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Graph-Based Methods for Forecasting Realized Covariances

Author

Listed:
  • Chao Zhang
  • Xingyue Pu
  • Mihai Cucuringu
  • Xiaowen Dong

Abstract

We forecast the realized covariance matrix of asset returns in the U.S. equity market by exploiting the predictive information of graphs in volatility and correlation. Specifically, we augment the Heterogeneous Autoregressive model via neighborhood aggregation on these graphs. Our proposed method allows for the modeling of interdependence in volatility (also known as spillover effect) and correlation, while maintaining parsimony and interpretability. We explore various graph construction methods, including sector membership and graphical LASSO (for modeling volatility), and line graph (for modeling correlation). The results generally suggest that the augmented model incorporating graph information yields both statistically and economically significant improvements for out-of-sample performance over the traditional models. Such improvements remain significant over horizons up to 1 month ahead, but decay in time. The robustness tests demonstrate that the forecast improvements are obtained consistently over the different out-of-sample sub-periods and are insensitive to measurement errors of volatilities.

Suggested Citation

  • Chao Zhang & Xingyue Pu & Mihai Cucuringu & Xiaowen Dong, 2025. "Graph-Based Methods for Forecasting Realized Covariances," Journal of Financial Econometrics, Oxford University Press, vol. 23(2), pages 1977-2016.
  • Handle: RePEc:oup:jfinec:v:23:y:2025:i:2:p:1977-2016.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbae026
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    More about this item

    Keywords

    realized covariance; HAR; graphical LASSO; line graph; graph learning;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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