783 resultados para Stock returns


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This thesis examines the equity market reactions on credit rating announcements. The study covers 12 European countries during the period of 2000-2012. By using an event study methodology and daily collected stock market returns, the impact of the sovereign credit rating announcements to national stock indices is examined. The thesis finds evidence for the rating downgrades having a statistically significant negative effect on the stock markets. This finding is in line with earlier literature (see Brooks, 2004). The paper also discusses whether the changes in the sovereign credit ratings are contagious, anticipated by the market, and persistent. There is some evidence found for the contagion effects in case of downgrades, but not for upgrades. Markets seem to anticipate rating upgrades, but not downgrades. In addition, market´s reaction towards rating announcements seems not to be persistent.

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This study examines the Magic Formula and ERP5 value strategies in the Finnish stocks markets. Magic Formula ranks stocks based on EV/EBIT and ROA and ERP5 based on EV/EBIT, ROA, P/B and five-year trailing ROA. The purpose of the study is to examine whether the value strategies can be used to generate excess returns over the market index. The data has been collected from the Datastream database for the sample period from May 1997 to May 2010 and consists of the companies listed on the main list of Helsinki Stock Exchange. This study confirms the findings of previous research that value premium exists in the Finnish stock markets and that systematic value strategies can be used to form portfolios that outperform the market index with lower volatility.

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The purpose of this research is to investigate how CIVETS (Colombia, Indonesia, Vietnam, Egypt, Turkey and South Africa) stock markets are integrated with Europe as measured by the impact of euro area (EA) scheduled macroeconomic news announcements, which are related to macroeconomic indicators that are commonly used to indicate the direction of the economy. Macroeconomic announcements used in this study can be divided into four categories; (1) prices, (2) real economy, (3) money supply and (4) business climate and consumer confidence. The data set consists of daily market data from CIVETS and scheduled macroeconomic announcements from the EA for the years 2007-2012. The econometric model used in this research is Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH). Empirical results show diverse impacts of macroeconomic news releases and surprises for different categories of news supporting the perception of heterogeneity among CIVETS. The analyses revealed that in general EA macroeconomic news releases and surprises affect stock market volatility in CIVETS and only in some cases asset pricing. In conclusion, all CIVETS stock markets reacted to the incoming EA macroeconomic news suggesting market integration to some extent. Thus, EA should be considered as a possible risk factor when investing in CIVETS.

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The aim of this work is to evaluate the mechanism of stock removal and the ground surface quality of advanced ceramics machined by a surface grinding process using diamond grinding wheels. The analysis of the grinding performance was done regarding the cutting surface wear behavior of the grinding wheel for ceramic workpieces. The ground surface was evaluated using Scanning Electron Microscopy (SEM). As a result it can be said that the mechanism of material removal in the grinding of ceramic is largely one of brittle fracture. The increase of the h max can reduce the tangential force required by the process. Although, it results in an increase in the surface damage, reducing the mechanical properties of the ground component.

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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.

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A rapidly growing gaming industry, which specializes on PC, console, online and other games, attracts attention of investors and analysts, who try to understand what drives changes of the gaming industry companies’ stock prices. This master thesis shows the evidence that, besides long-established types of events (M&A and dividend payments), the companies’ stock price changes depend on industry-specific events. I analyzed specific for gaming industry events - game releases with respect to its subdivisions: new games-sequels, games ratings and subdivision according to a developer of a game (self-developed by publisher or outsourced). The master thesis analyzes stock prices of 55 companies from gaming industry from all over the world. The research period covers 5 year, spreading from April 2008 to April 2013. Executed with an event study method, results of the research show that all the analyzed events types have significant influence on the stock prices of the gaming industry companies. The current master thesis suggests that acquisitions in the industry affect positively bidders’ and targets’ stock prices. Mergers events cause positive stock price reactions as well. But dividends payments and game releases events influence negatively on the stock prices. Game releases’ effect is up to -2.2% of cumulative average abnormal return (CAAR) drop during the first ten days after the game releases. Having researched different kinds of events and identified the direction of their impact, the current paper can be of high value for investors, seeking profits in the gaming industry, and other interested parties.

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This study examines the excess returns provided by G10 currency carry trading during the Euro era. The currency carry trade has been a popular trade throughout the past decades offering excess returns to investors. The thesis aims to contribute to existing research on the topic by utilizing a new set of data for the Euro era as well as using the Euro as a basis for the study. The focus of the thesis is specifically on different carry trade strategies’ performance, risk and diversification benefits. The study finds proof of the failure of the uncovered interest rate parity theory through multiple regression analyses. Furthermore, the research finds evidence of significant diversification benefits in terms of Sharpe ratio and improved return distributions. The results suggest that currency carry trades have offered excess returns during 1999-2014 and that volatility plays an important role in carry trade returns. The risk, however, is diversifiable and therefore our results support previous quantitative research findings on the topic.

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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.

