Measuring financial markets’ expectations of economic downturns in real time
Bulletin No. 264, article 2. In an economic environment marked by heightened uncertainty and rapid economic turnarounds, macroeconomic analysis relies heavily on econometric models designed to track and forecast changes in activity. These models, which rely primarily on indicators and surveys available on a monthly or quarterly basis, are not designed to incorporate shifts in the economic cycle in real time. Analysts therefore use financial variables that, in principle, continuously reflect market expectations. For example, an inverted yield curve (where long-term rates are lower than short-term rates) generally signals that markets expect an economic slowdown.
This article introduces a new indicator that uses machine learning techniques and aims to measure markets’ expectations regarding the risk of an economic downturn in the United States and Europe, based on a vast set of financial variables.
Economic recessions are among the most difficult macroeconomic phenomena to forecast. Public institutions, in particular central banks, traditionally rely on macroeconomic models designed to analyse the transmission mechanisms of economic policy and produce medium-term scenarios. These tools play a central role in the formulation of monetary policy decisions and rely to a large extent on low-frequency aggregate data. Despite advances in forecasting methods and the growing wealth of available data, economic downturns can generally only be identified as and when they are reflected in short-term economic indicators. This difficulty in detecting slowdowns at an early stage has led the literature to explore alternative data sources that are likely to reflect a deterioration in expectations regarding the future state of the economy at an earlier stage.
Financial markets are a valuable source of information for macro financial analysis. Thanks to the real-time, high-frequency availability of asset prices, economists and analysts are able to derive composite indicators that capture expectations, risk aversion and financial conditions. Indeed, investors’ expectations regarding the economy’s trajectory are a key determinant of financial market dynamics.
Over the 2022–25 period, Russia’s invasion of Ukraine, the tightening of monetary conditions in the United States and Europe, episodes of banking stress, and Donald Trump’s announcements of tariff increases led analysts and investors to reassess several times the risk of recession, both in the United States and in Europe. In both regions, the integration of the risk of an economic downturn was reflected in an adjustment of interest rates on their sovereign debt, a fall in share prices, and an appreciation in safe-haven assets.
These recent episodes illustrate how valuations across different asset classes (equities, bonds, derivatives and commodities) adjust in tandem to geopolitical tensions, measures taken by monetary and fiscal authorities, and, more broadly, financial shocks that may lead market participants to revise their expectations regarding economic activity, inflation and interest rates. The dynamics of these valuations are rarely isolated, and the intensity of their interactions may vary over time depending on the macroeconomic and financial context. Analysing these joint dynamics is therefore key to understanding financial conditions and their transmission to the real economy. …
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Updated on the 10th of September 2026