Forecasting the realized volatility of agricultural commodity prices : does sentiment matter?

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Authors

Bonato, Matteo
Cepni, Oguzhan
Gupta, Rangan
Pierdzioch, Christian

Journal Title

Journal ISSN

Volume Title

Publisher

Wiley

Abstract

We analyze the out-of-sample predictive power of sentiment for the realized volatility of agricultural commodity price returns. We use high-frequency intra-day data covering the period from 2009 to 2020 to estimate realized volatility. Our baseline forecasting model is a heterogeneous autoregressive (HAR) model, which we extend to include sentiment. We further enhance this model by incorporating various key realized moments such as leverage, realized skewness, realized kurtosis, realized upside (“good”) volatility, realized downside (“bad”) volatility, realized jumps, realized upside tail risk, and realized downside tail risk. In order to setup a forecasting model, we use (i) forward and backward stepwise predictor selection and (ii) a model-based averaging algorithm. The forecasting models constructed through these algorithms outperform both the baseline HAR-RV model and the HAR-RV-sentiment model. We conclude that, for the agricultural commodities studied in our research, realized moments play a more significant role in forecasting realized volatility compared to sentiment.

Description

DATA AVAILABILITY STATEMENT : The data that support the findings of this study are available from Refinitiv Eikon. Restrictions apply to the availability of these data, which were used under license for this study. Data are available from the author(s) with the permission of Refinitiv Eikon.

Keywords

Agricultural commodities, Forecasting, Realized moments, Realized volatility, Sentiment, SDG-08: Decent work and economic growth

Sustainable Development Goals

SDG-08:Decent work and economic growth

Citation

Bonato, M., Cepni, O., Gupta, R., & Pierdzioch, C. (2024). Forecasting the realized volatility of agricultural commodity prices: Does sentiment matter? Journal of Forecasting, 43(6), 2088–2125. https://DOI.org/10.1002/for.3106.