School of Business (SOB)

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Welcome to the School of Business (SoB) Community at Mzumbe University Institutional Repository. Explore a wealth of scholarly works, research publications, and intellectual contributions from the dynamic academic community within the School of Business. Our repository showcases a diverse range of research outputs, including articles, conference papers, theses, dissertations, and more, reflecting the innovative and impactful research endeavors of our academic staff, researchers, and students. Discover cutting-edge insights in business administration, procurement and supply chain management, marketing , entrepreneurship, accounting and finance, and related disciplines. The SoB Community is committed to fostering knowledge dissemination, collaboration, and academic excellence. Whether you're a researcher, student, or enthusiast, delve into the wealth of knowledge generated by the School of Business community at Mzumbe University. Join us on a journey of exploration, discovery, and collaboration within the School of Business community's rich academic landscape. Stay informed, inspired, and connected through the diverse research contributions housed in our dedicated repository.

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    Testing for the weak-form market efficiency of the Dar es Salaam Stock Exchange
    (Elsevier, 2016) Komba, Gabriel Vitus; Guney, Yilmaz
    This paper investigates into the weak-form efficiency of the Dar es Salaam Stock Exchange (DSE), a frontier market, in Tanzania. The study covers the period from January 2007 to December 2014. To establish the consistency and robustness of the obtained conclusions, we employ different tests (i.e., Augmented Dickey-Fuller test, Variance-ratio test, and Ranks and Sign test) to examine the hypothesis that the returns based on the price and return indices follow a random walk process. The results provide convincing evidence that returns series based on price indices indeed follow a random walk. However, when the same tests are performed for the returns based on the return indices, the findings reveal that these series are not weak-form efficient, suggesting that investors might be able to predict future returns based on the current and past data.