Magister Commercii - MCom / This study analyses the extent to which stock returns provide forecasts of changes in interest rates and inflation for the South African market. The period under investigation, January 1966 - February 1989, is characterised by structural changes in the South African economy, especially in the financial markets. The earnings yield on shares is used as a measure of the return on stocks. Stock returns of 10 specific industries are used in addition to the overall market return. Monthly inflation series were constructed by employing both the Consumer Price Index (CPI) and the Producer Price Index (PPI). Before examining that relationship, tests were done to examine the relationship between nominal stock returns and expected inflation. The relation between the stock market and expected inflation is estimated by using three measures of expected inflation. The results appear to suggest that the stock market reacted positively to expected inflation during the 1966 - 1982 period. Two proxies of expected inflation. Best results inflation are used to were obtained with measure future the Fama-Gibbons measure. In addition, the results suggest that stock returns provide additional information of future inflation to that contained in the Fama-Gibbons and interest rate models. Returns for specific industries, used in this study, appear to provide marginally better forecasts of inflation than the overall market return. The results also suggest that stock returns provide forecasts of changes in interest rates and inflation. There is no evidence that the specific industries used, provide consistent better forecasts of interest rate changes than the overall market.

This thesis addresses the relationship between financial development and CSR performance, based on countries within the EU. The main objective of this thesis is to critically analyse and discuss the impact of financial development on CSR performance, through using ESG performance as a proxy. Additionally, this study aims at analysing the inclusion of institutional factors when examining the relationship. While the issue of how financial development impacts individual sustainability dimensions is quite well-researched, only one study is found to examine the precise relationship between financial development and ESG performance, concluding a positive linkage in Asia. No similar study is found in the region of the EU. We find the relationship to be complex, where various channels of influence are identified when examining ESG dimensions separately. To examine this relationship, we used panel data regression analysis, based on country level data for EU’s individual member states. Our findings show a complex relationship, implying that financial development has various impacts on ESG performance and varies throughout the range of financial development. This is in contrast to previous empirical research regarding the relationship, concluding an overall positive impact. This study provides no evidence that institutional factors affect the relationship between financial development and ESG performance, but argues for the importance of institutional inclusion, due to the identified influence on ESG practices through channels such as governing laws, regulations, norms and culture. Finally, financial development is concluded as an important catalyst to promote ESG performance within the EU. When suggesting any policy implementation, it is important to keep in mind that different countries within the EU may have different needs regarding the most efficient approach to increase ESG.

Employing Vector Error Correction Model (VECM), this dissertation aims to explore the principal influential factors of economic growth from external and internal perspectives. After extensive analysis and previous research, trade openness is the external factor considered, while financial markets and institutions are the internal ones. Based on the dataset of four typical fast-growing emerging economies-- China, India, South Africa and Russian Federation, this study found that there is a significant long-term equilibrium among GDP growth, trade openness, financial markets and institutions in China, and bidirectional causality can be observed between trade openness and GDP growth. Regarding the remaining economies, there are two sets of long-term relationships among these variables, where internal factors concerning financial development are more crucial in these countries, which also significantly affect the trade volumes in the long run. Results from this research indicate that the dominant growth-enhancing factors are closely related with a country's policy, history, and the most importantly, the focus of its development strategy.

Product quality is an often-overlooked factor in the financial analysis of video games. Quality measurements have been proven to work as a reliable predictor of sales while also directly influencing performance in financial markets. If markets are efficient in reflecting new information, perception of video game quality will lead to a rational response. This thesis examines the market reaction to this information set. The release structure in the video game industry allows for a direct observation of the isolated quality effect through third-party reviews. These reviews form an objective measurement of game quality without having other revealing characteristics, as all other information is released prior to these reviews. The possibility to exploit this unique case motivates the analysis through multiple empirical designs. Results from a multivariate regression model show a statistically significant positive effect of higher quality on short-term returns over all models. The release of a lower quality game reduces returns only for high-profile games. Both of these results are confirmed by the results from a rules-based trading strategy. These effects subside in the face of longer holding periods and higher exposure. This thesis finds sufficient evidence that video game quality should be an important factor in the analysis of video game companies. At the same time, these effects are only persistent in the short-time validating an efficient response to new information by financial investors.

