Defining a framework model to determine total costs of managed desktops using ITIL best practices

In modern day organizations there are an increasing number of IT devices such as computers, mobile phones and printers. These devices can be located and maintained by using specialized IT management applications. Costs related to a single device accumulate from various sources and are normally categorized as direct costs like hardware costs and indirect costs such as labor costs. These costs can be saved in a configuration management database and presented to users using web based development tools such as ASP.NET. The overall costs of IT devices during their lifecycle can be ten times higher than the actual purchase price of the product and ability to define and reduce these costs can save organizations noticeable amount of money. This Master’s Thesis introduces the research field of IT management and defines a custom framework model based on Information Technology Infrastructure Library (ITIL) best practices which is designed to be implemented as part of an existing IT management application for defining and presenting IT costs.

Asymptotic analysis of stock price densities and implied volatilities in mixed stochastic models

In this paper, we obtain sharp asymptotic formulas with error estimates for the Mellin con- volution of functions de ned on (0;1), and use these formulas to characterize the asymptotic behavior of marginal distribution densities of stock price processes in mixed stochastic models. Special examples of mixed models are jump-di usion models and stochastic volatility models with jumps. We apply our general results to the Heston model with double exponential jumps, and make a detailed analysis of the asymptotic behavior of the stock price density, the call option pricing function, and the implied volatility in this model. We also obtain similar results for the Heston model with jumps distributed according to the NIG law.

Commodity Price Driven Risk Management from Viewpoint of High Grade Steel Alloys

The study of price risk management concerning high grade steel alloys and their components was conducted. This study was focused in metal commodities, of which nickel, chrome and molybdenum were in a central role. Also possible hedging instruments and strategies for referred metals were studied. In the literature part main themes are price formation of Ni, Cr and Mo, the functioning of metal exchanges and main hedging instruments for metal commodities. This section also covers how micro and macro variables may affect metal prices from the viewpoint of short as well as longer time period. The experimental part consists of three sections. In the first part, multiple regression model with seven explanatory variables was constructed to describe price behavior of nickel. Results were compared after this with information created with comparable simple regression model. Additionally, long time mean price reversion of nickel was studied. In the second part, theoretical price of CF8M alloy was studied by using nickel, ferro-chrome and ferro-molybdenum as explanatory variables. In the last section, cross hedging possibilities for illiquid FeCr -metal was studied with five LME futures. Also this section covers new information concerning possible forthcoming molybdenum future contracts as well. The results of this study confirm, that linear regression models which are based on the assumption of market rationality, are not able to reliably describe price development of metals at issue. Models fulfilling assumptions for linear regression may though include useful information of statistical significant variables which have effect on metal prices. According to the experimental part, short futures were found to incorporate the most accurate information concerning the price movements in the future. However, not even 3M futures were able to predict turning point in the market before the faced slump. Cross hedging seemed to be very doubtful risk management strategy for illiquid metals, because correlations coefficients were found to be very sensitive for the chosen time span.

Earnings quality and performance in the banking industry: a profit frontier approach

The analysis of efficiency and productivity in banking has received a great deal of attention for almost three decades now. However, most of the literature to date has not explicitly accounted for risk when measuring efficiency. We propose an analysis of profit efficiency taking into account how the inclusion of a variety of bank risk measures might bias efficiency scores. Our measures of risk are partly inspired by the literature on earnings management and earnings quality, keeping in mind that loan loss provisions, as a generally accepted proxy for risk, can be adjusted to manage earnings and regulatory capital. We also consider some variants of traditional models of profit efficiency where different regimes are stipulated so that financial institutions can be evaluated in different dimensions—i.e., prices, quantities, or prices and quantities simultaneously. We perform this analysis on the Spanish banking industry, whose institutions have been deeply affected by the current international financial crisis, and where re-regulation is taking place. Our results can be explored in multiple dimensions but, in general, they indicate that the impact of earnings management on profit efficiency is of less magnitude than what might a priori be expected, and that on the whole, savings banks have performed less well than commercial banks. However, savings banks are adapting to the new regulatory scenario and rapidly catching up with commercial banks, especially in some dimensions of performance.

