Statistical analysis of survey-based event history data with application to modeling of unemployment duration

Longitudinal surveys are increasingly used to collect event history data on person-specific processes such as transitions between labour market states. Surveybased event history data pose a number of challenges for statistical analysis. These challenges include survey errors due to sampling, non-response, attrition and measurement. This study deals with non-response, attrition and measurement errors in event history data and the bias caused by them in event history analysis. The study also discusses some choices faced by a researcher using longitudinal survey data for event history analysis and demonstrates their effects. These choices include, whether a design-based or a model-based approach is taken, which subset of data to use and, if a design-based approach is taken, which weights to use. The study takes advantage of the possibility to use combined longitudinal survey register data. The Finnish subset of European Community Household Panel (FI ECHP) survey for waves 1–5 were linked at person-level with longitudinal register data. Unemployment spells were used as study variables of interest. Lastly, a simulation study was conducted in order to assess the statistical properties of the Inverse Probability of Censoring Weighting (IPCW) method in a survey data context. The study shows how combined longitudinal survey register data can be used to analyse and compare the non-response and attrition processes, test the missingness mechanism type and estimate the size of bias due to non-response and attrition. In our empirical analysis, initial non-response turned out to be a more important source of bias than attrition. Reported unemployment spells were subject to seam effects, omissions, and, to a lesser extent, overreporting. The use of proxy interviews tended to cause spell omissions. An often-ignored phenomenon classification error in reported spell outcomes, was also found in the data. Neither the Missing At Random (MAR) assumption about non-response and attrition mechanisms, nor the classical assumptions about measurement errors, turned out to be valid. Both measurement errors in spell durations and spell outcomes were found to cause bias in estimates from event history models. Low measurement accuracy affected the estimates of baseline hazard most. The design-based estimates based on data from respondents to all waves of interest and weighted by the last wave weights displayed the largest bias. Using all the available data, including the spells by attriters until the time of attrition, helped to reduce attrition bias. Lastly, the simulation study showed that the IPCW correction to design weights reduces bias due to dependent censoring in design-based Kaplan-Meier and Cox proportional hazard model estimators. The study discusses implications of the results for survey organisations collecting event history data, researchers using surveys for event history analysis, and researchers who develop methods to correct for non-sampling biases in event history data.

Market integration, return and volatility dynamics; empirical evidence from African stock markets

Frontier and Emerging economies have implemented policies with the objective of liberalizing their equity markets. Equity market liberalization opens the domestic equity market to foreign investors and as well paves the way for domestic investors to invest in foreign equity securities. Among other things, equity market liberalization results in diversification benefits. Moreover, equity market liberalization leads to low cost of equity capital resulting from the lower rate of return by investors. Additionally, foreign and local investors share any potential risks. Liberalized equity markets also become liquid considering that there are more investors to trade. Equity market liberalization results in financial integration which explains the movement of two markets. In crisis period, increased volatility and co-movement between two markets may result in what is termed contagion effects. In Africa, major moves toward financial liberalization generally started in the late 1980s with South Africa as the pioneer. Over the years, researchers have studied the impact of financial liberalization on Africa’s economic development with diverse results; some being positive, others negative and still others being mixed. The objective of this study is to establish whether African stock-markets are integrated into the United States (US) and World market. Furthermore, the study helps to see if there are international linkages between the Africa, US and the world markets. A Bivariate- VAR- GARCH- BEKK model is employed in the study. In the study, the effect of thin trading is removed through series of econometric data purification. This is because thin trading, also known as non-trading or inconsistency of trading, is a main feature of African markets and may trigger inconsistency and biased results. The study confirmed the widely established results that the South Africa and Egypt stock markets are highly integrated with the US and World market. Interestingly, the study adds to knowledge in this research area by establishing the fact that Kenya is very integrated with the US and World markets and that it receives and exports past innovations as well as shocks to and from the US and World market.

