Sähkönmyyntiyhtiön riskienhallinnan kehittäminen

Sähkönmyyntiyhtiön liiketoimintaan liittyy muiden yritysten toiminnan tavoin erilaisia riskejä. Riskit jaetaan operationaalisiin ja markkinariskeihin. Operationaalisia riskejä ovat esimerkiksi erilaiset henkilöstöön, tietojärjestelmiin tai operatiiviseen toimintaan liittyvät riskit. Sähkönmyyntiyhtiön liiketoimintaan kohdistuu myös erilaisia markkinariskejä, joihin tyypillisesti liittyy sekä voiton että tappion mahdollisuus. Sähkönmyyntiyhtiön liiketoimintaan liittyviä markkinariskejä ovat esimerkiksi volyymiriski, profiiliriski, hintariski ja johdannaisriski. Työssä käydään läpi myös muita markkinariskejä sekä pohditaan riskien suojautumiskeinoja. Markkinariskejä voidaan hallita useiden eri keinojen avulla. Tavallisimpia näistä ovat esimerkiksi johdannaisten ja peak- sekä profiilituotteiden hankkiminen, joiden avulla hallitaan markkinahintojen muutosten vaikutuksia liiketoiminnan tulokseen. Lisäksi yritys voi käyttää riskienhallintakeinoina monipuolista jälkilaskentaa sekä raportointia liiketoiminnan keskeisiltä osilta. Erityisesti riskienhallintakeinona käytetään erilaisia riskimittareita, joista Profit at Risk-riskimittarin katsottiin soveltuvan parhaiten sähkönmyyntiyhtiön riskienhallinnan tueksi. Riskienhallinnan kehityksen näkökulmasta yrityksen on syytä miettiä sopimusten hinnoitteluaan sekä suojausstrategiaansa.

Subjectivity in the valuation : Case study on the Finnish biotechnology industry

The thesis combines valuation and behavioral economics literature, which is not common among the Finnish management accounting research. Furthermore, the valuation is studied in biotechnology context and those type of studies are rather rare as well. The thesis studies the valuation in the Finnish biotechnology industry. The concepts of behavioral finance are employed in the empirical part of the study to explore decision-makers’ behavior in valuation processes. The main interest of this study is to explore how subjectivity of a decision-maker affects the valuation in the biotechnology industry. The valuation is studied from two perspectives. First, what is the best valuation model for biotechnology companies suggested by the valuation literature? Second, how the valuation in biotechnology industry is done in practice and how the decision-makers subjectivity affects the valuation? The literature review aims at seeking the best valuation model. The real options were found to be the most suitable valuation model for biotechnology companies, especially in the early stages of product development. The real option’s ability to take the value of the inherent options into account results in theoretically most correct valuations. The only disadvantage is the model’s complexity when compared to other models, such as discounted cash flow models. The empirical part of the study consists of a case study, which examines the valuation practices of the Finnish biotechnology companies. When it comes to the valuation models used in practice, it was found that the companies were using rather simple valuation models, which was due to two reasons. First, the interviewees did not believe in the valuation models and second, they were familiar neither with the most sophisticated models nor with all the theoretical aspects of the models they were using. The material for the study was collected with theme interviews. Four CEO’s of highly successful Finnish biotechnology companies. Strong signs of the decision-makers’ subjectivity in valuation were observed. Most obvious were the signs of framing. Furthermore, herding, excessive optimism, and overconfidence were present. All the behavioral concepts observed most likely have a severe effect on the valuation. As a result, the valuation can easily become overly optimistic, which leads to overvalued investments and to continuation of already unprofitable projects. Framing had the strongest evidence. If the product being valued is framed successfully, the risk of overvaluation is high, thus a strong belief can justify almost any value.