Interpreting time varying phenomena is a key challenge in the capital markets. Time series analysis using autoregressive methods has been carried out over the last couple of decades, often with reassuring results. However, such methods sometimes fail to explain trends and cyclical fluctuations, which may be characterized by long-range dependencies or even dependencies between the input features. The purpose of this thesis is to investigate whether recurrent neural networks with LSTM-cells can be used to capture these dependencies, and ultimately be used as a complement for index trading decisions. Experiments are made on different setups of the S&P-500 stock index, and two distinct models are built, each one being an improvement of the previous model. The first model is a multivariate regression model, and the second model is a multivariate binary classifier. The output of each model is used to reason about the future behavior of the index. The experiment shows for the configuration provided that LSTM RNNs are unsuitable for predicting exact values of daily returns, but gives satisfactory results when used to predict the direction of the movement. / Att förstå och kunna förutsäga hur index varierar med tiden och andra parametrar är ett viktigt problem inom kapitalmarknader. Tidsserieanalys med autoregressiva metoder har funnits sedan årtionden tillbaka, och har oftast gett goda resultat. Dessa metoder saknar dock möjligheten att förklara trender och cykliska variationer i tidsserien, något som kan karaktäriseras av tidsvarierande samband, men även samband mellan parametrar som indexet beror utav. Syftet med denna studie är att undersöka om recurrent neural networks (RNN) med long short-term memory-celler (LSTM) kan användas för att fånga dessa samband, för att slutligen användas som en modell för att komplettera indexhandel. Experimenten är gjorda mot en modifierad S&P-500 datamängd, och två distinkta modeller har tagits fram. Den ena är en multivariat regressionsmodell för att förutspå exakta värden, och den andra modellen är en multivariat klassifierare som förutspår riktningen på nästa dags indexrörelse. Experimenten visar för den konfiguration som presenteras i rapporten att LSTM RNN inte passar för att förutspå exakta värden för indexet, men ger tillfredsställande resultat när modellen ska förutsäga indexets framtida riktning.

Over the last five years, the amount of retail investors has increased immensely. Trying to make informed decisions, many of the more active investors look to social media as a source of information. In early 2021, the eyes of the world focused on retail investors as Gamestop, a video game retailing company, experienced an immense price surge over the course of a few weeks on the stock market. This event, among others, lead the SEC (Securities and Exchange Commission) to open up a discussion about the impact of social media on the stock market. It seemed individual social media accounts were able to increase the volatility in a number of different stocks. This study investigates the immediate impact of larger Swedish Twitter accounts on the volatility and price of Swedish small- cap companies. Sentiment analysis and data modeling in the Python programming language were used in order to compare volatility and price changes before and after tweets of different sentiments were made about the companies. Our study was unable to find any correlation between an immediate change in price or an immediate increase in volatility and tweets made, suggesting Swedish finance Twitter accounts have little to no immediate impact on Swedish small- cap companies. / Under de senaste fem åren har antalet privata investerare ökat markant. När privata investerare försöker göra välgrundade investeringsbeslut brukar de ofta använda inlägg på sociala medier som ledstjärna. Tidigt på år 2021 vändes blickarna mot privata investerare när priset på spelåterförsäljningsföretaget Gamestops aktier ökat med flera hundratals procent under bara loppet av några få veckor. Denna prisökning fick SEC (Securities and Exchange Commission i USA) att inleda en diskussion om inverkan av sociala medier på aktiehandeln. Mycket påvisade att individuella konton på sociala medier hade förmågan att öka volatilitet av aktiepriser för vissa bolag. Det här forskningsprojektet ämnar att undersöka den omedelbara inverkan av svenska twitterkonton på pris och volatilitet av pris av svenska småföretags aktier. Sentimentanalys och datamodellering gjordes i programmeringsspråket Python för att jämföra volatilitet och prisändringar innan och efter tweets av olika sentiment gjordes om de olika företagen. Studien lyckades inte visa på korrelation mellan en omedelbar ändring i pris eller omedelbar ökning i volatilitet och gjorda tweets, vilket tyder på att twitterkonton har inget eller väldigt lite inflytande på svenska småföretag.

