927 resultados para market information
Resumo:
In this study we used market settlement prices of European call options on stock index futures to extract implied probability distribution function (PDF). The method used produces a PDF of returns of an underlying asset at expiration date from implied volatility smile. With this method, the assumption of lognormal distribution (Black-Scholes model) is tested. The market view of the asset price dynamics can then be used for various purposes (hedging, speculation). We used the so called smoothing approach for implied PDF extraction presented by Shimko (1993). In our analysis we obtained implied volatility smiles from index futures markets (S&P 500 and DAX indices) and standardized them. The method introduced by Breeden and Litzenberger (1978) was then used on PDF extraction. The results show significant deviations from the assumption of lognormal returns for S&P500 options while DAX options mostly fit the lognormal distribution. A deviant subjective view of PDF can be used to form a strategy as discussed in the last section.
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The main objective of this study is to assess the potential of the information technology industry in the Saint Petersburg area to become one of the new key industries in the Russian economy. To achieve this objective, the study analyzes especially the international competitiveness of the industry and the conditions for clustering. Russia is currently heavily dependent on its natural resources, which are the main source of its recent economic growth. In order to achieve good long-term economic performance, Russia needs diversification in its well-performing industries in addition to the ones operating in the field of natural resources. The Russian government has acknowledged this and started special initiatives to promote such other industries as information technology and nanotechnology. An interesting industry that is basically less than 20 years old and fast growing in Russia, is information technology. Information technology activities and markets are mainly concentrated in Russia’s two biggest cities, Moscow and Saint Petersburg, and areas around them. The information technology industry in the Saint Petersburg area, although smaller than Moscow, is especially dynamic and is gaining increasing foreign company presence. However, the industry is not yet internationally competitive as it lacks substantial and sustainable competitive advantages. The industry is also merely a potential global information technology cluster, as it lacks the competitive edge and a wide supplier and manufacturing base and other related parts of the whole information technology value system. Alone, the industry will not become a key industry in Russia, but it will, on the other hand, have an important supporting role for the development of other industries. The information technology market in the Saint Petersburg area is already large and if more tightly integrated to Moscow, they will together form a huge and still growing market sufficient for most companies operating in Russia currently and in the future. Therefore, the potential of information technology inside Russia is immense.
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Drying is a major step in the manufacturing process in pharmaceutical industries, and the selection of dryer and operating conditions are sometimes a bottleneck. In spite of difficulties, the bottlenecks are taken care of with utmost care due to good manufacturing practices (GMP) and industries' image in the global market. The purpose of this work is to research the use of existing knowledge for the selection of dryer and its operating conditions for drying of pharmaceutical materials with the help of methods like case-based reasoning and decision trees to reduce time and expenditure for research. The work consisted of two major parts as follows: Literature survey on the theories of spray dying, case-based reasoning and decision trees; working part includes data acquisition and testing of the models based on existing and upgraded data. Testing resulted in a combination of two models, case-based reasoning and decision trees, leading to more specific results when compared to conventional methods.
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The paper industry has been experiencing remarkable structural changes since paper demand growth has ceased and some markets are declining. One reason behind the declined demand is the Internet, which has partially substituted the newspaper as a source of information. Paper products alone can no longer provide livelihood, and the paper industry has to find new business areas. In this research, we studied radio frequency identification (RFID), and the market opportunities it could provide for paper industry. The research combined a quantitative industry analysis and qualitative interviews. RFID is a growing industry in the beginning of its life cycle, in which value chains and technologies still evolve significantly. The industry is going to concentrate on the future, and in the long term RFID-identifiers will probably be printed on paper substrate or directly onto products. Paper industry has the chance to enter the RFID industry, but it has to obtain the required competences, for example through acquisitions. The business potential RFID offers to paper industry is inadequate, and while reviewing new strategic options, the paper industry must consider more options, for example the entire printed intelligence.
