02. Master's Thesis
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Item Embargo EXPANDING HORIZONS: ESTABLISHMENT AND OPERATIONALIZATION OF THE SOCIAL INNOVATION HUB(Nazarbayev University Graduate School of Business, 2024-12-09) Zeeshan, Mohammad; Dussupova, Ainagul; Serikbayeva, AkmaralEXECUTIVE ABSTRACT This academic paper presents a comprehensive investigation into fostering social innovation and entrepreneurship in Central Asia, with a primary focus on the launch and establishment of the Social Innovation Hub (SIH) in Kazakhstan. The project envisions the SIH as a pioneering platform dedicated to addressing socio-economic challenges such as unemployment, inequality, and lack of entrepreneurial support by creating an ecosystem that encourages innovative problem-solving and sustainable development. At the heart of this initiative is the formation of an international collaboration and knowledge partnership with a globally recognized institution. This partnership aims to facilitate the sharing of resources, provide capacity-building support, and co-develop programs designed to promote social innovation and entrepreneurship. Through this collaboration, the SIH will gain access to global expertise and best practices, ensuring its alignment with international standards while addressing the unique challenges of the region. Another key element of this project is organizing an annual Eurasian-level summit to serve as a platform for dialogue and collaboration among diverse stakeholders, including business leaders, investors, government officials, academics, and representatives of civil society. This summit aims to forge partnerships, stimulate investment, and build a cohesive community committed to advancing social entrepreneurship. The summit will also be instrumental in positioning Kazakhstan as a regional hub for social innovation. The paper also emphasizes the importance of forging academic partnerships with universities to embed social innovation and entrepreneurship in their curricula. By incorporating these concepts into formal education, the project seeks to nurture a new generation of change-makers equipped with the skills and knowledge to create impactful social projects. These initiatives are complemented by the establishment of mentorship programs and incubation facilities to provide practical training and support for budding social entrepreneurs. A cornerstone of the SIH initiative is its financial sustainability plan. A dual-revenue model is proposed, comprising renting out facilities and offering training programs. This model ensures the hub’s self-sufficiency in managing operational expenditures and working capital. Financial analyses, including metrics like Net Present Value (NPV), Internal Rate of Return (IRR), and payback periods, validate the model’s viability. While training programs demonstrate high profitability, renting operations require optimization in terms of occupancy rates and cost efficiency to maximize their contribution. This paper further integrates strategic analyses using frameworks such as PESTEL, VRIO, and SWOT to evaluate the operational and strategic positioning of SIH. The findings underscore the potential of SIH to catalyze systemic change in the region by empowering individuals, building institutional capacity, and fostering collaboration. By addressing key challenges and leveraging the recommendations outlined, the SIH is poised to serve as a model for similar initiatives in Central Asia and beyond, driving a wave of social innovation and sustainable development.Item Open Access SERIAL ACQUIRERS AND LONG-TERM STOCK PRICE REACTIONS(Nazarbayev University Graduate School of Business, 2023-12-11) Malikova, AnelThis thesis explores the long-term impact of serial acquisitions on acquirers' stock performance, focusing on UK and European companies from January 2000 to August 2024. Using event study methodologies, including event dummy regressions and a modified Almon-lag approach, the study uncovers patterns in stock price behavior following acquisitions. The findings reveal that while UK acquirers experience immediate positive market reactions, European acquirers, particularly in Milan and Euronext, show prolonged but delayed positive effects. Market factors consistently influence excess returns, emphasizing the role of broader market dynamics. However, industry-level analysis highlights significant heterogeneity, with some results constrained by sample sizes. This research provides valuable insights into the stock price dynamics of serial acquirers, offering implications for corporate growth strategies and financial markets.Item Open Access MARKET RESEARCH ON BACHELOR OF BUSINESS ADMINISTRATION DUAL DEGREE LAUNCH AT NAZARBAYEV UNIVERSITY GRADUATE SCHOOL OF BUSINESS(Nazarbayev University Graduate School of Business, 2024-12) Temirkhanova, Aruzhan; Sybanbayeva, Aruzhan; Tilesheva, Ainur; Flores, Wendoly B.The research was conducted to analyze the demand for the Bachelor of Business Administration dual degree at Nazarbayev University Graduate School of Business (NUGSB) in partnership with the Hong Kong University of Science and Technology. It aimed to identify the target market, understand the program demand, and