Reaalioptioiden ja binomimallm hyväksikäyttö strategisten tutkimus ja tuotekehitysinvestointien arvioimisessa

Tutkielman tavoitteena oli tutkia ja analysoida kirjallisuuden pohjalta reaalioptioteoriaa ja reaalioptioiden arvonmääritystapana binomimallia. Erityisenä painona tutkimuksessa oli reaalioptioiden hyväksikäyttö strategiaan ja tutkimus- ja tuotekehitysinvestointeihin. Tutkielma on toteutettu kirjallisuustutkimuksena. Tutkimusmetodologia on käsiteanalyyttinen. Lähdeaineistona on käytetty ulkomaisia tieteellisen aikakausijulkaisujen artikkeleita ja reaalioptioihin liittyviä kirjoja. Tutkielman tarkoituksena oli keskittyä reaalioptioteorian ja binomimallin ymmärtämiseen, perusteisiin ja käsitteistöön. Reaalioptiot tuovat hankkeiden arvonmääritykseen joustavuuden komponentin. Nykyajan kilpailullisilla markkinoilla on lisääntyvässä määrin epävarmuutta. Epävarmuuden hyödyntäminen on reaalioptioajattelun lähtökohta. Binomimalli on yksi tapa määrittää arvo reaalioptioille ja tähän malliin paneudutaan tutkielmassa syvemmin.

PK-yritysten teknologiahankkeiden arvioiminen reaalioptioajattelun avulla

Tutkielman tavoitteena oli pyrkiä selvittämään kuinka hyvin reaalioptioajattelu soveltuu pienten ja keskisuurten yritysten teknologiahankkeiden arvioimiseen. Tutkimusvälineenä käytettiin reaalioptioajattelun mukaista Star-teknologian arviointilomaketta. Tutkimukseen saatiin mukaan 17 teknologiayrityksen vastaukset, joita sitten arvioitiin kvalitatiivisin ja kvantitatiivisin menetelmin. Teknologiahankkeisiin sisältyy usein suurta teknologista epävarmuutta sekä markkinaepävarmuutta. Reaalioptioajattelu soveltuu erinomaisesti teknologiahankkeiden arvioimiseen, sillä siinä korostetaan joustavuutta ja sen avulla voidaan pyrkiä hallitsemaan epävarmuuksia. Tutkimuksessa esiteltävä Starã-prosessi voi oikein ja huolellisesti käytettynä antaa teknologiahankkeesta uutta ja monipuolista näkökulmaa ja helpottaa näin päätöksentekoa. Uuden informaation avulla hanketta voidaan arvioida ja ohjata tehokkaammin.

Epävarmuuden mallintaminen investointilaskelmissa ja irtautumispäätöksen ajoittaminen: Case Paroc

Tässä diplomityössä on tutkittu epävarmuuden mallintamista investointilaskelmissa. Kirjallisuuden perusteella luotiin prosessimalli, jolla voidaan strukturoidusti tehdä yritysinvestointi- tai yritysirtaantumispäätös. Malli koostuu neljästä päävaiheesta, mutta pääpainopiste mallissa on laskentamenetelmissä. Luotua prosessimallia sekä erityisesti laskentamenetelmiä on sovellettu yritysesimerkin avulla. Epävarmuuden mallintamisongelmaa on käsitelty sekä perinteisten klassillisten investointiteorioiden että reaalioptioajatteluun pohjautuvien menetelmien avulla. Reaalioptioteoriaan perustuvien menetelmien avulla voidaan ottaa huomioon tulevat epävarmuudet ja päätöksentekomahdollisuudet. Perinteisten reaalioptioteorioiden käytännön elämän vastaisten taustaoletuksien vuoksi tutkittiin erityisesti uusimpia malleja. Diplomityössä yritysesimerkiksi valittiin Paroc Group, jonka yritysjärjestelytilannetta tutkittiin sen nykyisen omistajan eli pankin näkökulmasta. Diplomityön yhtenä keskeisenä tavoitteena oli selvittää, että kannattaako pankin myydä yhtiö tämän hetkisellä markkinahinnalla vai odottaa parempaa myyntiajankohtaa.

