Bakalauro baigiamajame darbe tiriama, ar akcijų rinkos signalizavo apie ekonomikos pokyčius 2000-2012 m. laikotarpiu Baltijos šalyse. Pirmojoje darbo dalyje pateikiami teoriniai ekonominio ciklo ir jo indikatorių aspektai, analizuojamos priežastys, kodėl akcijų rinkos gali būti vadinamos ekonomikos indikatoriais bei išanalizuojami orientuojančio ryšio tarp akcijų rinkų ir ekonominio ciklo moksliniai tyrimai. Antrojoje, tiriamojoje dalyje, siekiama išsiaiškinti ar akcijų rinkos Lietuvoje, Latvijoje ir Estijoje gali būti vadinami orientuojantys ekonomikos ciklo sekos indikatoriais. Tam kad būtų ištirtas šis ryšys, buvo pasirinkti keturi makroekonominiai rodikliai (BVP, neto darbo užmokestis, mažmeninė prekyba, pramoninės produkcijos apimtis) ir grafinės analizės, Grangerio priežastingumo testo bei VAR modelio pagalba šis ryšys buvo tiriamas. Rezultatai parodė, jog tik iš dalies akcijų rinkos yra orientuojantis ekonomikos ciklo sekos indikatorius Baltijos valstybėse, nes reikšmingas ir patikimas ryšys buvo rastas tik su BVP ir pramoninės produkcijos apimtimis. / The thesis investigates if the stock markets signaled about the economic changes for the period of 2000 – 2012 in the Baltic States. In the first part of this work the theoretical overview on economic cycle and its indicator aspects are introduced. What is more, the circumstances why the stock markets can be described as economic indicators are also presented. Moreover, the scientific researches about the orientation links between the stock markets and the economic cycle are analyzed in this final work. The practical part of the work seeks to find out if the stock markets in Lithuania, Latvia and Estonia can be called leading indicators of economic cycle sequence. In order to analyze these relations, four macroeconomic indicators were chosen (GDP, net earnings, retail and volume of industrial production). With the help of graphic analysis, Granger Causality Test and VAR model this relation was analyzed. The results show that the stock markets are just partially leading indicators of economic cycle sequence in the Baltic States because the significant and reliable relation was found only with the volumes GDP and industrial production.

Baltijos šalių akcijų rinkų istorija yra trumpa, tuo tarpu akcijų kainų ciklų nagrinėjimui bei galimam vėlesniam prognozavimui reikalinga ilgesnė duomenų imtis. Dėl šios priežasties šiame darbe bus siekiama išsiaiškinti ar šių šalių akcijų rinkos elgesys yra panašus į Skandinavijos šalių akcijų rinkų pokyčius. Panašumams ar skirtumams atskleisti teorinėje dalyje buvo nagrinėjami akcijų rinkos cikliškumo charakteristikos, o taip pat ciklų atsiradimo ir jų koreliacijos sąlygos. Antrojoje dalyje šalių ekonominės situacijos nagrinėjimui pasirinkti tokie rodikliai kaip: infliacijos ir BVP dinamika. O akcijų ciklai buvo identifikuojami pagal modifikuotą NBER metodą. Darbe buvo iškeltos trys hipotezės, kurios buvo nagrinėjamos tre�����iojoje darbo dalyje. Panašumas buvo nagrinėjamas trimis aspektais, kurie yra iškeltų hipotezių pagrindas: akcijų rinkos indekso charakteristikos, indeksų pokyčių koreliacija, ekonominių sąlygų akcijų kainų indeksų pakilimo metu panašumas. Patvirtintos buvo tik antroji ir iš dalies trečioji hipotezės. Vertinant bendrai tris hipotezes, Skandinavijos šalių patirtis netinka Baltijos šalių akcijų rinkos tendencijoms prognozuoti, nes egzistuoja daug skirtumų. / The history of stock markets in Baltic states is short, whereas analysis of stock market cycles requires longer time series data. Therefore, the objective of this thesis is to find out whether the behavior of stock market in above mentioned countries is similar to Scandinavian stock market changes. In theoretical chapter of paper work characteristics and conditions of stock market cycles were examined to determine similarities or differences in analyzed countries. Second chapter studies economic background and identifies stock market cycles using NBER method. Three hypotheses were raised based on three aspects of stock market cycles: stock market cycle characteristics, correlations of stock indices’ changes and economic background in light of stock cycles’ peaks. Only second and third hypotheses were proved. Assessing all three hypotheses Scandinavian stock market history is not suitable to make prognosis for stock markets cycles in Baltic states because of lots of differences.

