Terebinth’s Ann Sebastian: Applying maths to reverse archaic investing models – to very good effect
Head of equities at Terebinth Capital, Ann Sebastian, is having lots of fun participating in its co-sponsored Fantasy Fund Manager game. But her day-to-day work is to select the right stocks to invest in. She does so through a model that applies mathematical formulae to bring together many disparate factors, creating a "holistic" selection process that turns the old ones on their heads. She explained this – and the excellent returns from Naspers – to Alec Hogg of BizNews.
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Excerpts from the interview
Ann Sebastian on Terebinth's approach to investing
So what we like to do is we like to take a holistic approach to investing. We complement quantitative and qualitative information. So as much as we do look at bottom up from looking at companies that are good quality with attractive growth potential at a reasonable valuation, we also look at the top down macro environment from both a qualitative and quantitative perspective. So what's important for us is just amass a large volume of data of the equity market, especially with the market being externalised with 60% of the revenue of South African companies coming from abroad. So if you don't have a good context or understanding of the global macro environment and where we are in that environment, it's not optimal portfolio allocations that you can make. So what we like to do is we take a holistic approach. We blend top down and bottom up qualitative and quantitative information, and we assess the data in a systematic manner to understand where we are in the cycle and make optimal sector and style allocation. So unlike traditional fund managers just in the equity space which only focus on the specific company. We think the macro environment is especially important to make optimal sector allocation. So that's an important aspect that we include in our process.
What Terebinth stands for
So Terebinth – it was founded in 2013 by Erik Nel, and it's actually named after a [species of] tree. But the point is that you have roots that run deep and it really talks to our sustainability, paying it forward, expansion [and] empowering young future leaders and [women]. So it really talks to the deep-running roots and that kind of sustainable business that we try to build in South Africa.
On using AI and advanced technology in their business
[We don't use AI] to such a large extent, but what we do use is machine learning but in a very specific manner. We analyse the macro environment or the business cycle environment using a quantitative macro indicator. So to simply summarise that – what we're trying to do is understand where we are in the global cycle. So we'll summarise data from growth, inflation, liquidity and sentiment subcomponents, and summarise that data to understand where are we in the cycle? Are we in a recovery environment, an expansionary slowdown or contractionary environment? Because we've seen that each of those different phases, different types of companies or styles [or] sectors perform relatively better. So that's one of the ways where we use artificial intelligence or machine learning to understand – using this large volume of global data – where we are in the cycle and what that implies for different sector style opportunities.
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