Systematic Investing in practice

Prescient’s approach to investing in credit is systematic – our process is well-defined, researched, back-tested, and sufficiently forward-looking to prepare for any market movements that may come. 

While heavily reliant on quantitative modelling, given the nuances of South African credit, relative to developed global credit markets or more liquid asset classes, we strongly believe that our systematic approach creates consistent outperformance. We are rules-based and sticklers for following well-defined, data driven processes in a consistent manner. 

The PIM Credit Process: Summarised

When considering credit opportunities and, importantly, fund positioning, we start with a top-down approach, assessing the credit environment through the consideration of carefully selected economic variables that we believe contribute to fluctuations in the credit cycle. 

Our Credit Cycle Indicator informs our thematic positioning, which determines target sectoral, risk, term, duration and liquidity exposures for our optimisation process. The optimiser output then informs us which assets are appropriate or not for our funds. Using these outputs, our team can scour the market for deal opportunities.

Figure 1: The PIM Credit Process

Step 1: The Prescient Credit Cycle Indicator

The credit process begins with the Credit Cycle Indicator (CCI), which relies on various macro-economic variables that best explain changes in the level of credit risk we have seen over time in the market. Our CCI, represented in blue below, relies on the Dynamic Factor Model (DFM) framework proposed by Stock & Watson to illustrate the relationship between a set of macro-economic variables and the default probabilities of debt issuers in the market.

Given that corporates only release audited financial statements once a year, we turn to these macroeconomic variables to construct a nowcast of the state of the credit market. Simply put, our CCI statistically shows how the macro environment impacts borrowers’ creditworthiness, allowing us to consider the investments most appropriate for inclusion in our funds.

Starting with 44 different inputs, we regress these on our in-house default probabilities to obtain the factors shown to be most predictive of the current level of credit risk. These factors are then incorporated into the DFM to obtain the Prescient CCI. Importantly, our proprietary rating methodology for default probability assessment has been applied to more than 150 companies and continues to grow as and when we see new opportunities emerge. 

While we constantly test for the inclusion of new variables, at present, we note the following as key to our CCI:

• South African budget versus current account balance as a percentage of GDP
• Business sentiment
• Consumer sentiment
• Consumer price inflation
• Rolling JSE All Share Index returns
• Rolling rand-dollar exchange rate changes.

Figure 2: Credit Cycle Factors (2015 – current)

The graph above shows that the indicator captured the rise in credit risk going into and during the global pandemic, which “corrected” during late 2021 as economic conditions settled. While resultant improvements are noted, the CCI remains elevated compared with pre-pandemic levels.

Figure 3: The PIM Credit Cycle Indicator

Combining these to create a Credit Clock, we can form views on a per-sector and overall basis and determine if we are adequately compensated for the credit risk embedded in credit opportunities. Simply put – this informs our credit outlook, be it credit bullish, bearish, or merely credit neutral. 

Step 2: Thematic positioning 

After back-testing data over various cycles and importantly, considering the CCI, individual and sectoral default probabilities, we have identified the most appropriate assets to include in our portfolio depending on our clock plot. 

Using this, we can attempt to position our portfolio accordingly. Key considerations here include:

• Overall and sectoral credit risk (what to include/exclude)
• Credit spread duration
• Average term to maturity
• Term limits
• Liquidity considerations
• Fund diversity.

Step 3: The optimisation process

After understanding our overall risk view, the resultant factors (with their associated rules) can be fed into our proprietary Credit Optimiser.  This entire process is systematised and, at the click of a button, gives us an answer regarding which opportunities are most appropriate (or not) for our funds. 

Furthermore, the optimisation process yields various portfolio iterations, including a theoretically optimal portfolio. Importantly, we are not simply maximising return, but rather optimising portfolios based on our risk view, which includes, but is not limited to, our risk parameters. Taking this one step further, it allows us to consider whether the current portfolio positioning is appropriate or not. 

Consistently getting to the best solution is only one advantage of this systematic way of investing. Additionally, it removes the human bias inherent in non-quantitative investment decision-making. Portfolio managers can prove that their current fund is very close to, if not at, the optimal point using this mathematically rigorous method.

Step 4: Process focus - Risk management and continued monitoring 

For us, risk management is multi-faceted. While we emphasise downside protection through understanding of the credit cycle, counterparty default probability assessment and market liquidity is also very carefully considered. 

Our process involves getting both the relevant macro-variables that drive the credit market, and the underlying sector and company decisions right. In doing so, we believe that we appropriately measure credit risk across sectors and thereby identify appropriate investment opportunities for our wide range of funds. 

As one can imagine, a systematic investment process relies heavily on a well-oiled data science and analytics approach. With this being said, we continue to prioritise the systematisation of our thinking. This includes the default probability assessment, the optimisation process and, importantly, how we track market liquidity across cycles. Implementing these means that any analyst can consider an opportunity via our proprietary portal at any point. This efficiency allows us to focus on continually refining our process and finding value-adding alpha opportunities.

In summary, it’s important that, despite our sectoral preferences, our credit philosophy is premised on delivering consistent outperformance for our investors via our systematic investment approach. Systematic investing is rational, rules-based, and data-driven, backed by clear strategies that inform our processes. 

Our deep quantitative approach is supported by sound bottom-up analysis, which, when working together, enables us to measure corporate credit risk appropriately across all sectors and thereby identify appropriate investment opportunities for our wide range of funds. DM/BM

Author: Conway Williams – Head of Credit (left) and Sajjaad Ahmed – Quantitative Analyst (right) at Prescient Investment Management.

Disclaimer:

• Prescient Investment Management (Pty) Ltd is an authorised financial services provider (FSP 612).
• The value of investments may go up as well as down, and past performance is not necessarily a guide to future performance.
• There are risks involved in buying or selling a financial product.
• This document is for information purposes only and does not constitute or form part of any offer to issue or sell or any solicitation of any offer to subscribe for or purchase any particular investments. Opinions expressed in this document may be changed without notice at any time after publication. We therefore disclaim any liability for any loss, liability, damage (whether direct or consequential) or expense of any nature whatsoever which may be suffered as a result of or which may be attributable directly or indirectly to the use of or reliance upon the information.
• The forecasts are based on reasonable assumptions, are not guaranteed to occur and are provided for illustrative purposes only.