Promoting Cleantech in Emerging Markets: Business Model for Waste Pre-treatment Equipment in China

Waste incineration is becoming increasingly widespread method of waste disposal in China. Incineration plants mostly use grate and circular fluidized bed (CFB) technology. Waste combustion in cement production is also beginning to gradually increase. However, Chinese waste composition is causing problems for the energy utilization. Mechanical waste pre-treatment optimizes the combustion process and facilitates the energy recovery. The objective of this study is to identify how Western waste pre-treatment manufacturer could operate in Chinese markets. Chinese waste management industry is reviewed via PESTEL analysis. The current state and future predictions of grate and CFB incineration as well as cement manufacturing are monitored. Grate combustion, which requires lesser waste pre-treatment, is becoming more common at the expense of CFB incineration in China. The most promising future for waste treatment is in cement production industry. Waste treatment equipment manufacturer should try to create pilot projects with biggest cement producers with a view of growing co-operation in the future.

Do retail investors use technical analysis? Evidence from Stuttgart stock exchange.

Tutkielma käyttää automaattista kuviontunnistusalgoritmia ja yleisiä kahden liukuvan keskiarvon leikkauspiste –sääntöjä selittääkseen Stuttgartin pörssissä toimivien yksityissijoittajien myynti-osto –epätasapainoa ja siten vastatakseen kysymykseen ”käyttävätkö yksityissijoittajat teknisen analyysin menetelmiä kaupankäyntipäätöstensä perustana?” Perusolettama sijoittajien käyttäytymisestä ja teknisen analyysin tuottavuudesta tehtyjen tutkimusten perusteella oli, että yksityissijoittajat käyttäisivät teknisen analyysin metodeja. Empiirinen tutkimus, jonka aineistona on DAX30 yhtiöiden data vuosilta 2009 – 2013, ei tuottanut riittävän selkeää vastausta tutkimuskysymykseen. Heikko todistusaineisto näyttää kuitenkin osoittavan, että yksityissijoittajat muuttavat kaupankäyntikäyttäytymistänsä eräiden kuvioiden ja leikkauspistesääntöjen ohjastamaan suuntaan.

Forecasting financial weather - can we foresee market sentiment? Spectrum of stock price behavior - NYSE case study

The desire to create a statistical or mathematical model, which would allow predicting the future changes in stock prices, was born many years ago. Economists and mathematicians are trying to solve this task by applying statistical analysis and physical laws, but there are still no satisfactory results. The main reason for this is that a stock exchange is a non-stationary, unstable and complex system, which is influenced by many factors. In this thesis the New York Stock Exchange was considered as the system to be explored. A topological analysis, basic statistical tools and singular value decomposition were conducted for understanding the behavior of the market. Two methods for normalization of initial daily closure prices by Dow Jones and S&P500 were introduced and applied for further analysis. As a result, some unexpected features were identified, such as a shape of distribution of correlation matrix, a bulk of which is shifted to the right hand side with respect to zero. Also non-ergodicity of NYSE was confirmed graphically. It was shown, that singular vectors differ from each other by a constant factor. There are for certain results no clear conclusions from this work, but it creates a good basis for the further analysis of market topology.

Suomessa ja Itävallassa toimivien liiketoimintamallien siirrettävyys puupohjaisen uusiutuvan energian tuotantoon Puolaan, Romaniaan ja Slovakiaan