In this thesis, machine learning algorithms are used in NLP to get the public sentiment on individual stocks from social media in order to study its relationship with the stock price change. The NLP approach of sentiment detection is a two-stage process by implementing Neutral v.s. Polarized sentiment detection before Positive v.s. Negative sentiment detection, and SVMs are proved to be the best classifiers with the overall accuracy rates of 71.84% and 74.3%, respectively. It is discovered that users’ activity on StockTwits overnight significantly positively correlates to the stock trading volume the next business day. The collective sentiments for afterhours have powerful prediction on the change of stock price for the next day in 9 out of 15 stocks studied by using the Granger Causality test; and the overall accuracy rate of predicting the up and down movement of stocks by using the collective sentiments is 58.9%.

In a crisis managers are confronted with a dilemma between an ethical responsibility to respond to victims and their fiduciary responsibility to protect shareholder’s wealth. This study provides empirical evidence that a company apology made during a crisis can have a positive or negative effect on stock price depending on the level of responsibility for a crisis born by the firm. We use Coombs’ (2007) Situational Crisis Communication Theory to classify crises and appropriate re-sponse type for 235 unique crises between 1983 and 2013. We use event study methodology to study the effect of an apology on returns. The results show that managers apologizing to those affected for a victim or accidental crisis jeopardize shareholder wealth; however offering an apology for a preventable crisis offsets this negative effect.

Šiandieniniu globalizacijos ir modernių technologijų laikotarpiu nebeliko neprieinamų rinkų. Kapitalo srautai tapo tokiais mobiliais, kad per keletą valandų kapitalą galima perkelti iš vienos rinkos į kitą. Informacinių technologijų pagalba informacija tapo prieinama kiekvienam vartotojui. Besivystančios Centrinės ir Rytų Europos akcijų rinkos per paskutinius penketą metų netik pritraukė daug investuotojų dėmesio, bet užtikrino didelį investicijų pelningumą. Vidurio Balkanų akcijų rinkos dar nepažįstamos, tačiau laikomos labai perspektyviomis, didelės viltys siejamos su Europos sąjungos investicijomis ir politinės sistemos stabilumo užtikrinimu. Darbo objektas – Vidurio Balkanų regiono valstybių, Kroatijos, Serbijos, Bosnijos ir Hercegovinos akcijų rinkos. Darbo tikslas – įvertinti Vidurio Balkanų regiono valstybių, Kroatijos, Serbijos ir Bosnijos ir Hercegovinos makro ir mikro aplinką investicijoms akcijų rinkose, patikrinti akcijų portfelio optimizavimo teorijos pritaikymo galimybes praktikoje, esant skirtingoms rinkos tendencijoms. Siekiant nurodyto tikslo reiks išspręsti tokius pagrindinius uždavinius: • Išanalizuoti Vidurio Balkanų regiono valstybių makroekonominius rodiklius; • Apžvelgti verslo aplinką makro lygiu; • Įvertinti prekybos vertybiniais popieriais galimybes ir apribojimus, prekybos mastą; • Įvertinti akcijų rinkos pelningumą ir rizikingumą; • Atrikti tinkamiausias akcijas optimaliam akcijų portfeliui sudaryti pagal V. Šarpo metodiką; • Sudaryti šešis akcijų... [toliau žr. visą tekstą] / There are no inaccessible stock markets in these technology and globalization modern-days. Financial capital is very mobile, during several ours financial capital can be transferred from one market to another. Using information systems, new modern technologies, information is accessible for all users. Central and East Europe stock markets during five years were very attractive for investors, because the level risk of investments and profit was appropriate. Central Balkan stock markets are new area for investors and speculators. There is big positive influence from European Union to stabilize political and economical situation in Balkans. This is reason to trust that investments are safety and can be profitable. The mane purpose is to evaluate macro and micro environment for investments in stock market of Central Balkan region countries, Croatia, Serbia, Bosnia and Herzegovina and verify optimal stock portfolio theory (W. Sharpe) in practice, when market is in growing and downgrade trends. There are tasks to find the answers to the mane goal: • To make analysis for macro economical indicators of Central Balkan region countries; • To make business environmental review in macro level; • To evaluate opportunities and limitations to trade securities in stock markets; • To evaluate stock markets risk and profit; • To separate stocks for optimal stock portfolio construction using W. Sharpe model; • To make six stock portfolios when stock market is in growing and downgrade trends.; •... [to full text]