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Last two decades have seen a rapid change in the global economic and financial situation; the economic conditions in many small and large underdeveloped countries started to improve and they became recognized as emerging markets. This led to growth in the amounts of global investments in these countries, partly spurred by expectations of higher returns, favorable risk-return opportunities, and better diversification alternatives to global investors. This process, however, has not been without problems and it has emphasized the need for more information on these markets. In particular, the liberalization of financial markets around the world, globalization of trade and companies, recent formation of economic and regional blocks, and the rapid development of underdeveloped countries during the last two decades have brought a major challenge to the financial world and researchers alike. This doctoral dissertation studies one of the largest emerging markets, namely Russia. The motivation why the Russian equity market is worth investigating includes, among other factors, its sheer size, rapid and robust economic growth since the turn of the millennium, future prospect for international investors, and a number of important major financial reforms implemented since the early 1990s. Another interesting feature of the Russian economy, which gives motivation to study Russian market, is Russia’s 1998 financial crisis, considered as one of the worst crisis in recent times, affecting both developed and developing economies. Therefore, special attention has been paid to Russia’s 1998 financial crisis throughout this dissertation. This thesis covers the period from the birth of the modern Russian financial markets to the present day, Special attention is given to the international linkage and the 1998 financial crisis. This study first identifies the risks associated with Russian market and then deals with their pricing issues. Finally some insights about portfolio construction within Russian market are presented. The first research paper of this dissertation considers the linkage of the Russian equity market to the world equity market by examining the international transmission of the Russia’s 1998 financial crisis utilizing the GARCH-BEKK model proposed by Engle and Kroner. Empirical results shows evidence of direct linkage between the Russian equity market and the world market both in regards of returns and volatility. However, the weakness of the linkage suggests that the Russian equity market was only partially integrated into the world market, even though the contagion can be clearly seen during the time of the crisis period. The second and the third paper, co-authored with Mika Vaihekoski, investigate whether global, local and currency risks are priced in the Russian stock market from a US investors’ point of view. Furthermore, the dynamics of these sources of risk are studied, i.e., whether the prices of the global and local risk factors are constant or time-varying over time. We utilize the multivariate GARCH-M framework of De Santis and Gérard (1998). Similar to them we find price of global market risk to be time-varying. Currency risk also found to be priced and highly time varying in the Russian market. Moreover, our results suggest that the Russian market is partially segmented and local risk is also priced in the market. The model also implies that the biggest impact on the US market risk premium is coming from the world risk component whereas the Russian risk premium is on average caused mostly by the local and currency components. The purpose of the fourth paper is to look at the relationship between the stock and the bond market of Russia. The objective is to examine whether the correlations between two classes of assets are time varying by using multivariate conditional volatility models. The Constant Conditional Correlation model by Bollerslev (1990), the Dynamic Conditional Correlation model by Engle (2002), and an asymmetric version of the Dynamic Conditional Correlation model by Cappiello et al. (2006) are used in the analysis. The empirical results do not support the assumption of constant conditional correlation and there was clear evidence of time varying correlations between the Russian stocks and bond market and both asset markets exhibit positive asymmetries. The implications of the results in this dissertation are useful for both companies and international investors who are interested in investing in Russia. Our results give useful insights to those involved in minimising or managing financial risk exposures, such as, portfolio managers, international investors, risk analysts and financial researchers. When portfolio managers aim to optimize the risk-return relationship, the results indicate that at least in the case of Russia, one should account for the local market as well as currency risk when calculating the key inputs for the optimization. In addition, the pricing of exchange rate risk implies that exchange rate exposure is partly non-diversifiable and investors are compensated for bearing the risk. Likewise, international transmission of stock market volatility can profoundly influence corporate capital budgeting decisions, investors’ investment decisions, and other business cycle variables. Finally, the weak integration of the Russian market and low correlations between Russian stock and bond market offers good opportunities to the international investors to diversify their portfolios.
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Globalization has increased transport aggregates’ demand. Whilst transport volumes increase, ecological values’im portance has sharpened: carbon footprint has become a measure known world widely. European Union together with other communities emphasizes friendliness to the environment: same trend has extended to transports. As a potential substitute for road transport is noted railway transport, which decreases the congestions and lowers the emission levels. Railway freight market was liberalized in the European Union 2007, which enabled new operators to enter the markets. This research had two main objectives. Firstly, it examined the main market entry strategies utilized and the barriers to entry confronted by the operators who entered the markets after the liberalization. Secondly, the aim was to find ways the governmental organization could enhance its service towards potential railway freight operators. Research is a qualitative case study, utilizing descriptive analytical research method with a normative shade. Empirical data was gathered by interviewing Swedish and Polish railway freight operators by using a semi-structured theme-interview. This research provided novel information by using first-hand data; topic has been researched previously by utilizing second-hand data and literature analyses. Based on this research, rolling stock acquisition, needed investments and bureaucracy generate the main barriers to entry. The research results show that the mostly utilized market entry strategies are start-up and vertical integration. The governmental organization could enhance the market entry process by organizing courses, paying extra attention on flexibility, internal know-how and educating the staff.
