Half of Systematic Investors surveyed have already integrated AI: Invesco Global Systematic Investing Study reveals

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Invesco Ltd.

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  • Artificial intelligence (AI) revolution is already underway: half of systematic investors surveyed have integrated AI into the investment process and the majority (75%) expect AI to match or exceed importance of traditional investment analysis within a decade.
  • AI is mostly used to understand market trends and to optimize portfolio allocations; investors see potential in testing investment strategies and monitoring and adjusting trading positions in real-time.
  • 41% of respondents are using natural language processing for sentiment analytics, with three-quarters expecting to use it in future.
  • Most investors believe systematic strategies helped them navigate challenging market conditions in 2022.
  • Systematic investing is evolving: investors are broadening their systematic toolkits by using more diverse strategies.
  • 'Growth' becomes an established factor.

NEW YORK, Oct. 30, 2023 /PRNewswire/ -- Invesco Advisers, Inc., a subsidiary of Invesco Ltd. (NYSE: IVZ), today released the findings of its eighth annual Invesco Global Systematic Investing Study, which is the evolution of the Invesco Global Factor Investing Study, published annually since 2016. The reposition this year reflects the changes within the quantitative investing world, and the use of quantitative investment methods beyond just factors. The study, which is based on the views of 130 institutional and wholesale investors that collectively manage $22.5 trillion in assets, also finds a growing consensus that systematic tools can help investors navigate key challenges, such as volatile markets and imperfect data.

How do you use AI in your investment process? Where do you see the most value in the future? Sample size 112

The report found that half of systematic investors surveyed 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%) anticipate that, within a decade, AI will be as important as traditional investment analysis and 13% expect it to become more important.

The AI revolution already underway

Systematic investors are already using AI across a range of core functions. For example, respondents reported harnessing AI to better understand the market environment and identify macroeconomic turning points: (46%) are using AI to identify patterns in market behavior, and (38%) are using it for portfolio allocations and risk management. Investors appreciate AI's ability to help mitigate human biases and forecast the unexpected (Figure 1).

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

Wholesale investors identified improved risk management as the main benefit of AI, cited by (76%) of respondents, followed by the flexibility to adapt to changing market conditions (65%). However, challenges remain: wholesale respondents cited the cost of implementation (64%) and the complexity and interpretability of AI models (61%) as the main obstacles to adoption (Figures 2 and 3).

"AI driven-portfolio strategies certainly present a new opportunity when used correctly," said Mo Haghbin, Head of Solutions, Invesco. "Firms need to adapt quickly to leverage this technology as we see increasing interest in AI-driven models moving forward, especially among younger investors."

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

"Managing stakeholders and providing transparency is a key challenge for institutional investors," continued Mr. Haghbin. "Investors need to be prepared to clearly articulate how AI models are being used in portfolios to justify their use and value add."

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 summarizing 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%) of respondents are using NLP for sentiment analytics, and around three-quarters (73%) 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 (Figure 4).

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 skeptical than their APAC and North America counterparts.

The majority (51%) of EMEA investors believe that AI will still be less important than traditional analysis methods in ten years' time, versus just (10%) in North America and (7%) in APAC. Conversely, just (4%) of EMEA investors believe AI will supplant traditional analysis methods in that period, with much higher numbers observed in both North America (19%) and APAC (20%) (Figure 5).

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 behavior, 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 (Figure 6).  

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%) of investors agreed that systematic strategies helped them manage market volatility in the past year. Moreover, nearly (60%) of respondents said that the new higher inflation market regime was supportive of the systematic approach, with only (6%) of institutional investors and (10%) 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 characterize the underlying macroeconomic regime, allowing them to make inferences about its impact on different asset classes, factors, regions, and sectors.

"Investors are rethinking the way they approach portfolio construction in an environment with macro uncertainty," said Mr. Haghbin. "Respondent data showed investors want to move beyond strategic factors as they try to determine the best way to position portfolios across asset classes and styles."

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 environmental, social and governance (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.

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[1], 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%) view this as a focal point moving forward (Figure 7).

The new macroeconomic environment has also prompted investors to rethink conventional wisdom about what constitutes a factor. Notably, four in five respondents now recognize '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'.

About Invesco Ltd. 

Invesco Ltd. is a global independent investment management firm dedicated to delivering an investment experience that helps people get more out of life. Our distinctive investment teams deliver a comprehensive range of active, passive, and alternative investment capabilities. With offices in more than 20 countries, Invesco managed $1.49 trillion in assets on behalf of clients worldwide as of September 30, 2023. For more information, visit www.invesco.com.

