigrant associations in the societal and political integration of immigrants into Finnish society. The societal focus is on the ability of immigrant associations to mobilise their ethnic group members to participate in the socio-economic, cultural and political domains of Finnish society and in certain cases even beyond. The political integrative aims are the opportunities of immigrant associations to participate and represent the interests of their ethnic group in local and national policy making. This study focuses on associations in the Metropolitan Area of Finland, (Espoo, Helsinki and Vantaa).The qualitative research consisted of 71 interviews conducted with members of immigrant associations and civil servants. These interviews were mainly semi-structured, including some additional open-ended questions. Additional data consisted of documents, planning reports and of follow-up enquiries. -- In the analysis of the data I categorised thirty-two immigrant associations according to the activity forms and the description of the goals by the members. The four categories consisted of integrative, societal, ethno-cultural and transnational immigrant associations. Most of the immigrant associations belonged to the integrative category (15 of 32 associations). On the one hand the aims of these associations are to provide access for their ethnic group members into Finnish society, while on the other to strengthen the ethnic identity of their members by organising ethno-cultural activities. The societal associations only focused on activities with the objective of including immigrants into the Finnish labour market and educational system. The goal of ethno-cultural associations was to strengthen the ethnic identity of their ethnic group members. The transnational associations aimed at improving the living conditions of women and children in the members' country of origin. The possibilities for immigrant associations to mobilise their members depends partly on external financing. Subsidies have been allocated for societal activities in particular. There remains a risk of the crowding out of ethno-cultural activities: something which has already taken place in several European countries. Immigrant associations aim to strengthen the identity of immigrants mainly by organising social and ethno-cultural activities. Another important target was to provide peer support and therapy courses. Additionally, immigrant women's associations offer assistance to women who have encountered violence by providing counselling and in some cases access to shelter. The data showed that there is an ever growing need to pay heed to the well-being of women, children and elderly immigrants. The participation of immigrant associations in the municipalities' integrative issues takes place mainly through cooperative projects. Until the end of the 1990s there had not been much cooperation. The problem with the projects was that they had mainly been managed by civil servants, whereas members from immigrant associations had remained in a more passive position. Representation of immigrant associations in councils has been fairly weak. Immigrant associations are included in the multicultural councils of Espoo and Vantaa, but only in the planning stages. The municipality of Helsinki does not include immigrant associations due to the large number of organisations which causes problems in finding fair, democratic representation. At the national level, the ‘Advisory Board for Ethnic Relations’ – ETNO didn’t chose its members based on membership of ethnic associations, but based on belongingness to one of the larger language groups spoken by the foreign population in Finland. Since ETNO’s third period (2005-2007), the representatives of immigrant associations and ethnic minority groups have been chosen from proposed candidates. Key words: immigrant associations, integration, mobilisation, participation, representation, the Metropolitan area of Finland, immigrant (women), civil servants

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.

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.

Modelling and Forecasting Property Rents and Returns (summary section only)

Recently, focus of real estate investment has expanded from the building-specific level to the aggregate portfolio level. The portfolio perspective requires investment analysis for real estate which is comparable with that of other asset classes, such as stocks and bonds. Thus, despite its distinctive features, such as heterogeneity, high unit value, illiquidity and the use of valuations to measure performance, real estate should not be considered in isolation. This means that techniques which are widely used for other assets classes can also be applied to real estate. An important part of investment strategies which support decisions on multi-asset portfolios is identifying the fundamentals of movements in property rents and returns, and predicting them on the basis of these fundamentals. The main objective of this thesis is to find the key drivers and the best methods for modelling and forecasting property rents and returns in markets which have experienced structural changes. The Finnish property market, which is a small European market with structural changes and limited property data, is used as a case study. The findings in the thesis show that is it possible to use modern econometric tools for modelling and forecasting property markets. The thesis consists of an introduction part and four essays. Essays 1 and 3 model Helsinki office rents and returns, and assess the suitability of alternative techniques for forecasting these series. Simple time series techniques are able to account for structural changes in the way markets operate, and thus provide the best forecasting tool. Theory-based econometric models, in particular error correction models, which are constrained by long-run information, are better for explaining past movements in rents and returns than for predicting their future movements. Essay 2 proceeds by examining the key drivers of rent movements for several property types in a number of Finnish property markets. The essay shows that commercial rents in local markets can be modelled using national macroeconomic variables and a panel approach. Finally, Essay 4 investigates whether forecasting models can be improved by accounting for asymmetric responses of office returns to the business cycle. The essay finds that the forecast performance of time series models can be improved by introducing asymmetries, and the improvement is sufficient to justify the extra computational time and effort associated with the application of these techniques.

