Impact of ROBO Global Robotics and Automation Index ETF on stock market dynamics in emerging economies

This thesis consists of three empirical studies on what drives stock market dynamics. The first empirical study explores the effect of crude oil price changes on the stock market returns of oil-exporting countries and oil-importing countries as well as those of a number of global stock indices. Using the Ordinary Least Squares (OLS) approach as well as the more robust Quantile Regression (QR) approach to explore the relationship between crude oil and stock market dynamics. The empirical findings suggest that the QR approach provides further insights compared to the OLS approach. For instance, the QR approach is able to identify specific quantiles where a significant relation exists. In particular crude oil price increases tend to have a negative impact on the stock market returns for some oil-exporting countries (such as Mexico, Iraq, Ecuador, and Venezuela) and a positive effect for other oil-exporting countries (such as Brazil and Algeria). However, the OLS approach suggests that these relationships are insignificant at the level of the mean. Overall, the empirical findings confirm that the QR approach can reveal more information about the relationship between crude oil price changes and stock market return across different quantiles of their distribution.The second study explores the extent to which implied volatility extracted from commodity markets and developed stock markets can predict the implied volatility of stock markets in BRICS countries. Using daily data from 2011 to 2016 and employing the newly developed Bayesian Graphical Vector Autoregressive (BGVAR) model of Ahelegbey et al. (2016) which does not suffer from over-parameterization and the identification problems associated with traditional VAR frameworks, this study finds that implied volatilities extracted from global and regional stock markets have a significant predictive power over the implied volatilities in BRICS stock markets. However, the predictive power of implied volatility from commodity markets are significant only in the case of South Africa.The third empirical study analyses the relationship between illiquidity and stock market returns in the G7 and BRICS countries. More specifically, this study explore the extent to which the Amihud (2002) illiquidity measure can improve the explanatory power of three commonly used asset pricing models, namely the Capital Asset Pricing Model (CAPM), the Fama-French three-factor model and the Carhart four-factor model. The empirical analysis is based on 15 years of monthly data on the returns of seven stock portfolios: 100 largest companies (Largest100), small value (S/V), small neutral (S/N), small growth (S/G) stocks, big value (B/V) stocks, big neutral (B/N) stocks, and big growth (B/G) stocks. The findings suggest that incorporating illiquidity as an additional factor results in a significant improvement in the explanatory power of these asset pricing models across several of the sample countries (8 countries in the case of the CAPM and Carhart four-factor model, and 6 countries in the case of the Fama-French three-factor model). For example, in the US adding illiquidity to the CAPM leads to an increase of the goodness of fit by 2.6% in the B/V portfolio, and for the Fama-French three-factor model the goodness of fit increases by up to 3% in all portfolios Moreover, the goodness of fit increases in all portfolios in the US by adding illiquidity to the Carhart four-factor model, with an up to 36% increase in the B/N portfolio.

This paper investigates multiscale interdependence between the stock markets of Germany, Austria, France, and the United Kingdom. Wavelet energy additive decomposition was analyzed to investigate which scales capture the most energy (volatility), whereas a wavelet cross-correlation estimator was used to analyze comovement and lead/lag relationship between stock markets' return dynamics on a scale-by-scale basis. The main findings of the paper are as follows. First, major financial market crises had a significant impact on return volatility of investigated stock markets. Among them, the global financial crisis of 2007-2008 had the greatest and the most durable impact. Second, the lowest scale (associated with stock markets' return dynamics over a 2-4 days horizon) and the second lowest scale (associated with stock markets' return dynamics over 4-8 days horizon) MODWT (maximal overlap discrete wavelet transform) decompositions of stock markets' returns captured the greatest share (together about 70-80%) of indices' returns volatility. Third, comovement between stock market returns is a scale-dependent phenomenon. Fourth, a strong comovement between stock market returns of Germany, France, and the United Kingdom exists at all scales, while the Austrian stock market is less correlated with the three biggest stock markets in Europe. Fifth, the dynamics of stock market returns seems to be well time-synchronized at daily (raw returns) and the lowest scale (scale ) return decomposition as most of the return innovations are transmitted between stock markets intraday. Sixth, at the highest investigated scale (associated with stock markets' return dynamics over a 64-128 days horizon), significant leads and lags between dynamics of stock markets' returns were detected. The time-synchronization of the stock markets' return dynamics for investments of 64 to 128 days horizon is less perfect than for investments of shorter investment horizons.

