Category: Newsroom

For the past year-and-a-half, AIFMRM graduate Bandile Mbele has been working as a Fixed Income Strat in Morgan Stanley’s institutional securities group at their headquarters in New York. He lives in an apartment in Hell’s Kitchen and loves Italian pasta takeaway for dinner. While, in many ways, he is living the dream now, the journey has not been an easy one.

Bandile Mbele, 27, remembers where he was when he received the call that would change his life and put it on its current trajectory – working at one of the world’s top investment and financial services firms. He was playing video games early in 2019 when a friend called from the US, asking him if he was interested in studying a master’s in financial engineering at Haas School of Business at the University of California, Berkeley. Even though Bandile was working as a graduate trainee at Old Mutual Specialised Finance, he knew opportunities like these did not come around often. His answer was a decisive “yes”. His friend recommended him for the programme, and his application was accepted.

“It was so exciting; it was my first time out of the country, and I got to fly to the United States! Of course, two days after setting foot on campus, everything was shut down because of COVID-19!” says Bandile. “When I got there, it was so busy, and then just like that, it was empty. There was no one on campus.” He spent the rest of the year studying mostly from his room but managed to meet some of his classmates. But he has a top-rated degree to show for it – and obtained an internship at Morgan Stanley.

This led to his current position as a strat (strategist) on Morgan Stanley’s Agency Mortgage-Backed Securities Desk, where he has long days but finds the work very rewarding. “It’s really a financial hub. You meet so many smart people from all over the world, learning how to solve problems in different ways. In South Africa, we have diversity, but this is next level. All of us are trying to help the bank make better decisions; I’m really enjoying it.”

The money is good, too, though Bandile notes that the cost of living in New York is high, but he is able to put money aside as well. He has a hybrid working schedule, which means some time in the office and some working from home – but this is likely to change in 2023. He has made friends from all over the world, played casual pick-up soccer games and discovered a penchant for Italian pasta, particularly a vodka-flavoured fettuccine from a local eatery.

It may sound like he is a long way from home – Durban in KwaZulu-Natal – where he spent his formative years with his parents, who both worked for Correctional Services. But in many ways, he is still surrounded by what he loves the most – numbers and mathematics.

Bandile recalls how some of his first memories as a toddler were the posters of numbers that his mother put up for him in his room. “It was something my mom tried with me; I think to get me comfortable with numbers. I also remember, as a small child, having a special thing about numbers, like the number two. If I was playing with toys, I’d take the second toy aside and take it out of play; I don’t know why! I have no issue with the number today!” he laughs.

Bandile’s special relationship with mathematics continued in high school, where he ended up doing Advanced Programme Mathematics by himself, with self-study, to avoid incurring the cost of taking the subject at school. At the University of Cape Town, while studying actuarial science, he also won the class medal for first-year mathematics. Even now, when he finds time,  he plays around with mathematics, as a hobby, purely for enjoyment.

When he thinks back to mentors who have helped him along the way, he mentions Professor David Taylor at AIFMRM, whom he met while doing the MPhil in Mathematical Finance. He recalls stimulating conversations with Professor Taylor, which opened his mind to the possibilities within the field of financial mathematics. “I recall him saying to us that what we studied need not influence our career. He told us not to box ourselves in, not to limit ourselves, and that there are so many different routes we can take with these tools we’ve been given.”

Bandile is currently on a 24-month STEM Optional Practical Training programme, and he is not sure what will come after that. He may return to South Africa or continue working overseas. “I do miss home, my family, and friends, but I am learning a lot here, so I am not sure what the future holds.” It is clear that for this young man, the sky’s the limit – whether it is in the Southern or the Northern Hemisphere.

By Professor Jörg Kienitz

Over the past two years, banking, investment and financial institutions have shown significant interest in machine learning (ML) possibilities, specifically regarding quantitative finance.

In late October 2022, the African Institute of Financial Markets and Risk Management (AIFMRM) hosted a masterclass on machine learning for quantitative finance in Johannesburg, South Africa. It was an event for specialist finance professionals, academics, and researchers. What made this event especially interesting was the high number of attendees. While 55 people may not sound like a crowd, the numbers were significantly larger than similar events in Europe, for instance, where an audience of 15 or 20 people could be expected.