The Pay-Off Method as a Tool for Evaluating the Risk and Profitability of Public Real Estate Investments

Real option valuation, in particular the fuzzy pay-off method, has proven to be useful in defining risk and visualizing imprecision of investments in various industry applications. This study examines whether the evaluation of risk and profitability for public real estate investments can be improved by using real option methodology. Firstly, the context of real option valuation in the real estate industry is examined. Further, an empirical case study is performed on 30 real estate investments of a Finnish government enterprise in order to determine whether the presently used investment analysis system can be complemented by the pay-off method. Despite challenges in the application of the pay-off method to the case company’s large investment base, real option valuation is found to create additional value and facilitate more robust risk analysis in public real estate applications.

Fuzzy real option analysis in patent related decision making and patent valuation

The shift towards a knowledge-based economy has inevitably prompted the evolution of patent exploitation. Nowadays, patent is more than just a prevention tool for a company to block its competitors from developing rival technologies, but lies at the very heart of its strategy for value creation and is therefore strategically exploited for economic pro t and competitive advantage. Along with the evolution of patent exploitation, the demand for reliable and systematic patent valuation has also reached an unprecedented level. However, most of the quantitative approaches in use to assess patent could arguably fall into four categories and they are based solely on the conventional discounted cash flow analysis, whose usability and reliability in the context of patent valuation are greatly limited by five practical issues: the market illiquidity, the poor data availability, discriminatory cash-flow estimations, and its incapability to account for changing risk and managerial flexibility. This dissertation attempts to overcome these impeding barriers by rationalizing the use of two techniques, namely fuzzy set theory (aiming at the first three issues) and real option analysis (aiming at the last two). It commences with an investigation into the nature of the uncertainties inherent in patent cash flow estimation and claims that two levels of uncertainties must be properly accounted for. Further investigation reveals that both levels of uncertainties fall under the categorization of subjective uncertainty, which differs from objective uncertainty originating from inherent randomness in that uncertainties labelled as subjective are highly related to the behavioural aspects of decision making and are usually witnessed whenever human judgement, evaluation or reasoning is crucial to the system under consideration and there exists a lack of complete knowledge on its variables. Having clarified their nature, the application of fuzzy set theory in modelling patent-related uncertain quantities is effortlessly justified. The application of real option analysis to patent valuation is prompted by the fact that both patent application process and the subsequent patent exploitation (or commercialization) are subject to a wide range of decisions at multiple successive stages. In other words, both patent applicants and patentees are faced with a large variety of courses of action as to how their patent applications and granted patents can be managed. Since they have the right to run their projects actively, this flexibility has value and thus must be properly accounted for. Accordingly, an explicit identification of the types of managerial flexibility inherent in patent-related decision making problems and in patent valuation, and a discussion on how they could be interpreted in terms of real options are provided in this dissertation. Additionally, the use of the proposed techniques in practical applications is demonstrated by three fuzzy real option analysis based models. In particular, the pay-of method and the extended fuzzy Black-Scholes model are employed to investigate the profitability of a patent application project for a new process for the preparation of a gypsum-fibre composite and to justify the subsequent patent commercialization decision, respectively; a fuzzy binomial model is designed to reveal the economic potential of a patent licensing opportunity.

Reputational Risk Management as a key element for business continuity and value maximization

This thesis reveals the topic of reputational risk management as a key element for business continuity and value maximization. The purpose of the work is to investigate reputational risk from the side of its definition, management (including legal requirements on this risk category) and measurement and to analyse reputational risk’s impact on business continuity and value maximization. To be able to do this, different respective articles, reports of financial institutions are gathered and constructive summaries and analysis are made. In order to deeply investigate the impact of reputational risk on business continuity and value maximization, it was chosen to study it from three aspects: 1) check the impact of stock valuation of 7 companies that experienced reputational catastrophe / risk, 2) analyse a case study on disagreements in management of reputational risk among case companies and impact on their respective performance, and 3) conduct a survey of financial sector companies in Liechtenstein to see how reputational risk management works in practice. The findings of the research showed a significant impact of reputation decadence on company’s value and trading volume, and showed crucial importance of post-crisis management for the company’s financial performance. The results of the qualitative research based on survey proved that companies consider reputational risk management as a one of the key elements for their business continuity and value maximization.