2024 Estimates
Lamb Quantitative Research (LQR) estimates that assets under management (AuM) of global asset managers ended 2024 at USD 140 trillion - a new high water mark - with USD 10 trillion dollars added in 2024, a rise of 7.8%.
The majority of this increase came from market returns rather than inflows.
Unfortunately for asset managers, we doubt this AuM growth has translated into profit growth: persistant and predictable AuM margin decline (3.7% p.a.) and rising costs (at 3.3% p.a.) have limited profit growth. Moreover, with AuM growth skewed to the large U.S. managers, most managers will be reporting flat profits again for 2024.
We will document this in April, when asset managers have completed their year-end reporting.
2025 AuM Forecast
We forecast global AuM to reach USD 143 trillion at the end of 2025, adding another USD 3 trillion or 2.1%.
This is based on (1) our forecast for the S&P 500 equity index to rise 4.8% in 2025 - positive but below trend - and (2) global AuM's positive correlation with this index.
These forecasts are volatile. The 95% prediction interval range is -9% to +18% of the AuM figure. At the start of 2024, we estimated 2024 AuM growth to be +5%. This was below actual growth at +7.8% growth.
Low Value Creation
Global industry profits have hardly risen since 2012, only 2.5% p.a. in nominal terms. In real terms, factoring in average global inflation over the period of 4.2%, real profits declined 1.7% p.a.
The predicted small rise in AuM in 2025 will not be sufficient to offset rising costs, industry AuM margin decline, and lack in innovation.
Global Net Inflows
Global net inflows will have been 1.9% of global AuM in 2024 - below the 2.8% in 2023 and below trend of 2.5%.
We expect 2025 inflows to be around 2.0% of global AuM in 2024. Global industry net inflows are strongly negatively correlated with specific interest rates.
Happy New Year.
Further details in "Global Asset Management Industry Report: Financials 2024", "Global Asset Management Industry Report: Fundamental Analysis 2024", and "Better S&P 500 Forecasts Using Sentiment, Economic and Market Factors, and Machine Learning"
Source: Lamb Quantitative Research (www.lambqr.com)
Comments