Apart from the numbers – it is also worth noting the high level of interaction, which could be seen in the way participants asked questions, engaged in discussions, and asked about follow-up conversations and possible future collaborations. More companies enquired about application methods, implementation possibilities, and specifics in the research compared with a related masterclass presented two years ago.

This masterclass, aimed at the financial services industry, presented the latest research on the generation of synthetic market data and how machine learning techniques can extract characteristics and qualities to help identify more risks and expose new possibilities – which may be especially valuable for commodity traders and those in derivatives pricing, for instance. Synthetic data generation helps identify specific scenarios and risks that may not have arisen with existing models.

It also lays the basis for applying other techniques of machine learning based methods. Such methods depart from standard assumptions like governing stochastic differential equations. Techniques like Deep Hedging or Reinforcement Learning can be applied to more general set-ups.

It can be challenging to explain in layman’s terms the value of synthetic data generation and machine learning techniques. One way of looking at its relevance is to take something like the oil price. Oil is one of the world’s most important commodities, contributes to a third of global energy consumption, and is used in products ranging from transportation to plastics. Crude oil price fluctuations significantly impact global economies, as Shanu Jain and Ajay Gupta explain in an article on forecasting crude oil prices. Price forecasting is essential to a wide range of stakeholders and can help reduce risks related to oil price volatility.

Another area where these methodologies can help predict certain outcomes with greater accuracy is in determining electricity prices – a crucial sector with massive repercussions and impact, not only in South Africa but worldwide, when considering how the tensions in Russia and Ukraine have affected the energy situation in Europe.

For example, in a research paper published in 2021, Stanford University’s Dr Nathan Ratledge and others demonstrate how sparse data on key economic outcomes limit the development and efficacy of public policy. Their paper goes on to show that this challenge can be addressed by using satellite imagery and machine learning to evaluate the electrical grid in Uganda and find local measurements for the impact of electricity access on livelihoods. They were able to calculate how much grid access improved the asset wealth of villages, helping to provide much-needed data on the impact of grid-based infrastructure investments.

Over the past two years, we have seen greater adoption of virtual platforms and digital solutions in various industries as more organisations embrace remote working conditions and artificial intelligence (AI) software technology to speed up processes and improve work outcomes.

However, we have to outline that the presented methods are grounded in statistical analysis and do not relate to what is commonly known as AI. It is more like recognising and generating patterns observed in data. The underlying relationships of the used data and the features are often non-linear, and the methods help to understand this relationship.

It has brought increased comfort around new technology, like ML and AI. In the coming years, there will be even greater adoption and application of new techniques like synthetic data generation. It brings faster processing and greater depth and efficacy to financial and trading modelling and insights.

Additionally, the AIFMRM masterclass also looked at new research published in the quantitative finance field this year around Stochastic Local Volatility and specifically data-driven and model-free approaches for computing conditional expectations. The new method combines Gaussian Mean Mixture models with classic analytic techniques based on the properties of the Gaussian distribution. The importance of this work lies in the technique’s ability to produce accurate estimates and hedging strategies related to discrete minimal variance hedges.

New methods and techniques employing machine learning are being used more frequently nowadays. A recent financial report indicates a surge in the use of software and new technology in banks and financial institutions globally. The report reveals how advances in machine learning, cloud computing technologies, and artificial intelligence are shaping financial and banking services. Some say that technology and quants (quantitative analysts) are the future of finance. According to Dr Anthony Ledford, chief scientist at Man AHL, a quant-based subsidiary of the Mag Group, which partners with the University of Oxford, the cutting edge of being a quant in finance today is machine learning.

Whether or not one agrees with these statements, machine learning certainly holds much promise for various industries. Increasingly, more avenues are opening for those researching how machine learning can best improve processes and systems in their specific field or industry. It is undoubtedly an exciting time for those exploring the potential of machine learning in quantitative finance.