A wide variety of machine learning algorithms havebeen used to predict stock prices. The aim of this project hasbeen to implement a machine learning algorithm using supportvector regression to predict the stock price of two well knowncompanies—Apple and Microsoft—one day into the future usingthe current day’s stock price, macroeconomic data and microeconomicdata and to compare the prediction error with the differentdata inputs. The results show that the addition of macroeconomicand microeconomic data did not improve the prediction error.This suggests that the macroeconomic and microeconomic dataused in this project does not contain additional information aboutfuture stock prices. The results also show that support vectorregression performs worse than linear regression, however inthis case no definite conclusion can be drawn since only onekernel and a handful of parameter values were considered whentraining and testing the algorithm. However, these results mightalso suggest that using the current day’s data is not sufficient tobe able to predict the non-linear relationships. / Ett flertal maskininlärnings-algoritmer har använts för att förutspå aktiepriser. Målet med det här projektet har varit att implementera en maskininlärnings-algoritm som använder sig av support vector regression för att förutspå aktiepriset av två välkända företag—Apple och Microsoft—en dag in i framtiden genom att använda dagens aktiepris, makroekonomisk data och mikroekonomisk data samt att jämföra prediktionsfelet med dem olika indata. Resultaten indikerar att additionen av makroekonomisk och mikroekonomisk data inte förbättrade prediktionsfelet. Detta antyder att den makroekonomiska och mikroekonomiska data som användes i projektet inte innehåller någon ytterliggare information om framtida aktiepriser. Resultaten indikerade också att linjär regression presterar bättre än support vector regression, men i detta fallet kan ingen definitiv slutsats dras eftersom endast en kernel och ett par parameter-värden användes för att träna och testa algoritmen. Däremot kan dessa resultat också antyda att a inte är tillräcklig för att kunna förutspå dem icke-linjära förhållandena. / Kandidatexjobb i elektroteknik 2021, KTH, Stockholm

