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UFS students excel in the JSE Investment Challenge

23 October 2023 | Story SAMKELO FETILE | Photo SAMKELO FETILE

Third year students: Sipho Majenge, Thapelo Tinte, Dr Edson Vengesai, Busisiwe Nhlapo and Tsolofelo Zwane.

The University of the Free State (UFS), Department of Economics and Finance in the Faculty of Economic and Management Science, has recently made headlines by achieving remarkable success in the prestigious JSE Investment Challenge competition. The 3rd-year group secured an impressive second position, while the Honours group claimed an outstanding third place. These achievements are truly commendable, given the fierce competition and rigorous evaluation of financial acumen that characterises this national competition.

The 3rd-year group, consisting of Thapelo Tinte, Sipho Majenge, Busisiwe Nhlapo and Tsolofelo Zwane, showcased their financial prowess by excelling in trading futures, a complex financial instrument that demands in-depth knowledge and expertise. On the other hand, the Honours group, comprised of Dawie Bekker, Divan Koch, Keith Tarr, and William Oosthuysen, dedicated their efforts to the stock market. These talented individuals took on the trading aspect of the competition, meticulously constructing and managing their portfolios.

The significance of the JSE Investment Challenge

The JSE Investment Challenge, organised by the Johannesburg Stock Exchange (JSE), is a prestigious national competition designed to introduce students to investment fundamentals, offering practical experience that equips them with the knowledge and skills necessary for informed decision-making in real financial markets. This educational stock trading programme also champions financial inclusion and equality by welcoming students from all fields of study. Distinguished by its association with the JSE, one of Africa's leading stock exchanges, the competition exudes credibility and prestige. Participation from universities across South Africa further enhances its national appeal. Moreover, it imparts invaluable real-world financial skills and knowledge, highlighting the participants’ ability to navigate the complexities of the stock market and effectively manage portfolios.

A test of financial prowess

In the challenge, each participating team is allocated R1 million in virtual money and is tasked with constructing a portfolio by purchasing securities on the JSE. This portfolio is closely monitored over six months, from March to September, with the team that generates the highest return across all universities declared as the winner. The rewards are enticing, with the top team receiving R30,000 and an all-expenses-covered international trip. The second and third-placed teams receive R20,000 and R10,000, respectively.

Dr Edson Vengesai plays a pivotal role as the guiding force behind the JSE Investment Challenge in the Department of Economics and Finance. He emphasises, “The success of the students in the JSE Investment Challenge reflects the institution's commitment to providing practical and relevant education. It demonstrates that the students are not only learning theory but also how to apply that knowledge in real-world scenarios. This achievement enhances the institution's reputation, particularly in the fields of finance and economics. It signifies a high-quality curriculum and a dedication to excellence in education”.

For more information about the competition, interested individuals can contact Dr Vengesai through the Department of Economics and Finance in the Faculty of Economic and Management Sciences or via email at vengesaie@ufs.ac.za.

Dawie Bekker, William Oosthuysen, Dr Edson Vengesai, Divan Koch and Keith Tarr

Honours students: Dawie Bekker, William Oosthuysen, Dr Edson Vengesai, Divan Koch and Keith Tarr.

News Archive

Mathematical methods used to detect and classify breast cancer masses

2016-08-10

Description: Breast lesions Tags: Breast lesions

Examples of Acho’s breast mass
segmentation identification

Breast cancer is the leading cause of female mortality in developing countries. According to the World Health Organization (WHO), the low survival rates in developing countries are mainly due to the lack of early detection and adequate diagnosis programs.

Seeing the picture more clearly

Susan Acho from the University of the Free State’s Department of Medical Physics, breast cancer research focuses on using mathematical methods to delineate and classify breast masses. Advancements in medical research have led to remarkable progress in breast cancer detection, however, according to Acho, the methods of diagnosis currently available commercially, lack a detailed finesse in accurately identifying the boundaries of breast mass lesions.

Inspiration drawn from pioneer

Drawing inspiration from the Mammography Computer Aided Diagnosis Development and Implementation (CAADI) project, which was the brainchild Prof William Rae, Head of the department of Medical Physics, Acho’s MMedSc thesis titled ‘Segmentation and Quantitative Characterisation of Breast Masses Imaged using Digital Mammography’ investigates classical segmentation algorithms, texture features and classification of breast masses in mammography. It is a rare research topic in South Africa.

Characterisation of breast masses, involves delineating and analysing the breast mass region on a mammogram in order to determine its shape, margin and texture composition. Computer-aided diagnosis (CAD) program detects the outline of the mass lesion, and uses this information together with its texture features to determine the clinical traits of the mass. CAD programs mark suspicious areas for second look or areas on a mammogram that the radiologist might have overlooked. It can act as an independent double reader of a mammogram in institutions where there is a shortage of trained mammogram readers.

Light at the end of the tunnel

Breast cancer is one of the most common malignancies among females in South Africa. “The challenge is being able to apply these mathematical methods in the medical field to help find solutions to specific medical problems, and that’s what I hope my research will do,” she says.

By using mathematics, physics and digital imaging to understand breast masses on mammograms, her research bridges the gap between these fields to provide algorithms which are applicable in medical image interpretation.

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