Tutkimus kuvaa tiedon, osaamisen ja teknologian siirtoa Suomesta ja Itävallasta Puolaan, Romaniaan ja Slovakiaan hajautetussa puupohjaisessa sähkö- ja lämpöenergian tuotannossa. Metsävaroiltaan rikas ja bioenergia-asioissa toimintatavoiltaan edistynyt Suomi toimi Metsäntutkimuslaitoksen (nykyisin Luonnonvarakeskus) johdolla tutkimuksen empiirisen aineiston tuottaneen kehittäjäverkostohankkeen pääkoordinaattorina vuosina 2011-2014. Tutkimusmenetelmänä käytettiin hankkeen dokumentaation sisällönanalyysiä. Itävalta on tunnettu edistyksellisistä bioenergia-alan tuki- ja ohjausjärjestelmistä. Suomi ja Itävalta kuuluvat EU:n viiden edistyneimmän maan joukkoon uusiutuvien energialähteiden hyödyntämisessä. Tämän työn tavoitteena oli selvittää, miten Suomessa ja Itävallassa hyvin toimivia liiketoimintamalleja voidaan siirtää kohdemaihin puupohjaisen uusiutuvan energian tuotannossa hyödynnettäviksi. Työssä kuvataan tiedonsiirtäjämaiden eli Suomen ja Itävallan ydinosaaminen kiinteän biomassan energiantuotannossa politiikkatasolta käytännön liiketoiminnan tasolle. Lisäksi työssä analysoidaan poliittisen ohjauksen merkitystä alan kehittämisessä, missä käydään läpi maakohtaiset uusiutuvan energian toimintasuunnitelmat vuodelta 2010. Lopuksi arvioidaan tiedonsiirtäjä- ja tiedonhyödyntäjämaiden välisiä eroavaisuuksia kyseisellä liiketoiminta-alueella, ja onko olemassa sellaisia tekijöitä, mitkä estävät tiedonsiirtoa tai hyväksi todettujen liiketoimintamallien soveltamista kohdemaissa. Kussakin maassa metsänomistusolosuhteet ratkaisevat kiinteän biomassan tarjonnan toimivuuden eli tilanteen toimitusketjun alkupäässä. Tuotannon ohjauksen pyrkimys on myös hyödyntää mekaanisen puunjalostuksen sivutuotevirrat mahdollisimman tarkoin energiantuotannon tarpeisiin. Yleiset taloudelliset suhdanteet vaikuttavat ketjun toimivuuteen ja tehokkuuteen. Yksin energiantuotannon tarpeisiin puunkorjuuta ei kannata suunnitella, koska se harvemmin erikseen toteutettuna on kannattavaa liiketoimintaa. Puun käyttö energiantuotantoon tarvitsee hyvin suunniteltua tuki- ja ohjausjärjestelmää, joista kansalliset hallitukset vastaavat. Suomalainen tuotannon suunnittelun ja ohjauksen ajattelutapa sekä itävaltalainen energiapuun varastointi biomassan logistiikkakeskuksiin koettiin kohdemaiden yrittäjäkunnassa varteenotettavimpina liiketoiminnan kehittämisvaihtoehtoina paikallisissa toimintaympäristöissä. Lean-tuotantoajatteluun kuuluva hukan poistaminen toimitusketjusta liittyy mm. varastonhallinnan järjestelyihin ja sivutuotevirtojen hyödyntämiseen. Näitä piirteitä oli myös löydettävissä tiedonhyödyntäjämaiden yritysten toiminnassa hankkeen toteutuksen aikana.

Cross-border transmission capacity development – Experiences from the Nordic electricity markets

The liberalisation of the wholesale electricity markets has been considered an efficient way to organise the markets. In Europe, the target is to liberalise and integrate the common European electricity markets. However, insufficient transmission capacity between the market areas hampers the integration, and therefore, new investments are required. Again, massive transmission capacity investments are not usually easy to carry through. This doctoral dissertation aims at elaborating on critical determinants required to deliver the necessary transmission capacity investments. The Nordic electricity market is used as an illustrative example. This study suggests that changes in the governance structure have affected the delivery of Nordic cross-border investments. In addition, the impacts of not fully delivered investments are studied in this doctoral dissertation. An insufficient transmission network can degrade the market uniformity and may also cause a need to split the market into smaller submarkets. This may have financial impacts on market actors when the targeted efficient sharing of resources is not met and even encourage gaming. The research methods applied in this doctoral dissertation are mainly empirical ranging from a Delphi study to case studies and numerical calculations.

