Matteo Iacopini, Francesco Ravazzolo, Luca Rossini
arXiv 29 Nov 2022 · Econometrics · 5 citations (OpenAlex)
arXiv:2211.16121 · PDF · DOI · OpenAlex · Extracted main text
This article proposes a novel Bayesian multivariate quantile regression to forecast the tail behavior of energy commodities, where the homoskedasticity assumption is relaxed to allow for time-varying volatility. In particular, we exploit the mixture representation of the multivariate asymmetric Laplace likelihood and the Cholesky-type decomposition of the scale matrix to introduce stochastic volatility and GARCH processes and then provide an efficient MCMC to estimate them. The proposed models outperform the homoskedastic benchmark mainly when predicting the distribution's tails. We provide a model combination using a quantile score-based weighting scheme, which leads to improved performances, notably when no single model uniformly outperforms the other across quantiles, time, or variables.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Clark, T. E. and F. Ravazzolo (2015) Macroeconomic forecasting performance under alternative specifications of time-varying volatility | 1.000 | 5 | 3 | 100% |
| 2 | Aastveit, K. A., S. ter Ellen, and G. Mantoan (2024) Quantile density combination: An application to US GDP forecasts | 0.737 | 3 | 2 | 100% |
| 3 | Petrella, L. and V. Raponi (2019) Joint estimation of conditional quantiles in multivariate linear regression models with an application to financial distress | 0.737 | 3 | 2 | 100% |
| 4 | Atchadé, Y. F. and J. S. Rosenthal (2005) On adaptive Markov chain Monte Carlo algorithms | 0.644 | 2 | 2 | 100% |
| 5 | Bollerslev, T (1986) Generalized autoregressive conditional heteroskedasticity | 0.644 | 2 | 2 | 100% |
| 6 | Carriero, A., T. E. Clark, and M. Marcellino (2022) Nowcasting tail risk to economic activity at a weekly frequency | 0.644 | 2 | 2 | 100% |
| 7 | Kotz, S., T. Kozubowski, and K. Podgórski (2001) The Laplace distribution and generalizations: A revisit with applications to communications, economics, engineering, and finance | 0.644 | 2 | 2 | 100% |
| 8 | Cross, J. L., C. Hou, G. Koop, and A. Poon (2023) Large stochastic volatility in mean vars | 0.511 | 2 | 1 | 100% |
| 9 | Ando, T. and J. Bai (2020) Quantile co-movement in financial markets: A panel quantile model with unobserved heterogeneity | 0.405 | 1 | 1 | 100% |
| 10 | Chen, L., J. J. Dolado, and J. Gonzalo (2021) Quantile factor models | 0.405 | 1 | 1 | 100% |
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