develop possible marketing solutions to enhance its communication with customers. Key findings included the university's choice and decision-making process and the program’s appeal. However, the affordability and novelty of the program were seen as the main challenges. The recommendations included digital marketing enhancement, the establishment of partnerships with companies and counselors, and higher student engagement. Ultimately, the target market (high-achieving students from financially sustainable families in Astana, Almaty, Shymkent, and Aktau) and the level of demand (low with the potential to increase) were defined.Item Embargo DIVIDEND POLICY AND STOCK PRICE PERFORMANCE: EVIDENCE FROM THE KAZAKHSTAN STOCK EXCHANGE(Nazarbayev University Graduate School of Business, 2024-12-12) Shynatay, ZhassulanTheoretically, the publication of dividends does not have any impact on the financial position of the company, since capitalization and resources remain unchanged. Nevertheless, world practice shows that the market reacts to stock publications about the payment of dividends. This study performed an analysis of the impact of the publication of payments and the payment of dividends by Kazakhstani companies on the KASE and LSE trading exchanges. The study found that for financial companies an announcement of dividend increase positively impacts the stock prices and investors experience positive abnormal returns. However, for non-financial companies increase in the amount of dividends lead to negative abnormal returns which means drop in the price of stocks. Overall the market reacts negatively to the announcement of dividends.Item Embargo INCORPORATING GOOGLE TRENDS AS BIG DATA FOR ENHANCED INFLATION FORECASTING: EVIDENCE FROM KAZAKHSTAN(Nazarbayev University Graduate School of Business, 2024-12-11) Beisenbek, RakhatAccurate inflation forecasting is essential for policymakers and businesses, allowing for informed decision-making and economic stability. Most historical forecasting methods are based on a few key macroeconomic factors while leaving a wide variety of more detailed data from the big data sources unused. This paper aims to analyze the performance of using Google Trends data on improving the inflation forecast of Kazakhstan and compare the result with the traditional macroeconomic models. The research develops two primary models: a baseline model that includes conventional macroeconomic indicators such as GDP growth, oil prices, NEER, and inflation expectations, and an enhanced model that integrates Google Trends data for key terms like "inflation," "GDP," and "exchange rate." These data are preprocessed with standardization, lagging, and percentage change transformations. Machine learning techniques, specifically random forest and gradient boosting regressors, are applied to evaluate model performance. Statistical validation includes Likelihood Ratio tests for out-of-sample density forecast accuracy, as well as the Mean Squared Error (MSE), Mean Absolute Error (MAE) evaluation metrics calculation, Mincer-Zarnowitz regression for bias, and the Diebold-Mariano test for forecasting accuracy. Findings show that incorporating the set of variables of Google trends improves the forecasting accuracy of the enhanced model by making relatively small MSE and MAE compared to the baseline. The Likelihood Ratio test supports the improvement of the models for density forecasting, and in terms of feature importance, Google Trends data turn out to be critical for the enhanced model. While the result of the Diebold-Mariano test turned out to show the marginal significance, extending the dataset period and applying advanced techniques further maintained the robustness of the enhanced model. This research proves that Google Trends as a big data contributes to enhancing the accuracy of the inflation forecasts for developing economies.Although sentiment analysis was initially considered, it was excluded from the study due to data limitations in Google news and the absence of an access tokens for media sources like Facebook.Item Embargo TOTAL FACTOR PRODUCTIVITY IN KAZAKHSTAN'S SMALL AND MEDIUM ENTERPRISES (SME) SECTOR(Nazarbayev University Graduate School of Business, 2024-12) Nuraliyeva, MizhgonaThis study investigates the key drivers of Total Factor Productivity (TFP) in small and medium enterprises (SMEs) in Kazakhstan, focusing on a combination of firm-level data (2011–2023) and advanced econometric methods. TFP, which is a measure of efficiency and innovation, is analyzed using Olley-Pakes (OP), Levinsohn-Petrin (LP), Ackerberg-Caves-Frazer (ACF), and kernel-based learning techniques (KLT) in this paper. Exchange rate shocks serve as instrumental variables to address endogeneity concerns and explore the impact of materials, capital wage bill, energy costs, firm size, and other inputs on productivity. The results reveal that firm size and wage bills positively influence TFP under specific conditions, whereas inappropriate use of energy and capital can have negative influence on productivity. The use of each method helps to analyze the estimation approaches properly, providing a clear understanding of TFP dynamics. To be able to proceed with practical policy recommendations, counterfactual simulations of wage bill reductions were created. This research contributes to the existing literature by focusing on advanced methodologies to estimate TFP and providing practical policy recommendations to enhance SME productivity in Kazakhstan.Item Open Access HOW IS KAZAKHSTAN’S STOCK MARKET RESPONDING TO MONETARY AND FISCAL POLICY SIGNALS?