Commodity Future Price Premiums – Case EU ETS

The purpose of this thesis was to study commodity future price premiums and their nature on emission allowance markets. The EUA spot and future contracts traded on the secondary market during EU ETS Phase 2 and Phase 3 were selected for empirical testing. The cointegration of spot and future prices was examined with Johansen cointegration methodology. Daily interest rates with a similar tenor to the future contract maturity were used in the cost-of-carry model to calculate the theoretical future prices and to estimate the deviation from the fair value of future contracts, assumed to be explained by the convenience yield. The time-varying dependence of the convenience yield was studied by regression testing the correlation between convenience yield and the time to maturity of the future contract. The results indicated cointegration between spot and future prices, albeit depending on assumptions on linear trend and intercept in cointegration vector Dec-14 and Dec-15 contracts. The convenience yield correlates positively with the time-to-maturity of the future contract during Phase 2, but negatively during Phase 3. The convenience yield featured positive correlation with spot price volatility and negative correlation with future price volatility during both Phases 2 and 3.

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.

Characteristic Approach to Predicting Analysts’ Forecast Errors in the Finnish Market

Extensive literature shows that analysts’ forecasts and recommendations are often biased. Thus, it is important for the financial market to be able to recognize this bias to be able to correctly valuate public companies. This thesis uses characteristic approach, which was introduced by So (2013, pp. 615-640), to forecast analysts’ forecast errors and tests if predictable forecast error is fully incorporated into share prices. Data is collected of listed Finnish companies. Thesis’ timeframe spans over ten years from 2004 to 2013 consisting of 788 firm-years. Although there is earlier evidence that the characteristic approach is able to predict analysts’ forecast errors, no support for this is found in the Finnish market. This thesis contributes to the current knowledge by showing that the characteristic approach does not work universally as such but requires development to work especially in the smaller markets.

Regime-Switching in the Impact of Oil Price Shocks on Stock Market Volatility: Evidence from Oil-Importing and Oil-Exporting Countries

Research has highlighted the adequacy of Markov regime-switching model to address dynamic behavior in long term stock market movements. Employing a purposed Extended regime-switching GARCH(1,1) model, this thesis further investigates the regime dependent nonlinear relationship between changes in oil price and stock market volatility in Saudi Arabia, Norway and Singapore for the period of 2001-2014. Market selection is prioritized to national dependency on oil export or import, which also rationalizes the fitness of implied bivariate volatility model. Among two regimes identified by the mean model, high stock market return-low volatility regime reflects the stable economic growth periods. The other regime characterized by low stock market return-high volatility coincides with episodes of recession and downturn. Moreover, results of volatility model provide the evidence that shocks in stock markets are less persistent during the high volatility regime. While accelerated oil price rises the stock market volatility during recessions, it reduces the stock market risk during normal growth periods in Singapore. In contrast, oil price showed no significant notable impact on stock market volatility of target oil-exporting countries in either of the volatility regime. In light to these results, international investors and policy makers could benefit the risk management in relation to oil price fluctuation.

Evaluating and improving demand forecast practices for B2B and B2C sectors

Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. Former literature points out that even though many forecasting methods and approaches are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, it’s relatively rare that researches are focused on the differences in forecasting between consumer and industrial companies. The aim of this thesis is to investigate the potential of improving demand forecasting practices for B2B and B2C sectors in the global supply chains. Business to business (B2B) sector produces products for other manufacturing companies. On the other hand, consumer (B2C) sector provides goods for individual buyers. Usually industrial sector have a lower number of customers and closer relationships with them. The research questions of this thesis are: 1) What are the main differences and similarities in demand planning between B2B and B2C sectors? 2) How the forecast performance for industrial and consumer companies can be improved? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from a case company. Evaluation and improving in organizing demand forecasting can be found in three interlinked areas: 1) demand planning operational environment, 2) demand forecasting techniques, 3) demand information sharing scenarios. In this research current B2B and B2C demand practices are presented with further comparison between those two sectors. It was found that B2B and B2C sectors have significant differences in demand practices. This research partly filled the theoretical gap in understanding the difference in forecasting in consumer and industrial sectors. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

