Global industry flows: a new enhancement to our systematic investment process
Global industry flows: a new enhancement to our systematic investment process
Yuangao Liu and Amadeo Alentorn describe a new enhancement the Jupiter systematic team has developed and introduced into its investment process.
Over recent months we have been researching, developing and testing a new enhancement to our investment process that we believe has the potential to increase returns from our allocation to industries and sectors, and to increase diversification.
The enhancement is based on our analysis of data about funds flows into global industries. Fund flows are the cash that goes in and out of relevant funds and as those funds allocate to stocks, sectors and industries. By industries we mean MSCI’s GICS industries at a global level: for example, airlines, banks, electrical equipment, insurance, software, and water utilities. There are currently 74 industries in the MSCI GICS classification. By carefully analysing money flowing through funds into each industry, we believe we can invest more successfully in each of them, in the context of our entire investment process. The enhancement is founded on a simple intuition: that as money flows into relevant funds, and they allocate to specific industries, that tends to increase the prices of stocks in those industries. Our analysis has backed this simple intuition by highly detailed empirical research based on large amounts of data. After concluding several months of thorough research and successful testing, we have now brought the new industry flows enhancement into operation across all the systematic strategies we manage, both long-short and long-only, for all regions.
The enhancement is based on our analysis of data about funds flows into global industries. Fund flows are the cash that goes in and out of relevant funds and as those funds allocate to stocks, sectors and industries. By industries we mean MSCI’s GICS industries at a global level: for example, airlines, banks, electrical equipment, insurance, software, and water utilities. There are currently 74 industries in the MSCI GICS classification. By carefully analysing money flowing through funds into each industry, we believe we can invest more successfully in each of them, in the context of our entire investment process. The enhancement is founded on a simple intuition: that as money flows into relevant funds, and they allocate to specific industries, that tends to increase the prices of stocks in those industries. Our analysis has backed this simple intuition by highly detailed empirical research based on large amounts of data. After concluding several months of thorough research and successful testing, we have now brought the new industry flows enhancement into operation across all the systematic strategies we manage, both long-short and long-only, for all regions.
Investor behaviour
Analysing fund flows is important, we believe, because of behavioural tendencies towards herding and synchronisation among market participants. Investors can tend to mimic each other’s behaviour. In situations where information is insufficient or ambiguous, it is a psychological trait to assume that the consensus view is correct. Humans have been described as ‘predictably irrational’1. Behavioural tendencies can lead to persistent flows into popular industries. When flows are persistent, there can be forecastable effects on stock prices, especially in the short to medium term.
Alpha from industries
It would be possible to manage a systematic process by neutralising industry-level exposure and focusing entirely on stock-level exposure. However, we believe there is alpha to be gained by exposure to industries. We have for many years developed and employed signals that help our positioning in sectors and industries, and the new industry flows component is a way of enhancing our existing analysis, and an evolutionary step within our long-term research programme. Specifically, it adds to the strength of our shorter-term industry level signals within our market dynamics stock selection criterion. It complements existing signals within our sentiment and market dynamics stocks selection criteria. (We have five main stock selection criteria: dynamic valuation, sustainable growth, sentiment, management quality, and market dynamics.)
Those familiar with our process will be aware that the majority of our returns in excess of the benchmark have historically been attributable to stock selection (individual stock picking), and only a minority to sector allocation. We believe the new industry flows enhancement has the potential to increase our alpha from sector allocation, while not detracting from stock selection. However, we expect most of our alpha to continue to come from stock selection as before. We believe in incremental, well-researched improvements that accumulate over time.
In recent months we have reported numerous enhancements to our process, of which industry flows is just the latest2.
Those familiar with our process will be aware that the majority of our returns in excess of the benchmark have historically been attributable to stock selection (individual stock picking), and only a minority to sector allocation. We believe the new industry flows enhancement has the potential to increase our alpha from sector allocation, while not detracting from stock selection. However, we expect most of our alpha to continue to come from stock selection as before. We believe in incremental, well-researched improvements that accumulate over time.
In recent months we have reported numerous enhancements to our process, of which industry flows is just the latest2.
Momentum and fund flows
The generic momentum factor in general has been widely studied and a number of important academic papers have been published about it3. For many years there has been good evidence that stocks which have performed well in the past exhibit a significant tendency to outperform. Despite the wide academic study of momentum, the factor has persisted (which is an argument against the validity of the efficient market hypothesis relied upon by many passive investors). We believe that markets contain exploitable behavioural anomalies that can be detected by careful analysis and better outcome can be achieved through active and systematic management. For many years we have deployed sophisticated ways of exploiting momentum (progressing far beyond a vanilla generic form of the factor) within our market dynamics criterion.