This thesis seeks to address three important issues relating to the efficient functioning of the Istanbul Stock Exchange. In particular the thesis seeks to answer the following questions 1. What makes markets informationally efficient or inefficient? 2. Has increased stock market volatility had an impact on the equity risk premium and the cost of equity capital to firms? and 3. How is it possible to reconcile the view that markets are weak form efficient and technical analysis is a pervasive activity in such markets? Unlike previous studies, this thesis seeks to examine the issue of efficiency when institutional features specific to the market under investigation are taken into account. Specifically, the thesis adopts a testing methodology which enables us to recognize possible non-linear behaviour, thin trading and institutional changes in testing market efficiency. The results from this investigation show that informationally efficient markets are brought about by improving liquidity, ensuring that investors have access to high quality and reliable information and minimising the institutional restrictions on trading. In addition, the results suggest that emerging markets may initially be characterised as inefficient but over time, with the right regulatory framework, will develop into efficient and effective markets. The second important issue to be examined in this thesis concerns the impact of regulatory changes on market volatility and the cost of equity capital to firms. It is not sufficient to simply examine whether volatility has increased following a fmancial market innovation such as changes in regulation. Rather, it is necessary to investigate why volatility has changed, if it has changed, and the impact of such a change on the equity risk premium and the cost of equity capital to firms. Only then can inferences be drawn about the desirability or otherwise of innovations which bring about increases in volatility. Surprisingly, these issues have not been addressed in the literature. The evidence presented here suggests that the innovations which have taken place in the ISE have increased volatility, but also improved the pricing efficiency of the market and reduced the cost of equity capital to firms. Finally, the thesis tries to identify the conditions under which weak-form efficiency is consistent with technical analysis. It is shown that this paradox can be explained if adjustments to information are not immediate, such that market statistics, in particular statistics on trading volume contain information not impounded in current prices. In this context technical analysis on volume can be viewed as part of the process by which traders learn about fundamentals. Therefore, the thesis investigates the issue whether studying the joint dynamics of stock prices and trading volume can be used to predict weakly efficient stock prices. In summary, the findings of this thesis will be of interest to international investors, stock market regulators, firms raising funds from stock markets and participants in emerging capital markets in general. The implication of the results presented here is that informational efficient emerging markets are brought about by improving liquidity, ensuring that investors have access to high quality and reliable information and minimising the institutional restrictions on trading. In addition, the evolution in the regulatory framework of, and knowledge and awareness of investors in, emerging markets may mean that they will initially be characterised by inefficiency, but over time will develop into informational efficient and effectively functioning markets which allocate resources efficiently. In addition, the results of this thesis have important implications, for emerging markets in general, in identifying the regulatory framework that will achieve efficient pricing and a reduction in the cost of equity capital to firms operating in the economy.

