Representation and learning schemes for sentiment analysis.

This thesis identifies four novel techniques of improving the performance of sentiment analysis of text systems. Thes include feature extraction and selection, enrichment of the document representation and exploitation of the ordinal structure of rating classes. The techniques were evaluated on four sentiment-rich corpora, using two well-known classifiers: Support Vector Machines and Na¨ıve Bayes. This thesis proposes the Part-of-Speech Pattern Selector (PPS), which is a novel technique for automatically selecting Part-of-Speech (PoS) patterns. The PPS selects its patterns from a background dataset by use of a number of measures including Document Frequency, Information Gain, and the Chi-Squared Score. Extensive empirical results show that these patterns perform just as well as the manually selected ones. This has important implications in terms of both the cost and the time spent in manual pattern construction. The position of a phrase within a document is shown to have an influence on its sentiment orientation, and that document classification performance can be improved by weighting phrases in this regard. It is, however, also shown to be necessary to sample the distribution of sentiment rich phrases within documents of a given domain prior to adopting a phrase weighting criteria. A key factor in choosing a classifier for an Ordinal Sentiment Classification (OSC) problem is its ability to address ordinal inter-class similarities. Two types of classifiers are investigated: Those that can inherently solve multi-class problems, and those that decompose a multi-class problem into a sequence of binary problems. Empirical results showed the former to be more effective with regard to both mean squared error and classification time performances. Important features in an OSC problem are shown to distribute themselves across similar classes. Most feature selection techniques are ignorant of inter-class similarities and hence easily overlook such features. The Ordinal Smoothing Procedure (OSP), which augments inter-class similarities into the feature selection process, is introduced in this thesis. Empirical results show the OSP to have a positive effect on mean squared error performance

Analysis of the Relationship Between Trade Openness and Economic Growth in Kenya

Given that policy makers and civil society in Kenya disagree on the contribution of openness to economic growth. It is therefore not clear whether trade openness does or does not promote growth in the case of Kenya. The purpose of this study was therefore to analyze relationship between trade openness and economic growth in Kenya. This study was modeled on Adam Smith’s absolute advantage theory. The study used correlation research design based on annual time series data spanning 30 years from 1980 – 2009. Data was obtained from the World Development Indicators. The study used Vector Error Correction Mechanism to integrate long run and short run dynamics and Granger causality for directional causality. The results indicated significant positive effect and unidirectional causality between trade openness and economic growth in Kenya, with coefficient of 0.98 implying that 1 % increase in trade openness increases economic growth by 0.98% respectively. Economic growth is significantly error correcting at 34.7% annually. The study concluded that in the long run trade openness promote growth in Kenya. In view of this, the study recommends that the government of Kenya to continue pursuing trade openness policies to increase trade volumes to enhance economic growth. Keywords: Trade Openness, Economic Growth, Keny

FINANCIAL LEVERAGE AND PERFORMANCE OF LISTED FIRMS IN A FRONTIER MARKET: PANEL EVIDENCE FROM KENYA

This paper investigates the relationship between financial leverage and the financial performance of listed firm in Kenya. We use annual data for the period 2007 – 2011. Using various panel procedures, the study finds reasonably strong evidence that financial leverage significantly, and negatively, affects the performance of listed firms in Kenya (ROA, β = - .0438, p = .0350) and Tobin’s Q, β = -.5144, p = .0124). However, financial leverage negative but insignificant effect on ROE, β = -.0176, p = .5765). Unit root test results indicate: all the variables are integrated of order zero (p = .000). Second, because the performance of firms depends on other things than just their financial leverage, we control for the effects of those other variables by including them in our models. In this respect, the findings suggest that asset tangibility (β = .2302, p = .0215) and ownership concentration (β = -.0057 (p = .0353) are important determinants of performance measured in terms of Tobin’s Q. The study concludes that; that financial leverage is an important negative predictor of financial performance measured in terms of ROA and Tobin’s Q; ownership concentration is a pertinent negative predictor of financial performance measured in terms of Tobin’s Q and asset tangibility is a significant positive predictor of performance measured in terms of ROE and Tobin’s Q

IS KENYA’S CURRENT ACCOUNT SUSTAINABLE? A STATIONARITY AND COINTEGRATION APPROACH

The objective of this paper is to examine the sustainability of the current account deficits in Kenya. In this respect, stationarity and Cointegration test was employed to ascertain sustainability of the current account in Kenya between 1970 to 2012.The choice of the set of variables were motivated by the existing theories about the long-run intertemporal budget constraint. Results indicate that Current account is stationary at levels implying that its mean reverting and temporary and that external debt is finite and sustainable. The empirical results suggest that exports and imports are cointegrated with the cointegrating coefficient of 0.21989 which is significantly not equal to one, but equal to zero, implying that the current account was not on the sustainable path indicating a weak form of sustainability. The paper concludes that Current account deficit of Kenya may not be sustainable in the long-run

Causality between Disagregated Energy Consumption and Manufacturing Growth in Kenya: an Empirical Approach