Tanzania is among the poorest countries in the world, with most of its population living in rural areas. Like most other developing countries, rural households' access to financial services is very limited. The government has adopted series of economic reform measures since mid-1980s that include financial liberalization. Liberalization of the financial sector facilitated participation of private financial institutions, restructuring of public financial institutions and privatization, elimination of interest rate controls, credit allocation and targeting. In addition, the role of the Bank of Tanzania in supervision and regulation of financial institutions was strengthened. Following the privatization of the financial sector, the number of financial service providers increased and diversified, which include commercial banks, development banks, insurance and social security funds, and capital markets. The role of the central bank was re-defined and strengthened in terms of price stability, supervision and regulation. Although there is an increase in financial sector service providers and products, rural households' access to financial services did not improve. To the contrary access to formal financial services is diminishing significantly, hence making poverty reduction initiatives more difficult. This study analyzed constraints to access to rural financial services, examined its impact on rural households' livelihoods, and recommended appropriate financial sector development strategies. The data for the study were collected from various sources - both primary and secondary. Primary data were collected from selected thirteen villages in Babati and government offices in the district through interviews, focus group discussions, questionnaire, and observation. Secondary information was gathered from documentary sources in the form of reports, records and review of literature. A combination of analytical tools was used - qualitative and quantitative. The study observed that history of rural finance in Tanzania is associated with colonialization of Tanganyika. The German colonial administration was the first to introduce establishment of modern commercial banking in the country in 1905 when the Deutsche Ostafrikanische bank opened a branch in Dar es Salaam. The British colonial administration, after the defeat of Germans in World War I, promoted establishment of commercial banks in Tanganyika in order to support commercialization of the economy. Consequently, German banks were replaced and commercial bank branches were established in other parts of the country. The independent government undertook massive re-organization of the financial sector and much attention was put on agricultural credit. Agricultural credit was organized through specialized agricultural credit organizations that corroborated with state owned commercial banks. However, the co-operative movement were assigned important role in credit administration on the ground as they are closer to the beneficiaries. The financial structure after independence up to the 1990s, when reforms were ushered in, is characterized by state owned financial institutions with pervasive interference. Credit was directed on the basis of the government priorities with little regard to credit worthiness analysis. The National Bank of Commerce (NBC) and Co-operative and Rural Development Bank (CRDB) were the dominant banks that implemented the government monetary policy. Emphasis was put on credit and savings mobilization was neglected. The CRDB operated mostly on managing donor funds meant for rural development. Liberalization of the financial sector was introduced through the Banking and Financial Institutions Act (BAFIA) of 1991 to address the weaknesses observed in the financial sector. It was envisaged to improve access to financial services through enhanced competition, increased and diversified financial products and providers, and improved integration of the financial system. However, assessment of the impact of the financial liberalization has mixed results. While there are distinct expansion in financial institutions, products and services; these are more concentrated in urban areas and accessed mostly by wealthy clients. Consequently, rural households' access to finance is diminishing. On the other hand, most financial institutions continue to employ traditional banking approaches - of insistence on collateral, preference for less risky category of clients, bias towards large loans, and bureaucratic procedures in providing loans. Besides, there are limited initiatives in product innovation, design of appropriate delivery mechanisms, and high interest rates spreads that discouraged potentials borrowers and depositors. As a result of poor access to financial services, most households have strengthened self-financing mechanisms through the informal arrangements. Although, the semi-formal - especially member based financial institutions and some Financial NGOs (FiNGOs) are attempting to correct the financial imbalances, their outreach, products and services are still limited. While there are improvement in supervision and regulation of the financial sector, it must be noted that prudential regulation and supervisions as part of the financial infrastructure if not carefully used, will undermine the efficiency of the financial market. The study concludes that rural households need a variety of financial products that include savings facilities, loans, insurance, leasing, and means of transfer payments. The degree of demand for these products is, however, determined by household's level of poverty, household size, level of education and skills, life cycle needs, and local market opportunities. However, financial sector reforms had little impact on households' livelihoods. Its implementation is associated with an increase in inequalities and poverty. Besides, there is a reduced funding as well as investment in agriculture, which forms the key sector of the economy. Consequently, the performance of the agricultural sector has been declining although its contribution to GDP is still significant. Assessing the supply and demand for rural financial services, it is concluded that rural areas are hardly served by banks hence limiting access to financial services. Prior to liberalization, government owned financial institutions provided limited financial services to rural areas organized through co-operatives and specialized credit agencies. CRDB was responsible for organization of credit for farm inputs, while NBC provided crop finance. In addition, CRDB also facilitated rural development programmes through donor funds. With the liberalization of the financial sector - co-operatives have collapsed, development banks are no longer active, and commercial banks have withdrawn from serving rural areas, thus creating a "supply gap" that is being replaced by informal finance. Furthermore, the study observed that demands for financial services is determined by age of the borrower, household size, and distance from a financial institution, the cost of borrowing that include loan transaction costs plus interest rate charged, bank procedures and conditions, policy and regulatory framework and institutional and infrastructural conditions. The study recommends the following: (i) Continued efforts for establishment of supportive macroeconomic and sectoral policies - financial, fiscal, monetary & rural development - and legal and regulatory framework that facilitates the growth of the rural financial markets, (ii) A facilitative intervention by the government in the development of the financial markets that addresses the national poverty reduction development objective through economic growth is required. The desired actions are those that focus on improvement in demand for financial services, reduced bureaucratic banking conditions, reduced transactions costs, improved infrastructure, and reduction of other structural bottlenecks limiting access to financial services, (iii) Development of appropriate financial institutions and products relevant for the rural sector requires government guidance through policy, development of appropriate financial infrastructure (legal, regulation and information), and incentive mechanisms. (iv) Intervention by the government in institutional and infrastructural development is required so as to facilitate the functioning of markets. There must be purposive investment strategy that supports development of the public infrastructure - such as transport and communication, electricity, security system, and research and development. Institutional development - judiciary machinery, credit bureaus, and property rights and business registry are required. Furthermore, training and capacity building so as to change peoples' mindsets concerning loans and savings mobilization, and (v) There is a need for building up a "New Role" for financial institutions. Financial institutions need to revisit their financial terms and conditions in favor of the development of RFMs, especially in terms of bank conditions, interest rate spreads, demand for collateral, and requirements for addressing the needs of the poor and rural population, Furthermore, financial institutions need to become more innovative in developing new products and services, improvement in organization of rural financial institutions, delivery mechanisms, and establishment of the institutional framework for integration of MFIs into the national financial system in the country. The following areas require further studies: (i) development of realistic rural development strategy that covers, among others, the development of the financial markets, (ii) institutionalization of the rural property ownership rights in order to establish how these can be used productively, through say mortgage, collateral, and/or sale for cash income, and (iii) Mechanisms for enforcement of loan repayments in rural areas - especially the lessons from informal operators. Experiences have shown that under informal credit arrangements, there are few default cases as opposed to formal commercial credit practices. / Development Studies / D. Litt. et Phil. (Development Studies)

