Portfolio Selection via Composite Measure Analysis: Evidence from the U.S. Stock Market

The aim of this research is to examine the pricing anomalies existing in the U.S. market during 1986 to 2011. The sample of stocks is divided into decile portfolios based on seven individual valuation ratios (E/P, B/P, S/P, EBIT/EV, EVITDA/EV, D/P, and CE/P) and price momentum to investigate the efficiency of individual valuation ratio and their combinations as portfolio formation criteria. This is the first time in financial literature when CE/P is employed as a constituent of composite value measure. The combinations are based on median scaled composite value measures and TOPSIS method. During the sample period value portfolios significantly outperform both the market portfolio and comparable glamour portfolios. The results show the highest return for the value portfolio that was based on the combination of S/P & CE/P ratios. The outcome of this research will increase the understanding on the suitability of different methodologies for portfolio selection. It will help managers to take advantage of the results of different methodologies in order to gain returns above the market.

The Impact of Electrical Capacity Market Mechanisms on Capacity Mobility and End Use Customer Pricing

Potential impacts of electrical capacity market design on capacity mobility and end use customer pricing are analyzed. Market rules and historical evolution are summarized to provide a background for the analysis. The summarized rules are then examined for impacts on capacity mobility. A summary of the aspects of successful capacity markets is provided. Two United States market regions are chosen for analysis based upon their market history and proximity to each other. The MISO region is chosen due to recent developments in capacity market mechanisms. The PJM region neighbors the MISO region and is similar in size and makeup. The PJM region has had a capacity market mechanism for over a decade and allows for a controlled comparison of the MISO region’s developments. Capacity rules are found to have an impact on the mobility of capacity between regions. Regulatory restrictions and financial penalties for the movement of capacity between regions are found which effectively hinder such mobility. Capacity market evolution timelines are formed from the historical evolution previously summarized and compared to historical pricing to inspect for a correlation. No direct and immediate impact on end use customer pricing was found due to capacity market design. The components of end use customer pricing are briefly examined.

Building a Roadmap for a Market Intelligence function in a Global B2B company

Tämän diplomityötutkimuksen tarkoituksena on luoda markkinaälyyn (MI) erikoistunut funktio suurelle, globaalisti toimivalle B2B-yritykselle. Tämän päivän muut-tuvilla markkinoilla, teollisuusyrityksen on oltava markkinalähtöinen selviytyäkseen. Markkinatiedon tehokas hyödyntäminen ei pelkästään luo tietoa markkinoista, vaan tuottaa kilpailukykyistä tietoa ja toimii strategisen päätöksenteon tukena pitkällä aikavälillä. Tämä tutkimus on kvalitatiivinen toimintatutkimus, joka sisältää kirjallisuuskat-sauksen, yritystapaustutkimuksen sekä syväanalyysin yrityksen MI-ympäristöstä. Kirjallisuuskatsaus pitää sisällään teoriaa liittyen markkinaälyyn useassa eri kon-tekstissa, asiakassuhteeseen, sekä prosessinmallintamiseen. Empiiriseen osaa seuraa tutkimusmenetelmäkappale, joka sisältää kaksivaiheisen tutkimuksen mukaan lu-kien 20 päällikkötason haastattelua sekä yhden laaja-alaisen työryhmätapaamisen. Työn tuloksena syntyy kolmivaiheinen tiekartta, jonka tarkoitus on toimia pohjana uuden MI-funktion rakentamiselle Case-yrityksessä. Tuloksen mukaan MI-funktio tulisi sijoittaa yrityksen asiakasrajapintaan sekä tukea yksiköiden välistä integraa-tiota. Markkinaälyn jakaminen yrityksen sisällä vaatii käytäntöjen, tarpeiden ja ta-voitteiden systemaattista viestintää eri organisaatiotasoille, jotta yritys voi edelleen saada asiakkaalta tarpeeseen vastaavaa tietoa. Viestintä yrityksen ja asiakkaan välil-lä on oltava molemminpuolista, jotta tulokset voisivat parantaa asiakassuhdetta. Kun asiakassuhde paranee, yritys voi oppia asiakkaalta arvokasta tietoa, markkinaälyä.

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.

Forecasting financial weather - can we foresee market sentiment? Quantitative analysis of nodal prices in the New Zealand Electricity Spot Market

Time series of hourly electricity spot prices have peculiar properties. Electricity is by its nature difficult to store and has to be available on demand. There are many reasons for wanting to understand correlations in price movements, e.g. risk management purposes. The entire analysis carried out in this thesis has been applied to the New Zealand nodal electricity prices: offer prices (from 29 May 2002 to 31 March 2009) and final prices (from 1 January 1999 to 31 March 2009). In this paper, such natural factors as location of the node and generation type in the node that effects the correlation between nodal prices have been reviewed. It was noticed that the geographical factor affects the correlation between nodes more than others. Therefore, the visualisation of correlated nodes was done. However, for the offer prices the clear separation of correlated and not correlated nodes was not obtained. Finally, it was concluded that location factor most strongly affects correlation of electricity nodal prices; problems in visualisation probably associated with power losses when the power is transmitted over long distance.