A quantitative view on fuzzy numbers

Since its introduction, fuzzy set theory has become a useful tool in the mathematical modelling of problems in Operations Research and many other fields. The number of applications is growing continuously. In this thesis we investigate a special type of fuzzy set, namely fuzzy numbers. Fuzzy numbers (which will be considered in the thesis as possibility distributions) have been widely used in quantitative analysis in recent decades. In this work two measures of interactivity are defined for fuzzy numbers, the possibilistic correlation and correlation ratio. We focus on both the theoretical and practical applications of these new indices. The approach is based on the level-sets of the fuzzy numbers and on the concept of the joint distribution of marginal possibility distributions. The measures possess similar properties to the corresponding probabilistic correlation and correlation ratio. The connections to real life decision making problems are emphasized focusing on the financial applications. We extend the definitions of possibilistic mean value, variance, covariance and correlation to quasi fuzzy numbers and prove necessary and sufficient conditions for the finiteness of possibilistic mean value and variance. The connection between the concepts of probabilistic and possibilistic correlation is investigated using an exponential distribution. The use of fuzzy numbers in practical applications is demonstrated by the Fuzzy Pay-Off method. This model for real option valuation is based on findings from earlier real option valuation models. We illustrate the use of number of different types of fuzzy numbers and mean value concepts with the method and provide a real life application.

Pankin reaalioptiot kriisiytyneiden asiakasyrityksien riskienhallinnallisessa lisäluototuksessa

Tämän tutkielman tarkoituksena on ollut tutkia pankin mahdollisuuksia soveltaa reaalioptioajattelua kriisiyrityksien käyttöpääomaan liittyvissä lisäluototusprosesseissa. Kohdepankin rahoitusasiantuntijoita haastattelemalla ja esimerkkitapauksiin tutustumalla tutkia on tutkittu pk-yritysten lisäluototusprosessia ja reaalioptioteorian soveltuvuutta luottoriskinhallintaan. Tutkimuksessa saatiin selville, että pankin luottoprosessin päätöksentekologiikassa on selkeitä yhteneväisyyksiä reaalioptioajattelun kanssa, mutta tietoisesti pankin asiantuntijat eivät sovella reaalioptioteoriaa toimintaansa. Tutkimuksessa havaittiin myös, että tiedostamattoman reaalioptioajattelun hyödyntämisaktiivisuus lisääntyy pankissa sitä mukaa, kun asiakaskohtainen riski kasvaa. Lisäksi kohdepankin asiantuntijat suhtautuivat luottoprosessissa kriisiyrityksille myönnettyihin lisäluottoihin suojautumisoption kaltaisen ajattelumallin tavoin. Toisin sanoen lisäluotto katsottiin asiakasyrityksen toiminnan jatkumisen mahdollistavana tekijänä, jonka avulla pitkän tähtäimen luottoriskin laskeminen on todennäköistä. Reaalioptioteorian tietoinen hyödyntäminen saattaisi tarjota lisätyökaluja asiakasyrityksien skenaarioiden arviointiin ja tukea sitä kautta luottopäätöksen tekemistä ja riskienhallintaa. Reaalioptiot voisivat tuoda joustavuutta ja lisäarvoa sellaisiin tilanteisiin, joissa asiakasyrityksen osalta ei ole olemassa laajaa historiatietoa tai asiakastuntemusta. Reaalioptioiden mahdollistaman joustavuuden sovittaminen säädösten mukaisiin proseduureihin saattaisi olla merkittävä keino pankin prosessin kehittämiseksi ja sisäisen viestinnän tehostamiseksi.

ERP Systems as Investments: Analysing Costs vs. Benefits

An ERP system investment analysis method using a Fuzzy Pay-Off approach for Real Option valuation is examined. It is studied, how the investment can be incrementally adopted and analyzed as a compounding Real Option model. The modeling allows follow-up. IS system development model COCOMO is presented as an example for investment analysis. The thesis presents the usage of Real Options as an alternative for the valuation of an investment. An idea is presented to use a continuous investment follow-up during the investment. This analysis can be performed using Real Options. As a tool for the analysis, the Fuzzy Pay-Off method is presented as an alternative for investment valuation.

Dynamic Analysis Model of Spherical Roller Bearings with Defects

Rolling element bearings are essential components of rotating machinery. The spherical roller bearing (SRB) is one variant seeing increasing use, because it is self-aligning and can support high loads. It is becoming increasingly important to understand how the SRB responds dynamically under a variety of conditions. This doctoral dissertation introduces a computationally efficient, three-degree-of-freedom, SRB model that was developed to predict the transient dynamic behaviors of a rotor-SRB system. In the model, bearing forces and deflections were calculated as a function of contact deformation and bearing geometry parameters according to nonlinear Hertzian contact theory. The results reveal how some of the more important parameters; such as diametral clearance, the number of rollers, and osculation number; influence ultimate bearing performance. Distributed defects, such as the waviness of the inner and outer ring, and localized defects, such as inner and outer ring defects, are taken into consideration in the proposed model. Simulation results were verified with results obtained by applying the formula for the spherical roller bearing radial deflection and the commercial bearing analysis software. Following model verification, a numerical simulation was carried out successfully for a full rotor-bearing system to demonstrate the application of this newly developed SRB model in a typical real world analysis. Accuracy of the model was verified by comparing measured to predicted behaviors for equivalent systems.