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This study investigates the over and underreaction effects in nine emerging stock markets of Europe. Especially, the possible behavioral aspects behind them are an area of interest. These aspects would link them strongly to behavioral finance. Second, our aim is to provide more evidence of the similar or dissimilar behavior in general among these countries. Third, the possibility to gain abnormal returns from these markets is also under investigation. Data from nine emerging stock market indexes in Europe is gathered from January 1, 1998 to January 1, 2008 to find answers to the stated questions. Studies for the over and underreaction effects are done using a variant of the event study methodology which in this case includes two different calculation methods for the expected returns. Studies are performed using 60 day time intervals. The results between the two different methods used are relatively similar concerning the over and underreaction effects. Another of the methods, however, suggests there to be behavioral aspects behind the effects interpreted. On the other hand, the another method does not support this suggestion. However, a conclusion can be made that the factors driving these countries' behavior are related to their geographical location and to the fact that they are emerging countries.
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Fast changing environment sets pressure on firms to share large amount of information with their customers and suppliers. The terms information integration and information sharing are essential for facilitating a smooth flow of information throughout the supply chain, and the terms are used interchangeably in research literature. By integrating and sharing information, firms want to improve their logistics performance. Firms share information with their suppliers and customers by using traditional communication methods (telephone, fax, Email, written and face-to-face contacts) and by using advanced or modern communication methods such as electronic data interchange (EDI), enterprise resource planning (ERP), web-based procurement systems, electronic trading systems and web portals. Adopting new ways of using IT is one important resource for staying competitive on the rapidly changing market (Saeed et al. 2005, 387), and an information system that provides people the information they need for performing their work, will support company performance (Boddy et al. 2005, 26). The purpose of this research has been to test and understand the relationship between information integration with key suppliers and/or customers and a firm’s logistics performance, especially when information technology (IT) and information systems (IS) are used for integrating information. Quantitative and qualitative research methods have been used to perform the research. Special attention has been paid to the scope, level and direction of information integration (Van Donk & van der Vaart 2005a). In addition, the four elements of integration (Jahre & Fabbe-Costes 2008) are closely tied to the frame of reference. The elements are integration of flows, integration of processes and activities, integration of information technologies and systems and integration of actors. The study found that information integration has a low positive relationship to operational performance and a medium positive relationship to strategic performance. The potential performance improvements found in this study vary from efficiency, delivery and quality improvements (operational) to profit, profitability or customer satisfaction improvements (strategic). The results indicate that although information integration has an impact on a firm’s logistics performance, all performance improvements have not been achieved. This study also found that the use of IT and IS have a mediocre positive relationship to information integration. Almost all case companies agreed on that the use of IT and IS could facilitate information integration and improve their logistics performance. The case companies felt that an implementation of a web portal or a data bank would benefit them - enhance their performance and increase information integration.
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Purpose of the study is to evaluate performance of active portfolio management and the effect of stock market trend on the performance. Theory of efficient markets states that market prices reflect all available information and that all investors share a common view of future price developments. This view gives little room for the success of active management, but the theory has been disputed – at least the level of efficiency. Behavioral finance has developed theories that identify irrational behavior patterns of investors. For example, investment decisions are not made independent of past market developments. These findings give reason to believe that also the performance of active portfolio management may depend on market developments. Performance of 16 Finnish equity funds is evaluated during the period of 2005 to 2011. In addition two sub periods are constructed, a bull market period and a bear market period. The sub periods are created by joining together the two bull market phases and the two bear market phases of the whole period. This allows for the comparison of the two different market states. Performance of the funds is measured with risk-adjusted performance by Modigliani and Modigliani (1997), abnormal return over the CAPM by Jensen (1968), and market timing by Henriksson and Merton (1981). The results suggested that in average the funds are not able to outperform the market portfolio. However, the underperformance was found to be lower than the management fees in average which suggests that portfolio managers are able to do successful investment decisions to some extent. The study revealed substantial dependence on the market trend for all of the measures. The risk-adjusted performance measure suggested that in bear markets active portfolio managers in average are able to beat the market portfolio but not in bull markets. Jensen´s alpha and the market timing model also showed striking differences between the two market states. The results of these two measures were, however, somewhat problematic and reliable conclusions about the performance could not be drawn.