Governmental Measures to Enhance the Finnish Innovation System to Respond to the Challenge of Mitigating Climate Change

Climate innovations, that cover both technological applications and process and service innovations, play a key role in climate change mitigation. The purpose of this study was to examine how the Finnish innovation system could be enhanced with governmental measures so that the diffusion of climate innovations could be speeded up. During the study, it became evident that the governmental measures need to support the whole innovation chain, which comprises of research, development, demonstration and deployment. Only this can lead to the successful birth and diffusion of low carbon innovations. The study found that the strengths of the Finnish innovation system are research and development, and the current national innovation policies strongly support these activities. However, these have been emphasised at the expense of the demonstration and deployment. Consequently, the biggest bottlenecks in the Finnish innovation landscape are the lack of pilot and demonstration projects and slow commercialisation, thus the high price of the innovation. To meet with the challenge, the government should firstly promote strict greenhouse gas emission reduction targets. This would boost up the innovation activities, which would also lower the prices of the innovations. To speed up the commercialisation process, measures that stimulate the domestic market, such as feed-in-tariffs and public procurements, are needed. Special attention should also be paid to the measures that could shift the traditional closed innovation chain towards open innovation. This means that the product development should involve experts from several fields such as the user and marketing experts to speed up the commercialisation. In addition, efficient innovation co-operation between both private and public sector is essential. Finally, as the domestic resources are not adequate for producing all the innovations needed, the domestic innovation activities should be focused on a few sectors, and at the same time promote efficient import policies.

Earnings Management Shareholders point of view

This paper studies the relationship of earnings management and investors. Analysis of incentives reveals that most of them are opportunistic in nature. Unfortunately the investor would need insider information to distinguish between different forms of earnings management. Investors in some countries seem to devalue earnings when government body has signaled that earnings management might be involved, unfortunately without a clear signal the behavior seems reverse among non-institutional investors.

From Fluid Dynamics to Human Psychology.What Drives Financial Markets Towards Extreme Events

For decades researchers have been trying to build models that would help understand price performance in financial markets and, therefore, to be able to forecast future prices. However, any econometric approaches have notoriously failed in predicting extreme events in markets. At the end of 20th century, market specialists started to admit that the reasons for economy meltdowns may originate as much in rational actions of traders as in human psychology. The latter forces have been described as trading biases, also known as animal spirits. This study aims at expressing in mathematical form some of the basic trading biases as well as the idea of market momentum and, therefore, reconstructing the dynamics of prices in financial markets. It is proposed through a novel family of models originating in population and fluid dynamics, applied to an electricity spot price time series. The main goal of this work is to investigate via numerical solutions how well theequations succeed in reproducing the real market time series properties, especially those that seemingly contradict standard assumptions of neoclassical economic theory, in particular the Efficient Market Hypothesis. The results show that the proposed model is able to generate price realizations that closely reproduce the behaviour and statistics of the original electricity spot price. That is achieved in all price levels, from small and medium-range variations to price spikes. The latter were generated from price dynamics and market momentum, without superimposing jump processes in the model. In the light of the presented results, it seems that the latest assumptions about human psychology and market momentum ruling market dynamics may be true. Therefore, other commodity markets should be analyzed with this model as well.

Earnings management in the process of preparing corporate financial reports

Earnings management (EM) literature examines managers’ use of judgment in financial reporting and in structuring transactions to alter financial reports for a specific reason. Mainstream EM literature strongly concentrates on statistical research methodologies and it is driven by positive accounting theory. Although EM occurs in the process of preparing corporate financial reports, that process has so far largely remained a “black box” in prior literature. The purpose of this study is to analyze what EM is, how and why it unfolds and how it is intertwined in the process of preparing corporate financial reports. In order to meet the needs of the study, a qualitative case study method will be used. The contribution of this study is threefold. First, it indicates that the concept of EM is not as unam-biguous as the prior literature has assumed. I find that EM is socially constructed and more open to interpretation than absolutely dichotomous conception given by previous studies. Second, this study contributes to our knowledge of the role and the importance of actors involved in conducting EM, indicating that EM is much more actor-dependent than the prior literature has assumed. Third, this study broadens our knowledge base with regard to the processes and potential for EM in academic research.

