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.

The Use of Data Envelopment Analysis as Equity Portfolio Selection Criterion in the Finnish Stock Market

This thesis examines the application of data envelopment analysis as an equity portfolio selection criterion in the Finnish stock market during period 2001-2011. A sample of publicly traded firms in the Helsinki Stock Exchange is examined in this thesis. The sample covers the majority of the publicly traded firms in the Helsinki Stock Exchange. Data envelopment analysis is used to determine the efficiency of firms using a set of input and output financial parameters. The set of financial parameters consist of asset utilization, liquidity, capital structure, growth, valuation and profitability measures. The firms are divided into artificial industry categories, because of the industry-specific nature of the input and output parameters. Comparable portfolios are formed inside the industry category according to the efficiency scores given by the DEA and the performance of the portfolios is evaluated with several measures. The empirical evidence of this thesis suggests that with certain limitations, data envelopment analysis can successfully be used as portfolio selection criterion in the Finnish stock market when the portfolios are rebalanced at annual frequency according to the efficiency scores given by the data envelopment analysis. However, when the portfolios were rebalanced every two or three years, the results are mixed and inconclusive.

Interdependence of International Stock Markets, European Government Bond Market and Gold Market

This thesis examines the interdependence of international stock markets (the USA, Europe, Japan, emerging markets, and frontier markets), European government bond market, and gold market during the 21st century. Special focus is on the dynamics of the correlations between the markets, as well as on, spillovers in mean returns and volatility. The mean return spillovers are examined on the basis of the bivariate VAR(1) model, whereas the bivariate BEKK-GARCH(1, 1) model is employed for the analysis of the volatility spillovers. In order to analyze the spillover effects in different market conditions, the full sample period from 2000 to 2013 is divided into the pre-crisis period (2000–2006) and the crisis period (2007–2013). The results indicate an increasing interdependence especially within international stock markets during the periods of financial turbulence, and are thus consistent with the existing literature. Hence, bond and gold markets provide the best diversification benefits for equity investors, particularly during the periods of market turmoil.

[In a Persian market]

Soitinnus: orkesteri.

Corn and soybean yields as affected by cover crops and herbicide timing under no-tillage system

To achieve better results in the no-tillage system (NTS), it is important to properly manage the cover crop prior to planting by using herbicides, usually glyphosate. The effect of glyphosate on plant coverage is slow, and plants take a few days to die completely. Thus, when applying the herbicide on the same day of planting soybean or corn, cover crops are still alive and standing, causing initial shading on seedlings of the crop and delaying its establishment. Therefore, this study aimed to evaluate the effect of distinct cover crops and their timing of desiccation prior to planting soybean or corn, on crop yield and yield components. Two experiments were installed, one for soybean and another for corn. Each experiment consisted in combining three cover crops (Brachiaria brizantha, common bean or millet) chemically desiccated at two timings before planting the crop (15 or 0 days before planting) under no-tillage system (NTS). Experiments were installed in a completely randomized block design with five replications. Brachiaria brizantha produced the highest amount of biomass; common bean and millet as cover crops allowed higher soybean grain yields; herbicide application under common bean, millet and Brachiaria brizantha 15 days before planting soybean allowed higher crop grain yields; desiccation timing of common bean did not affect corn grain yield; Brachiaria brizantha should be desiccated 15 days before planting corn to allow maximum grain yield; when millet was used as a cover crop, glyphosate application at planting of corn allowed the highest grain yield.

Export Tire Entry to Chinese Market

After the economic reform, China has undergone fast economic growth, urbanization and adopted the western lifestyle. Global enterprises are investing in China and Finnish companies began to enter the Chinese market after the 1980s. Fast economic growth has downside effects like pollution and thus more cleantech solutions are needed. There are different kinds of entry modes that companies are using when entering the Chinese market. This thesis focuses on export tire entry mode. The purpose of this study is to examine cleantech companies’ opinions about the export tire operations. The background of this study is built by combining the written knowledge about the history of the Chinese industry and market entry modes. The empirical part of the study is a semi-structured, qualitative analysis of five case companies that are operating together in a particular export tire and represent the highest Finnish cleantech knowledge. The results of this study indicate that the export tire entry is an easy and cost effective way to enter new markets or market segment. Export tire is really dependent on the leader who in this particular case succeeded well.

