FNB Securities trading game 2024
A team from Stellenbosch University achieved a third-place position in the FNB Securities trading game 2024. Organised by Prof. Hylton Hollander and supported by FNB Securities, the competition challenged students to trade in real-time global markets using a simulated $100 000 portfolio. Over three months, ten teams competed head-to-head, navigating volatile markets and geopolitical uncertainty to achieve the highest returns.
The first and second place teams were from the University of Cape Town:
In first place, team members: Siphelele Mbense, Mojalefa Molahloe, Lindokuhle Xaba, and Mpilontle Mbambo, who achieved an absolute return of 32%. In second place were Darryl Nyamayaro, Shaun Brick, and Jason Joannou, achieving an absolute return of 21%.
The third team, from Stellenbosch, were Oliver Guest, Sam Hardie, Ruan Palvie, and Danshil Naidoo and achieved an absolute return over the preiod of 8%. Their approach was grounded in data-driven decision-making, combining trend-following techniques with insights from social media speculation and geopolitical analysis. They closely monitored platforms like Reddit and Twitter for emerging opportunities and executed trades swiftly to capitalise on short-term volatility. The team acknowledged the challenges of speculative trading but emphasised the importance of risk management and agility in maintaining consistent returns.
The team's report outlines their approach in more detail:
Overview: Our team adopted a dynamic and data-driven trading strategy for the FNB Trading Challenge, leveraging a combination of trend analysis, speculative insights from social media, and
geopolitical awareness. This approach allowed us to react quickly to market developments and
capitalize on short-term opportunities while maintaining a forward-looking perspective.
Trend Following: We actively tracked market trends using technical analysis tools and indicators such as moving averages, RSI, and MACD. By identifying strong upward or downward momentum, we positioned ourselves early in trending markets, ensuring we maximized gains while minimizing exposure to stagnation or reversals.
Social Media Speculation:
Platforms like Reddit and Twitter served as valuable tools for gauging market sentiment and
uncovering emerging opportunities. We monitored discussions around earnings reports, company announcements, and investor sentiment, enabling us to anticipate price movements ahead of major events. Particular focus was placed on trending hashtags, influential accounts, and retail-driven "meme stock" movements.
Geopolitical Trend Analysis:
Global events such as elections, trade negotiations, and conflict developments were integral to
our decision-making process. By staying informed about the geopolitical landscape, we identified sectors and commodities most likely to be impacted.
Execution and Risk Management:
Execution: Trades were executed swiftly to take advantage of short-lived opportunities, with
careful monitoring of entry and exit points.
Risk Management: To mitigate risks, we employed diversification and set strict stop-loss levels
for each position. This allowed us to protect our portfolio from adverse market movements
while maintaining flexibility.
Results and Reflection:
Our strategy proved effective in navigating the dynamic nature of the competition, enabling us
to generate consistent returns. However, we recognized the challenges of relying on speculative
social media data, which at times led to overreactions or misinterpretations. Moving forward,
integrating machine learning sentiment analysis tools could further refine this aspect of our
strategy.
Conclusion:
By combining trend-following techniques, speculative insights from social media, and
geopolitical analysis, our team developed a robust and adaptable approach to trading. This
strategy capitalized on the volatility and complexity of the markets, showcasing the importance
of both agility and informed decision-making in trading
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