Pricing anomalies in the Finnish stock market

The aim of this thesis is to examine whether the pricing anomalies exists in the Finnish stock markets by comparing the performance of quantile portfolios that are formed on the basis of either individual valuation ratios, composite value measures or combined value and momentum indicators. All the research papers included in the thesis show evidence of value anomalies in the Finnish stock markets. In the first paper, the sample of stocks over the 1991-2006 period is divided into quintile portfolios based on four individual valuation ratios (i.e., E/P, EBITDA/EV, B/P, and S/P) and three hybrids of them (i.e. composite value measures). The results show the superiority of composite value measures as selection criterion for value stocks, particularly when EBITDA/EV is employed as earnings multiple. The main focus of the second paper is on the impact of the holding period length on performance of value strategies. As an extension to the first paper, two more individual ratios (i.e. CF/P and D/P) are included in the comparative analysis. The sample of stocks over 1993- 2008 period is divided into tercile portfolios based on six individual valuation ratios and three hybrids of them. The use of either dividend yield criterion or one of three composite value measures being examined results in best value portfolio performance according to all performance metrics used. Parallel to the findings of many international studies, our results from performance comparisons indicate that for the sample data employed, the yearly reformation of portfolios is not necessarily optimal in order to maximally gain from the value premium. Instead, the value investor may extend his holding period up to 5 years without any decrease in long-term portfolio performance. The same holds also for the results of the third paper that examines the applicability of data envelopment analysis (DEA) method in discriminating the undervalued stocks from overvalued ones. The fourth paper examines the added value of combining price momentum with various value strategies. Taking account of the price momentum improves the performance of value portfolios in most cases. The performance improvement is greatest for value portfolios that are formed on the basis of the 3-composite value measure which consists of D/P, B/P and EBITDA/EV ratios. The risk-adjusted performance can be enhanced further by following 130/30 long-short strategy in which the long position of value winner stocks is leveraged by 30 percentages while simultaneously selling short glamour loser stocks by the same amount. Average return of the long-short position proved to be more than double stock market average coupled with the volatility decrease. The fifth paper offers a new approach to combine value and momentum indicators into a single portfolio-formation criterion using different variants of DEA models. The results throughout the 1994-2010 sample period shows that the top-tercile portfolios outperform both the market portfolio and the corresponding bottom-tercile portfolios. In addition, the middle-tercile portfolios also outperform the comparable bottom-tercile portfolios when DEA models are used as a basis for stock classification criteria. To my knowledge, such strong performance differences have not been reported in earlier peer-reviewed studies that have employed the comparable quantile approach of dividing stocks into portfolios. Consistently with the previous literature, the division of the full sample period into bullish and bearish periods reveals that the top-quantile DEA portfolios lose far less of their value during the bearish conditions than do the corresponding bottom portfolios. The sixth paper extends the sample period employed in the fourth paper by one year (i.e. 1993- 2009) covering also the first years of the recent financial crisis. It contributes to the fourth paper by examining the impact of the stock market conditions on the main results. Consistently with the fifth paper, value portfolios lose much less of their value during bearish conditions than do stocks on average. The inclusion of a momentum criterion somewhat adds value to an investor during bullish conditions, but this added value turns to negative during bearish conditions. During bear market periods some of the value loser portfolios perform even better than their value winner counterparts. Furthermore, the results show that the recent financial crisis has reduced the added value of using combinations of momentum and value indicators as portfolio formation criteria. However, since the stock markets have historically been bullish more often than bearish, the combination of the value and momentum criteria has paid off to the investor despite the fact that its added value during bearish periods is negative, on an average.

The Anchoring Bias of Investors and the 52-Week High Momentum Strategy in the OMX Helsinki Stock Exchange: Psychological Approach to Market Efficiency

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.

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.

