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Bond Risk Premia and Return Predictability

The expectations hypothesis says a steep yield curve should just mean rates are expected to rise, but a steep curve actually predicts positive excess returns on long bonds — evidence of a time-varying risk premium that forward rates only partly reveal.

Prerequisites: The Expectations Hypothesis and Term Premium, Spot, Par and Forward Curve Relationships

If the expectations hypothesis were literally true, a steep yield curve would carry no trading signal at all — it would simply mean short rates are expected to rise, and holding a long bond versus rolling short-term cash would earn the same expected return either way. Decades of data say otherwise. When the curve is unusually steep, long-maturity bonds go on to outperform, on average, over the following year. The curve's slope is forecasting excess returns, not just future short rates — evidence that the "extra" yield on a steep curve is compensation for risk, and that compensation moves around over time.

Regress a bond's future one-year excess return on today's forward-spot spread and the slope comes out positive and statistically significant, not zero. A steeper curve today predicts richer bond returns over the next year — the forward rate is a biased forecast of the future spot rate, and the bias is the (time-varying) term premium.

The regression that started it

Fama and Bliss showed that the spread between a forward rate and the current short rate, ft,nyt,1f_{t,n} - y_{t,1}, predicts the excess return of an nn-year bond held for one year:

rxt+1(n)=α+β(ft,nyt,1)+εt+1rx_{t+1}^{(n)} = \alpha + \beta \left(f_{t,n} - y_{t,1}\right) + \varepsilon_{t+1}

Under the expectations hypothesis, β\beta should be zero — the forward-spot spread should only forecast where the short rate is heading, contributing nothing to excess returns. Empirically β\beta comes out well above zero and often close to one, meaning almost the entire forward-spot spread is return-predictive rather than rate-predictive.

Worked example: turning a spread into a forecast

Say the five-year forward-spot spread (ft,5yt,1f_{t,5} - y_{t,1}) is currently 1.20%, and historical fitting gives α0\alpha \approx 0 and β0.8\beta \approx 0.8 for this maturity.

rx^(5)=0+0.8×1.20%=0.96%\widehat{rx}^{(5)} = 0 + 0.8 \times 1.20\% = 0.96\%

The model forecasts about 0.96% of excess return on the five-year bond over the coming year, above what you'd earn just rolling one-year cash. If instead the pure expectations hypothesis held (β=0\beta = 0), that same 1.20% spread would forecast zero excess return — all of it would be "explained" by an expected rise in short rates. The gap between β=0.8\beta = 0.8 found in the data and β=0\beta = 0 predicted by the simple theory is the empirical case for a real, forecastable term premium.

Now suppose a year passes and the five-year bond actually returns 1.40% in excess of cash. The realized term premium for that period was 1.40%, close to the 0.96% forecast — the forecast doesn't have to be exact, only informative on average across many such periods, which is what the regression's statistical significance is certifying.

forward-spot spread, today next year's excess return 0
Under pure expectations-hypothesis, this line should be flat at zero. It isn't — a steeper forward-spot spread reliably comes with higher realized excess returns.

Why the premium moves at all

If the term premium were a constant, it would just be a fixed markup and the expectations hypothesis's logic would still roughly hold up to a constant shift. What the data actually show is that the premium is time-varying: it rises in recessions and around periods of high uncertainty (investors demand more compensation for duration risk when the macro outlook is murky) and compresses during calm, low-volatility stretches. Cochrane and Piazzesi later showed that a single "tent-shaped" combination of forward rates across the whole curve, not just the one at the traded maturity, captures even more of this predictability than the two-point Fama-Bliss spread alone.

Return predictability from a forward-spot spread is a statement about average, ex-ante forecasts across many periods — it is not a promise that this particular steep curve will pay off this particular year. The regression's R2R^2 is typically modest (often under 20%), meaning most of next year's bond return is still unexplained noise; sizing a trade as if the forecast were a certainty is the classic misuse of this result.

Where it shows up

This is the empirical foundation for systematic bond risk-premia and carry strategies: going long steep parts of global curves and short flat ones, informed by exactly this kind of spread regression. It is also the reason central-bank watchers distinguish "the market expects rate cuts" from "the market is being paid a risk premium to hold duration" — conflating the two is a common and costly misreading of the curve.

The same logic extends across countries: a systematic global bond strategy can rank sovereign curves by their forward-spot spreads and take relative positions accordingly, treating each country's curve steepness as an independent signal about that market's compensation for duration risk, much like a cross-sectional value strategy ranks stocks by valuation rather than trading a single name in isolation.

Key terms

  • Excess return — a bond's holding-period return minus the return from rolling short-term cash over the same period.
  • Forward-spot spread — the gap between a forward rate and today's short rate; the standard predictor variable.
  • Term premium — the average compensation, above expected future short rates, for holding duration risk.
  • Expectations hypothesis — the (empirically rejected in its pure form) claim that forward rates are unbiased forecasts of future spot rates.

Related concepts

Practice in interviews

Further reading

  • Fama & Bliss, The Information in Long-Maturity Forward Rates (AER, 1987)
  • Cochrane & Piazzesi, Bond Risk Premia (AER, 2005)
  • Cochrane, Asset Pricing (ch. 19)
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