The study investigates the effect of financial market development on foreign portfolio investment in Nigeria and South Africa between the periods of first quarter in 1995 to fourth quarter of 2022. The study employs an ex-post factor research design, the study deploys panel autoregressive distributed lag modelling. The inferences were made at 5% significant level. Findings from the study reveal that lagged Portfolio Investment is not statistically significant to foreign portfolio investment (coefficient = -0.5026613, p-value = 0.275), in contrast, lagged Stock Market Turnover Ratio has a significant positive coefficient (coefficient = 0.5696119, p-value < 0.000), indicating a positive short-term relationship with changes in Portfolio Investment. However, other lagged variables like Stock Market Capitalization, All Share Index, Broad Money Supply, and Real Credit to the Private Sector show coefficients without statistical significance, suggesting limited short-term predictive power. In the long run, the adjusted term for lagged Portfolio Investment exhibits a highly significant negative effect (coefficient = -1.502661, p-value = 0.001). Lagged Broad Money Supply and Real Credit to the Private Sector also lack statistical significance in the long term, while lagged Stock Market Turnover Ratio and All Share Index have statistically significant positive coefficients. However, Stock Market Capitalization lacks statistical significance in predicting long-term changes in foreign Portfolio Investment. In respect to the result, the study recommended that policy makers should implement measures to enhance transparency and regulation within financial markets to promote investor confidence and attract foreign capital inflows. This may include strengthening regulatory frameworks, improving reporting standards, and ensuring effective oversight mechanisms.

Analysing the gold-stock nexus using VARMA-BEKK-AGARCH and Quantile regression models: New evidence from South Africa and Nigeria

<abstract> <p>Using the quantile regression approach to reveal the conditional relationships, the study re-examined the oil-stock co-movement in the context of oil-exporting countries in Africa. The data employed include daily OPEC basket price for crude oil and daily data on stock market indices for six major stock markets of oil-exporting economies in Africa—Egypt, Ghana, Morocco, Nigeria, South Africa, and Tunisia, from 02 January 2020 to 06 May 2021. We found that crude oil cannot act as safe haven instrument for stock markets in oil-exporting African countries. Notably, the oil-stock co-movement is consistent and more intense at the lower tails only. Investors are encouraged to employ oil as a diversification instrument rather than as a safe haven asset, based on market conditions. Regulators should devise strategies to strengthen the market for crude oil to lessen adverse volatilities during the COVID-19 pandemic by way of mitigating downward returns in African stock markets. The findings of the study offer more interesting economic insights to all classes of investors as well as policymakers in oil-exporting economies in Africa.</p> </abstract>

The impacts of the Subprime Financial crisis resulted in generally similar decline and volatility in both developed and emerging stock markets. However, in the aftermath of the crisis, the performance of emerging economies was stronger. To investigate this phenomena, this paper seeks to gauge the structure of one of the BRICS economies, the Brazilian stock market, for the period 2003 -- 2013, to determine possible determinants of this behavior.Using a Pearson and partial correlation analysis we find that the IBOVESPA index has little affect on the magnitude of the correlations of its components. This finding differs from results obtained recently for developed markets. Finally, we introduce a novel method to investigate the cohesion and dynamics of financial markets that provide new insights into the structure and dynamics of the stock market and its relation to the real economy.

The article examines the role of the global stock market in the development of both the individual state and the world economy as a whole. Since today the stock market is one of the most important buffers for the formation and use of investment resources by all economic entities, the main prerequisite for its sustainable development and efficient operation is a favorable economic situation in the country, widespread network of stock exchanges, high confidence and the population to stock market instruments. The place of the stock market as one of the most important components of the world financial market is described. The global stock market can be represented as a mechanism that allows the exchange of financial assets between countries and that shapes their prices. The development of information transfer technologies, new means of payment and assets make significant adjustments to the mechanism of functioning of modern financial markets. In recent years, the global financial market has undergone significant structural changes that have radically changed the conditions and features of their operation, so a comprehensive analysis of the dynamics of the global stock market over the past five years. The globalization of the world economy has led to significant changes in the stock market, such as a significant increase in the size of the international investment market and an increase in the share of portfolio and speculative investors. Acceleration of globalization processes, which are becoming a characteristic feature of modernity, requires a study of the peculiarities of the entry of national markets into the international investment space, so highlighted the structure of investment flows in the global stock market. Uncertainty of the environment, which is a fundamental characteristic of the modern socio-economic system, creates financial shocks and directly proportionally affects the state of securities trading in the global stock market, so the assessment of the leading countries in the world stock market. stock market capitalization. The change in the capitalization of the world's largest stock exchanges over the past five years has been analyzed.

