The aim of this master thesis is to create a fundamental analysis of selected European automobile manufacturing companies, which are enlisted in the stock market and are publically traded. Goal of this fundamental analysis is to propose an ideal portfolio which should outperform the average car industry market. All information which are used during this work are publically accessible on the websites of every mentioned company. First part of this work is devoted to the description of methods, which are used through the whole article. Second part is describing selected companies and the reasons of the selection itself. Third part is devoted to the comparison of selected companies. Forth part is describing methods used for verification of the results, methods used for this verification are calculation of the inner value of security and bankruptcy models. The recommendation for the ideal portfolio for the European car industry is created in the last part of this thesis.

This work deals with the usage of neural network for the purpose of stock market prediction. A basic stock market theory and trading approaches are mentioned at the beginning of this work. Then neural networks and their application are discussed with their deeper description. Similar approaches are referred and finally two new prediction systems are designed. These systems are utilized by proposed trading model and tested on selected data. The results are compared to human and random trading models and new development steps are devised at the end of this work.

This master's thesis describes creation of prediction system. This system predicts future market development based on stock exchange data and twitter messages analysis. Tweets from two different sources are analysed by mood dictionaries or via recurrent neural networks. This analysis results and technical analysis of stock exchange data results are used in multilayer neural network for prediction. A business strategy is created and tested based on results of this prediction. Design and implementation of prediction system is described in this thesis. This system achieved revenue increase more than 25 % of some business strategies by tweets analysis. However this improvement applies for certain data and timeframe.

Las Pymes son el principal sector empresarial en el Perú y generadoras de fuentes de empleo en el país pero tienen problemas de acceso al financiamiento a tasas de interés bajas y falta de gestión de calidad, por lo general, debido al desconocimiento de alternativas de financiamiento y falta de profesionalización en la gestión. La presente investigación tiene como hipótesis que Participar del Mercado Alternativo de Valores mejora la gestión financiera de las Pymes, en el Perú, en el año 2018, debido a que el financiamiento por medio del mercado de capitales tiene una menor tasa de interés en comparación con un banco, brinda una alternativa de financiamiento, poder de negociación frente a los Stakeholders y mejora la gestión por medio de la profesionalización. Esta Tesis es descriptiva correlacional, de enfoque mixto, de diseño no experimental y transversal. Se describen los conceptos que apoyarán a evaluar la relación que existe entre las variables planteadas. Además, se explican las etapas a seguir para que una Pyme realice todo el proceso de preparación y colocación de obligaciones en el mercado de capitales. Para validar la hipótesis general y específica se ha realizado 6 entrevistas a profundidad a expertos con experiencia en Pymes y conocimiento del MAV. También se ha realizado treinta encuestas a profesionales con experiencia en Pymes. En el caso práctico se describen las mejoras en los indicadores y en la gestión financiera, por medio de la participación de la Pyme en el Mercado Alternativo de Valores. / Pymes are the main business sector in Peru and generators of sources of employment in the country, but they have problems of access to financing at low interest rates of lack quality management, generally due to ignorance of financing alternatives and lack of professionalization in management. The present research has as a hypothesis that participating in the Alternative Stock Market improves the financial management of Pymes, in Peru, in 2018, due to the fact that financing through the capital market has a lower interest rate compared to a bank, provides a financing alternative, bargaining power Stakeholders and improves management through professionalization. This thesis is descriptive correlational, of mixed approach, of non – experimental and transversal design. The concepts that will support the evaluation of the relationship between the proposed variables are described. In addition, the steps to be followed for a Pyme to carry out the entire process of preparing and placing obligations in the capital market are explained. To validate the general and specific hypothesis, have conducted 6 interviews to depth to experts with experience in Pymes and knowledge of the MAV. Furthermore, have conducted thirty surveys to professionals with experience in Pymes. The practical case describes the improvements in the indicators and financial management, through the participation of the Pyme in the alternative stock market. / Tesis

