Sigurd Steffensen

Peer-Reviewed Publications:

Monetary Policy Expectation Errors

with Andreas Schrimpf and Maik Schmeling

Journal of Financial Economics 146 (2022), 841-858

(full paper) -- (internet appendix) -- (replication code)

Methodology reused as part of ECB Economic Bulletin, Issue 1/2024.

How are financial markets pricing the monetary policy outlook? We use surveys to decompose excess returns on money market instruments into expectation errors and term premia. Excess returns are primarily driven by expectation errors, whereas term premia are negligible. Investors face challenges when learning about the Federal Reserve's response to large, but infrequent, negative shocks in real-time. Rather than reflecting risk compensation, excess returns stem from investors underestimating how much the central bank eases policy in response to such rare shocks. We show, for the US and internationally, that expectation errors imply excess return predictability from past stock returns.

Forecast errors about monetary policy actions (blue) vary substantially over time and strongly comove with excess returns on money market derivatives (black).

Working Papers:

Countercyclical Expected Returns

with Stig Vinther Møller and Thomas Quistgaard Pedersen

We study investor expectations of stock returns on the S&P 500 index using data from the Livingston survey over the 1952-2019 period. We find that investors have slow-moving and countercyclical expected stock returns consistent with consumption-based model predictions. We find no evidence that investors form return expectations by extrapolating from past trends in returns as under the adaptive expectations hypothesis.

Predicting the Fed: Do futures need risk adjustment?

Do fed funds futures need adjustment for risk premia? I study the predictability of time-varying risk premia in fed funds futures and find that standard predictor variables do not outperform the expectations hypothesis when evaluated out-of-sample. I apply the advanced forecasting methods Dynamic Model Averaging and Complete Subset Regressions to account for model instability and find considerably more accurate return predictions than from simple linear prediction models. These predictions do not, however, yield systematic economic value to investors, showing that federal funds futures do not need adjustment for time-varying risk premia when used to gauge market participants' expectations of future Fed policy.