Stock Price Reactions on M&A, Dividends and Game Releases. Evidence from Gaming Industry.

A rapidly growing gaming industry, which specializes on PC, console, online and other games, attracts attention of investors and analysts, who try to understand what drives changes of the gaming industry companies’ stock prices. This master thesis shows the evidence that, besides long-established types of events (M&A and dividend payments), the companies’ stock price changes depend on industry-specific events. I analyzed specific for gaming industry events - game releases with respect to its subdivisions: new games-sequels, games ratings and subdivision according to a developer of a game (self-developed by publisher or outsourced). The master thesis analyzes stock prices of 55 companies from gaming industry from all over the world. The research period covers 5 year, spreading from April 2008 to April 2013. Executed with an event study method, results of the research show that all the analyzed events types have significant influence on the stock prices of the gaming industry companies. The current master thesis suggests that acquisitions in the industry affect positively bidders’ and targets’ stock prices. Mergers events cause positive stock price reactions as well. But dividends payments and game releases events influence negatively on the stock prices. Game releases’ effect is up to -2.2% of cumulative average abnormal return (CAAR) drop during the first ten days after the game releases. Having researched different kinds of events and identified the direction of their impact, the current paper can be of high value for investors, seeking profits in the gaming industry, and other interested parties.

Performance Determinants of Renewable Energy Companies

The purpose of this thesis is to identify the Performance Determinants (PD) of Renewable Energy (RE) companies. It analyzes the background of the RE industry while reflecting simultaneous developments in the fossil based industries. I divided the determinants into two groups: market level and firm level and established hypotheses based on the existing literature. Data from public companies was gathered to construct a Panel Data structure. This is then tested by using a Linear Regression with Fixed Effects model. The model specification was efficient at reflecting the analyzed phenomena. My results showed that both market level and firm level determinants are significant in the RE Industry but the firm level determinants had higher explanatory power (R2). The determinants' relationships were found to follow those from the manufacturing industry more than the utilities' industry. Out of the market level determinants Consumer Price Index (CPI), Interest Rates and Oil prices were significant. Out of the firm level determinants Debt to Assets, Net Investments, Cash flows from operations, Sales and Earnings Before Interests and Taxes (EBIT) were significant. I concluded that this information is valuable for key industry players as they can achieve their objectives faster by elaborating better strategies using these results.

Economical potential of controlling charging of electric vehicles by using price signal

The number of electric vehicles grows continuously and the implementation of charging electric vehicles is an important issue for the future. Increasing amount of electric vehicles can cause problems to distribution grid by increasing peak load. Currently charging of electric vehicles is uncontrolled, but as the amount of electric vehicles grows, smart charg-ing (controlled charging) will be one possible solution to handle this situation. In this thesis smart charging of electric vehicles is examined from electricity retailers` point of view. The purpose is to find out plausible saving potentials of smart charging, when it´s controlled by price signal. Saving potential is calculated by comparing costs of price signal controlled charging and uncontrolled charging.

Achieving EU energy targets – Impacts of evolutionary and revolutionary transition paths on power systems

Ambitious energy targets set by EU put pressures to increase share of renewable electricity supply in this and next decades and therefore, some EU member countries have boosted increasing renewable energy generation capacity by implementing subsidy schemes on national level. In this study, two different change approaches to increase renewable energy supply and increase self-sufficiency of supply are assessed with respect to their impacts on power system, electricity market and electricity generation costs in Finland. It is obtained that the current electricity generation costs are high compared to opportunities of earnings from present-day investor’s perspective. In addition, the growth expectations of consumptions and the price forecasts do not stimulate investing in new generation capacity. Revolutionary transition path is driven by administrative and political interventions to achieve the energy targets. Evolutionary transition path is driven by market-based mechanisms, such as market itself and emission trading scheme. It is obtained in this study that in the revolutionary transition path operation of market-based mechanisms is distorted to some extent and it is likely that this path requires providing more public financial resources compared to evolutionary transition path. In the evolutionary transition path the energy targets are not achieved as quickly but market-based mechanisms function better and investment environment endures more stable compared to revolutionary transition path.