In fixed income markets, inflation expectations are among the most powerful drivers of return. They influence nominal yields, central bank policy, and the premium investors demand for holding inflation-sensitive assets. But capturing these expectations with precision isn’t straightforward. No single measure fully captures market sentiment, and real-time data can be elusive. That’s why combining different types of inflation indicators—market-based breakeven rates and data-driven estimates—can offer a more robust trading signal.
Understanding the Two Faces of Inflation Expectations
Inflation expectations can be inferred in two primary ways: through market prices and through economic data. Market-implied expectations, like breakeven inflation rates, are drawn from the pricing of inflation-linked assets. On the other hand, formulaic models use actual inflation data and central bank targets to derive estimates that approximate how informed participants might view future inflation.
Each approach has distinct advantages. Breakeven rates reflect real-time sentiment and respond rapidly to new information. However, they are influenced by risk premia and liquidity conditions, which can introduce noise. Formulaic estimates, while slower to adjust, offer transparency and reflect a structured interpretation of recent inflation trends and central bank credibility.
Market-Based Breakevens: Fast, But Flawed
Breakeven rates are derived from the difference between yields on nominal and inflation-linked bonds or swaps. They represent the market’s implicit forecast of inflation. Because these rates react immediately to financial developments, they are useful for capturing high-frequency sentiment shifts. However, they also reflect compensation for inflation uncertainty and liquidity premiums. This means that breakeven rates may deviate from “true” inflation expectations, especially in times of market stress or policy uncertainty.
For countries with deep bond or swap markets, such as the U.S., U.K., and euro area, breakevens provide continuous and tradable signals. But interpreting these rates correctly requires caution, particularly when markets are distorted by central bank interventions or sharp swings in risk appetite.
Data-Driven Estimates: Stable and Structured
Formulaic inflation estimates approach the problem from another angle. They assume that market participants build expectations based on historical inflation and the credibility of policy targets. A typical model might weigh recent core and headline inflation data against official inflation targets, adjusted for past deviations.
This method offers several strengths. It is methodical, transparent, and avoids the noise of market swings. These estimates are well suited to capturing structural shifts in inflation dynamics or central bank behavior. However, they miss short-term market insights and do not reflect prices of commodities or exchange rates unless these are already embedded in CPI.
Despite their limitations, formulaic expectations complement breakeven rates by offering a longer-term and less volatile view.
Inflation Signals and Swap Returns
Changes in inflation expectations have clear implications for interest rate swap (IRS) returns. Rising expectations typically lead to higher nominal yields, increasing the cost of fixed-rate positions and reducing returns for fixed receivers. This impact flows through three channels: the need to maintain real interest rate levels, inflation risk premia, and anticipated central bank tightening.
In theory, changes in expectations should be reflected immediately in swap pricing. In practice, markets respond gradually. Factors such as trading frictions, investor inertia, and macro data lags mean that shifts in expectations often take time to be priced in. This creates an opportunity for predictive modeling.
Empirical Insights from the U.S. and Euro Area
Empirical analysis focused on 5-year swap returns in the U.S. and euro area—two markets most influenced by their own inflation trends. By measuring changes in both breakeven and formulaic expectations over the previous month, analysts found that each indicator provided valuable predictive insight.
For breakeven changes, the relationship with swap returns was significantly negative, as expected. Market-implied inflation shifts tended to precede swap price adjustments. Prediction accuracy for return direction reached just above 53%.
Formulaic expectation changes performed slightly better. These data-driven signals, though less volatile, correlated more strongly with subsequent swap returns, with accuracy nearing 54%.
Combining the Signals: A More Potent Predictor
The most striking results came from blending the two inflation signals. Although breakevens and formulaic estimates shared only modest correlation, their combination produced a stronger, more consistent predictive model.
By standardizing both series and summing their z-scores, a composite signal was created. This signal captured the complementary strengths of each metric—breakevens for short-term sentiment and formulaic models for long-term structure. The resulting indicator was noticeably more effective than either input alone.
Backtests over a 17-year period showed the composite signal achieved nearly 57% accuracy in predicting the direction of 5-year IRS returns on a monthly basis. The signal’s predictive power held in both rising and falling yield environments, suggesting versatility across market conditions.
Final Thoughts
Inflation expectations remain a cornerstone of fixed income pricing. While no single measure can capture their full impact, combining breakeven rates and formulaic estimates can provide a balanced, high-quality signal for tactical swap positioning. Traders and portfolio managers seeking to improve their timing and reduce noise would do well to monitor both types of inflation expectations—especially when used together as a composite indicator.
In an environment where inflation remains central to policy and market direction, refining the tools for understanding expectations is not just useful—it’s essential.
