Page 33 - Profile's Unit Trusts & Collective Investments - March 2025

History of Collective Investment Schemes

recovery which, apart from a major ‘correction’ in 2002/3 (the DJIA and Alsi fell 35% and 37%
respectively), continued until late 2007. In the US, markets peaked in October 2007; in SA the JSE
enjoyed a final burst which took it to record levels in May 2008 – 20 times what it had been in
February 1988.
As with the crash of 1987, the market declines in 1998 and 2002/3 had a relatively muted impact
on the unit trust industry. In 2002, total industry assets still rose 3% in spite of an 11% fall in equity
prices over the calendar year – although in the decade from 1992 to 2001 industry assets grew by
32% per year, on average. From 2003 to 2007 industry assets again grew at almost 30% per annum.
In spite of 2008’s 26% decline in the JSE’s All Share index and global fears of an economic
meltdown comparable to the crash of 1929 (which led to the Great Depression of the 1930s),
industry assets still managed to show 1% growth in 2008, testimony to the newfound resilience of
the unit trust industry and the hard-earned wisdom of investors.
As in 1987, many seasoned investors who had been in the market for decades had confidence
that markets, given time, would recover, and some investors saw the decline in equities as an
opportunity to get into the market at favourable levels.
The number of rand-denominated collective investment schemes has steadily increased over the
years – at the end of September 2024, according to ASISA, there were 1 856 domestic funds in South
Africa, of which approximately 15% were institutional-only funds (ie, funds with no retail classes,
although many of these are available indirectly in the retail market via LISPs). In addition, 723 foreign
currency denominated funds registered with the FSCA were on sale in SA at the end of September 2024.
The Impact of Technology
As in most areas of the modern world, technology has had a significant impact on the evolution
of collective investment schemes.
The explosion of products seen in the 1990s was partly due to the development of sophisticated
computer systems which made the administration of CISs relatively easy. Most aspects of the
administration of a unit trust depend on computer systems, from calculating daily NAV prices to
managing asset allocation, from administering repurchases to allocation of interest and dividends.
As computer systems became more user-friendly and more widely available, the systems
requirements for setting up and managing unit trusts became less of a barrier to entry, allowing
new, smaller companies to launch unit trusts, and allowing the larger institutions to manage
multiple unit trust offerings with comparative ease.
The impact of technology was not only felt in the “back office”, however. While administration of
unit trusts was getting easier, technology was also creating new opportunities for fund managers.
Modern, sophisticated computer systems give fund managers far more control over portfolios
than their counterparts of four decades ago. Tracker funds, ETFs and funds that are based on
quantitative analysis are good examples of products that would not exist were it not for the
advances in data processing and automation of computer systems. These popular products rely on
the fund manager’s ability to construct a portfolio which mimics, as far as possible, the
composition of a major index (such as the JSE’s Top 40 index, for example). Calculating the correct
proportions of each stock holding on a daily basis in the face of day-to-day changes in share prices –
and generating orders early enough to ensure they are filled – is dependent on computer systems.
Artificial intelligence and big data analysis is the latest technological advance that is having a
major impact on asset management and investing in general.
Data analysis has always been a key feature in the selection of shares and other securities. AI
and machine learning is now being used to rapidly collect and analyse huge data sets that include
market trends, economic indicators, and customer behaviour helping managers to gain deeper
insights into the securities they select.
AI and machine learning is also being used to optimize asset allocation and the risk
management of portfolios.
Products such as hedge funds are also highly dependent on technology from an asset
management point of view. A fund manager making extensive use of derivatives may seek to adjust

Profile’s Unit Trusts & Collective Investments — Understanding Unit Trusts 31