Price spike forecasting in a competitive day-ahead energy market

Electricity price forecasting has become an important area of research in the aftermath of the worldwide deregulation of the power industry that launched competitive electricity markets now embracing all market participants including generation and retail companies, transmission network providers, and market managers. Based on the needs of the market, a variety of approaches forecasting day-ahead electricity prices have been proposed over the last decades. However, most of the existing approaches are reasonably effective for normal range prices but disregard price spike events, which are caused by a number of complex factors and occur during periods of market stress. In the early research, price spikes were truncated before application of the forecasting model to reduce the influence of such observations on the estimation of the model parameters; otherwise, a very large forecast error would be generated on price spike occasions. Electricity price spikes, however, are significant for energy market participants to stay competitive in a market. Accurate price spike forecasting is important for generation companies to strategically bid into the market and to optimally manage their assets; for retailer companies, since they cannot pass the spikes onto final customers, and finally, for market managers to provide better management and planning for the energy market. This doctoral thesis aims at deriving a methodology able to accurately predict not only the day-ahead electricity prices within the normal range but also the price spikes. The Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and its structure is studied in detail. It is almost universally agreed in the forecasting literature that no single method is best in every situation. Since the real-world problems are often complex in nature, no single model is able to capture different patterns equally well. Therefore, a hybrid methodology that enhances the modeling capabilities appears to be a possibly productive strategy for practical use when electricity prices are predicted. The price forecasting methodology is proposed through a hybrid model applied to the price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select the optimal input set of the explanatory variables. The numerical studies show that the proposed methodology has more accurate behavior than all other examined methods most recently applied to case studies of energy markets in different countries. The obtained results can be considered as providing extensive and useful information for participants of the day-ahead energy market, who have limited and uncertain information for price prediction to set up an optimal short-term operation portfolio. Although the focus of this work is primarily on the Finnish price area of Nord Pool Spot, given the result of this work, it is very likely that the same methodology will give good results when forecasting the prices on energy markets of other countries.

The Use of Data Envelopment Analysis as Equity Portfolio Selection Criterion in the Finnish Stock Market

This thesis examines the application of data envelopment analysis as an equity portfolio selection criterion in the Finnish stock market during period 2001-2011. A sample of publicly traded firms in the Helsinki Stock Exchange is examined in this thesis. The sample covers the majority of the publicly traded firms in the Helsinki Stock Exchange. Data envelopment analysis is used to determine the efficiency of firms using a set of input and output financial parameters. The set of financial parameters consist of asset utilization, liquidity, capital structure, growth, valuation and profitability measures. The firms are divided into artificial industry categories, because of the industry-specific nature of the input and output parameters. Comparable portfolios are formed inside the industry category according to the efficiency scores given by the DEA and the performance of the portfolios is evaluated with several measures. The empirical evidence of this thesis suggests that with certain limitations, data envelopment analysis can successfully be used as portfolio selection criterion in the Finnish stock market when the portfolios are rebalanced at annual frequency according to the efficiency scores given by the data envelopment analysis. However, when the portfolios were rebalanced every two or three years, the results are mixed and inconclusive.

Interdependence of International Stock Markets, European Government Bond Market and Gold Market

This thesis examines the interdependence of international stock markets (the USA, Europe, Japan, emerging markets, and frontier markets), European government bond market, and gold market during the 21st century. Special focus is on the dynamics of the correlations between the markets, as well as on, spillovers in mean returns and volatility. The mean return spillovers are examined on the basis of the bivariate VAR(1) model, whereas the bivariate BEKK-GARCH(1, 1) model is employed for the analysis of the volatility spillovers. In order to analyze the spillover effects in different market conditions, the full sample period from 2000 to 2013 is divided into the pre-crisis period (2000–2006) and the crisis period (2007–2013). The results indicate an increasing interdependence especially within international stock markets during the periods of financial turbulence, and are thus consistent with the existing literature. Hence, bond and gold markets provide the best diversification benefits for equity investors, particularly during the periods of market turmoil.

[In a Persian market]

Soitinnus: orkesteri.

Export Tire Entry to Chinese Market

After the economic reform, China has undergone fast economic growth, urbanization and adopted the western lifestyle. Global enterprises are investing in China and Finnish companies began to enter the Chinese market after the 1980s. Fast economic growth has downside effects like pollution and thus more cleantech solutions are needed. There are different kinds of entry modes that companies are using when entering the Chinese market. This thesis focuses on export tire entry mode. The purpose of this study is to examine cleantech companies’ opinions about the export tire operations. The background of this study is built by combining the written knowledge about the history of the Chinese industry and market entry modes. The empirical part of the study is a semi-structured, qualitative analysis of five case companies that are operating together in a particular export tire and represent the highest Finnish cleantech knowledge. The results of this study indicate that the export tire entry is an easy and cost effective way to enter new markets or market segment. Export tire is really dependent on the leader who in this particular case succeeded well.

Insiders´ views as a predictor of stock performance : can insider trading be used to predict stock performance on the United States stock market?