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Several papers document idiosyncratic volatility is time-varying and many attempts have been made to reveal whether idiosyncratic risk is priced. This research studies behavior of idiosyncratic volatility around information release dates and also its relation with return after public announcement. The results indicate that when a company discloses specific information to the market, firm’s specific volatility level shifts and short-horizon event-induced volatility vary significantly however, the category to which the announcement belongs is not important in magnitude of change. This event-induced volatility is not small in size and should not be downplayed in event studies. Moreover, this study shows stocks with higher contemporaneous realized idiosyncratic volatility earn lower return after public announcement consistent with “divergence of opinion hypothesis”. While no significant relation is found between EGARCH estimated idiosyncratic volatility and return and also between one-month lagged idiosyncratic volatility and return presumably due to significant jump around public announcement both may provide some signals regarding future idiosyncratic volatility through their correlations with contemporaneous realized idiosyncratic volatility. Finally, the study show that positive relation between return and idiosyncratic volatility based on under-diversification is inadequate to explain all different scenarios and this negative relation after public announcement may provide a useful trading rule.
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The behavioural finance literature expects systematic and significant deviations from efficiency to persist in securities markets due to behavioural and cognitive biases of investors. These behavioural models attempt to explain the coexistence of intermediate-term momentum and long-term reversals in stock returns based on the systematic violations of rational behaviour of investors. The study investigates the anchoring bias of investors and the profitability of the 52-week momentum strategy (GH henceforward). The relatively highly volatile OMX Helsinki stock exchange is a suitable market for examining the momentum effect, since international investors tend to realise their positions first from the furthest security markets by the time of market turbulence. Empirical data is collected from Thomson Reuters Datastream and the OMX Nordic website. The objective of the study is to provide a throughout research by formulating a self-financing GH momentum portfolio. First, the seasonality of the strategy is examined by taking the January effect into account and researching abnormal returns in long-term. The results indicate that the GH strategy is subject to significantly negative revenues in January, but the strategy is not prone to reversals in long-term. Then the predictive proxies of momentum returns are investigated in terms of acquisition prices and 52-week high statistics as anchors. The results show that the acquisition prices do not have explanatory power over the GH strategy’s abnormal returns. Finally, the efficacy of the GH strategy is examined after taking transaction costs into account, finding that the robust abnormal returns remain statistically significant despite the transaction costs. As a conclusion, the relative distance between a stock’s current price and its 52-week high statistic explains the profits of momentum investing to a high degree. The results indicate that intermediateterm momentum and long-term reversals are separate phenomena. This presents a challenge to current behavioural theories, which model these aspects of stock returns as subsequent components of how securities markets respond to relevant information.
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.
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Long-term independent budget travel to countries far away has become increasingly common over the last few decades, and backpacking has now entered the tourism mainstream. Nowadays, backpackers are a very important segment of the global travel market. Backpacking is a type of tourism that involves a lot of information search activities. The Internet has become a major source of information as well as a platform for tourism business transactions. It allows travelers to gain information very effortlessly and to learn about tourist destinations and products directly from other travelers in the form of electronic word-of-mouth (eWOM). Social media has penetrated and changed the backpacker market, as now modern travelers can stay connected to people at home, read online recommendations, and organize and book their trips very independently. In order to create a wider understanding on modern-day backpackers and their information search and share behavior in the Web 2.0 era, this thesis examined contemporary backpackers and their use of social media as an information and communication platform. In order to achieve this goal, three sub-objectives were identified: 1. to describe contemporary backpacker tourism 2. to examine contemporary backpackers’ travel information search and share behavior 3. to explore the impacts of new information and communications technologies and Web 2.0 on backpacker tourism The empirical data was gathered with an online survey, thus the method of analysis was mainly quantitative, and a qualitative method was used for a brief analysis of open questions. The research included both descriptive and analytical approaches, as the goal was to describe modern-day backpackers, and to examine possible interdependencies between information search and share behavior and background variables. The interdependencies were tested for statistical significance with the help of five research hypotheses. The results suggested that backpackers no longer fall under the original backpacker definitions described some decades ago. Now, they are mainly short-term travelers, whose trips resemble more those of mainstream tourists. They use communication technologies very actively, and particularly social media. Traditional information sources, mainly guide books and recommendations from friends, are of great importance to them but also eWOM sources are widely used in travel decision making. The use of each source varies according to the stage of the trip. All in all, Web 2.0 and new ICTs have transformed the backpacker tourism industry in many ways. Although the experience has become less authentic in some travelers’ eyes, the backpacker culture is still recognizable.
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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.
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.