E-commerce value chain in Russian markets – The role of market specific factors

International e-commerce is still rather new concept and therefore lacks comprehensive research. Different nature of markets and companies has challenged the traditional theories as well as redefined traditional operations. Prior research has mainly concentrated on studying the specific topics as barriers and the choice of international strategy. For this reason, there is a lack of research that comprehensively analyzes the operations of international e-commerce companies. The aim of this study was to increase knowledge on operations of Finnish e-commerce companies in Russia. In order to receive comprehensive knowledge of the operations, research analyzed the internationalization process, the effects of market specific factors to e-commerce and the implementation of various value chain activities of e-commerce. Research focused on examining how companies have seen the peculiarities of Russian markets and how to respond to them. The empiric part of the study was conducted as a qualitative research by interviewing five company representatives and three specialists of international e-commerce and Russian business.The results of this research revealed that having e-commerce in Russia is challenging and requires long term, strategy-based work. E-commerce is assumed to be inherently global business model, but in the case of Russia, numerous e-commerce activities require localization. The most crucial activity to localize is a content and language of content. Even though e-commerce market in Russia has a lot of peculiarities, operating via marketspace decreases the level of bureaucracy and market risk. Despite the challenges, developing e- commerce market in Russia offers a huge potential for companies, whose international strategy needs Russian operation to achieve company goals.

Market anomalies and tactical asset allocation: Utilising market anomalies in multiple asset class portfolios with the Black−Litterman model

This thesis discusses the basic problem of the modern portfolio theory about how to optimise the perfect allocation for an investment portfolio. The theory provides a solution for an efficient portfolio, which minimises the risk of the portfolio with respect to the expected return. A central feature for all the portfolios on the efficient frontier is that the investor needs to provide the expected return for each asset. Market anomalies are persistent patterns seen in the financial markets, which cannot be explained with the current asset pricing theory. The goal of this thesis is to study whether these anomalies can be observed among different asset classes. Finally, if persistent patterns are found, it is investigated whether the anomalies hold valuable information for determining the expected returns used in the portfolio optimization Market anomalies and investment strategies based on them are studied with a rolling estimation window, where the return for the following period is always based on historical information. This is also crucial when rebalancing the portfolio. The anomalies investigated within this thesis are value, momentum, reversal, and idiosyncratic volatility. The research data includes price series of country level stock indices, government bonds, currencies, and commodities. The modern portfolio theory and the views given by the anomalies are combined by utilising the Black-Litterman model. This makes it possible to optimise the portfolio so that investor’s views are taken into account. When constructing the portfolios, the goal is to maximise the Sharpe ratio. Significance of the results is studied by assessing if the strategy yields excess returns in a relation to those explained by the threefactormodel. The most outstanding finding is that anomaly based factors include valuable information to enhance efficient portfolio diversification. When the highest Sharpe ratios for each asset class are picked from the test factors and applied to the Black−Litterman model, the final portfolio results in superior riskreturn combination. The highest Sharpe ratios are provided by momentum strategy for stocks and long-term reversal for the rest of the asset classes. Additionally, a strategy based on the value effect was highly appealing, and it basically performs as well as the previously mentioned Sharpe strategy. When studying the anomalies, it is found, that 12-month momentum is the strongest effect, especially for stock indices. In addition, a high idiosyncratic volatility seems to be positively correlated with country indices on stocks.

The Forecast Performance of Model-Free Implied Volatility: Evidence from DAX Index Options

Volatility has a central role in various theoretical and practical applications in financial markets. These include the applications related to portfolio theory, derivatives pricing and financial risk management. Both theoretical and practical applications require good estimates and forecasts for the asset return volatility. The goal of this study is to examine the forecast performance of one of the more recent volatility measures, model-free implied volatility. Model-free implied volatility is extracted from the prices in the option markets, and it aims to provide an unbiased estimate for the market’s expectation on the future level of volatility. Since it is extracted from the option prices, model-free implied volatility should contain all the relevant information that the market participants have. Moreover, model-free implied volatility requires less restrictive assumptions than the commonly used Black-Scholes implied volatility, which means that it should be less biased estimate for the market’s expectations. Therefore, it should also be a better forecast for the future volatility. The forecast performance of model-free implied volatility is evaluated by comparing it to the forecast performance of Black-Scholes implied volatility and GARCH(1,1) forecast. Weekly forecasts for six years period were calculated for the forecasted variable, German stock market index DAX. The data consisted of price observations for DAX index options. The forecast performance was measured using econometric methods, which aimed to capture the biasedness, accuracy and the information content of the forecasts. The results of the study suggest that the forecast performance of model-free implied volatility is superior to forecast performance of GARCH(1,1) forecast. However, the results also suggest that the forecast performance of model-free implied volatility is not as good as the forecast performance of Black-Scholes implied volatility, which is against the hypotheses based on theory. The results of this study are consistent with the majority of prior research on the subject.