This thesis studies the possibility of using information on insiders’ transactions to forecast future stock returns after the implementation of Sarbanes Oxley Act in July 2003. Insider transactions between July 2003 and August 2009 are analysed with regression tests to identify the relationships between insiders’ transactions and future stock returns. This analysis is complemented with rudimentary bootstrapping procedures to verify the robustness of the findings. The underlying assumption of the thesis is that insiders constantly receive pieces of information that indicate future performance of the company. They may not be allowed to trade on large and tangible pieces of information but they can trade on accumulation of smaller, intangible pieces of information. Based on the analysis in the thesis insiders’ profits were found not to differ from the returns from broad stock index. However, their individual transactions were found to be linked to future stock returns. The initial model was found to be unstable but some of the predictive power could be sacrificed to achieve greater stability. Even after sacrificing some predictive power the relationship was significant enough to allow external investors to achieve abnormal profits after transaction costs and taxes. The thesis does not go into great detail about timing of transactions. Delay in publishing insiders’ transactions is not taken into account in the calculations and the closed windows are not studied in detail. The potential effects of these phenomena are looked into and they do not cause great changes in the findings. Additionally the remuneration policy of an insider or a company is not taken into account even though it most likely affects the trading patterns of insiders. Even with the limitations the findings offer promising opportunities for investors to improve their investment processes by incorporating additional information from insiders’ transaction into their decisions. The findings also raise questions on how insider trading should be regulated. Insiders achieve greater returns than other investors based on superior information. On the other hand, more efficient information transfer could warrant more lenient regulation. The fact that insiders’ returns are dominated by the large investment stake they maintain all the time in their own companies also speaks for more leniency. As Sarbanes Oxley Act considerably modified the insider trading landscape, this analysis provides information that has not been available before. The thesis also constitutes a thorough analysis of insider trading phenomenon which has previously been somewhat separated into several studies.

Prediction of market switching and delisting events from OMX First North Nordic multilateral stock exchange

This thesis studies the predictability of market switching and delisting events from OMX First North Nordic multilateral stock exchange by using financial statement information and market information from 2007 to 2012. This study was conducted by using a three stage process. In first stage relevant theoretical framework and initial variable pool were constructed. Then, explanatory analysis of the initial variable pool was done in order to further limit and identify relevant variables. The explanatory analysis was conducted by using self-organizing map methodology. In the third stage, the predictive modeling was carried out with random forests and support vector machine methodologies. It was found that the explanatory analysis was able to identify relevant variables. The results indicate that the market switching and delisting events can be predicted in some extent. The empirical results also support the usability of financial statement and market information in the prediction of market switching and delisting events.

Stock Market reaction to the CSR announcements of American fast food companies

The purpose of this study is to examine whether Corporate Social Responsibility (CSR) announcements of the three biggest American fast food companies (McDonald’s, YUM! Brands and Wendy’s) have any effect on their stock returns as well as on the returns of the industry index (Dow Jones Restaurants and Bars). The time period under consideration starts on 1st of May 2001 and ends on 17th of October 2013. The stock market reaction is tested with an event study utilizing CAPM. The research employs the daily stock returns of the companies, the index and the benchmarks (NASDAQ and NYSE). The test of combined announcements did not reveal any significant effect on the index and McDonald’s. However the stock returns of Wendy’s and YUM! Brands reacted negatively. Moreover, the company level analyses showed that to their own CSR releases McDonald’s stock returns respond positively, YUM! Brands reacts negatively and Wendy’s does not have any reaction. Plus, it was found that the competitors of the announcing company tend to react negatively to all the events. Furthermore, the division of the events into sustainability categories showed statistically significant negative reaction from the Index, McDonald’s and YUM! Brands towards social announcements. At the same time only the index was positively affected by to the economic and environmental CSR news releases.

The Effect of Plant Closures on Market Value: Empirical Evidence from Pulp and Paper Industry 2004-2012

The aim of this study was to research how plant closure announcements affect the market value of the largest pulp and paper industry companies in the world. Also the effect of announcements on competitors was researched and whether the location of plants, timing, reasons for the closures, and characteristics of the closing firms and competitors have an impact on the results. The overall sample included 57 events in the years 2004-2012 and event study was used as a research method. Main theories were signaling theory and spillover effect. According to empirical results, investors consider plant closure announcements as a positive signal for market value. The spillover effect on competitors was, on average, positive and characteristics of the firms and closures had an effect on the results. Furthermore, the market generally predicted the closures and overreacted to them on the announcement day and after it. It is possible for corporate management and investors to learn from the results and use them as support for their decision making.