The article examines the role and importance of the financial market in the modern economic system. It is determined that the financial market is one of the spheres of market economic relations, the specificity of which is that the object of sale is financial funds. It was found that in the early stages of financial relationship development, financial asset purchase and sale agreements were concluded directly between the owner and the consumer of capital. However, as the world's wealth and scale of production grows, the volume of such agreements has increased substantially, and the conditions for their implementation have become more difficult. It is noted that the financial market consists of two fundamentally different areas - the securities market and the bank loan market. It has been investigated that corporations are one of the subjects of the financial market. They act on it as large issuers, sellers of their securities and large investors who invest their temporarily free funds in financial assets. As an issuer, the corporation acts on the financial market as a debtor-borrower as an investor - a lender-lender. In the financial market, the corporation functions as a net borrower. It is established that the corporation is active in all spheres and segments of the financial market: in the money and stock markets, in the market of bank loans, in the primary and secondary markets, in the stock and over-the-counter markets. Market choice is determined by the operational and strategic goals that corporate financial managers set for themselves. In the money market, the corporation acts as an issuer of short-term securities, in the market of bank loans - a borrower of short-term capital in order to mobilize short-term funds to finance working (working) capital. In the stock market, it issues long-term securities in order to finance long-term development projects. It is noted that the main advantage of a large corporation as a form of business organization is the ease of transferring ownership rights and the relatively quick receipt of additional cash through the issue of new shares. This advantage is realized in the financial (stock) market, which plays an important role in corporate financing of economically developed countries. The conclusions about the role and importance of the corporation's activity in the financial market have been made.

Remittance inflows have become a vital source of income for many developing economies, significantly contributing to national income and influencing economic activities, including stock market dynamics. This study investigates the impact of remittances on the stock market dynamics, focusing on whether remittance inflows contribute to stock market growth and investor behavior. Employing a quantitative approach, the research uses econometric tools like VAR models, co-integration analysis, Granger causality tests, and variance decomposition analysis. Findings reveal that, contrary to earlier studies, remittances have no significant short-term influence on the stock market dynamics. The stock market is primarily driven by its past values, with remittances playing a minimal role in stock price fluctuations. Furthermore, co-integration analysis indicates no long-term relationship between remittances and the stock market, challenging previous assumptions of remittances fostering sustained market growth. The Granger causality test also shows that remittances do not cause stock market movements; rather, the stock index has a marginal influence on remittances. These results suggest that while remittances contribute to liquidity and market stability, their impact on stock market development in Nepal is limited. Policymakers should focus on improving financial infrastructure and investor confidence to better leverage remittances for capital market growth.

This paper aims to examine the contemporaneous relationship between trading volume and returns in the Taiwan exchange-traded fund (ETF) market taking the stock market as a contrast. While past research using correlation analysis and ordinary least squares method to specify a linear regression model only catches the average relationship between volume and return, this paper applies the quantile regression analysis to provide a more complete description for the volume-return relationship in the ETF and stock markets. The empirical results show that a symmetric volume-return relationship is found in the ETF market and an asymmetric volume-relationship, however, is discovered in the stock market. The volume-return relationship of the stock market has become more symmetric after the exempt for some stocks from the short-sale restriction. The results demonstrate that the transaction cost and the short-sale restriction are important factors to influence the patter of volume-return relationship.

This study examines the impact of macroeconomic uncertainties on stock market dynamics in Tanzania, motivated by the need to understand volatility patterns in a frontier market characterized by limited liquidity and high sensitivity to economic shocks. We employ symmetric and asymmetric generalized autoregressive conditional heteroskedasticity (GARCH) models, including the nonlinear asymmetric GARCH (NAGARCH) model, to capture complex volatility dynamics. The selection of macroeconomic variables is theoretically motivated: the inflation rate represents domestic monetary policy uncertainty; GDP captures economic performance and growth expectations; and gold prices serve as a proxy for global commodity conditions and safe-haven demand, which is particularly relevant given Tanzania’s mining sector. Using monthly data on the Tanzania share index, inflation rate, GDP, and gold prices from February 2007 to December 2023, we examine how macroeconomic variations influence stock market volatility. While symmetric GARCH models assume equal impacts from positive and negative shocks, asymmetric models including EGARCH, GJR-GARCH, and NAGARCH, capture differential responses. The NAGARCH model allows for nonlinearity in the relationship between past returns and volatility, offering a nuanced understanding of market reactions. Empirical findings suggest that the asymmetric NAGARCH model provides a more accurate representation of Tanzanian stock market behavior, capturing heightened sensitivity to negative shocks typical in emerging markets. The results reveal that inflation and gold prices have significant, long-term influences on stock market volatility. This study contributes to the emerging market finance literature and offers valuable insights for investors and policymakers in understanding risk patterns and designing appropriate strategies for frontier markets.