Whereas generic momentum has been widely studied, by contrast, momentum due specifically to fund flows is an under-researched field, in our view. One of the academics who has pioneered this field is Dong Lou, Professor of Finance at the London School of Economics, who researched a significant flow-induced price pressure effect on stock returns4. Professor Lou is also an academic consultant to the Jupiter Systematic team. We believe our new industry flows enhancement goes beyond existing published academic research. We discovered it by empirical investigations of hundreds of gigabytes of data. In academic research, it is typical for fund flow data to suffer from low frequency and lengthy time lags. This blunts the sharpness of the analysis. We were able to identify a third-party data provider that improves both the frequency and time lag of such data. An analogy would be using a more powerful microscope, allowing you to see more detail.
The industry flows enhancement builds on previous research we have undertaken into fund flows. In November 2021, we introduced a new component to extract useful stock level information from fund flows5. The current enhancement differs in that it focuses on information at the global industry level. The fund flow signal utilises the information we have discovered in fund flow data to inform our expectations of the future return pattern of individual stocks, whereas the new global industry level signal focuses on the aggregated information in groups defined by GICS industries, also augmented by the lead-lag effect within each group.
For many years we have incorporated (within our sentiment stock selection criterion) signals based on sell-side analysts’ research; we are pleased that both the 2021 flows enhancement and the new industry flows enhancement add signals based on research into the buy-side, thus broadening our analysis of market participants’ activity.
Central to the Jupiter Systematic philosophy is a continuous and disciplined research effort to ensure that our investment process improves over time. Over the past 18 years, this philosophy has resulted in a regular stream of evolutionary changes to our investment process, leading to improvements in our expected risk adjusted returns over time. We currently have several other exciting research projects under way, and we look forward to bringing you more details of these in due course.
Whereas generic momentum has been widely studied, by contrast, momentum due specifically to fund flows is an under-researched field, in our view. One of the academics who has pioneered this field is Dong Lou, Professor of Finance at the London School of Economics, who researched a significant flow-induced price pressure effect on stock returns4. Professor Lou is also an academic consultant to the Jupiter Systematic team. We believe our new industry flows enhancement goes beyond existing published academic research. We discovered it by empirical investigations of hundreds of gigabytes of data. In academic research, it is typical for fund flow data to suffer from low frequency and lengthy time lags. This blunts the sharpness of the analysis. We were able to identify a third-party data provider that improves both the frequency and time lag of such data. An analogy would be using a more powerful microscope, allowing you to see more detail.
The industry flows enhancement builds on previous research we have undertaken into fund flows. In November 2021, we introduced a new component to extract useful stock level information from fund flows5. The current enhancement differs in that it focuses on information at the global industry level. The fund flow signal utilises the information we have discovered in fund flow data to inform our expectations of the future return pattern of individual stocks, whereas the new global industry level signal focuses on the aggregated information in groups defined by GICS industries, also augmented by the lead-lag effect within each group.
For many years we have incorporated (within our sentiment stock selection criterion) signals based on sell-side analysts’ research; we are pleased that both the 2021 flows enhancement and the new industry flows enhancement add signals based on research into the buy-side, thus broadening our analysis of market participants’ activity.
Central to the Jupiter Systematic philosophy is a continuous and disciplined research effort to ensure that our investment process improves over time. Over the past 18 years, this philosophy has resulted in a regular stream of evolutionary changes to our investment process, leading to improvements in our expected risk adjusted returns over time. We currently have several other exciting research projects under way, and we look forward to bringing you more details of these in due course.
1 Dan Ariely, Predictably Irrational: The Hidden Forces That Shape Our Decisions, 2008, HarperCollins.
2 For an overview of our enhancements over recent years see https://www.jupiteram.com/uk/en/professional/insights/gear-enhancing-our-investment-process/
3 A seminal paper is Jegadeesh, Narasimhan and Titman, Sheridan, Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency (1993), The Journal of Finance, 48, 1, pp. 65-91.
4 Lou, Dong, A flow-based explanation for return predictability (2012), Review of Financial Studies 25, pp. 3457-3489.
5 https://www.jupiteram.com/uk/en/professional/insights/go-with-the-flo-a-new-alpha-model-factor/
2 For an overview of our enhancements over recent years see https://www.jupiteram.com/uk/en/professional/insights/gear-enhancing-our-investment-process/
3 A seminal paper is Jegadeesh, Narasimhan and Titman, Sheridan, Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency (1993), The Journal of Finance, 48, 1, pp. 65-91.
4 Lou, Dong, A flow-based explanation for return predictability (2012), Review of Financial Studies 25, pp. 3457-3489.
5 https://www.jupiteram.com/uk/en/professional/insights/go-with-the-flo-a-new-alpha-model-factor/
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