Research published by LSEG Data & Analytics has cast fresh doubt on some of the most widely cited tools used to anticipate equity market turning points, finding that investor sentiment surveys and fund flow data offer little predictive power, while financial conditions indicators (FCIs) may provide more actionable intelligence.
The analysis, authored by LSEG’s research team, challenges conventional wisdom around measures such as the Investors Intelligence and AAII sentiment surveys. Though frequently referenced in financial media, the bull-to-bear ratio these surveys produce has no identifiable threshold at which “bullish” tips into “dangerously bullish.” Plotted against S&P 500 performance, the signals are, at best, inconclusive.
Similarly, European investment fund equity exposure, tracked using LSEG Lipper data, is now at its highest level in three decades, reaching 45.53% at end-2025. While that figure sounds alarming, the research notes it reflects asset revaluation and a corresponding decline in bond holdings rather than any active repositioning that could flag a forthcoming reversal. An investor who treated the previous pre-GFC peak in 2006–07, when exposure hit 41.44%, as a sell signal would have missed substantial subsequent gains.
Fund flows tell a similarly murky story. Annual equity inflows into European-domiciled mutual funds and ETFs averaged €35.49bn between 2000 and 2024. The largest single-year inflows, €303.49bn in 2021 and €172.54bn in 2020, did not precede notable drawdowns in the short term, and correlation between annual flows and the following year’s returns is, statistically speaking, negligible.
Where the paper’s findings are more constructive is on FCIs. Since the global financial crisis of 2008 upended the assumption that markets are inherently self-correcting, FCIs have grown in influence among both institutional investors and central banks. LSEG’s own suite of FCIs, covering the US, eurozone, Japan, the UK, Canada and China, uses seven equally weighted macro variable subsets, Z-scored to avoid look-ahead bias.
For the full breakdown, read the story here.
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