1000 resultados para market liberalization
Resumo:
The European transport market has confronted several changes during the last decade. Due to European Union legislative mandates, the railway freight market was deregulated in 2007. The market followed the trend started by other transport modes as well as other previously regulated industries such as banking, telecommunications and energy. Globally, the first country to deregulate the railway freight market was the United States, with the introduction of the Staggers Rail Act in 1980. Some European countries decided to follow suit already before regulation was mandated; among the forerunners were the United Kingdom, Sweden and Germany. The previous research has concentrated only on these countries, which has provided an interesting research gap for this thesis. The Baltic Sea Region consists of countries with different kinds of liberalization paths, including Sweden and Germany, which have been on the frontline, whereas Lithuania and Finland have only one active railway undertaking, the incumbent. The transport market of the European Union is facing further challenges in the near future, due to the Sulphur Directive, oil dependency and the changing structure of European rail networks. In order to improve the accessibility of this peripheral area, further action is required. This research focuses on topics such as the progression of deregulation, barriers to entry, country-specific features, cooperation and internationalization. Based on the research results, it can be stated that the Baltic Sea Region’s railway freight market is expected to change in the future. Further private railway undertakings are anticipated, and these would change the market structure. The realization of European Union’s plans to increase the improved rail network to cover the Baltic States is strongly hoped for, and railway freight market counterparts inside and among countries are starting to enhance their level of cooperation. The Baltic Sea Region countries have several special national characteristics which influence the market and should be taken into account when companies evaluate possible market entry actions. According to thesis interviews, the Swedish market has a strong level of cooperation in the form of an old-boy network, and is supported by a positive attitude of the incumbent towards the private railway undertakings. This has facilitated the entry process of newcomers, and currently the market has numerous operating railway undertakings. A contrary example was found from Poland, where the incumbent sent old rolling stock to the scrap yard rather than sell it to private railway undertakings. The importance of personal relations is highlighted in Russia, followed by the railway market’s strong political bond with politics. Nonetheless, some barriers to entry are shared by the Baltic Sea Region, the main ones being acquisition of rolling stock, bureaucracy and needed investments. The railway freight market is internationalizing, which is perceived via several alliances as well as the increased number of mergers and acquisitions. After deregulation, markets seem to increase the number of railway undertakings at a rather fast pace, but with the passage of time, the larger operators tend to acquire smaller ones. Therefore, it is expected that in a decade’s time, the number of railway undertakings will start to decrease in the deregulation pioneer countries, while the ones coming from behind might still experience an increase. The Russian market is expected to be totally liberalized, and further alliances between the Russian Railways and European railway undertakings are expected to occur. The Baltic Sea Region’s railway freight market is anticipated to improve, and, based on the interviewees’ comments, attract more cargoes from road to rail.
Resumo:
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.
Resumo:
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.
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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.
Resumo:
Soitinnus: orkesteri.
Resumo:
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.
Resumo:
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.
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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.
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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.
Resumo:
In recent decades, business intelligence (BI) has gained momentum in real-world practice. At the same time, business intelligence has evolved as an important research subject of Information Systems (IS) within the decision support domain. Today’s growing competitive pressure in business has led to increased needs for real-time analytics, i.e., so called real-time BI or operational BI. This is especially true with respect to the electricity production, transmission, distribution, and retail business since the law of physics determines that electricity as a commodity is nearly impossible to be stored economically, and therefore demand-supply needs to be constantly in balance. The current power sector is subject to complex changes, innovation opportunities, and technical and regulatory constraints. These range from low carbon transition, renewable energy sources (RES) development, market design to new technologies (e.g., smart metering, smart grids, electric vehicles, etc.), and new independent power producers (e.g., commercial buildings or households with rooftop solar panel installments, a.k.a. Distributed Generation). Among them, the ongoing deployment of Advanced Metering Infrastructure (AMI) has profound impacts on the electricity retail market. From the view point of BI research, the AMI is enabling real-time or near real-time analytics in the electricity retail business. Following Design Science Research (DSR) paradigm in the IS field, this research presents four aspects of BI for efficient pricing in a competitive electricity retail market: (i) visual data-mining based descriptive analytics, namely electricity consumption profiling, for pricing decision-making support; (ii) real-time BI enterprise architecture for enhancing management’s capacity on real-time decision-making; (iii) prescriptive analytics through agent-based modeling for price-responsive demand simulation; (iv) visual data-mining application for electricity distribution benchmarking. Even though this study is from the perspective of the European electricity industry, particularly focused on Finland and Estonia, the BI approaches investigated can: (i) provide managerial implications to support the utility’s pricing decision-making; (ii) add empirical knowledge to the landscape of BI research; (iii) be transferred to a wide body of practice in the power sector and BI research community.
Resumo:
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.