2019/04/17 by Théophile Griveau-Billion, Griveau-Billion, Théophile, Ben Calderhead +1
Decision Sciences · Economics, Econometrics and Finance · #Computational Finance (q-fin.CP) #FOS: Economics and business #Financial Risk and Volatility Modeling #Market Dynamics and Volatility #Statistical Finance (q-fin.ST) #Stock Market Forecasting Methods #q-fin.CP #q-fin.ST
paper · pdf · doi:10.48550/arxiv.1904.08153
59 pages, 14 figures, 2 tables
openalex publication_date 2019/04/17 · arxiv created 2020/01/20 · arxiv updated 2020/01/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We propose a heterogeneous simultaneous graphical dynamic linear model (H-SGDLM), which extends the standard SGDLM framework to incorporate a heterogeneous autoregressive realised volatility (HAR-RV) model. This novel approach creates a GPU-scalable multivariate volatility estimator, which decomposes multiple time series into economically-meaningful variables to explain the endogenous and exogenous factors driving the underlying variability. This unique decomposition goes beyond the classic one step ahead prediction; indeed, we investigate inferences up to one month into the future using stocks, FX futures and ETF futures, demonstrating its superior performance according to accuracy of large moves, longer-term prediction and consistency over time.