This thesis investigates the pricing relationship between the FTSE 100 Stock Index and the FTSE 100 Stock Index futures market. We develop and apply a framework in which it is possible to evaluate whether or not markets can be said to function effectively and efficiently. The framework is applied to both the daily and intra-daily pricing relationship between the aforementioned markets. In order to analyse the pricing relationship within days, we develop a new method to remove the effects of nonsynchronous trading from the FTSE 100 Index. We find that on a daily basis the markets generally function effectively, although this does not carryover to the intra-daily pricing relationship. This is especially true during the October 1987 stock market crash, where it is argued that a possible cause of the breakdown lies with the stock market. If this is the case, then any regulation should be aimed at the stock market, not the stock index futures market.

Background: Since the early 60’s, the CAPM or Capital Asset Pricing Model, has been an invaluable tool for assessing an asset's expected return, assuming that the asset is added to an already well-diversified portfolio of assets. CAPM theory assume that the unsystematic risk can be diversified and that the systematic, market-specific, risk is determined by the Beta value, from the Greek β. An investor who takes big risks expect higher returns. One of the CAPM’s basic assumptions is that disruption in the market is not taken into account. This assumption may lead to results that do not correspond to reality. Objective: This study examined the relationship between systematic risk, and return on a stable and volatile market. Methodology: The study was performed using a quantitative research with secondary data, in which 30 companies listed on the OMX 30 on the Stockholm stock exchange was studied. The investigation period was from 2003 to 2012 and was divided into three parts. Using the statistics program SPSS and Excel the data required to answer the purpose of the essay was calculated. Results: The analysis of the first time period between 2003 and 2007 showed that there was a statistically significant relationship between beta value and the average return for the period. The second time period between 2008 and 2012, which was characterized by an extremely volatile stock market, showed different results. The result of this period showed no statistical relationship existed when the market was characterized by high volatility. The third and final period between 2003 and 2012, which was a combination of a stable and a volatile market. The results for this period showed no significant association between beta value and average returns. The conclusion of this study is therefore that the CAPM model to assess an asset's return fails when the market is unstable, e.g. due to a financial crisis. To compensate for this error that is built into the model, one should therefore use alternative models, or revised versions of the CAPM, if the aim is to produce data in a realistic way that can be used as basis for investment decisions. / Bakgrund: Sedan början av 60-talet har CAPM, eller Capital Asset Pricing Model, varit ett ovärderligt instrument för att bedöma en tillgångs förväntade avkastning, där man antar att tillgången läggs till i en redan väldiversifierad portfölj av tillgångar. CAPM teorin antar vidare att den osystematiska risken diversifieras bort samt att den systematiska, marknadsspecifika, risken bestäms med hjälp av Beta-värdet, från grekiskans β. En investerare som tar stora risker förväntar sig högre avkastning. Ett av CAPM:s grundantaganden är att störningar på marknaden inte tas hänsyn till. Detta antagande kan leda till resultat som inte stämmer överens med verkligheten.   Syfte: I denna studie undersöktes sambandet mellan systematisk risk, samt avkastning på en stabil respektive volatil marknad. Metod: Undersökningen genomfördes med en kvantitativ forskningsmetodik med sekundära data där 30 bolag noterade på OMX30 på stockholmsbörsen studerades. Undersökningsperioden var mellan 2003 till 2012 och delades upp till tre delar Med hjälp av statistikprogrammet SPSS samt Excel beräknades nödvändiga data för att svara på uppsatsens syfte. Resultat: Analysen av den första tidsperioden mellan 2003-2007 visade att det förelåg ett statistiskt signifikant samband mellan betavärdet och den genomsnittliga avkastningen för perioden. Den andra tidsperioden mellan 2008-2012, som kännetecknades av en mycket volatil aktiemarknad, visade annorlunda resultat. Resultatet av denna tidsperiod visade att inget statistiskt samband förelåg när marknaden kännetecknades av en hög volatilitet. Den tredje och sista och perioden mellan 2003-2012, som alltså var en kombination av en stabil och en volatil marknad. Resultatet för denna tidsperiod visade inget signifikant samband mellan betavärdet och den genomsnittliga avkastningen. Slutsatsen av denna studie blir därmed att CAPM som metod för att bedöma en tillgångs avkastning fallerar när marknaden är ostabil, t.ex. beroende på en finanskris. För att kompensera för detta fel som är inbyggt i modellen bör därför alternativa modeller, eller justerade versioner av CAPM, användas om syftet är att ta fram data som på ett verklighetstroget sätt kan vara underlag för investeringsbedömningar.