(Nazarbayev University Graduate School of Business, 2024-12-12) Nashirali, AltynayThis thesis investigates the impact of monetary and fiscal policies on stock market performance in Kazakhstan, utilizing a Structural Vector Autoregressive (SVAR) framework. The study focuses on key monetary and fiscal policy instruments, such as the base rate and TONIA, money supply, government expenditures, and their relationship with stock market returns. The results suggest that the spread between the base rate and TONIA significantly influences stock market performance, which indicates that market participants respond to liquidity imbalances. Fiscal policy does not have a significant impact on the stock market, potentially due to the pro-cyclical nature of fiscal policy in Kazakhstan. The study also highlights Kazakhstan’s vulnerability to external oil price shocks. Overall, findings highlight the challenges of weak policy transmission mechanisms in emerging markets and suggest that improving policy coordination, enhancing fiscal discipline, and diversifying the economy are crucial for improving policy transmission to the equity market.Item Embargo THE IMPACT OF EXCHANGE RATE REGIME CHANGES ON INFLATION AND ECONOMIC GROWTH: EVIDENCE FROM MEXICO, TURKEY, RUSSIA, AND KAZAKHSTAN(Nazarbayev University Graduate School of Business, 2024-12) Bageyi, Maolidi; Yeerken, ReyilaThe research team used a vector autoregression (VAR) model to evaluate the impact of changes in exchange rate regimes on inflation and economic growth in Mexico, Turkey, Russia and Kazakhstan during the analysis period. The study includes multiple endogenous variables, including exchange rate (Er), consumer price index (CPI), gross domestic product (GDP) and trade balance (TB), as well as exogenous variables such as oil prices (OIL) and the US Federal Reserve interest rate (IFED). The study used impulse response functions (IRFs) and forecast error variance decomposition (FEVD) to analyze the short-term and long-term responses of inflation and economic growth to exchange rate shocks. The results reveal the impact and role of exchange rate changes on GDP, CPI and trade balance. Based on these data analysis results, the study recommends a gradual transition to a floating exchange rate regime; maintaining adequate reserves and intervening when necessary; strengthening regional and international cooperation to achieve export diversification and improve competitiveness.Item Open Access EVALUATION OF THE FORECASTING ABILITY OF RISK-NEUTRAL DENSITY IN BITCOIN OPTIONS(Nazarbayev University Graduate School of Business, 2024-12-12) Saparbekov, DiasThis study assesses the out-of-sample forecasting capabilities of risk-neutral density models in Bitcoin options market, with a focus on the Normal Inverse Gaussian (NIG) density. Understanding forward-looking price dynamics becomes critical as cryptocurrencies continue to gain a reputation in financial markets. This research examines how the NIG model, with its capability to capture skewness and kurtosis, compares to the benchmark log-normal (LN) distribution. The analysis applies the likelihood ratio test to evaluate the predictive performance of the models. As a result, NIG model improves the accuracy of tail forecasts, outperforming LN in capturing extreme market movements, which holds implications for risk management and market timing in Bitcoin market.Item Open Access INTERVAL YIELD CURVE ESTIMATION FOR KAZAKHSTAN BETWEEN 2019-2023(Nazarbayev University Graduate School of Business, 2024) Yertayev, DamirThis paper is a continuation of a thesis “Estimation of the term structure of interest rates for Kazakhstan government bonds using modified Nelson-Siegel methodology.” (Issayev&Post, 2019) This paper attempts to build forecast interval estimates of the linearized Nelson-Siegel model replacing TTM with the notion of tenure as it proved to increase the precision of the estimates in the low-liquidity environment of the Kazakhstani bonds market in the abovementioned paper. This work adds to the literature on the topic as there was no extensive research done on the yield curve estimation between 2019 and 2023.Item Embargo THE ECONOMIC IMPLICATIONS OF DIGITAL TENGE ON MONETARY POLICY IN KAZAKHSTAN(Nazarbayev University Graduate School of Business, 2024-12-11) Kalaganova, NurdanaThis paper analyzes the economic implications of Digital Tenge (DT) introduction on the monetary policy of Kazakhstan. The research mainly focuses on formulating suggestions for the cost and distribution of DT. Optimal suggestions are derived by analyzing the effect of various options for cost and possible distribution limitations on economic agents’ welfare. The analysis reports minor positive welfare gains in the case of costless DT (from 0.0010% to 0.0040%) with a slightly higher welfare achieved and cost range possible