Interest rate markets respond not only to central bank policy but also to underlying macroeconomic momentum. One key driver is aggregate demand—the overall pace of spending in the economy relative to its potential. When demand outpaces sustainable levels, pressure builds for tighter monetary policy and higher interest rates. Conversely, subdued demand signals the need for lower rates or easier financial conditions.
This post explores how real-time indicators of demand growth can be used to predict interest rate swap (IRS) returns across developed and emerging markets. By combining data on GDP trends, consumer activity, credit expansion, and import dynamics, traders can construct a composite demand score that guides both directional duration positions and yield curve strategies.
Demand and Its Influence on Rates
The link between demand and interest rates is rooted in macroeconomic fundamentals. As demand rises, central banks may raise policy rates to prevent overheating and keep inflation expectations anchored. This tightening typically pushes short-term yields up faster than long-term yields, flattening the curve. On the other hand, weak demand leads to looser policy, driving short-term yields lower and steepening the curve.
Duration exposure—like a fixed receiver position in a 5-year swap—tends to perform poorly when demand is strong and rates are rising. Yield curve flatteners benefit from this environment, while steepeners thrive when demand is weak and central banks are easing.
Building a Demand Signal from Real-Time Macro Data
To capture the evolving state of demand, we use macro-quantamental indicators derived from point-in-time information—data that reflects what was known by the market at each point. These are taken from the J.P. Morgan Macrosynergy Quantamental System (JPMaQS) and cover 24 economies with active IRS markets.
The demand indicators fall into four main categories:
- Excess GDP Growth: Measures current GDP growth relative to a five-year median, using both technical nowcasting and intuitive regression-based estimates.
- Excess Retail Sales Growth: Tracks consumer spending trends above or below expected levels, adjusted for inflation and medium-term GDP benchmarks.
- Excess Private Credit Growth: Assesses credit expansion relative to long-term GDP and inflation expectations, capturing the financial fuel for demand.
- Excess Merchandise Import Growth: Reflects import activity exceeding expected levels, which often indicates strong domestic demand spilling over into global trade.
Each indicator is normalized over time to account for differences in volatility across countries and series. The four category scores are then averaged to form a composite aggregate demand score for each country.
Predicting Duration Returns with Demand Scores
We test the relationship between the aggregate demand score and subsequent returns on 5-year IRS fixed receiver positions. Positions are rebalanced monthly, scaled to target 10% annualized volatility, and constrained by tradability filters.
From 2000 to 2023, the composite demand score showed a strong and consistent negative relationship with future duration returns. Periods of above-trend demand were followed by weaker performance for fixed receivers, confirming the theoretical link. The predictive power held across both monthly and quarterly horizons.
A simple trading strategy using the demand score as a signal—buying or reducing exposure based on signal strength—delivered solid results. The strategy produced a Sharpe ratio of 0.8 and a Sortino ratio of 1.2. A long-biased version, which maintained net exposure but adjusted position size based on the score, improved performance further to a Sharpe of 0.9 and Sortino of 1.3.
Each demand sub-score contributed positively, with retail sales and private credit growth posting Sharpe ratios near or above 1.0.
Anticipating Curve Moves with Demand Trends
Beyond directional duration plays, the demand score also helps in predicting curve flattening trades. These involve receiving on longer-term swaps (e.g., 5-year) and paying on shorter maturities (e.g., 2-year), benefiting when short rates rise more quickly than long rates.
Stronger demand implies tighter policy, leading to flatter curves. Historical tests confirm this logic. The demand score significantly predicted positive returns on flattening strategies across the 24-country panel. The strategy’s accuracy in calling monthly return directions exceeded 53%.
Economic value was substantial. The curve flattening strategy achieved a 24-year Sharpe ratio of 1.2 and a Sortino ratio of 1.9—higher than for the directional IRS approach. Importantly, its returns were uncorrelated with U.S. Treasury performance, making it a valuable complement to traditional fixed income exposure.
Among the sub-scores, import growth delivered the highest Sharpe ratio (1.1), followed by GDP growth (0.9). Retail and credit indicators added value but with less consistency.
Conclusion: Demand Signals Offer Diversified Alpha
Aggregate demand signals—built from real-time economic inputs—provide valuable insight into interest rate behavior. They anticipate not just the direction of rates but also the shape of the yield curve, offering multiple ways to express macro views in IRS markets.
The strategy’s strength lies in its adaptability across countries and regimes, especially when economic conditions diverge. While performance can be seasonal, tied to phases of the business cycle, the consistent patterns observed over two decades affirm the usefulness of macro demand scores as a practical guide for fixed income traders.