Professor Jörg Kienitz is an Assistant Professor at the University of Wuppertal in Germany and an Adjunct Associate Professor at UCT’s African Institute of Financial Markets and Risk Management (AIFMRM). 

It was only once he had completed his MCom in Risk Management of Financial Markets at AIFMRM that Mohapi Mohlamonyane really saw his career taking off in the direction he wanted it to – into a world where the work is stimulating and exciting, and each day brings new challenges.

After finishing his undergraduate degree in mechanical engineering at the University of Cape Town (UCT), Mohapi Mohlamonyane, 30, got a job at SSH Design as a junior public health engineer. It was an excellent position with international travel prospects, and he even moved to Dubai for a year to work on international building projects.

But Mohapi was restless. “I seemed to lose the passion for engineering; maybe I was a little bored. I could see the job was about doing the same kind of thing over and over again.” He had always been interested in the world of finance and started looking into graduate programmes at financial institutions but had no luck getting in. He then called some of his friends who had studied engineering with him, and this is where he heard about AIFMRM for the first time.

“Many of them had done the MCom or the MPhil, and they highly recommended it,” remembers Mohapi. He enrolled for the MCom in Risk Management of Financial Markets and hasn’t looked back since. “The financial sector is so dynamic and exciting. Everything is interconnected, like if you look at what is happening in Ukraine and how the war affects commodity prices, for instance. Every day there is a new challenge, and it is a very fast-paced environment,” says Mohapi.

After graduating from AIFMRM, he got a job at Sanlam Investments as a Graduate Product Specialist, leaving in 2021 to become a Project Manager at Zenysis Technologies before returning to Sanlam Investments in his current position as a Product Analyst.

Coming back was not an issue. “Sanlam Investments is a wonderful place to work. When I left, it wasn’t because I was running away – I was pursuing another opportunity more in software development. When the project came to an end, I talked to people about returning, and I was so happy to see numbers again!” He says the work culture at Sanlam Investments is professional and fluid. “If you don’t burn bridges and have good relationships, they always look for talent – even if you left before. The skills taught at AIFMRM are gold, making you so marketable and in demand.”

He enjoys being in asset management. “Whether you like talking to people, dealing with clients or being in a sales team or more on the quant side, there is a place for you.” He believes it is because of what he learnt at AIFMRM. “The MCom is so practical, so hands-on,” he says. “From the moment you walk into a classroom, you open your laptop and start building models to trade or build instruments. It’s like that from the word go.”

While there is theory too, Mohapi values the practical application and real-world insights he gained during his MCom. “You learn the financial language, how to operate in these spaces, and how to deal with a fast-paced environment.”

He also has high praise for his lecturers, some of whom were more like mentors, engaging and interacting with students. The way complicated and specialised concepts were explained blew him away. “The lecturers were brilliant,” he says. While there were times when he felt out of his depth, he never felt like he was unable to make it. “There were challenges, but they were fun challenges!” he laughs, remembering how he and a few other engineers stuck together throughout the course.

In terms of his career, Mohapi has numerous options and while going overseas is not off the table, he is here to stay for now. “South Africa is a pretty special place to live, and I don’t think things are that bad, even though I believe there’s much work to be done by all of us to help this country prosper. But for now, I don’t think things are so bad that I’d want to leave.”

What is next for him? Maybe an MBA or a more business leadership role. He says, “The MCom has opened many doors for me, and it has given me the freedom to explore my next career move.”

When Ralph Rudd looked for a job after completing his PhD at UCT, there were many opportunities and possibilities, but he was finally drawn to Iceland and the position of Assistant Professor in Financial Engineering at Reykjavik University.

Ralph Rudd could probably not have travelled further north from South Africa for his new job at Reykjavik University in Iceland, just south of the Arctic Circle. The quantitative mathematician, born and raised at the tip of the African continent in South Africa, travelled to the island capital with his wife in 2021. Here, they had to get used to having only five hours of daylight in the middle of winter – and almost 24-hour sunlight in summer.

But this was only a small part of the adventure for Ralph. He was drawn to his new position in the relatively new field of financial engineering at a university that is rated among the top young universities in the world.

