Details

Autor(en) / Beteiligte

• Salisu, Afees A.
• Swaray, Raymond
• Oloko, Tirimisiyu F.

Titel

Improving the predictability of the oil–US stock nexus: The role of macroeconomic variables

Ist Teil von

• Economic modelling, 2019-01, Vol.76, p.153-171

Ort / Verlag

Elsevier B.V

Erscheinungsjahr

2019

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• In this study, we revisit the oil–stock nexus by accounting for the role of macroeconomic variables and testing their in-sample and out-of-sample predictive powers. We follow the approaches of Lewellen (2004) and Westerlund and Narayan (2015), which were formulated into a linear multi-predictive form by Makin et al. (2014) and Salisu et al. (2018) and a nonlinear multi-predictive model by Salisu and Isah (2018). Thereafter, we extend the multi-predictive model to account for structural breaks and asymmetries. Our analyses are conducted on aggregate and sectoral stock price indexes for the US stock market. Our proposed predictive model, which accounts for macroeconomic variables, outperforms the oil-based single-factor variant as well as the constant returns (historical average) model for both in-sample and out-of-sample forecasts. We find that it is important to account for structural breaks in our proposed predictive model, although asymmetries do not seem to improve predictability. In addition, we show that it is important to pre-test the predictors for persistence, endogeneity, and conditional heteroscedasticity, particularly when modeling with high-frequency series. Our results are robust to different forecast measures and forecast horizons and are useful for making effective hedging decisions in the US stock market. •A multi-factor predictive model for oil-stock nexus is proposed.•The proposed model outperforms the single-factor & constant returns models.•The proposed model is suitable for analyzing hedging effectiveness in US stocks.•Accounting for structural breaks improves the forecast of the proposed model.•The results are robust to different forecast measures and forecast horizons.