Comovement of stock price risk in strategic alliance — Case: mobile internet

The focus of this study has been comovement of stock price risk level between two companies as they form strategic alliance. Thus the main reason has been to shed more light to possible increased risk level that the stockholder confronts when a company he owns forms a strategic alliance with another company. This study has centralized to interfirm cooperation between mobile and internet companies, which have furthered the development of mobile internet. The study has been divided into theoretical and empirical part. In theoretical part the main concepts riskiness of a stock (volatility), comovement and strategic alliance have been run through. In empirical part seven strategic alliances formed by mobile internet companies have been examined. Based on this, strategic alliance seems to increase comovement of stock price risk in some degree. This comovement seems to be stronger when core businesses or operating environments of cooperating companies differ more from each other.

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.

Computer-aided discovery of biological activity spectra for anti-aging and anti-cancer olive oil oleuropeins

Aging is associated with common conditions, including cancer, diabetes, cardiovascular disease, and Alzheimer"s disease. The type of multi‐targeted pharmacological approach necessary to address a complex multifaceted disease such as aging might take advantage of pleiotropic natural polyphenols affecting a wide variety of biological processes. We have recently postulated that the secoiridoids oleuropein aglycone (OA) and decarboxymethyl oleuropein aglycone (DOA), two complex polyphenols present in health‐promoting extra virgin olive oil (EVOO), might constitute a new family of plant‐produced gerosuppressant agents. This paper describes an analysis of the biological activity spectra (BAS) of OA and DOA using PASS (Prediction of Activity Spectra for Substances) software. PASS can predict thousands of biological activities, as the BAS of a compound is an intrinsic property that is largely dependent on the compound"s structure and reflects pharmacological effects, physiological and biochemical mechanisms of action, and specific toxicities. Using Pharmaexpert, a tool that analyzes the PASS‐predicted BAS of substances based on thousands of"mechanism‐ effect" and"effect‐mechanism" relationships, we illuminate hypothesis‐generating pharmacological effects, mechanisms of action, and targets that might underlie the anti‐aging/anti‐cancer activities of the gerosuppressant EVOO oleuropeins.

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.

Carboidratos como fonte de compostos para a indústria de química fina

Coal, oil, natural gas, and shale gas are biomass that is formed millions of years ago. These are non-renewable and depleting, even considering the recent discovery of new sources of oil in the presalt and new technologies for the exploitation of shale deposits. Currently, these raw materials are used as a source of energy production and are also important for the production of fine chemicals. Since these materials are finite and their (oil) price is increasing, it is clear that there will be a progressive increase in the chemical industry to use renewable raw materials as a source of energy, an inevitable necessity for humanity. The major challenge for the society in the twenty first century is to unite governments, universities, research centers, and corporations to jointly act in all areas of science with one goal of finding a solution to global problems, such as conversion of biomass into compounds for the fine chemical industry.Non-renewable raw materials are used in the preparation of fuels, chemical intermediates, and derivatives for the fine chemical industry. However, their stock in nature has a finite duration, and their price is high and will likely increase with their depletion. In this scenario, the alternative is to use renewable biomass as a replacement for petrochemicals in the production of fine chemicals. As the production of biomass-based carbohydrates is the most abundant in nature, it is judicious to develop technologies for the generation of chain products (fuels, chemical intermediates, and derivatives for the fine chemicals industry) using this raw material. This paper presents some aspects and opportunities in the area of carbohydrate chemistry toward the generation of compounds for the fine chemical industry.

UCL Discovery: raising the Open Access profile at the institution

Presentation at the "Tutkimus vapaaksi verkkoon!" seminar in Helsinki, January 25, 2011

Luminescence-based assay methods in drug discovery

The drug discovery process is facing new challenges in the evaluation process of the lead compounds as the number of new compounds synthesized is increasing. The potentiality of test compounds is most frequently assayed through the binding of the test compound to the target molecule or receptor, or measuring functional secondary effects caused by the test compound in the target model cells, tissues or organism. Modern homogeneous high-throughput-screening (HTS) assays for purified estrogen receptors (ER) utilize various luminescence based detection methods. Fluorescence polarization (FP) is a standard method for ER ligand binding assay. It was used to demonstrate the performance of two-photon excitation of fluorescence (TPFE) vs. the conventional one-photon excitation method. As result, the TPFE method showed improved dynamics and was found to be comparable with the conventional method. It also held potential for efficient miniaturization. Other luminescence based ER assays utilize energy transfer from a long-lifetime luminescent label e.g. lanthanide chelates (Eu, Tb) to a prompt luminescent label, the signal being read in a time-resolved mode. As an alternative to this method, a new single-label (Eu) time-resolved detection method was developed, based on the quenching of the label by a soluble quencher molecule when displaced from the receptor to the solution phase by an unlabeled competing ligand. The new method was paralleled with the standard FP method. It was shown to yield comparable results with the FP method and found to hold a significantly higher signal-tobackground ratio than FP. Cell-based functional assays for determining the extent of cell surface adhesion molecule (CAM) expression combined with microscopy analysis of the target molecules would provide improved information content, compared to an expression level assay alone. In this work, immune response was simulated by exposing endothelial cells to cytokine stimulation and the resulting increase in the level of adhesion molecule expression was analyzed on fixed cells by means of immunocytochemistry utilizing specific long-lifetime luminophore labeled antibodies against chosen adhesion molecules. Results showed that the method was capable of use in amulti-parametric assay for protein expression levels of several CAMs simultaneously, combined with analysis of the cellular localization of the chosen adhesion molecules through time-resolved luminescence microscopy inspection.

Building Next Generation Consortium Services – part 3: The National Metadata Repository, Discovery Service Finna, and the New Library System

Kristiina Hormia-Poutasen esitys CBUC-konferenssissa Barcelonassa 12.4.2013.

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.

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.

Customer value assessment in business markets

Understanding how firms create, communicate, and deliver value to customers is a key factor when firms seek to differentiate in increasingly competitive and commoditized business markets. As product and price have become less important differentiators in many industries, suppliers are increasingly seeking ways to differentiate themselves based on delivered customer value. Therefore, to gain a holistic understanding on what their offerings are worth to the customer, suppliers need to conduct customer value assessment, which quantifies the impact of a supplier´s offering to customers’ costs and returns. However, from a managerial perspective, customer value assessment is the single most critical challenge for firms in business markets. Consequently, developing holistic frameworks for customer value assessment is seen as one of the most important research priorities for marketing research. The purpose of this study is to explore the process of customer value assessment in business markets. Business markets represent a context where an increasing number of industrial firms are transitioning from basic product offerings towards service-based and solution-oriented hybrid offerings, which emphasize value co-creation and realization in the long term, thus making it difficult to quantify their monetary value. This study employs exploratory and qualitative research design by applying inductive and discovery-oriented grounded theory and multiple case research methods. The empirical data comprise interviews with 61 managers from 12 industrial firms, including seven best practice firms in customer value assessment. The findings of this study show that customer value assessment is essentially a crossfunctional process, which involves several organizational functions. The process begins well before and continues long after the actual delivery, often until the end of a supplier´s offering’s life-cycle. Furthermore, the findings shed light on alternative strategies that firms in business markets can adopt to implement the customer value assessment process. Overall, the findings contribute to customer value research, the sales and organizational management literature, the service marketing and solutions business literature, and suggest several managerial implications on how firms in business markets can adopt a holistic approach to assess value created for customers.