Notes to editors

Figure 1. How investors are using AI in investment process, % citations

How do you use AI in your investment process? Where do you see the most value in the future? Sample size 112

Figure 2. Benefits of AI, % citations

What do you see as the main benefits of using AI in the investment process? Sample size 119

Figure 3. Challenges of AI, % citations

What are the main challenges of using AI in the investment process? Sample size 120

Figure 4. Use of natural language processing, % citations

What types of Natural Language Processing (NLP) techniques do you use in your investment process? Which do you see as playing an important role in the future? Sample size 109

Figure 5. Role of AI in 10 years' time, % citations

How do you see the role of AI in the investment process evolving in the next 10 years? Sample size 127.

Figure 6. How investors are using AI in investment process, % citations

How do you use AI in your investment process? Where do you see the most value in the future? Sample size 112

Figure 7. Asset classes using systematic approach, % citations

In which asset classes of your portfolio are you using a systematic approach? In which parts of your portfolio do you think a systematic approach could be applied? Sample size 128

Important Information

Institutional investors are defined as pension funds (both defined benefit and defined contribution), sovereign wealth funds, insurers, endowments and foundations. Wholesale investors are defined as discretionary managers or model portfolio constructors for pools of aggregated wholesale investor assets, including discretionary investment teams and fund selectors at private banks and financial advice providers, as well as discretionary fund managers serving those intermediaries.

Survey participants experience may not be representative of others, nor does it guarantee the future performance or success of any factor, strategy or product. There may be material differences in the investment goals, liquidity needs, and investment horizons of individual and institutional investors.

Invesco is not affiliated with NMG Consulting.

Investment Risks

Factor investing (also known as smart beta) is an investment strategy in which securities are chosen based on certain characteristics and attributes that may explain differences in returns. Factor investing represents an alternative and selection index-based methodology that seeks to outperform a benchmark or reduce portfolio risk, both in active and passive vehicles. There can be no assurance that performance will be enhanced or risk will be reduced for strategies that seek to provide exposure to certain factors. Exposure to such investment factors may detract from performance in some market environments, perhaps for extended periods. Factor investing may underperform market cap-weighted benchmarks and increase portfolio risk. There is no assurance that the factor strategies discussed in this material will achieve their investment objectives or be successful.

There are risks involved with investing in ETFs, including possible loss of money. Index-based ETFs are not actively managed. Actively managed ETFs do not necessarily seek to replicate the performance of a specified index. Both index-based and actively managed ETFs are subject to risks similar to stocks, including those related to short selling and margin maintenance. Ordinary brokerage commissions apply.

The use of environmental and social factors to exclude certain investments for non-financial reasons may limit market opportunities available to funds not using these criteria. Further, information used to evaluate environmental and social factors may not be readily available, complete or accurate, which could negatively impact the ability to apply environmental and social standards. A strategy that uses an ESG scoring methodology to evaluate securities may forego some market opportunities available to strategies that do not use ESG factors. As a result, a strategy may underperform strategies that do not screen or score companies based on ESG factors or that use a different methodology.

Commodities generally are volatile and are not suitable for all investors.

All data provided by Invesco as at 31 March 2023, unless otherwise stated. The opinions expressed are current as of the date of this publication, are subject to change without notice and may differ from other Invesco investment professionals. The document contains general information only and does not take into account individual objectives, taxation position or financial needs. Nor does this constitute a recommendation of the suitability of any investment strategy for a particular investor. Investors should consult a financial professional before making any investment decisions. Past performance is not indicative of future results. Diversification does not guarantee a profit or eliminate the risk of loss.

Invesco Advisers, Inc. is an investment adviser; it provides investment advisory services to individual and institutional clients and does not sell securities. It is an indirect, wholly owned subsidiary of Invesco Ltd.

1 Quantitative easing is a monetary policy action where a central bank purchases predetermined amounts of government bonds or other financial assets in order to stimulate economic activity.

Not a Deposit Not FDIC Insured Not Guaranteed by the Bank May Lose Value Not Insured by any Federal Government Agency

Media Relations Contact: Matthew Chisum, matthew.chisum@invesco.com, 212-652-4368

 

What do you see as the main benefits of using AI in the investment process? Sample size 119

What are the main challenges of using AI in the investment process? Sample size 120

What types of Natural Language Processing (NLP) techniques do you use in your investment process? Which do you see as playing an important role in the future? Sample size 109

How do you see the role of AI in the investment process evolving in the next 10 years? Sample size 127.

How do you use AI in your investment process? Where do you see the most value in the future? Sample size 112

In which asset classes of your portfolio are you using a systematic approach? In which parts of your portfolio do you think a systematic approach could be applied? Sample size 128

(PRNewsfoto/Invesco Ltd.)

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SOURCE Invesco Ltd.

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