Many investors use different types of data methods before making a decision, regardless of whether it is long or short term. The choice of which analysis method is generally determined by risk, removal of bias and the cost. One method that has been investigated is the use of machine lerning in data analysis. The advantage of machine lernig is that the method successfully handles comples, non-linear and non-stationary problems. In this essay, it will be investigated whether unattended machine learning, which uses the K-meaning method, which is a method that has not been investigated to any great extent either in practice or in theory to create a beneficial portfolio. The data used for the k-meaning method was historical data from the Swedish stock market between 1 January 2018 and 2 November 2020. The k-meaning analysis consists of the return of all shares included within OMX30 and the average deviation, which created a cluster of 11 shares that could generate a relatively high return compared to the remaining shares. To analyze whether the generated cluster were acceptable, an analysis of the sharpe-ratio and downward risk was preformed, which showed that the portfolio had a good risk-adjusted returnbut a worse result on downward risk.

No description available.

Closed-end funds (CEFs) are popular investments amongst the Swedish population as they provide diversification to investors and have in many cases historically outperformed the market. In deciding whether to invest in a CEF, the method of valuation differs from classical financial ratios used to value most companies, as the revenue-bringing operations differ significantly. The Net Asset Value (NAV) per share is compared to the market price per share of a CEF, to determine if the share is traded at a discount or premium. The purpose is based upon the rationalization that a share’s market price and the value of the closed-end fund’s underlying assets cannot drift too far apart from each other. In other words, the discount cannot drift too far from its mean over time, as there would be an upward pressure on the share price if the NAV-discount is large, and a downward pressure on the share price if the premium is large. Tests of unit roots and cointegration are applied and analysed in the light of previous findings for discounts in CEFs. Our findings show that the majority of selected CEFs’ prices and NAVs have long-run equilibrium relationships. Additionally, the discount appears to be stationary over time for the majority of CEFs, supporting the notion of mean reversion in the discount. For certain Swedish CEFs, the findings allow for investment decisions to be made upon the deviation from the mean. This study contributes to previous research done on the topic of mean reversion in the financial market as it finds statistical evidence of mean-reverting process for the NAV-discount of Swedish CEFs. The thesis also provides additional value to the plethora of research provided in the financial field as it specifies its findings to the Swedish market of CEFs.

Under flera år har forskare kunnat hittat stöd för en stark initial avkastning när ett företag noteras på en börslista för första gången. Samtidigt tenderar dessa bolag att underprestera marknaden och liknande noterade bolag på längre sikt. Flera mönster har också identifierats gällande i vilka perioder där noteringsaktiviteten varit som störst. Examensarbetet syftar till att utvärdera om det råder något samband mellan värderingen som föreligger på börsen och antalet bolag som noteras. I examensarbetet ska vi även analysera om det finns en skillnad i avkastning på kort och lång sikt för noteringarna beroende på vilken värdering som varit på börsen när bolaget har noterats. Genom att använda data för de börsnoteringar som har noterats under 2007 till 2021 samt börsens värdering under samma tidsperiod genomförs en regressionsanalys. Vidare delas börsnoteringarna in i två grupper, där gruppen låg värdering innehåller börsnoteringar som noterades när börsen värderades under medelvärdet för undersökningsperioden. Gruppen hög värdering inkluderade börsnoteringarna som noterades då börsen värderades över medelvärdet. Skillnaden i kursutveckling för börsnoteringarna i de två olika grupperna utvärderas sedan med ett T-test. Studien gav stöd för att det finns ett laggat samband med antalet noteringar som sker och värderingen som finns på aktiemarknaden. Studien kunde däremot inte dra några slutsatser om det finns några skillnader i den avkastningen som genererats av noteringarna baserat på värderingen på börsen vid introduktionstillfället. / Researchers have for years documented an initial return for companies listing their stock on a public exchange for the first time. However, there is also a tendency for these firms to underperform compared to the general market and similarly sized firms in the long run. Patterns have also been identified regarding which periods have the strongest activity among IPOs. This thesis tries to evaluate if a relationship exists between the number of IPOs and the valuation of the stock market. Further, the thesis also tests if there is a difference in the performance of the IPOs in both the short run and the long run based on the valuations in the stock market during their market entry. Using data over the IPOs between 2007-2021 and the stock market valuation for the same period, a regression analysis is then run. Further the IPOs are divided into two groups, where the group low valuation includes IPOs that were offered when the stock market valuation was lower than the mean valuation of the time period. The group high valuation included IPOs that were offered when the stock market valuation was higher than the mean valuation. Differences between the groups in the IPOs stock performance are then evaluated with a t-test. The results from the study showed evidence of a strong lagged relationship between the number of IPOs and the stock market valuation. However, the results did not support the existence of differences of performance based on the valuations of the stock market at the time of their entry.

