Systematic investing: how we use quantitative techniques to manage Granite multi-asset portfolios

Aly Somani, CFA, Portfolio Manager, SLGI Asset Management Inc.

Quantitative vs. discretionary when managing portfolios

There are two common yet distinct approaches that portfolio managers can use in making investment decisions: discretionary and quantitative (or systematic). Discretionary investing relies on investor experience, judgment and intuition. Quantitative investing typically involves the use of mathematical models or algorithms, often relying on large sets of data or “features.”

Potential advantages of a quantitative investment approach include:

1. Objectivity: Quantitative investing is meant to be objective, reducing or eliminating the influence of emotions to stay disciplined during periods of market panic or euphoria.
2. Quantification of potential performance: Quantitative strategies can be back-tested on historical data, and sometimes simulated on potential future market data. This helps investors assess how such strategies could perform in varying market environments.
3. Risk measurement: Armed with back-tested/simulated performance of an investment strategy, an investor can better manage risk. This includes approximating how much a strategy can add or reduce overall portfolio risk and return as well as enhance diversification. This is also helpful to decide if a stop loss mechanism, volatility threshold or other overlay can further mitigate risk.
4. Scalability, efficiency and speed: Systematic strategies can handle large volumes of data and be applied across multiple markets and asset classes. They can also be automated, enabling faster decision-making even during periods of heightened market volatility.

Potential disadvantages of a quantitative investment approach include:

1. Model risk: A quantitative model is only as good as the accuracy and validity of the data and assumptions behind it. If the model is based on faulty data, inappropriate logic or fails to account for certain trading conditions, it may fail.
2. Overfitting risk: Overfitting occurs when a model is too finely tuned to past data, meaning it might not work well in the future because real markets are never an exact repeat of history. In particular, quantitative models may struggle during unforeseen events, such as financial crises or global pandemics, where markets behave in ways that models may not have adequate data to account for.
3. False sense of precision and potential biases: Quantitative investment models can create a false sense of security due to their mathematical nature. New information and unexpected events can often break quantitative models. If quantitative models are not designed well, the models can have embedded biases such as over-reliance on certain factors or misinterpretation of correlations as causation. Such flaws could lead to systematic errors in investment decision-making.

Despite these risks, quantitative strategies built and overseen by qualified and thoughtful practitioners can significantly enhance long-term investment outcomes. A blend of quantitative models and human judgment combines disciplined, data-driven decision-making with the flexibility to adapt when necessary. At Sun Life Global Investments, the Multi-Asset Solutions Team (MAS) continues to evolve our quantitative models within a broader investment process that retains skilled oversight and an appropriate degree of discretion and judgement.

How quantitative models guide our tactical moves

In early August, one of our tactical quantitative equity models (below) signaled an opportunity to overweight equities within our multi-asset solutions. The headlines at the time were scary, given investor worries about the U.S. economy and a potentially dangerous unwind of the carry trade on the Japanese Yen. Given the immense market volatility, it would have been difficult for a solely discretionary investor to “go against the crowd” at the time and buy equities. But after a rigorous assessment of the model’s signal and the market environment and potential risks, we decided to follow our model’s signal to increase equity exposure.

Our diligence in following the model was rewarded with an over 8% trade return over the next three weeks. Investor worries abated over this three-week period and sentiment shifted closer to being neutral, leading the model (and us) to promptly close the trade. This trade is one example of how quantitative models are being used by us to remain data-driven, objective and nimble in challenging markets to continue to add value for clients.

MAS short-term equity risk appetite indicator

The above chart shows the price of the S&P 500 (USD) in the upper pane with our Short-term Equity Risk Appetite Indicator in the bottom pane. The green shaded area represents the period during which we added and then exited our equity portfolio addition. The Short-term Equity Risk Appetite Indicator looks for unusual readings in a wide variety of normalized metrics (including volatility, correlation between stocks, credit spreads, liquidity, etc.) meant to capture aspects of short-term capitulatory investor behaviour that tend to revert over approximately the next two-eight weeks.

Views expressed regarding a particular company, security, industry or market sector should not be considered an indication of trading intent of any mutual funds managed by SLGI Asset Management Inc. These views are subject to change at any time and are not to be considered as investment advice nor should they be considered a recommendation to buy or sell. Examples of trading strategies are included for illustrative purposes only and are not predictive of future results of the manager or the strategy it employs to identify and act on leading market indicators.  Any discussion of past results may have been favorably impacted by events and economic conditions that may not prevail in the future.  There are numerous other factors related to the markets in general or to the implementation of any specific trading strategy that cannot be fully accounted for in the preparation of hypothetical performance results and all of which can adversely affect actual trading results.  Undue reliance should not be placed on these results.  It is not possible to directly invest in an index or quantitative model.

Commissions, trailing commissions, management fees and expenses all may be associated with mutual fund investments. Please read the prospectus before investing. Mutual funds are not guaranteed, their values change frequently, and past performance may not be repeated.

SLGI Asset Management Inc. is the investment manager of the Sun Life family of mutual funds. Sun Life Global Investments is a trade name of SLGI Asset Management Inc., Sun Life Assurance Company of Canada, and Sun Life Financial Trust Inc., all of which are members of the Sun Life group of companies.

© SLGI Asset Management Inc. and its licensors, 2024. SLGI Asset Management Inc. is a member of the Sun Life group of companies. All rights reserved.