Value of Information Logistics Integration in Digital Business Ecosystem

Digital business ecosystems (DBE) are becoming an increasingly popular concept for modelling and building distributed systems in heterogeneous, decentralized and open environments. Information- and communication technology (ICT) enabled business solutions have created an opportunity for automated business relations and transactions. The deployment of ICT in business-to-business (B2B) integration seeks to improve competitiveness by establishing real-time information and offering better information visibility to business ecosystem actors. The products, components and raw material flows in supply chains are traditionally studied in logistics research. In this study, we expand the research to cover the processes parallel to the service and information flows as information logistics integration. In this thesis, we show how better integration and automation of information flows enhance the speed of processes and, thus, provide cost savings and other benefits for organizations. Investments in DBE are intended to add value through business automation and are key decisions in building up information logistics integration. Business solutions that build on automation are important sources of value in networks that promote and support business relations and transactions. Value is created through improved productivity and effectiveness when new, more efficient collaboration methods are discovered and integrated into DBE. Organizations, business networks and collaborations, even with competitors, form DBE in which information logistics integration has a significant role as a value driver. However, traditional economic and computing theories do not focus on digital business ecosystems as a separate form of organization, and they do not provide conceptual frameworks that can be used to explore digital business ecosystems as value drivers—combined internal management and external coordination mechanisms for information logistics integration are not the current practice of a company’s strategic process. In this thesis, we have developed and tested a framework to explore the digital business ecosystems developed and a coordination model for digital business ecosystem integration; moreover, we have analysed the value of information logistics integration. The research is based on a case study and on mixed methods, in which we use the Delphi method and Internetbased tools for idea generation and development. We conducted many interviews with key experts, which we recoded, transcribed and coded to find success factors. Qualitative analyses were based on a Monte Carlo simulation, which sought cost savings, and Real Option Valuation, which sought an optimal investment program for the ecosystem level. This study provides valuable knowledge regarding information logistics integration by utilizing a suitable business process information model for collaboration. An information model is based on the business process scenarios and on detailed transactions for the mapping and automation of product, service and information flows. The research results illustrate the current cap of understanding information logistics integration in a digital business ecosystem. Based on success factors, we were able to illustrate how specific coordination mechanisms related to network management and orchestration could be designed. We also pointed out the potential of information logistics integration in value creation. With the help of global standardization experts, we utilized the design of the core information model for B2B integration. We built this quantitative analysis by using the Monte Carlo-based simulation model and the Real Option Value model. This research covers relevant new research disciplines, such as information logistics integration and digital business ecosystems, in which the current literature needs to be improved. This research was executed by high-level experts and managers responsible for global business network B2B integration. However, the research was dominated by one industry domain, and therefore a more comprehensive exploration should be undertaken to cover a larger population of business sectors. Based on this research, the new quantitative survey could provide new possibilities to examine information logistics integration in digital business ecosystems. The value activities indicate that further studies should continue, especially with regard to the collaboration issues on integration, focusing on a user-centric approach. We should better understand how real-time information supports customer value creation by imbedding the information into the lifetime value of products and services. The aim of this research was to build competitive advantage through B2B integration to support a real-time economy. For practitioners, this research created several tools and concepts to improve value activities, information logistics integration design and management and orchestration models. Based on the results, the companies were able to better understand the formulation of the digital business ecosystem and the importance of joint efforts in collaboration. However, the challenge of incorporating this new knowledge into strategic processes in a multi-stakeholder environment remains. This challenge has been noted, and new projects have been established in pursuit of a real-time economy.

Analyzing the Effects of the New Renewable Energy Policy in Russia on Investments into Wind, Solar and Small Hydro Power