This paper examines the effects of oil price shocks on the stock market returns of the Gulf Cooperation Council countries. The empirical method used is quantile regression analysis. In addition, we allow for structural breaks and asymmetry by differentiating between positive and negative oil price changes. Unlike OLS analysis, quantile regression allows the coefficient estimates to vary throughout the distribution of the dependent variable, which provides a complete picture of the relationship between the explanatory variables and the dependent variable. Our results suggest that the coefficient estimates have not been constant throughout the distribution of stock returns; that oil price shocks have asymmetrical effects on stock returns; and that the effects of oil price shocks on stock market returns are affected by stock market conditions. Overall, the results suggest that rising oil prices increase stock returns only when stock markets are bullish (high quantiles) and normal (medium quantiles), and that falling oil prices lower stock returns only when stock markets are bearish (low quantiles) and normal (medium quantiles). This suggests that oil and stock markets are more likely to boom together or crash together.

The goal of this study was to examine how selected pressure points or areas of vulnerability are related to individual differences in reading comprehension and whether the importance of these pressure points varies as a function of the level of children’s reading comprehension. A sample of 245 third-grade children were given an assessment battery that included multiple measures of vocabulary, grammar, higher-level language ability, word reading, working memory, and reading comprehension. Ordinary least squares (OLS) and quantile regression analyses were undertaken. OLS regression analyses indicated that all variables except working memory accounted for unique variance in reading comprehension. However, quantile regression showed that the extent of the relationships varied in some cases across readers of different ability levels. Results suggest that quantile regression may be a useful approach for the study of reading in both typical and atypical readers and aid greater specification of componential models of reading comprehension across the ability range.

Purpose The varying impacts of climate policy uncertainty on stock market performance have emerged as a critical research area, driven by the challenges that climate change poses to financial markets. This study seeks to emphasize the crucial role of climate policy uncertainty (CPU) in predicting financial market fluctuation [Dow Jones Asia (ASIA), Dow Jones Islamic (ISLAMIC) and NASDAQ OMX Clean Energy Asia (CLEAN)] for the period from 2018 to 2024. Design/methodology/approach This paper uses three innovative techniques, including wavelet quantile regression, wavelet nonparametric causality and quantile on quantile regression. Findings The results reveal that climate policy uncertainty exerts a positive influence on the selected stock markets across various quantiles and time scales. However, the relationship between CPU and ISLAMIC stock returns shows both negative and positive associations. More importantly, CPU exhibits predictive power over stock markets, indicating causality across all quantiles and frequencies. Practical implications These findings highlight the importance for investors to pay more attention to climate policies during the current climate crisis. Originality/value To the best of the authors’ knowledge, this study is among the first to investigate the time-frequency nexus and predictability between CPU and stock markets in the Asia region. Specifically, the authors use an innovative three-stage methodology to analyze the influence of CPU on Asian stock markets. These methods include wavelet-based quantile regression, wavelet-based nonparametric quantile causality and quantile-on-quantile regression (QQR). The nonparametric quantile causality technique identifies causal relationships and their respective timeframes, while the wavelet-based quantile regression evaluates the strength and direction of these interactions. Additionally, they explore how CPU impacts various quantiles across different distributions of Asian stock market returns and visualize these effects using QQR 2D-plane graphics. This robust methodology provides valuable insights, making this research particularly relevant for academic scholars, market regulators, investors and policymakers.

Navigating through the complex interface of commodities and stock markets, this paper elucidates the pivotal role of commodities in sustaining China's expansive economic and infrastructural panorama. Amidst significant urbanization, industrial advancement, and burgeoning population, China's vast commodities sector plays a vital role in satisfying domestic consumption, facilitating export operations, and underpinning sustained growth. Exploring the intricate linkage between commodities and stock markets, the study reveals a positive correlation between commodity futures and stock market dynamics, enriching the discourse on their co-movements within an emerging economy framework like China. The research, while offering invaluable insights into the complexities of these relationships, also lays the groundwork for future studies, inviting exploration into the causal dynamics and global perspectives. The findings, though illuminative, underscore the necessity for holistic, judicious investment and policy decision-making, reminding stakeholders to meticulously consider broader financial landscapes and market peculiarities alongside analytical insights, thus balancing data-driven decisions with strategic foresight in the vast, interconnected world of financial markets.