This thesis investigates the two investment strategies Dogs of Dow and The Magic Formula. We test how the strategies perform when getting weighted to ESG scores and also if they outperform OMXSPI during the years 2012-2022. What we find in our study is that when returns are risk adjusted, both Dogs of Dow and The Magic Formula and their ESG weighted portfolios outperform the benchmark during the period. We also conclude that ESG weighted portfolios yield lower returns than equally weighted Dogs of Dow and The Magic Formula portfolios. The portfolio that produce the highest return was the equally weighted Dogs of Dow portfolio. For the value at risk we find that on a five percent significant level, the portfolios observe values from -1,55% to -1,69%.

In late 2019, the spread of the coronavirus SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2) began. The viral disease, also known as covid-19, started spreading from China to large parts of the world in early 2020, resulting in a large number of cases, deaths, as well as major impacts on the economy of nations, organizations, and individuals alike. In order to limit the spread of the virus, several pharmaceutical companies, including Pfizer and Moderna, initiated a vaccine development. This process led pharmaceutical companies to communicat ea large amount of corporate news to investors, among other stakeholders. Previous research has shown how the stock market responds to corporate news. However, prior to this study, a lack of research on how the stock market behaves in relation to corporate news announced by companies under difficult global conditions was identified. The aim of this study is to investigate the stock market's reaction to press releases by Moderna and Pfizer regarding their vaccine development for covid-19. The methods used to study the subject are based on analysis of historical share price data and the calculation of abnormal returns. The results have to some extent indicated that selected press releases have played a significant role as an influencer in relation to investor sentiment and the stock market’s behavior. In terms of the result as a whole, the number of significant days is not sufficient to support the alternative hypothesis. Market reactions in the share prices were identified on the dates surrounding the press releases regarding the vaccine-development, but since only 22 percent of the abnormal yield was significant, the result did not appear to be aligned with the alternative hypothesis. / Under slutet av år 2019 började spridningen av coronaviruset SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2). Virussjukdomen, i folkmun känd som covid-19, började under år 2020 spridas från Kina till stora delar av övriga världen, vilket har resulterat i ett stort antal insjuknade, dödsfall och även en påverkan på såväl nationers som organisationers och individers ekonomi. För att begränsa spridningen av viruset påbörjade ett flertal läkemedelsbolag en vaccinframtagning. Denna process ledde till att läkemedelsbolagen kommunicerade en stor mängd bolagsnyheter till omvärlden, däribland investerare. Tidigare forskning har visat hur aktiemarknaden svarat på bolagsnyheter, men inför denna studie identifierades en brist på forskning kring hur aktiemarknaden agerar i förhållande till bolagsnyheter under extrema världssituationer likt coronaviruspandemin. Syftet med denna studie är att undersöka marknadens reaktion till följd av pressmeddelanden från företagen Moderna och Pfizer rörande vaccinutvecklingen för covid-19. Reaktionen studeras med hjälp av historiska aktiekursdata och beräkning av onormal avkastning. Resultaten har till en viss del indikerat på att utvalda pressmeddelanden har spelat en signifikant roll som påverkande faktor gentemot aktiemarknaden. Sett till resultatet i sin helhet är antalet signifikanta dagar inte tillräckligt för att utgöra stöd till alternativhypotesen. Marknadsreaktioner kunde identifieras till följd av pressmeddelanden om vaccinutvecklingen, men eftersom enbart 22 procent av den onormala avkastningen var signifikant så föreföll inte resultatet i linje med alternativhypotesen.