This thesis presents an analysis of recently enacted Russian renewable energy policy based on capacity mechanism. Considering its novelty and poor coverage by academic literature, the aim of the thesis is to analyze capacity mechanism influence on investors’ decision-making process. The current research introduces a number of approaches to investment analysis. Firstly, classical financial model was built with Microsoft Excel® and crisp efficiency indicators such as net present value were determined. Secondly, sensitivity analysis was performed to understand different factors influence on project profitability. Thirdly, Datar-Mathews method was applied that by means of Monte Carlo simulation realized with Matlab Simulink®, disclosed all possible outcomes of investment project and enabled real option thinking. Fourthly, previous analysis was duplicated by fuzzy pay-off method with Microsoft Excel®. Finally, decision-making process under capacity mechanism was illustrated with decision tree. Capacity remuneration paid within 15 years is calculated individually for each RE project as variable annuity that guarantees a particular return on investment adjusted on changes in national interest rates. Analysis results indicate that capacity mechanism creates a real option to invest in renewable energy project by ensuring project profitability regardless of market conditions if project-internal factors are managed properly. The latter includes keeping capital expenditures within set limits, production performance higher than 75% of target indicators, and fulfilling localization requirement, implying producing equipment and services within the country. Occurrence of real option shapes decision-making process in the following way. Initially, investor should define appropriate location for a planned power plant where high production performance can be achieved, and lock in this location in case of competition. After, investor should wait until capital cost limit and localization requirement can be met, after that decision to invest can be made without any risk to project profitability. With respect to technology kind, investment into solar PV power plant is more attractive than into wind or small hydro power, since it has higher weighted net present value and lower standard deviation. However, it does not change decision-making strategy that remains the same for each technology type. Fuzzy pay-method proved its ability to disclose the same patterns of information as Monte Carlo simulation. Being effective in investment analysis under uncertainty and easy in use, it can be recommended as sufficient analytical tool to investors and researchers. Apart from described results, this thesis contributes to the academic literature by detailed description of capacity price calculation for renewable energy that was not available in English before. With respect to methodology novelty, such advanced approaches as Datar-Mathews method and fuzzy pay-off method are applied on the top of investment profitability model that incorporates capacity remuneration calculation as well. Comparison of effects of two different RE supporting schemes, namely Russian capacity mechanism and feed-in premium, contributes to policy comparative studies and exhibits useful inferences for researchers and policymakers. Limitations of this research are simplification of assumptions to country-average level that restricts our ability to analyze renewable energy investment region wise and existing limitation of the studying policy to the wholesale power market that leaves retail markets and remote areas without our attention, taking away medium and small investment into renewable energy from the research focus. Elimination of these limitations would allow creating the full picture of Russian renewable energy investment profile.

Robust real-time tracking for visual surveillance

This paper describes a real-time multi-camera surveillance system that can be applied to a range of application domains. This integrated system is designed to observe crowded scenes and has mechanisms to improve tracking of objects that are in close proximity. The four component modules described in this paper are (i) motion detection using a layered background model, (ii) object tracking based on local appearance, (iii) hierarchical object recognition, and (iv) fused multisensor object tracking using multiple features and geometric constraints. This integrated approach to complex scene tracking is validated against a number of representative real-world scenarios to show that robust, real-time analysis can be performed. Copyright (C) 2007 Hindawi Publishing Corporation. All rights reserved.

Fast adaptive real-time classification for data streams with concept drift

An important application of Big Data Analytics is the real-time analysis of streaming data. Streaming data imposes unique challenges to data mining algorithms, such as concept drifts, the need to analyse the data on the fly due to unbounded data streams and scalable algorithms due to potentially high throughput of data. Real-time classification algorithms that are adaptive to concept drifts and fast exist, however, most approaches are not naturally parallel and are thus limited in their scalability. This paper presents work on the Micro-Cluster Nearest Neighbour (MC-NN) classifier. MC-NN is based on an adaptive statistical data summary based on Micro-Clusters. MC-NN is very fast and adaptive to concept drift whilst maintaining the parallel properties of the base KNN classifier. Also MC-NN is competitive compared with existing data stream classifiers in terms of accuracy and speed.

Avaliação de Projetos de Investimento com Opções Reais: Cálculo de Valor de Opção de Espera de uma Unidade Separadora de Propeno

O tema central deste trabalho é a avaliação do valor da opção real de espera do investimento em uma Unidade Separadora de Propeno, em comparação com uma análise estática de Valor Presente Líquido. Para isso, foi exposta a teoria de opções reais, os processos estocásticos para a estimação das suas principais variáveis de incerteza (preço de produto e insumo), bem como a descrição das ferramentas de simulação a serem utilizadas. Com os instrumentos expostos, pretendemos demonstrar aos responsáveis por projetos de investimento que as incertezas podem ser medidas, levando a maior flexibilidade na tomada de decisões. Os resultados obtidos apontam para o exercício imediato da opção pela abordagem de ativos contingentes e resultados divergentes na análise de ativos contingentes em função do diferencial de preços, em função da taxa de dividendos adotada. A influência dos valores da volatilidade e da taxa de dividendos nos resultados também foi avaliada, levando à conclusão de que o primeiro gera impactos maiores no valor da opção do que o segundo.