“These are such uncertain times globally, taking into account the COVID-19 pandemic, the climate crisis, the conflict in the Ukraine and its consequences for trade, economic stability and energy security across the globe,” says Ralph. “More than ever, the world needs financial risk specialists and accurate financial modelling and data analysis.”

He lectures on Reykjavik University’s MSc in Financial Engineering, an intensive and interdisciplinary programme combining financial expertise, engineering knowledge, mathematical and statistical tools and programming. The degree was designed in partnership with the Sloan School of Management and the Operations Research Centre at MIT.

Ralph, previously a senior lecturer at the African Institute of Financial Markets and Risk Management (AIFMRM) at UCT, has always enjoyed new challenges. In 2017, while doing his PhD in Quantitative Finance at UCT, he helped to pioneer a numerical method along with Professor Tom McWalter, and they presented their findings at a prestigious international conference in Barcelona, Spain.

He is still closely involved with AIFMRM, helping to supervise master’s dissertations and wanting to organise exchange programmes with students from Reykjavik University. He believes the institute is among the finest in the world. “The MPhil specialising in Mathematical Finance is rated in the top 100 programmes worldwide, as ranked by Eduniversal. It is an exceptional programme, and I say that as someone who has interacted with mathematics graduates from around the world.”

He says the employment offer rate of AIFMRM students is over 100%. “There is an extremely high demand for them, and most get more than one job offer.” He ascribes this to AIFMRM’s emphasis on practical, real-life interactions with financial institutions to help find innovative solutions and involving students with financial companies for maximum exposure to industry.

He recalls a story from his PhD studies when he and a colleague were invited to a leading financial services firm. The company presented them with a list of 20 to 30 issues they were struggling with. They asked Ralph and his colleague which areas they thought they could help. “We looked at each other and then told them that, basically, we could help them with every one of their problems.”

The institute’s commitment to its students is exceptional, says Ralph. He recalls how AIFMRM rallied to help students, especially during lockdown following the outbreak of COVID-19 in early 2020. Providing mobile data and assisting with physical relocation, as well as providing online counselling, were among many AIFMRM interventions to ensure students were able to cope with the rigorous demands of their academic programme along with the personal and emotional strain of studying online during a pandemic.

Ralph maintains close ties with Professor David Taylor and his former colleagues at AIFMRM, but he is fascinated by working in a field that is so new that there is no widely accepted definition of what it is yet. “Financial engineering includes financial mathematics and quantitative finance. But what it really is, is applied problem-solving. It is building models, doing simulations and considering all aspects of, say, building a nuclear power plant. Financial engineers from the Reykjavik University’s programme can walk out of university and be qualified engineers, or they can work on Wall Street.”

He is a passionate teacher and loves breaking down complex issues. Now that he has started to settle into his new professional role, he is also beginning to work on research ideas in collaboration with AIFMRM colleagues.

“For anyone wondering if a course like the MPhil in Mathematical Finance is for them, I want to say, once you have money, life is easier. With a master’s degree in finance, you will always be able to earn good money.” But there is an important social and psychological benefit to studying at AIFMRM. Ralph experienced it himself while working on his PhD, a time of his life during which he was often frustrated and felt isolated. Support from Professor Taylor and colleagues at AIFMRM helped him to keep going. “What I really see in AIFMRM graduates is the transformation. AIFMRM pushes them to do more than they thought they were capable of. They realise how robust and resilient they are, and for me, that is the primary contribution of this programme.”

An adjunct professor from the University of Cape Town’s (UCT) African Institute of Financial Markets and Risk Management (AIFMRM) has collaborated with other academics on a novel and easily-implementable way for banks and financial institutions to step up their role in driving sustainable finance and combating climate change.

Earlier this year, University College of London (UCL) mathematician, Dr Andrea Macrina, was busy cooking a birthday dinner for his wife when the phone rang. It was one of his collaborators, asking if he had a few minutes for a quick conversation about their research. Two hours later, he was still on the phone, and his wife had taken over the cooking of her own birthday dinner.

