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Invesco study finds AI widely integrated into systematic investing


Invesco has released the findings of its eighth annual Invesco Global Systematic Investing Study. 

The Invesco Global Systematic Investing Study is an evolution of the Invesco Global Factor Investing Study, published annually since 2016. The firm writes that the reposition this year reflects the changes within the quantitative investing world, and the use of quantitative methods beyond just factors. The study, which is based on the views of 130 institutional and wholesale investors that collectively manage USD22.5 trillion in assets, also finds a growing consensus that the systematic toolkit can help investors navigate key challenges, such as volatile markets and imperfect data.

The report found that half of systematic investors have already integrated artificial intelligence (AI) into their investment process and reveals a widespread expectation that AI tools will transform portfolio management in the years to come. The majority (62 per cent) anticipate that, within a decade, AI will be as important as traditional investment analysis and 13 per cent expect it to become more important.

The AI revolution already underway

Systematic investors are already using AI across a range of core functions.

Respondents reported harnessing AI to better understand the market environment and identify macroeconomic turning points: (46 per cent) are using AI to identify patterns in market behaviour, and (38 per cent) are using it for portfolio allocations and risk management. Investors appreciate AI’s ability to help mitigate human biases and forecast the unexpected.

Investors expect the use of AI to grow significantly in the coming years. While a significant minority (29 per cent) already use it to develop and test investment strategies, the vast majority (76 per cent) anticipate doing this in future, and while (20 per cent) currently use it to monitor and adjust investments positions in real-time, more than half (55 per cent) expect to do so moving forward.

Wholesale investors identified improved risk management as the main benefit of AI, cited by (76 per cent) of respondents, followed by the flexibility to adapt to changing market conditions (65 per cent). However, challenges remain: wholesale respondents cited the cost of implementation (64 per cent) and the complexity and interpretability of AI models (61 per cent) as the main obstacles to adoption.

“Among wholesale investors, we found a concern around the potential for AI-driven portfolio strategies to overshadow traditional models”, says Bernhard Langer, CIO, Quantitative Strategies at Invesco. “There is a sense that AI-driven models will be attractive to investors moving forward, particularly younger ones, meaning firms must adapt quickly.”

Institutional investors instead see accurate and timely insights (78 per cent) as the most compelling benefit of AI, followed by improved risk management (74 per cent) and increased efficiency and automation (68 per cent). Their primary concerns are complexity (78 per cent) and data quality and completeness (51 per cent).

“The key challenge for institutional investors is stakeholder management. Investors need to be able to explain and justify the use of AI models as their stakeholders are wary of ‘black box’ solutions”, says Langer. “The regulatory landscape surrounding the use of AI and decision accountability also remains ambiguous.”

The rise of natural language processing tools

Investors have embraced natural language processing (NLP) tools, which have been harnessed for a range of operations, such as summarising and digesting whitepapers, converting recommendations into accessible language for sales teams, and modifying communication tonality for different client groups.

NLP models have also been deployed in the investment process. (41 per cent) of respondents are using NLP for sentiment analytics, and around three-quarters (73 per cent) expect to do so in the future. Several investors reported searching online social channels to uncover prevailing market narratives around firms, measuring frequency of mentions and context, providing valuable insight for assessing risks and making short-term trading decisions.

APAC and North America lead the way

However, Invesco’s study found significant regional variations in attitudes towards AI and NLP, with investors in EMEA markedly more sceptical than their APAC and North America counterparts.

The majority (51 per cent) of EMEA investors believe that AI will still be less important than traditional analysis methods in ten years’ time, versus just (10 per cent) in North America and (7 per cent) in APAC. Conversely, just (4 per cent) of EMEA investors believe AI will supplant traditional analysis methods in that period, with much higher numbers observed in both North America (19 per cent) and APAC (20 per cent).

Moreover, North America and APAC investors are currently far more likely to be using AI in the investment process. APAC investors are twice as likely as EMEA investors to be using AI to identify patterns in market behaviour, and more than three times as likely to be using AI to adjust investment positions in real time. EMEA investors trail North America and APAC investors in each aspect of AI adoption. 

The growing systematic toolkit helps investors tame markets

Factor investing has historically been the cornerstone of systematic investing, but Invesco’s study reveals a far larger toolkit of systematic strategies that have helped investors navigate the key challenges of recent years.

Tools to decipher the macroeconomic environment have become especially important, and the ability of systematic approaches to help mitigate market risks was a key theme in this year’s study: the majority (63 per cent) of investors agreed that systematic strategies helped them manage market volatility in the past year. Moreover, nearly (60 per cent) of respondents said that the new higher inflation market regime was supportive of the systematic approach, with only (6 per cent) of institutional investors and (10 per cent) of wholesale investors disagreeing. 

For three-quarters of respondents, dynamic asset allocation has become a core component of their approach, helping them to rebalance and adjust their portfolios in response to the market environment. Systematic tools have helped investors identify and characterise the underlying macroeconomic regime, allowing them to make inferences about its impact on different asset classes, factors, regions, and sectors.

“Recent challenges have prompted investors to question how they navigate unexpected obstacles”, said Langer. “Respondents spoke of expanding beyond factors to better understand markets and identify when certain asset classes tend to outperform others”.

Bridging the ESG data gap

However, the usefulness of systematic approaches is not limited to the macroeconomic picture; respondents have commended systematic strategies as an antidote to the challenges around ESG, particularly bridging the ‘data gap’.

Invesco’s study found around two-thirds of respondents are using systematic strategies to incorporate ESG into their portfolios, and systematic tools have become useful for helping investors decode ESG variables and metrics, which can have a meaningful impact on performance.

Around half of respondents agree that systematic investing can help to apply ESG when data is scarce, and many noted that they were using systematic tools to reconcile the inconsistencies between ratings agencies and develop company scores from raw data.

“There is a low correlation between different ESG ratings agencies, which is of course a much less mature market than credit ratings. So we found investors were turning to systematic models to boost the quality of available data”, says Langer.

Beyond traditional asset classes and factors

Invesco’s study also found a growing consensus that the systematic approach can be applied across a broader range of asset classes than previously thought.

Systematic models are now well-embedded within fixed income and equities, but higher yields, coupled with a shift from quantitative easing, has meant that conventional macroeconomic considerations have returned to the fore in determining returns across various countries and sectors. This has boosted the appeal of systematic strategies for commodities and currencies: while only a quarter currently target commodities this way, (59 per cent) view this as a focal point moving forward.

The new macroeconomic environment has also prompted investors to rethink conventional wisdom about what constitutes a factor.

Notably, four in five respondents now recognise ‘growth’ as a standalone factor, challenging traditional academic views which contended that ‘growth’ was difficult to define precisely. Investors do not see growth as the opposite of value, or vice versa; rather, as distinct and in some cases complementary factors, as evidenced by the rise of nuanced and blended factors like ‘growth at a reasonable price’.

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