Corporate Governance in China (summary section only)

The negative relationship between economic growth and stock market return is not an anomaly according to evidence documented in many economies. It is argued that future economic growth is largely irrelevant for predicting future equity returns, since long-run equity returns depend mainly on dividend yields and the growth of per share dividends. The economic growth does result in a higher standard of living for consumers, but does not necessarily translate into higher returns for owners of the capital. The divergence in performance between the real sector and stock markets appears to support the above argument. However, this thesis strives to offer an alternative explanation to the apparent divergence within the framework of corporate governance. It argues that weak corporate governance standards in Chinese listed firms exacerbated by poor inventor protection results into a marginalized capital market. Each of the three essays in the thesis addresses one particular aspect of corporate governance on the Chinese stock market in a sequential way through gathering empirical evidence on three distinctive stock market activities. The first essay questions whether significant agency conflicts do exist by building a game on rights issues. It documents significant divergence in interests among shareholders holding different classes of shares. The second essay investigates the level of agency costs by examining value of control through constructing a sample of block transactions. It finds that block transactions that transfer ultimate control entail higher premiums. The third essay looks into possible avenues through which corporate governance standards could be improved by investigating the economic consequences of cross-listing on the Chinese stock market. It finds that, by adopting a higher disclosure standard through cross-listings, firms voluntarily commit themselves to reducing information asymmetry, and consequently command higher valuation than their counterparts.

Inference on Cointegration in Vector Autoregressive Models (summary section only)

In the thesis we consider inference for cointegration in vector autoregressive (VAR) models. The thesis consists of an introduction and four papers. The first paper proposes a new test for cointegration in VAR models that is directly based on the eigenvalues of the least squares (LS) estimate of the autoregressive matrix. In the second paper we compare a small sample correction for the likelihood ratio (LR) test of cointegrating rank and the bootstrap. The simulation experiments show that the bootstrap works very well in practice and dominates the correction factor. The tests are applied to international stock prices data, and the .nite sample performance of the tests are investigated by simulating the data. The third paper studies the demand for money in Sweden 1970—2000 using the I(2) model. In the fourth paper we re-examine the evidence of cointegration between international stock prices. The paper shows that some of the previous empirical results can be explained by the small-sample bias and size distortion of Johansen’s LR tests for cointegration. In all papers we work with two data sets. The first data set is a Swedish money demand data set with observations on the money stock, the consumer price index, gross domestic product (GDP), the short-term interest rate and the long-term interest rate. The data are quarterly and the sample period is 1970(1)—2000(1). The second data set consists of month-end stock market index observations for Finland, France, Germany, Sweden, the United Kingdom and the United States from 1980(1) to 1997(2). Both data sets are typical of the sample sizes encountered in economic data, and the applications illustrate the usefulness of the models and tests discussed in the thesis.

New Evidence on the Properties of the Financial Statement Information Pricing Process

This study contributes to our knowledge of how information contained in financial statements is interpreted and priced by the stock market in two aspects. First, the empirical findings indicate that investors interpret some of the information contained in new financial statements in the context of the information of prior financial statements. Second, two central hypotheses offered in earlier literature to explain the significant connection between publicly available financial statement information and future abnormal returns, that the signals proxy for risk and that the information is priced with a delay, are evaluated utilizing a new methodology. It is found that the mentioned significant connection for some financial statement signals can be explained by that the signals proxy for risk and for other financial statement signals by that the information contained in the signals is priced with a delay.