IDEAS home Printed from https://ideas.repec.org/a/wly/jforec/v43y2024i6p2088-2125.html
   My bibliography  Save this article

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

Author

Listed:
  • Matteo Bonato
  • Oguzhan Cepni
  • Rangan Gupta
  • Christian Pierdzioch

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.

Suggested Citation

  • Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024. "Forecasting the realized volatility of agricultural commodity prices: Does sentiment matter?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2088-2125, September.
    • Handle: RePEc:wly:jforec:v:43:y:2024:i:6:p:2088-2125
    DOI: 10.1002/for.3106
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/for.3106
    Download Restriction: no
    File URL: https://libkey.io/10.1002/for.3106?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:jforec:v:43:y:2024:i:6:p:2088-2125. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/2966 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.