Darjus Hosszejni, Gregor Kastner
arXiv 28 Jun 2019 · Statistics — Computation · publishedJournal of Statistical Software (2021) · 45 citations (OpenAlex)
arXiv:1906.12123 · PDF · DOI · OpenAlex · Extracted main text
Stochastic volatility (SV) models are nonlinear state-space models that enjoy increasing popularity for fitting and predicting heteroskedastic time series. However, due to the large number of latent quantities, their efficient estimation is non-trivial and software that allows to easily fit SV models to data is rare. We aim to alleviate this issue by presenting novel implementations of four SV models delivered in two R packages. Several unique features are included and documented. As opposed to previous versions, stochvol is now capable of handling linear mean models, heavy-tailed SV, and SV with leverage. Moreover, we newly introduce factorstochvol which caters for multivariate SV. Both packages offer a user-friendly interface through the conventional R generics and a range of tailor-made methods. Computational efficiency is achieved via interfacing R to C++ and doing the heavy work in the latter. In the paper at hand, we provide a detailed discussion on Bayesian SV estimation and showcase the use of the new software through various examples.
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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 | Omori Y, Chib S, Shephard N, Nakajima J (2007) Stochastic Volatility with Leverage: Fast and Efficient Likelihood Inference | 1.000 | 5 | 3 | 100% |
| 2 | Kastner G (2019) Sparse Bayesian Time-Varying Covariance Estimation in Many Dimensions | 0.874 | 5 | 2 | 100% |
| 3 | Harvey AC, Shephard N (1996) Estimation of an Asymmetric Stochastic Volatility Model for Asset Returns | 0.843 | 3 | 3 | 100% |
| 4 | Kastner G, Frühwirth-Schnatter S (2014) Ancillarity-Sufficiency Interweaving Strategy (ASIS) for Boosting MCMC Estimation of Stochastic Volatility Models | 0.811 | 4 | 2 | 100% |
| 5 | Kastner G, Frühwirth-Schnatter S, Lopes HF (2017) Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models | 0.811 | 4 | 2 | 100% |
| 6 | Nakajima J, Omori Y (2012) Stochastic Volatility Model with Leverage and Asymmetrically Heavy-Tailed Error Using GH Skew Student's $t$ Distribution | 0.737 | 3 | 2 | 100% |
| 7 | Griffin JE, Brown PJ (2010) Inference with Normal-Gamma Prior Distributions in Regression Problems | 0.644 | 2 | 2 | 100% |
| 8 | Kastner G (2016) Dealing with Stochastic Volatility in Time Series Using the R Package stochvol | 0.644 | 2 | 2 | 100% |
| 9 | Kim S, Shephard N, Chib S (1998) Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models | 0.644 | 2 | 2 | 100% |
| 10 | Park T, Casella G (2008) The Bayesian Lasso | 0.644 | 2 | 2 | 100% |
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