This thesis consists of four self-contained papers related to the change of market structure and the quality of equity market. In Paper [I] we found, by using of a Flexible Dynamic Component Correlations (FDCC) model, that the creation of a common cross-border stock trading platform has increased the long-run trends in conditional correlations between foreign and domestic stock market returns. In Paper [II] we study whether the creation of a uniform Nordic and Baltic stock trading platform has affected weak-form information efficiency. The results indicate that the stock market consolidations have had a positive effect on the information efficiency and turnover for an average firm. The merger effects are, however, asymmetrically distributed in the sense that relatively large (small) firms located on relatively large (small) markets experience an improved (reduced) information efficiency and turnover. Although the results indicate that changes in the level of investor attention (measured by turnover) may explain part of the changes in information efficiency, they also lend support to the hypothesis that merger effects may partially be driven by changes in the composition of informed versus uninformed investors following a stock. Paper [III] analyzes whether the measured level of trust in different countries can explain bilateral stock market correlations. One finding is that generalized trust among nations is a robust predictor for stock market correlations. Another is that the trust effect is larger for countries which are close to each other. This indicates that distance mitigates the trust effect. Finally, we confirm the effect of trust upon stock market correlations, by using particular trust data (bilateral trust between country A and country B) as an alternative measurement of trust. In Paper [IV] we present the impact of the stock market mergers that took place in the Nordic countries during 2000 – 2007 on the probabilities for stock price jumps, i.e. for relatively extreme price movements. The main finding is that stock market mergers, on average, reduce the likelihood of observing stock price jumps. The effects are asymmetric in the sense that the probability of sudden price jumps is reduced for large and medium size firms whereas the effect is ambiguous for small size firms. The results also indicate that the market risk has been reduced after the stock market consolidations took place.

There has been much hype in vocational and academic circles surrounding the emergence of web 2.0 or social media; however, relatively little work was dedicated to substantiating the actual concept of web 2.0. Many have dismissed it as not deserving of this new title, since the term web 2.0 assumes a certain interpretation of web history, including enough progress in certain direction to trigger a succession [i.e. web 1.0 → web 2.0]. Others provided arguments in support of this development, and there has been a considerable amount of enthusiasm in the literature. Much research has been busy evaluating current use of web 2.0, and analysis of the user generated content, but an objective and thorough assessment of what web 2.0 really stands for has been to a large extent overlooked. More recently the idea of collective intelligence facilitated via web 2.0, and its potential applications have raised interest with researchers, yet a more unified approach and work in the area of collective intelligence is needed. This thesis identifies and critically evaluates a wider context for the web 2.0 environment, and what caused it to emerge; providing a rich literature review on the topic, a review of existing taxonomies, a quantitative and qualitative evaluation of the concept itself, an investigation of the collective intelligence potential that emerges from application usage. Finally, a framework for harnessing collective intelligence in a more systematic manner is proposed. In addition to the presented results, novel methodologies are also introduced throughout this work. In order to provide interesting insight but also to illustrate analysis, a case study of the recent financial crisis is considered. Some interesting results relating to the crisis are revealed within user generated content data, and relevant issues are discussed where appropriate.