Derivative hedging strategies for bitumen price risk

The objective of the study is to extend the existing hedging literature of the commodity price risks by investigating what kind of hedging strategies can be used in companies using bitumen as raw material in their production. Five different alternative swap hedging strategies in bitumen markets are empirically tested. Strategies tested are full hedge strategy, simple, conservative, and aggressive term structure strategies, and implied volatility strategy. The effectiveness of the alternative strategies is measured by excess returns compared to no hedge strategy. In addition, the downside risk of each strategy is measured with target absolute semi-deviation. Results indicate that any of the tested strategies does not outperform the no hedge strategy in terms of excess returns in all maturities. The best-performing aggressive term structure strategy succeeds to create positive excess returns only in short maturities. However, risk seems to increase hand-in-hand with the excess returns so that the best-performing strategies get the highest risk metrics as well. This implicates that the company willing to gain from favorable price movements must be ready to bear a greater risk. Thus, no superior hedging strategy over the others is found.

Keskikokoisen maatilan biokaasu- ja aurinkosähköratkaisujen kannattavuus Etelä-Savossa

Tässä kandidaatintyössä perehdytään biokaasun syntyprosessiin ja sen hyödyntämismahdollisuuksiin, sekä vertaillaan biokaasun tuotannon määrää Suomessa ja Saksassa. Työssä tarkastellaan biokaasuvoimalan kannattavuutta keskikokoisen maatilan yhteydessä Etelä-Savossa ja käydään läpi biokaasuvoimalalle Suomessa myönnettäviä tukimuotoja. Tukimuotojen lisäksi käydään läpi erilaisia lupia ja hyväksyntöjä, joita maatilan yhteyteen rakennettava biokaasu-voimalaitos tarvitsee. Työn toisessa osassa käydään läpi aurinkoenergian hyödyntämismahdollisuuksia, aurinkosähköjärjestelmän komponentteja, sekä perehdytään aurinkopaneelin toimintaperiaatteeseen. Tarkastellaan biokaasuvoimalan lisäksi myös aurinkovoimalan kannattavuutta maatilan yhteydessä ja vertaillaan biokaasu- ja aurinkovoimalan ominaisuuksia keskenään. Lisäksi vertaillaan aurinkosähkön tuotantoa Suomessa ja Saksassa. Työn tavoitteena on selvittää biokaasu- ja aurinkosähkövoimalan kannattavuus esimerkkimaatilalla. Biokaasulaitoksen hinta-arvio saatiin vastauksena tarjouspyyntöön ja aurinkosähköjärjestelmän hinta arvioitiin kotimaisten toimittajien aurinkosähköpakettien hintojen avulla. Biokaasuvoimalan sähköntuottoennuste sekä huolto- ja käyttökustannukset perustuvat kirjallisuudesta saatuihin arvoihin. Aurinkovoimalan sähköntuottoennuste ja paneelien suuntauksen vaikutusta tuotantoon laskettiin PVGIS:n laskurilla sekä HOMER-ohjelmistolla. Kannattavuuslaskelmien perusteella kumpikaan voimalaitostyyppi ei tutkituilla voimalaitosten suuruuksilla ole kannattava 20 tai edes 30 vuoden pitoajalla esimerkkimaatilalla nykyisellä sähkönhinnalla ja tukitasolla. Aurinkosähköjärjestelmälle saadaan kuitenkin 20 vuoden takaisinmaksuaika, jos se hankitaan ilman lainarahaa. Tällöin voidaan ajatella, että laitos on kannattava. Biokaasulaitoksen kannattavuutta parantaisivat tukien ja sähkön hinnan nousun ohella kaasun ja lämmön myyntimahdollisuudet, joita esimerkkimaatilalla ei ole. Aurinkovoimalan kannattavuutta parantaisivat puolestaan tukien ja korkeamman sähkön hinnan lisäksi paremmin paneelien tuotantoa seuraava kulutus, jolloin pienempi osuus sähköstä päätyisi myyntiin.