Overcoming the flaw in human judgment
Advancements in technology are leading to new investment approaches. One we think eliminates noise.
Last year we introduced the concept of ‘noise’. Wherever there is human judgment there is noise, and this ‘noise’ is a flaw. This deficiency in decision-making was the subject of Nobel prize-winning psychologist Daniel Kahneman’s1 final book Noise: A Flaw in Human Judgment, co-written with Olivier Sibony and Cass Sunstein.
The book argued, “The simplest rules and algorithms have big advantages over human judges: they are free of noise, and they do not attempt to apply complex, usually invalid insights about the predictors.”
We applied this contention to investing. We argued that it would be possible to analyse large data sets, say company’s balance sheets and annual reports, and then make rules to capture those companies with common patterns.
In our example, we said you could capture those companies with the highest return on equity, lowest leverage and stable earnings growth. These are characteristics of companies that exhibit the ‘quality’ factor. These more ‘complex’ models, we said, are the foundation of smart beta investing.
Rules can be created for other identifiable investment ‘factors’ such as value and low size. VanEck is a leader in smart beta ETF innovation on ASX.
In these ETFs, ‘noise’ is eliminated from the decisions. The advantage of more complex rules, according to Kahneman and his co-authors, “is not just the absence of noise but also the ability to exploit much more information.”
Over the past few years, one of the biggest themes in the investing world has been the artificial intelligence (AI) boom.
The authors of Noise considered AI too. Chapter 10, Noiseless Rules starts with, “In recent years, artificial intelligence (AI), particularly machine-learning techniques, has enabled machines to perform many tasks formerly regarded as quintessentially human.” The authors went on, “AI often performs better than simpler models do.”
More Complexity: Toward Machine Learning
Under the above subheading, the authors of Noise say, “What if we could use many more predictors, gather much more data about each of them, spot relationship patterns that no human could detect, and model these patterns to achieve better prediction? This, in essence, is the promise of AI.
“Very large data sets are essential for sophisticated analyses, and the increasing availability of such data sets is one of the main causes of the rapid progress of AI in recent years.”
What if we could use this technology, which is now being used around the world in other fields, to create equity portfolios?
Advancements in technology and hardware to cater for an unimaginable number of calculations and data points make it possible to construct portfolios to further eliminate ‘noise’, we think.
For example, LLMs (large language models) allow for intricate calculations, programmed learning and consideration of factors beyond traditional investing metrics to create portfolios designed to harvest investment outcomes.
Using all the rules and algorithms
VanEck has a distinguished history of harnessing technology-driven insights and advanced analysis to identify and unlock opportunities for investors. As pioneers of smart beta strategies in Australia for over a decade, we have launched smart beta ETFs that were the first of their kind on the ASX enabling investors to construct investment strategies with a targeted outcome in mind.
Extending on this experience, this week we will be launching the VanEck Australian Long Short Complex ETF (ALFA). ALFA leverages a very large data set to systematically assess 12,000 strategies across quantitative, technical & pairs trading and macroeconomic inputs to create a high-conviction, benchmark and style-agnostic Australian equity portfolio that targets long and short positions.
We think investments like smart beta and investment approaches like ALFA are the portfolio construction tools of the future, echoing the authors of Noise who pondered, when considering rules and technology, “Given these advantages and the massive amount of evidence supporting them, it is worth asking why algorithms are not used much more extensively.”
To learn more about ALFA, register now to join our live session at 11am AEDT Thursday, 30 January.
Key risks: An investment in the Fund carries risk. The Fund is considered to have a higher investment risk than a comparable fund that does not engage in short selling and leverage. Investors should actively monitor their investment as frequently as daily to ensure it continues to meet their investment objectives. Risks associated with an investment in the fund include those associated with short selling risk, leverage risk, prime broker risk, counterparties risk, concentration risk, operational risk and material portfolio information risk. See the VanEck Australian Long Short Complex ETF PDS and TMD for more details.
Source
1. There is no Nobel Prize for psychology. Kahneman was awarded the Nobel Memorial Prize in Economic Sciences in 2002 for his work on Prospect theory.
Published: 19 January 2025
Any views expressed are opinions of the author at the time of writing and is not a recommendation to act.
This information is prepared in good faith by VanEck Investments Limited ACN 146 596 116 AFSL 416755 (‘VanEck’) as responsible entity and issuer of units in VanEck ETFs traded on the ASX. Units in the VanEck Australian Long Short Complex ETF are not currently available. VanEck Australian Long Short Complex ETF has been registered by ASIC. The PDS will be available at vaneck.com.au. The Target Market Determination will be available at vaneck.com.au. You should consider whether or not any VanEck fund is appropriate for you. Investing in ETFs has risks, including possible loss of capital invested. See the PDS for details. No member of the VanEck group guarantees the repayment of capital, the payment of income, performance, or any particular rate of return from any fund.