“I was very apologetic,” recalls Dr Macrina, who is also an adjunct professor at the African Institute of Financial Markets and Risk Management (AIFMRM) at the University of Cape Town (UCT). “It didn’t feel right at all, and my heart was very heavy. I had spoken to my wife about this research project, and she knew how excited we all were.” In fact, he and co-authors Chris Kenyon and Mourad Berrahoui worked through the Christmas and New Year period, taking very few breaks over the festive season, to complete their research to be put in the public domain in early 2022.

Their paper called the Transparency Principle for Carbon Emissions Drives Sustainable Finance has already drawn much interest from the financial services industry. It was presented publicly to academics, peers, and figures in the financial sector at the AIFMRM-QuantsSA Research Seminar on 10 March 2022.

“This research is very exciting,” explains AIFMRM Director Professor David Taylor. “The alignment of financial market incentives and carbon emissions disincentives is key to limiting global warming. This research provides a new way of designing financial instruments according to the enabled carbon flows and is compatible with existing bank systems. So, it does not call for new systems or software to be introduced.”

In layman’s terms, the researchers developed a new way to structure financial products, like loans, to include information about the enabled carbon emissions. This means adding a number quantifying the enabled carbon impact that institutions can use to calculate financial risk associated with carbon flows. By asking for more carbon-related disclosures and entering them in the terms sheets, banks can use these to compare cash flows and carbon flows and apply them to evaluate financial loans provided to fund projects, for example.

By accounting for the enabled carbon emissions of projects like new coal-fired power stations, disincentives could arise to build such power plants, encouraging more cost-effective and environmentally friendly alternatives or new designs that offset the carbon emissions. “Accounting for carbon emissions allows the banks to determine the financial requirements to balance costs arising from the enabled carbon flows which will radically change project costs, decreasing the risk that assets become stranded (unusable),” says Dr Macrina. This will lead to projects being restructured to include negative emissions technologies and, in their paper, the researchers offer new suggestions for mixed financial-physical solutions to minimise costs.

“Sustainability and the focus on climate change are key issues for financial market participants,” says Professor Taylor. “WWF International, among many other global organisations, has emphasised the crucial need for financial organisations and systems to play their part in reducing carbon emissions. Innovative research like this suggests actual and implementable ways in which financial institutions can play a bigger and more active role in reducing carbon emissions.”

With energy and power generation crises hitting not only South Africa but also various countries worldwide due to oil price uncertainty following Russia’s war in Ukraine, the approaches banks and financial institutions take toward financing future power plants have become even more relevant than ever before.

Dr Macrina and his co-authors in the paper introduce a carbon equivalence principle, which can be used to quantify how green a project is. Dr Macrina says they prefer not to use the term “green” as it is too narrow to describe emission impact. “We find labelling something as ‘green’ can be very limiting and inadequate as ‘green’ projects can still have a big carbon impact that is not acknowledged.” He explains, “A building may qualify as being ‘green’ due to certain building practices and materials used, but once you take into account the power sources it uses, you see its carbon emissions actually may no longer make it ‘green’.”

By considering instead enabled carbon emissions, a more accurate representation is gained. The researchers call this the Carbon Equivalence Principle (CEP) and they believe it enables greater incentive alignment between sustainability and normal financial management.

Dr Macrina says this also paves the way to cutting down on greenwashing, where organisations and activities claim to be environmentally friendly but do not accurately account for the carbon impact of their projects, products, or practices. Environmental organisation Greenpeace defines greenwashing as: “A PR tactic used to make a company or product appear environmentally friendly without meaningfully reducing its environmental impact.”

As pressures increase on organisations to be more ESG (environmentally, socially, and corporate governance) compliant, there have been calls on the financial services industry to adapt systems to more accurately reflect what the carbon footprint of a project, like a coal-fired power plant, will be. “Our paper talks about the transparency principle because it allows financial systems to truly reflect the environmental impact,” says Dr Macrina.

“Finance is the means by which so much is enabled and achieved. From construction to manufacturing, production and even service delivery. These must be financed and if we can innovate financial systems and find new ways to structure financial instruments, we can make a more meaningful contribution to the role finance plays in incentivising environmentally friendly practices and projects and how physical and financial risk is managed.”