AbstractThis paper considers how information from the implied volatility (IV) term structure can be harnessed to improve stock return volatility forecasting within the state‐of‐the‐art HAR model. Factors are extracted from the IV term structure and included as exogenous variables in the HAR framework. We found that including slope and curvature factors leads to significant forecast improvements over the HAR benchmark at a range of forecast horizons, compared with the standard HAR model and HAR model with VIX as IV information set.