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Tutkielman tavoitteena on tutkia osingon irtoamispäivän tapahtumia OMX Helsinki 25:n yrityksillä vuosina 2005–2013. Vallitsevan käsityksen mukaan osakkeen hinta laskee irtoamispäivänä osingon verran +/- markkinoiden yleisestä hintamuutoksesta johtuva nousu/lasku. Käsitystä on pyritty murtamaan vuosien saatossa neljän eri teorian avulla, jotka ovat veroasiakaskuntateoria, lyhytaikaisen vaihdon hypoteesi, dynaaminen malli sekä mikrorakenneteoria. Osingon irtoamispäivää tarkastellaan kolmen eri tutkimuksen avulla ja saatuja tuloksia verrataan teoriaan sekä aikaisempiin löydöksiin. Tutkimusosuudet ovat kurssilaskusuhteet, epänormaalit tuotot sekä epänormaalit kaupankäyntivolyymit. Kurssilaskusuhdetta tarkastellaan vertaamalla cum-päivän ja irtoamispäivän osakkeiden hintojen erotusta maksetun osingon määrään. Epänormaaleja tuottoja ja epänormaaleja kaupankäyntivolyymejä tarkastellaan tapahtumatutkimus-menetelmällä viisi päivää ennen ja viisi päivää jälkeen osingon irtoamisen. Kurssilaskusuhteet olivat eri tavoilla laskettuina 77 – 94 %. Irtoamispäivän ympärillä oli havaittavissa 1,5 %:n negatiivisia epänormaaleja tuottoja. Epänormaalit kaupankäyntivolyymit kasvoivat tasaisesti lähestyttäessä irtoamispäivää ja olivat voimakkaimmillaan irtoamispäivänä. Irtoamispäivän jälkeen kaupankäyntivolyymit palautuivat hiljalleen normaalille tasolle. Tulokset vastaavat aikaisempia löydöksiä kurssilaskusuhteita ja epänormaaleja volyymejä tarkasteltaessa, mutta eroavat epänormaaleissa tuotoissa.

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The purpose of the thesis is to examine the long-term performance persistence and relative performance of hedge funds during bear and bull market periods. Performance metrics applied for fund rankings are raw return, Sharpe ratio, mean variance ratio and strategy distinctiveness index calculated of the original and clustered data correspondingly. Four different length combinations for selection and holding periods are employed. The persistence is examined using decile and quartile portfolio formatting approach and on the basis of Sharpe ratio and SKASR as performance metrics. The relative performance persistence is examined by comparing hedge portfolio returns during varying stock market conditions. The data is gathered from a private database covering 10,789 hedge funds and time horizon is set from January 1990 to December 2012. The results of this thesis suggest that long-term performance persistence of the hedge funds exists. The degree of persistence also depends on the performance metrics employed and length combination of selection and holding periods. The best results of performance persistence were obtained in the decile portfolio analysis on the basis of Sharpe ratio rankings for combination of 12-month selection period and the holding period of equal length. The results also suggest that the best performance persistence occurs in the Event Driven and Multi strategies. Dummy regression analysis shows that a relationship between hedge funds and stock market returns exists. Based on the results, Dedicated Short Bias, Global Macro, Managed Futures and Other strategies perform well during bear market periods. The results also indicate that the Market Neutral strategy is not absolutely market neutral and the Event Driven strategy has the best performance among all hedge strategies.

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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.

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Tämän tutkielman tavoitteena on selvittää ja analysoida tunnuslukuihin perustuvien sijoitusstrategioiden tuottoja voimakkailla lasku- ja nousumarkkinoilla finanssikriisin aikana. Säilyttääkö arvostrategian alhaisten tunnuslukujen portfolio arvonsa laskukausilla parhaiten tai tuottaako kasvustrategia vahvalla nousukaudella parhaan tuoton? Miten yhtiöiden taloudellinen asema vaikuttaa tuottoihin jyrkillä laskukausilla ja nousukaudella? Tutkimusaineistona ovat julkisesti noteeratut Helsingin pörssin yhtiöt aikavälillä 13.7.2007 - 4.10.2011. Ajanjaksoon mahtuu kaksi laskukautta ja nousukausi. Yhtiöt on jaettu tunnuslukujen arvostuksen mukaan viiteen portfolioon. Tutkittavat tunnusluvut ovat P/E-luku, P/B-luku, EV/Ebit-luku, oman pääoman tuotto, omavaraisuusaste, current ratio ja Grahamin luku. Tulosten perusteella arvostrategia menestyi hyvin nousukaudella niin P/E-luvun kuin P/B-luvun kategorian tuotoissa, mutta ei erottunut edukseen laskukausilla. Huomattavaa oli myös korkean omavaraisuuden yhtiöiden voimakas defensiivisyys molemmilla laskukausilla. Toisaalta ne olivat myös nousukaudella vähätuottoisia.

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Tutkielman tavoitteena on selvittää osinkosuhteen, osinkotuoton ja omavaraisuusasteen vaikutus osakkeesta saatavaan kokonaistuottoon Suomenosakemarkkinoilla vuosina 2002–2013. Muuttujien kausaliteettisuhde kokonaistuottoon selvitetään regressioanalyysilla. Portfolioanalyysin avulla tutkitaan valittujen tunnuslukujen toimivuutta sijoitusstrategiana. Tutkimuksessa muodostetaan myös osinkosuhteen ja osinkotuoton yhdistelmänä tunnusluku, jolla pyritään maksimoimaan sijoittajan saama tuotto. Empiiriset tulokset osoittivat, että sijoittaja pystyy saavuttamaan ylituottoja hyödyntämällä edellä mainittuja tunnuslukuja osakevalinnassa. Osinkotuoton ja osakkeen kokonaistuoton välillä havaittiin positiivinen lineaarinen korrelaatio. Portfolioanalyysin perusteella sekä omavaraisuusasteen että osinkosuhteen osalta vaikutus sijoittajan saamaan riskisuhteutettuun kokonaistuottoon on ei-lineaarinen. Valittuja tunnuslukuja ja menetelmiä hyödyntäen sijoittaja saa parhaimman riskisuhteutetun tuoton valitsemalla sijoitussalkkuunsa osakkeita, joiden osinkosuhteen arvo sijoittuu toiseksi ylimpään kvartiiliin sekä osakkeita, joiden osinkotuotto on korkea ja omavaraisuusaste on samanaikaisesti alhainen.

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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.

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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.