through allowing only 20% of the population to carry DT.Item Embargo MEASURING HIGH- AND LOW-FREQUENCY STOCK MARKET LIQUIDITY IN A FRONTIER MARKET: THE CASE OF KAZAKHSTAN(Nazarbayev University Graduate School of Business, 2024-12-12) Abdullina, Medina; Mendygaliev, KaiyrbekThis paper investigates the relationship between high-frequency and low-frequency liquidity measures in a frontier market, specifically Kazakhstan. Using one year of trade and quote data from two exchanges – the Astana International Exchange (AIX) and the Kazakhstan Stock Exchange (KASE) – covering eight and nine stocks, respectively, we find that Abdi Ranaldo's daily liquidity measure emerges as the most effective low-frequency proxy for intraday liquidity in this frontier market.Item Open Access THE EFFECT OF MONETARY POLICY REGIME ON THE DEVELOPMENT OF THE ECONOMY(Nazarbayev University Graduate School of Business, 2024-12) Qaiyrzhan, MaqsatThis work investigates how the Kazakhstani economy is affected by the monetary regimes, given the susceptibility to volatile oil prices and foreign capital flows. Dynamic Stochastic General Equilibrium Model (DSGE) was utilized to analyze the effect of shocks on real GDP, consumption, investment, wages, exports, imports, prices, and real exchange rates. Next, the effectiveness of fixed exchange rates, inflation targeting, strict inflation targeting, and hybrid inflation targeting monetary policy regimes in smoothing the impulse of shocks on the above-mentioned variables. The results suggest that hybrid inflation targeting regime has relatively better performance.Item Open Access IS THERE EVIDENCE OF A CARBON PREMIUM IN THE STOCK MARKETS OF EMERGING ECONOMIES?(Nazarbayev University Graduate School of Business, 2024-12-12) Kessikbay, AruzhanThis thesis aims to determine the existence of carbon premium in the stock markets of emerging economies that have different financial and regulatory systems than the developed markets. The current study employs portfolio sorting and panel regression analyses to examine the linkage between stock returns and carbon emissions with the help of absolute levels and intensity of emissions. The findings of this study reveal that intensity of emissions as a size matched variable is a better explanatory factor of returns than the levels of emissions. While brown portfolios generally outperform green portfolios, the carbon premium varies across countries, being significant in some (e.g., Brazil) and absent in others. These findings offer insights for sustainable investment strategies and policymaking in emerging markets.Item Open Access UTILIZATION OF MACHINE LEARNING FOR EMPIRICAL ASSET PRICING IN EMERGING MARKETS(Nazarbayev University Graduate School of Business, 2024-12-12) Adilov, DastanWe perform Principal Component Regression (PCR) analysis to predict cross-sectional stock returns in emerging market economies. As a benchmark comparison, we employ OLS models and demonstrate predictive power of the machine learning based PCR model. We utilize 64 firm characteristics to determine the most significant predictors for the emerging market countries as well as for individual countries. The results, demonstrate predictive power of the PCR model over the linear regression model, showing consistent results in both the country-specific analysis and in the overall analysis of the emerging market. The most important set of predictors throughout the analysis proved to be book-to-market, sales-to-price, leverage (lev), cash flow-to-price (cfp), dividends (dy), and gross profitability (gma).Item Embargo TRANSITION RISK PREMIUM(Nazarbayev University Graduate School of Business, 2024-12-12) Rustemova, TumarayThis study explores the relationship between climate exposure measures and the cross-section of emerging market companies' returns. It focuses on 1,370 companies from 24 emerging market countries, including Kazakhstan. By merging two unique datasets from Refinitiv Eikon on corporate fundamentals and Sautner et al. (2023) on exposure measures, constructed from earnings call transcripts, for the 2002-2023-year period, the study uncovers a meaningful discovery: the higher the overall exposure measure which incorporates opportunities, regulatory frameworks, sentiment, and physical measures related to climate change, the higher the returns, even when controlling for the size, book-to-market, and other return determinants. This finding suggests a significant transition risk premium. This premium, distinct from carbon risk premium, reflects investors’ trust, reward, and compensation for firms that actively strive to mitigate climate risks and innovate to meet sustainability standards. It is interesting to note that opportunity and physical exposure measures related to climate change have zero effect on stock returns, indicating their uncertain, long-term, and localized nature. Importantly, these findings serve as evidence for the growth potential of emerging market countries considering the challenges of transitioning to a low-carbon economy. This research is important because it posits the significance of incorporating climate risk management into financial plans to assure investor confidence and sustainable growth.Item Open Access