The Challenges of Technology and Economic Catch-up in Emerging Economies

This book synthesizes and interprets existing knowledge on technology upgrading failures as well as lessons from successes and failures in order to better understand the challenges of technology upgrading in emerging economies. The objective is to bring together in one volume diverse evidence regarding three major dimensions of technology upgrading: paths of technology upgrading, structural changes in the nature of technology upgrading, and the issues of technology transfer and technology upgrading. The knowledge of these three dimensions is being synthesized at the firm, sector, and macro levels across different countries and world macro-regions. Compared to the old and new challenges and uncertainties facing emerging economies, our understanding of the technology upgrading is sparse, unsystematic, and scattered. While our understanding of these issues from the 1980s and 1990s is relatively more systematized, the changes that took place during the globalization and proliferation of GVCs, the effects of the post-2008 events, and the effects of the current COVID-19 and geopolitical struggles on technology upgrading have not been explored and compared synthetically. Moreover, the recent growth slowdown in many emerging economies, often known as a middle-income trap, has reinforced the importance of understanding the technology upgrading challenges of catching-up economies. We believe that the time is ripe for “taking stock of the area” in order to systematize and evaluate the existing knowledge on processes of technology upgrading of emerging economies at the firm, sector, and international levels and to make further inroads in research on this issue. This volume aims to significantly contribute towards this end

Information Outlook, October 2004

Volume 8, Issue 10https://scholarworks.sjsu.edu/sla_io_2004/1009/thumbnail.jp

Analysis of calendar effects and market anomalies on the Johannesburg Stock Exchange

This study sought to empirically investigate the existence of calendar effects and market anomalies on the JSE using monthly and daily closing prices of the ALSI, Top 40, Mid Cap and Small Cap index; as well as, daily closing prices on the Value, Growth and Dividend Plus index during the sample period 2002 – 2013. The anomalies analysed are the January effect, the weekend effect, the size effect, the value effect, and the dividend yield effect. The empirical analysis uses a number of MSAR with a different number of regimes and lag orders. The results from the investigation of the January effect show the non-existence of the January effect and the value effect on the JSE during the periods 2002 – 2013 and 2004 – 2013, respectively. However, the weekend effect was found significant in the Mid Cap and the Small Cap index, and the size effect was also found significant during the same period 2002 - 2013. Finally the results from a Granger causality test concluded that there is a relationship between the returns on the Dividend Plus index and the ALSI, effectively proving the existence of the dividend yield effect on the JSE between 2006 and 2013. Additionally, the anomalies found imply the opportunity for investors to make returns above buy-and-hold

Quantitative Methods for Economics and Finance

This book is a collection of papers for the Special Issue “Quantitative Methods for Economics and Finance” of the journal Mathematics. This Special Issue reflects on the latest developments in different fields of economics and finance where mathematics plays a significant role. The book gathers 19 papers on topics such as volatility clusters and volatility dynamic, forecasting, stocks, indexes, cryptocurrencies and commodities, trade agreements, the relationship between volume and price, trading strategies, efficiency, regression, utility models, fraud prediction, or intertemporal choice

Decision Support Systems for Financial Market Surveillance

Entscheidungsunterstützungssysteme in der Finanzwirtschaft sind nicht nur für die Wis-senschaft, sondern auch für die Praxis von großem Interesse. Um die Finanzmarktüber-wachung zu gewährleisten, sehen sich die Finanzaufsichtsbehörden auf der einen Seite, mit der steigenden Anzahl von onlineverfügbaren Informationen, wie z.B. den Finanz-Blogs und -Nachrichten konfrontiert. Auf der anderen Seite stellen schnell aufkommen-de Trends, wie z.B. die stetig wachsende Menge an online verfügbaren Daten sowie die Entwicklung von Data-Mining-Methoden, Herausforderungen für die Wissenschaft dar. Entscheidungsunterstützungssysteme in der Finanzwirtschaft bieten die Möglichkeit rechtzeitig relevante Informationen für Finanzaufsichtsbehörden und Compliance-Beauftragte von Finanzinstituten zur Verfügung zu stellen. In dieser Arbeit werden IT-Artefakte vorgestellt, welche die Entscheidungsfindung der Finanzmarktüberwachung unterstützen. Darüber hinaus wird eine erklärende Designtheorie vorgestellt, welche die Anforderungen der Regulierungsbehörden und der Compliance-Beauftragten in Finan-zinstituten aufgreift