Hanwen Xuan, Luca Maestrini, Feng Chen, Clara Grazian
arXiv 29 Aug 2023 · Statistics — Computation · publishedStatistics and Computing (2023) · 3 citations (OpenAlex)
arXiv:2308.14952 · PDF · DOI · OpenAlex · Extracted main text
Stochastic variational inference algorithms are derived for fitting various heteroskedastic time series models. We examine Gaussian, t, and skew-t response GARCH models and fit these using Gaussian variational approximating densities. We implement efficient stochastic gradient ascent procedures based on the use of control variates or the reparameterization trick and demonstrate that the proposed implementations provide a fast and accurate alternative to Markov chain Monte Carlo sampling. Additionally, we present sequential updating versions of our variational algorithms, which are suitable for efficient portfolio construction and dynamic asset allocation.
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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 | Tran MN, Nguyen TN, Dao VH (2021) b) A practical tutorial on variational Bayes | 1.000 | 11 | 4 | 100% |
| 2 | Tomasetti N, Forbes C, Panagiotelis A (2022) Updating variational Bayes: fast sequential posterior inference | 1.000 | 5 | 3 | 100% |
| 3 | Ong VMH, Nott DJ, Smith MS (2018) b) Gaussian variational approximation with a factor covariance structure | 0.928 | 4 | 3 | 100% |
| 4 | Ranganath R, Gerrish S, Blei D (2014) Black box variational inference | 0.874 | 8 | 2 | 100% |
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| 7 | Titsias M, Lázaro-Gredilla M (2014) Doubly stochastic variational Bayes for non-conjugate inference | 0.811 | 4 | 2 | 100% |
| 8 | Bishop CM, Nasrabadi NM (2006) Pattern Recognition and Machine Learning, vol 4 | 0.737 | 3 | 2 | 100% |
| 9 | Hoffman MD, Blei DM, Wang C, et al (2013) Stochastic variational inference | 0.737 | 3 | 2 | 100% |
| 10 | Kingma DP, Welling M (2013) Auto-encoding variational Bayes | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 68 scored citations.