The objective of the study is to analyze the effects of two breakpoints on the relationships of Istanbul Stock Exchange with the European stock markets and on the relationships among these European stock markets to increase the economic integration. The breakpoints are the execution of the Customs Union Agreement of Turkey with the European Union in 1/1/1996 and the introduction of the Euro in 1/1/1999. While both breakpoints have effects on Turkey&rsquo / s economic relations, the European Union countries are expected to be influenced by only the introduction of the Euro. Stock market indices provided by DataStream is utilized. The statistical techniques used include the correlation and cointegration analysis. Results indicate that when examined on pair wise basis Turkish stock market has more liaisons with the European stock markets, in general, after the Customs Union / but less liaisons after the conversion to Euro. However, when examined as a group, the cointegration result finds the Euro as influential as the Customs Union. Alternatively, the European stock markets have decreasing integrations as a result of correlation analysis after the Euro, but it is an influential breakpoint according to cointegrating structures.

Doctor of Philosophy / The motivation for the research presented in this thesis stems from the recent availability of high frequency limit order book data, relative scarcity of studies employing such data, economic significance of transaction costs management, and a perceived potential of data mining for uncovering patterns and relationships not identified by the traditional top-down modelling approach. We analyse and build computational models for order submissions on the Australian Stock Exchange, an order-driven market with a public electronic limit order book. The focus of the thesis is on the trade implementation problem faced by a trader who wants to transact a buy or sell order of a certain size. We use two approaches to build our models, top-down and bottom-up. The traditional, top-down approach is applied to develop an optimal order submission plan for an order which is too large to be traded immediately without a prohibitive price impact. We present an optimisation framework and some solutions for non-stationary and non-linear price impact and price impact risk. We find that our proposed transaction costs model produces fairly good forecasts of the variance of the execution shortfall. The second, bottom-up, or data mining, approach is employed for trade sign inference, where trade sign is defined as the side which initiates both a trade and the market order that triggered the trade. We are interested in an endogenous component of the order flow, as evidenced by the predictable relationship between trade sign and the variables used to infer it. We want to discover the rules which govern the trade sign, and establish a connection between them and two empirically observed regularities in market order submissions, competition for order execution and transaction cost minimisation. To achieve the above aims we first use exploratory analysis of trade and limit order book data. In particular, we conduct unsupervised clustering with the self-organising map technique. The visualisation of the transformed data reveals that buyer-initiated and seller-initiated trades form two distinct clusters. We then propose a local non-parametric trade sign inference model based on the k-nearest-neighbour classifier. The best k-nearest-neighbour classifier constructed by us requires only three predictor variables and achieves an average out-of-sample accuracy of 71.40% (SD=4.01%)1, across all of the tested stocks. The best set of predictor variables found for the non-parametric model is subsequently used to develop a piecewise linear trade sign model. That model proves superior to the k-nearest-neighbour classifier, and achieves an average out-of-sample classification accuracy of 74.38% (SD=4.25%). The result is statistically significant, after adjusting for multiple comparisons. The overall classification performance of the piecewise linear model indicates a strong dependence between trade sign and the three predictor variables, and provides evidence for the endogenous component in the order flow. Moreover, the rules for trade sign classification derived from the structure of the piecewise linear model reflect the two regularities observed in market order submissions, competition for order execution and transaction cost minimisation, and offer new insights into the relationship between them. The obtained results confirm the applicability and relevance of data mining for the analysis and modelling of stock market order submissions.