Avaliação de projetos de investimento em cogeração de energia utilizando bagaço de cana-de-açúcar em biorrefinarias a partir do uso da teoria das opções reais

O cenário de continuo aumento do consumo de derivados do petróleo aliado a conscientização de que é necessário existir um equilíbrio com relação a exploração de recursos naturais e preservação do meio ambiente, vem impulsionando a busca por fontes alternativas de energia. Esse crescente interesse vem se aplicando a geração de energia a partir de biomassa da cana de açúcar, que vem se tornando cada vez mais comuns no Brasil, porém ainda existe um imenso potencial a ser explorado. Dentro deste contexto, se torna relevante a tomada de decisão de investimentos em projetos de cogeração e este trabalho busca incrementar a analise e tomada de decisão com a utilização da Teoria das Opções Reais, uma ferramenta de agregação de valor às incertezas, cabendo perfeitamente ao modelo energético brasileiro, onde grandes volatilidades do preço de energia são observadas ao longo dos anos. O objetivo do trabalho é determinar o melhor momento para uma biorrefinaria investir em unidades de cogeração. A estrutura do trabalho foi dividida em três cenários de porte de biorrefinarias, as de 2 milhões de capacidade de moagem de cana-de-açúcar por ano, as de 4 milhões e as de 6 milhões, visando assim ter uma representação amostral das biorrefinarias do país. Além disso, analisaram-se três cenários de volatilidade atrelados ao preço futuro de energia, dado que a principal variável de viabilização deste tipo de projeto é o preço de energia. As volatilidades foram calculadas de acordo com histórico do ambiente regulado, o dobro do ambiente regulado e projeção de PLD, representando, respectivamente, níveis baixos, médios e altos, de volatilidade do preço de energia. Após isso, foram elaboradas as nove árvores de decisão, que demonstram para os gestores de investimento que em um cenário de baixa volatilidade cria-se valor estar posicionado e ter a opção real de investir ou adiar investimento para qualquer porte de usina. No cenário de média volatilidade de preço, aconselha-se ao gestor estar posicionado em usinas de médio a grande porte para viabilização do investimento. Por fim, quando o cenário de preços é de grande volatilidade, tem-se um maior risco e existe a maior probabilidade de viabilização do investimento em usinas de grande porte.

Risky business: social media metrics and political risk analysis

A quantificação do risco país – e do risco político em particular – levanta várias dificuldades às empresas, instituições, e investidores. Como os indicadores econômicos são atualizados com muito menos freqüência do que o Facebook, compreender, e mais precisamente, medir – o que está ocorrendo no terreno em tempo real pode constituir um desafio para os analistas de risco político. No entanto, com a crescente disponibilidade de “big data” de ferramentas sociais como o Twitter, agora é o momento oportuno para examinar os tipos de métricas das ferramentas sociais que estão disponíveis e as limitações da sua aplicação para a análise de risco país, especialmente durante episódios de violência política. Utilizando o método qualitativo de pesquisa bibliográfica, este estudo identifica a paisagem atual de dados disponíveis a partir do Twitter, analisa os métodos atuais e potenciais de análise, e discute a sua possível aplicação no campo da análise de risco político. Depois de uma revisão completa do campo até hoje, e tendo em conta os avanços tecnológicos esperados a curto e médio prazo, este estudo conclui que, apesar de obstáculos como o custo de armazenamento de informação, as limitações da análise em tempo real, e o potencial para a manipulação de dados, os benefícios potenciais da aplicação de métricas de ferramentas sociais para o campo da análise de risco político, particularmente para os modelos qualitativos-estruturados e quantitativos, claramente superam os desafios.

Product development process: Using real options for assessments and to support the decision-making at decision gates

Enterprises need continuous product development activities to remain competitive in the marketplace. Their product development process (PDP) must manage stakeholders' needs - technical, financial, legal, and environmental aspects, customer requirements, Corporate strategy, etc. -, being a multidisciplinary and strategic issue. An approach to use real option to support the decision-making process at PDP phases in taken. The real option valuation method is often presented as an alternative to the conventional net present value (NPV) approach. It is based on the same principals of financial options: the right to buy or sell financial values (mostly stocks) at a predetermined price, with no obligation to do so. In PDP, a multi-period approach that takes into account the flexibility of, for instance, being able to postpone prototyping and design decisions, waiting for more information about technologies, customer acceptance, funding, etc. In the present article, the state of the art of real options theory is prospected and a model to use the real options in PDP is proposed, so that financial aspects can be properly considered at each project phase of the product development. Conclusion is that such model can provide more robustness to the decisions processes within PDP.