Nick Millington, Head of Systematic Index Solutions at Aberdeen says investing quant investing offers the potential of enhanced returns relative to funds that simply track an index, but at a lower cost than traditional active strategies.
Systematic investing, also often referred to as ‘quant investing’, may appear an arcane science to some fund selectors, one which draws on algorithms and complex mathematics.
And while most will be comfortable with traditional active funds or passive trackers that simply replicate a benchmark index, a systematic approach to portfolio management may be a more challenging concept.
Despite the seeming complexity lying behind systematic investing, the goal of strategies that apply this approach is very simple: to help investors achieve better outcomes driven by evidence by harnessing the power of data and technology.
In doing so, investing becomes more objective, repeatable and robust, removing human emotion at times of market duress when judgement can become clouded by fear or greed.
Put simply, these funds aim to outperform standard index trackers by making small, systematic bets without taking on extra risk.
At the heart of systematic strategies lies the discipline of applying well-established and sensible investing concepts at scale.
These include buying well run companies at a reasonable price and at a point in the cycle when the market looks set to reward them.
This discipline can be implemented across a whole universe of investment opportunities to take profits, cut losses and avoid drifting into unintended risk concentration within portfolios or taking on risk where you don’t have conviction, while reviewing weightings in light of fresh market information.
A growing number of fund selectors are recognising the appeal of quant investing and a range of broader trends are driving greater market presence and demand.
One of the most significant developments over recent years is the explosion of data governing all areas of life and financial data is no different.
This abundance of data can be processed and analysed much more quickly and efficiently by quant models than their human equivalents.
Another key driver of fund selection that has risen to prominence is the need for value for money, evidenced in part by the significant market share now commanded by low cost passive investment vehicles.
Systematic investing, however, can offer the potential of enhanced returns relative to funds that simply track an index, but at a lower cost than traditional active strategies.
Finally, the consistency and transparency that quant investing offers, with a methodical, disciplined and repeatable framework is proving appealing at a time of market instability.
Framed in these terms, it would be difficult to deny the attraction of systematic investing, but fund selectors will rightly want to look under the bonnet to understand how these funds work in practice.
The process typically starts with teams of quantitative analysts building models that process vast amounts of financial information and assess factors that may impact stock returns. These might include company earnings, market trends and sentiment among market participants.
These models follow a disciplined process that is designed to recognise trends and patterns in markets, unearth opportunities and avoid risk and, in doing so, select appropriate investments.
Importantly, this process is conducted without the gut instinct and biases that might influence asset allocation decisions made solely by humans. While some might describe this as ‘black box’ portfolio management, we feel the term ‘glass box’ is more appropriate.
We believe this more accurately reflects the transparency with which investors can see how investment decisions are made and where risks and returns arise.
While the economic rationales that systematic investing references may vary from one firm to another, by way of example, we focus on three key factors that influence the scores which we attribute to every stock in the market: valuation, quality and momentum.
The first, valuation, considers whether a stock is trading at an attractive price. Second, quality is a measure of a company’s fundamentals – whether it is well managed and financially sound.
Finally, momentum reflects whether a stock is benefitting from positive sentiment within the broader market.
Based on these scores, the model then ranks all stocks within a chosen universe and allocates a larger proportion of capital relative to that index to those which rank higher while investing less in those that look least attractive.
The resulting portfolio weightings are not static, however. The process is repeated regularly, often on a monthly basis, enabling them to be adapted to reflect fresh information and an evolving market backdrop.
There is a wide range of systematic investment strategies available, making them compelling considerations for most investors.
For instance, rules-based index solutions will aim to outperform standard index funds by making small, systematic bets without taking on extra risk.
Other solutions, meanwhile, may be customised by quant teams who tilt portfolios to meet specific investor objectives, such as sustainable investing, income generation or risk management.
In addition, quant models can be applied across regions and asset classes, creating the building blocks of diversification and sources of return.
Systematic investing can also apply dynamic risk management, adapting quickly to new risks such as economic shocks, geopolitical events or regulatory changes.
This will adjust portfolio exposures as markets shift so the strategy remains intentional. Against the current market backdrop where economic shocks occur with frequency and geopolitical risk is heightened, this steady discipline may have a particular resonance with investors.
Regardless of the algorithms that underlie it, quant investing is not about replacing human insight, it’s about enhancing it.
It combines the discipline of data-driven models with the expertise of investment professionals to offer investors of all stripes transparent solutions with the potential of providing consistent, risk-adjusted returns within a cost-effective strategy.
Past performance is not a reliable guide to future returns. You may not get back the amount originally invested, and tax rules can change over time. The writer’s views are their own and do not constitute financial advice.
This information should not be relied upon by retail clients or investment professionals. Reference to any particular investment does not constitute a recommendation to buy or sell the investment.
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