EFFECT OF SPOT AND FUTURES PRICES OF CRUDE OIL ON THE STOCK MARKET RETURN OF KAZAKHSTAN(Nazarbayev University Graduate School of Business, 2024-12-12) Zhandossay, BakytThis thesis investigates the relationship between crude oil spot prices, crude oil futures prices, interest rates and stock market return of Kazakhstan, which is an oil exporting country. ARCH family regressions along with VAR and IRF models used to evaluate the impact of oil prices, revealed that both spot prices and futures prices of crude oil have a significant positive effect on the stock market returns, while interest rates predominantly influence the volatility of stock market gains. Paper also examines how the market responds to shocks in oil prices and interest rates. Furthermore, analysis of the asymmetric effect of oil prices showed that negative shocks in oil prices had a higher impact on the market volatility, compared to the positive shocks. The findings in this thesis may prove to provide valuable insights to the behavior of the stock market of Kazakhstan and its relationship with crude oil prices that can be utilized by policymakers, investors and portfolio managers.Item Embargo RETAILER HETEROGENEITY IN OPTIMAL INFLATION IN KAZAKHSTAN(Nazarbayev University Graduate School of Business, 2024-12-11) Argynbek, AselThis paper studies the retailer heterogeneity in optimal inflation in Kazakhstan. Adam and Weber's (2022) relative price trend model is applied to AC Nielsen Urban Kazakhstan data for the 2019-2022 period. The results highlight significant variations in optimal rates across outlets, varying from -0.79 to 2.13%, suggesting the importance of retailers in estimating the national-level inflation rate. Also, the paper calculated national-level inflation in two ways: 1) by aggregating prices using equal weights for outlets and 2) by aggregating scanner data by weighting prices using product categories' expenditure weights for given outlets. Two approaches generate 4.9% and 1.6% optimal rate, respectively. This shows the importance of accounting for the expenditure weights of retailers in tailoring optimal inflation, and a uniform target may only partially capture pricing behavior across outlets.Item Embargo EMPIRICAL ASSET PRICING: SUSTAINABLE INVESTING IN EMERGING MARKET(Nazarbayev University Graduate School of Business, 2024-12-12) Duolikun, KelanThis thesis explores the potential role for sustainable investing and in emerging markets more broadly, while looking at how environmental, social and corporate governance (ESG) factors affect asset pricing. The study takes a look at how a relative greenness score, which is derived from the Eikon data from 2014 to 2024, perform green and brown portfolios across industries and countries. The results indicate brown portfolios outperform green portfolios in terms of cumulative returns and there is increasing interest in ESG practice in emerging markets. The performance of green-minus-brown (GMB) portfolios cannot be explained fully by traditional asset pricing models, suggesting the use of alternative models. Overall, this research is filling a substantial gap in research on sustainable investing by exploring the challenges and opportunities of sustainable investing in emerging markets, which have higher geographical risks.Item Open Access ANALYZING BOND YIELD SPREAD DYNAMICS IN KAZAKHSTAN AND RUSSIA: A STUDY AMID REGIONAL UNCERTAINTIES(Nazarbayev University Graduate School of Business, 2024-12-12) Mashirapov, DarkhanThis thesis examines the determinants of bond yield spreads between corporate and government bonds with maturities of 1, 5, and 10 years in Kazakhstan and Russia. The study utilizes regression analysis to explore how macroeconomic factors and their lags influence these spreads, providing insights into the dynamics of fixed-income markets in both countries. Key explanatory variables include growth rates, macroeconomic ratios such as gross international reserves to GDP, and exchange rate volatilities, among others. A significant component of this research focuses on the geopolitical and economic impact of the Russian invasion of Ukraine, captured through the inclusion of a war dummy variable to assess shifts in bond market behavior post-February 2022. In addition to analyzing bond spreads within each country, the study investigates cross-country dynamics by modeling the differences between Russia's corporate bond index yield and Kazakhstan's corporate bond index yield. To capture the long-term equilibrium relationship between these spreads and macroeconomic determinants, cointegration techniques are used. The findings suggest that macroeconomic indicators, such as GDP growth rates, international reserve ratios, and exchange rate movements, play a critical role in shaping bond yield spreads. Moreover, the results indicate that the Russian invasion of Ukraine significantly altered the determinants and behavior of bond spreads, highlighting the sensitivity of financial markets to geopolitical events. This study contributes to the understanding of bond market dynamics in emerging economies and offers a framework for policymakers and investors to evaluate risk and return in the presence of economic and geopolitical shocks.