Simulating the dynamics of silver market using computational market dynamics

Traditional econometric approaches in modeling the dynamics of equity and commodity markets, have, made great progress in the past decades. However, they assume rationality among the economic agents and and do not capture the dynamics that produce extreme events (black swans), due to deviation from the rationality assumption. The purpose of this study is to simulate the dynamics of silver markets by using the novel computational market dynamics approach. To this end, the daily data from the period of 1st March 2000 to 1st March 2013 of closing prices of spot silver prices has been simulated with the Jabłonska-Capasso-Morale(JCM) model. The Maximum Likelihood approach has been employed to calibrate the acquired data with JCM. Statistical analysis of the simulated series with respect to the actual one has been conducted to evaluate model performance. The model captures the animal spirits dynamics present in the data under evaluation well.

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.

Emerging market patterns in recycled paper trade

The international recovered paper trade serves two important functions: increasing raw material availability in the paper and board industry and providing economic incentives to recycle. The purpose of this paper is to shed further light on emerging patterns in this trade by empirically analysing the changes in the bilateral trade flows of recycled paper between 1992 and 2008. According to our estimations, two important changes have taken place in the 1990s and 2000s. First, the growing importance of developing economies in global recycled paper trade plays a significant role in import demand as a determinant of trade flows. Second, the changes in global trade patterns necessitate investigating the transportation cost measures used in applied research.

Service product internationalisation : market selection for new service products in a multinational financial service firm

The significance and impact of services in the modern global economy has become greater and there has been more demand for decades in the academic community of international business for further research into better understanding internationalisation of services. Theories based on the internationalisation of manufacturing firms have been long questioned for their applicability to services. This study aims at contributing to understanding internationalisation of services by examining how market selection decisions are made for new service products within the existing markets of a multinational financial service provider. The study focused on the factors influencing market selection and the study was conducted as a case study on a multinational financial service firm and two of its new service products. Two directors responsible for the development and internationalisation of the case service products were interviewed in guided semi-structured interviews based on themes adopted from the literature review and the outcome theoretical framework. The main empirical findings of the study suggest that the most significant factors influencing the market selection for new service products within a multinational financial service firm’s existing markets are: commitment to the new service products by both the management and the rest of the product related organisation; capability and competence by the local country organisations to adopt new services; market potential which combines market size, market structure and competitive environment; product fit to the market requirements; and enabling partnerships. Based on the empirical findings, this study suggests a framework of factors influencing market selection for new service products, and proposes further research issues and methods to test and extend the findings of this research.

Kalman filter for computational market dynamics

Kalman filter is a recursive mathematical power tool that plays an increasingly vital role in innumerable fields of study. The filter has been put to service in a multitude of studies involving both time series modelling and financial time series modelling. Modelling time series data in Computational Market Dynamics (CMD) can be accomplished using the Jablonska-Capasso-Morale (JCM) model. Maximum likelihood approach has always been utilised to estimate the parameters of the JCM model. The purpose of this study is to discover if the Kalman filter can be effectively utilized in CMD. Ensemble Kalman filter (EnKF), with 50 ensemble members, applied to US sugar prices spanning the period of January, 1960 to February, 2012 was employed for this work. The real data and Kalman filter trajectories showed no significant discrepancies, hence indicating satisfactory performance of the technique. Since only US sugar prices were utilized, it would be interesting to discover the nature of results if other data sets are employed.

Foreign companies’ strategies on the Russian market during the crisis

Concept of crisis is the subject of many studies and publications in specialized articles and in journalistic publications. The thesis includes next key objectives: concept of the crisis is defined, disclosed external and internal factors affected company’s strategy, shown specific characteristics of Russian market and their influence on the foreign companies. The Master’s Thesis identifies successful foreign companies’ strategies on the Russian market during crises in 2008 and 2014. The study is qualitative and it is based on integrative analysis of literature, secondary data and results of the interview, conducted among foreign companies that operates on the Russian market Findings of the thesis show an effect of the crisis on the company’s strategy. It provides information about specific external and internal factors that affects on company’s strategy during the crisis. Theoretical findings help to understand complex concept of crisis and its main aspects in context of strategy. Analysis of specific characteristics of Russian market provides a base for assessment of efficiency of chosen strategy. Comparison between Russian cresses and companies behaviors in these periods shows how different is strategy because of the nature of the crisis. Results of the thesis could be used as a guideline for foreign companies in Russian market during the crisis period

Visual analytics for behavioral and niche market segmentation

Companies require information in order to gain an improved understanding of their customers. Data concerning customers, their interests and behavior are collected through different loyalty programs. The amount of data stored in company data bases has increased exponentially over the years and become difficult to handle. This research area is the subject of much current interest, not only in academia but also in practice, as is shown by several magazines and blogs that are covering topics on how to get to know your customers, Big Data, information visualization, and data warehousing. In this Ph.D. thesis, the Self-Organizing Map and two extensions of it – the Weighted Self-Organizing Map (WSOM) and the Self-Organizing Time Map (SOTM) – are used as data mining methods for extracting information from large amounts of customer data. The thesis focuses on how data mining methods can be used to model and analyze customer data in order to gain an overview of the customer base, as well as, for analyzing niche-markets. The thesis uses real world customer data to create models for customer profiling. Evaluation of the built models is performed by CRM experts from the retailing industry. The experts considered the information gained with help of the models to be valuable and useful for decision making and for making strategic planning for the future.

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.