Besides labour and capital, energy is a critical factor of economic production worldwide. In the circumstances, the role that it plays in policy regimes designed for fast and efficient economic growth cannot be overemphasized. However causality between energy consumption and manufacturing growth is not known in Kenya. Therefore, the study provides analyses of causality between disaggregated energy consumption (electricity and petroleum) and manufacturing growth using data from Kenya between 1970-2010. An integration and cointegration test shows that the variables are  and cointegrated. As a result, the granger causality error correction test was conducted and it indicated that there is granger causality from electricity and petroleum consumption to manufacturing in short and long run periods, and bidirectional causality between manufacturing and electricity consumption in both runs. Thus, the manufacturing sector requires electricity for economical operation. On the other hand, the lack of causality from manufacturing to petroleum consumption is attributed to the fact that very few manufacturing industries in Kenya significantly depends on petroleum because of its cost and price volatilities. Fossil energy cost impacts adversely on prices of manufactured products, consequently making Kenya's manufacture to be less competitive in the regional markets. Poor competition is one major reason for the widespread migration of the manufacturing firms to hydro-energy based technologies in Kenya. Therefore, change in manufacturing technology may significantly change petroleum consumption patterns in Kenya. However, given that there are good indications of petroleum potential within the country, the trend may reverse. Key Words: Energy consumption; Manufacturing growth; Cointegration; Granger causality; Keny

OWNERSHIP CONCENTRATION AND FINANCIAL PERFORMANCE OF LISTED FIRMS IN KENYA: AN ECONOMETRIC ANALYSIS USING PANEL DATA

In this study, we use panel methodology comprising 53 firms listed at the Nairobi Securities Exchange to establish the effect of ownership concentration on financial performance of these firms for the period 2007 to 2011. Before empirical estimations were conducted, the data series were subjected to unit root tests to establish their stationarity conditions and where a series is found to be non-stationary at levels, it was differenced until it become stationary. The study findings revealed that on average, firms listed at the Nairobi Securities Exchange enjoy a return on equity and return on assets of about 16.5 percent. The sectors that registered the highest return on equity included insurance, commerce and construction at 20.8 percent, 19.3 percent and 20.1 percent, respectively. On the other hand, the sectors that registered relatively higher return on assets include commerce, telecommunications and manufacturing with average ROA of 23.0 percent, 20.0 percent and 25.4 percent; respectively. The study also found that the highest ownership concentration is 96.310 %, while the lowest is 11.040%, with an average ownership concentration of 64.286 % and variability of 17.292 % implying that the percentage of shares held by those considered as large shareholders range between 96.310 % and 11.040 %, with a mean of 64.286 % and finally the results of correlation analysis revealed non-significant relationship between ownership concentration and performance of firms at the Nairobi Securities Exchange. On the other hand, from the panel regression analysis results, ownership concentration was found to be negatively related to all the three measures of performance in firms listed at the Nairobi Securities Exchange namely ROE, ROA and Tobin’s Q with coefficients of -0.0005, -0.0002 and 0.0057 respectively. The adjusted R squared for the return on equity, return on assets and Tobin’s Q models were 77.32%, 88.52% and 85.94% respectively

CORPORATE SIZE, PROFITABILITY AND MARKET VALUE: AN ECONOMETRIC PANEL ANALYSIS OF LISTED FIRMS IN KENYA

In corporate finance, the size of a firm is a primary factor in determining the success of a firm due to economies of scale. While, previous studies have confined their analyses on either a single industry or a few firms, in this study, we consider a rather comprehensive sample of firms that represent a sufficiently broad range of firm sizes in all sectors of Kenyan economy hence amplifying the importance of the study. Global corporate size literature shows plausable but mixed relationship between firm size, profitability and market value. The effect of corporate size on profitability and market value in a frontier market using panel methodology is unknown. The purpose of this study is to explore the effect of corporate size on profitability and market value of listed firms in Kenya. In this study, data for companies which were active in Nairobi Securities Exchange (NSE) between the years 2010 to 2014 has been used. Unit root test results indicate that all the variables are integrated of order zero (p = .000) meaning that they were stationary at levels. Panel correlation and multiple regression methods are used in the empirical estimations. Results indicate that there is a positive significant relationship between firm size and profitability, that is, return on equity (β = .012, t = 2.585) impying that value that a unit change in firm size leads to an increase in return on equity of firms listed at the Nairobi Securities Exchange of 0.012, all things being fixed whereas firm size insignificantly positively predicts profitability, that is, return on asset (β =.012, t = 1.659). In addition, the results show that corporate size has no statistically significant impact on firm market value (β = -.011, t = -.225) under random effects specification

EXISTING TRENDS IN FOREIGN EXCHANGE RATES OF KENYA’S MAIN TRADING CURRENCIES

Performance of a security market reflects the economic situation of a country as it is affected by both a country’s domestic and foreign economic events. Given the current increased level of cross borders transactions with the value of total exports growing by 25.6% between 2007 and 2008 and imports increasing by 27.4% between the same periods, it was likely that fluctuations in foreign exchange rate market continued to fuel changes in financial markets like Nairobi Securities Exchange market. Since securities markets trade on assets with varying degree of risks, foreign exchange rates fluctuations was believed to be a factor that affect the performance of financial markets. The purpose of this study was to determine the trend of foreign exchange rates fluctuation of Kenya’s main trading currencies, the US Dollar, the Euro and the UK Pound. The study used secondary data collected between the periods January, 2006 to December, 2010 from the Central Bank of Kenya website in establishing the existing trend of foreign exchange rates fluctuation in Kenya. Descriptive statistics, Pearson Product Moment Correlation and Trend Analysis were used in the study. The findings revealed the existence of positive trends in US dollar and the Euro exchange rates and negative trends in UK pound exchange rates. Therefore the study recommended that market players like corporate investors and investment mangers should closely monitor these trends as they are useful in predicting future financial market outcomes