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.

The Russian National Innovation System - an International Perspective

Russia inherited a large research and development (R&D) sector from the Soviet times, and has retained a substantial R&D sector today, compared with other emerging economies. However, Russia is falling behind in all indicators measuring innovative output in comparison with most developed countries. Russia’s innovation performance is disappointing, despite the available stock of human capital and overall investment in R&D. The communist legacy still influences the main actors of the innovation system. The federal state is still the most important funding source for R&D. Private companies are not investing in innovative activities, preferring to “import” innovations embedded in foreign technologies. Universities are outsiders in the innovation system, only a few universities carry out research activities. Nowadays, Russia is a resource-depended country. The economy depends on energy and metals for growth. The Russian economy faces the challenge of diversification and should embrace innovation, and shift to a knowledge economy to remain competitive in the long run. Therefore, Russia has to tackle the challenge of developing an efficient innovation system with its huge potential in science expertise and engineering know-how.

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.

Factors Affecting Consumer Investment Intentions. Empirical Evidence from Finland

The thesis aims to build a theoretical model to explain consumer investment intentions in stocks and investment funds. The model examines the relationships between subjective investment knowledge, expected sacrifice, expected investment value, compatibility, perceived behavioral control and investment intentions. The data was collected via web-based survey and consisted of 45- to 65-year-old Finnish consumers (n=154). Confirmatory factor analysis (CFA), structural equation modeling (SEM) and t-tests were applied in analyzing the data. The results suggest that among average household consumers expected investment value consists of three dimensions, namely, economic, functional, and emotional, whereas expected sacrifice consists of effort, financial risk, source risk, and psychological risk. Two structural models were assessed, one for stock investments and one for investment funds. Whereas the models presented somewhat different outcomes, in both models compatibility had an essential role in explaining consumer investment intentions. Compatibility was affected by expected investment value and expected sacrifice. Subjective investment knowledge impacted consumers’ evaluations of the value and sacrifices. The effect of perceived behavioral control on investment intentions was rather small, however significant. Moreover, the results suggest that there are significant differences between consumers with no investment experience and consumers with investment experience in subjective investment knowledge, the dimensions of expected sacrifices and expected investment value, perceived behavioral control, compatibility and investment intentions.

Liquidity and Asset Pricing in the French Stock Market

This thesis investigates pricing of liquidity in the French stock market. The study covers 835 ordinary shares traded in the period of 1996-2014 on Paris Euronext. The author utilizes the Liquidity-Adjusted Capital Asset Pricing Model (LCAPM) recently developed by Acharya and Pedersen (2005) to test whether liquidity level and risks significantly affect stock returns. Three different liquidity measures – Amihud, FHT, and PQS – are incorporated into the model to find any difference between the results they could provide. It appears that the findings largely depend on the liquidity measure used. In general the results exhibit more evidence for insignificant influence of liquidity level and risks as well as market risk on stock returns. The similar conclusion was reported earlier by Lee (2011) for several regions, including France. This finding of the thesis, however, is not consistent across all the liquidity measures. Nevertheless, the difference in the results between these measures provides new insight to the existing literature on this topic. The Amihud-based findings might indicate that market resiliency is not priced in the French stock market. At the same time the contradicting results from FHT and PQS provide some foundation for the hypothesis that one of two leftover liquidity dimensions – market depth or breadth – could significantly affect stock returns. Therefore, the thesis’ findings suggest a conjecture that different liquidity dimensions have different impacts on stock returns.

Together Everyone Achieves More? Herding Behavior in the Finnish Stock Market

This thesis examines whether or not Finnish stock markets has herding behavior. Sample data is from 2004 to 2013. Including total of 2516 market days. Market wide herding, up and down market herding, extreme price movement herding and turnover volume herding are measured in this thesis. Methods used in this thesis are cross-sectional absolute dispersion and cross-sectional standard deviation. This thesis found no signs of herding in the Finnish stock market.

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.

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.

Time Varying Conditional Correlation Between Stock And Bond Returns: Evidence From CIVETS Nations

This thesis estimates long-run time variant conditional correlation between stock and bond returns of CIVETS (Colombia, Indonesia, Vietnam, Egypt, Turkey, and South Africa) nations. Further, aims to analyse the presence of asymmetric volatility effect in both asset returns, as well as, obverses increment or decrement in conditional correlation during pre-crisis and crisis period, which lead to make a reliable diversification decision. The Constant Conditional Correlation (CCC) GARCH model of Bollerslev (1990), the Dynamic Conditional Correlation (DCC) GARCH model (Engle 2002), and the Asymmetric Dynamic Conditional Correlation (ADCC) GARCH model of Cappiello, Engle, and Sheppard (2006) were implemented in the study. The analyses present strong evidence of time-varying conditional correlation in CIVETS markets, excluding Vietnam, during 2005-2013. In addition, negative innovation effects were found in both conditional variance and correlation of the asset returns. The results of this study recommend investors to include financial assets from these markets in portfolios, in order to obtain better stock-bond diversification benefits, especially during high volatility periods.

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.

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.