Prediction of market switching and delisting events from OMX First North Nordic multilateral stock exchange

This thesis studies the predictability of market switching and delisting events from OMX First North Nordic multilateral stock exchange by using financial statement information and market information from 2007 to 2012. This study was conducted by using a three stage process. In first stage relevant theoretical framework and initial variable pool were constructed. Then, explanatory analysis of the initial variable pool was done in order to further limit and identify relevant variables. The explanatory analysis was conducted by using self-organizing map methodology. In the third stage, the predictive modeling was carried out with random forests and support vector machine methodologies. It was found that the explanatory analysis was able to identify relevant variables. The results indicate that the market switching and delisting events can be predicted in some extent. The empirical results also support the usability of financial statement and market information in the prediction of market switching and delisting events.

Stock Market reaction to the CSR announcements of American fast food companies

The purpose of this study is to examine whether Corporate Social Responsibility (CSR) announcements of the three biggest American fast food companies (McDonald’s, YUM! Brands and Wendy’s) have any effect on their stock returns as well as on the returns of the industry index (Dow Jones Restaurants and Bars). The time period under consideration starts on 1st of May 2001 and ends on 17th of October 2013. The stock market reaction is tested with an event study utilizing CAPM. The research employs the daily stock returns of the companies, the index and the benchmarks (NASDAQ and NYSE). The test of combined announcements did not reveal any significant effect on the index and McDonald’s. However the stock returns of Wendy’s and YUM! Brands reacted negatively. Moreover, the company level analyses showed that to their own CSR releases McDonald’s stock returns respond positively, YUM! Brands reacts negatively and Wendy’s does not have any reaction. Plus, it was found that the competitors of the announcing company tend to react negatively to all the events. Furthermore, the division of the events into sustainability categories showed statistically significant negative reaction from the Index, McDonald’s and YUM! Brands towards social announcements. At the same time only the index was positively affected by to the economic and environmental CSR news releases.

On advancing business intelligence in the electricity retail market

In recent decades, business intelligence (BI) has gained momentum in real-world practice. At the same time, business intelligence has evolved as an important research subject of Information Systems (IS) within the decision support domain. Today’s growing competitive pressure in business has led to increased needs for real-time analytics, i.e., so called real-time BI or operational BI. This is especially true with respect to the electricity production, transmission, distribution, and retail business since the law of physics determines that electricity as a commodity is nearly impossible to be stored economically, and therefore demand-supply needs to be constantly in balance. The current power sector is subject to complex changes, innovation opportunities, and technical and regulatory constraints. These range from low carbon transition, renewable energy sources (RES) development, market design to new technologies (e.g., smart metering, smart grids, electric vehicles, etc.), and new independent power producers (e.g., commercial buildings or households with rooftop solar panel installments, a.k.a. Distributed Generation). Among them, the ongoing deployment of Advanced Metering Infrastructure (AMI) has profound impacts on the electricity retail market. From the view point of BI research, the AMI is enabling real-time or near real-time analytics in the electricity retail business. Following Design Science Research (DSR) paradigm in the IS field, this research presents four aspects of BI for efficient pricing in a competitive electricity retail market: (i) visual data-mining based descriptive analytics, namely electricity consumption profiling, for pricing decision-making support; (ii) real-time BI enterprise architecture for enhancing management’s capacity on real-time decision-making; (iii) prescriptive analytics through agent-based modeling for price-responsive demand simulation; (iv) visual data-mining application for electricity distribution benchmarking. Even though this study is from the perspective of the European electricity industry, particularly focused on Finland and Estonia, the BI approaches investigated can: (i) provide managerial implications to support the utility’s pricing decision-making; (ii) add empirical knowledge to the landscape of BI research; (iii) be transferred to a wide body of practice in the power sector and BI research community.

Target audience and message alignment for integrated marketing communication of luxury products: entering the Chinese market

The purpose of this study is to identify opportunities to match marketing communication message strategies with the target audience characteristics in the Chinese luxury market entry context. Therefore, consumer behaviour and psychographic marketing segmentation fields are being reviewed in a holistic view in order to identify the similarities and connection points. Through the analysis of the messages in advertisements placed in a certain luxury and fine living magazine, message creation strategies are being anticipated.

The obstacles for cross-border transmission network investments in the Nordic electricity market: Case South-West link

The Nordic electricity market is often seen as an example of how to create a working, developed and integrated electricity market. Nevertheless, this thesis studies the obstacles of transmission network investments and the market integration challenges in the Nordic electricity market. The main focus is in the Nordic Transmission system operators (TSOs), which have a key role in grid development. This study introduces a case study of cancellation of South-West link, Western part, which was seen as essential grid investment in order to improve the Nordic electricity market functioning but ended up with cancellation in 2013. This study includes semi-structured theme interviews of the experts among Nordic electricity industry stakeholders. Despite the political will to create more equal prices for electricity in the Nordic market, the differing national regulation, mixed incentives created by bottleneck income and the focus moving from Nordic integration to European integration may create challenges to the Nordic electricity market integration in the future.