arXiv 13 Sep 2020 · Mathematics — Statistics Theory · publishedBayesian Analysis (2021) · 5 citations (OpenAlex)
arXiv:2009.06007 · PDF · DOI · OpenAlex · Extracted main text
Conditional heteroscedastic (CH) models are routinely used to analyze financial datasets. The classical models such as ARCH-GARCH with time-invariant coefficients are often inadequate to describe frequent changes over time due to market variability. However we can achieve significantly better insight by considering the time-varying analogues of these models. In this paper, we propose a Bayesian approach to the estimation of such models and develop computationally efficient MCMC algorithm based on Hamiltonian Monte Carlo (HMC) sampling. We also established posterior contraction rates with increasing sample size in terms of the average Hellinger metric. The performance of our method is compared with frequentist estimates and estimates from the time constant analogues. To conclude the paper we obtain time-varying parameter estimates for some popular Forex (currency conversion rate) and stock market datasets.
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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 | Sayar Karmakar, Stefan Richter, and Wei Biao Wu (2020) Simultaneous inference for time-varying models self | 1.000 | 6 | 4 | 100% |
| 2 | Rainer Dahlhaus and Suhasini Subba Rao (2006) Statistical inference for time-varying ARCH processes | 0.737 | 3 | 2 | 100% |
| 3 | Piotr Fryzlewicz, Theofanis Sapatinas, and Suhasini Subba Rao (2008) Normalized least-squares estimation in time-varying ARCH models | 0.737 | 3 | 2 | 100% |
| 4 | Piotr Fryzlewicz, Theofanis Sapatinas, and Suhasini Subba Rao (2008) Normalized least-squares estimation in time-varying ARCH models | 0.737 | 3 | 2 | 100% |
| 5 | Subhashis Ghosal and Aad Van der Vaart (2017) Fundamentals of nonparametric Bayesian inference, volume 44 | 0.644 | 2 | 2 | 100% |
| 6 | Radford M Neal et al (2011) Mcmc using hamiltonian dynamics | 0.644 | 2 | 2 | 100% |
| 7 | Bo Ning, Seonghyun Jeong, Subhashis Ghosal, et al (2020) Bayesian linear regression for multivariate responses under group sparsity | 0.644 | 2 | 2 | 100% |
| 8 | Neelabh Rohan and T. V. Ramanathan (2012) Nonparametric estimation of a time-varying GARCH model | 0.644 | 2 | 2 | 100% |
| 9 | Donald R. Hoover, John A. Rice, Colin O. Wu, and Li-Ping Yang (1998) Nonparametric smoothing estimates of time-varying coefficient models with longitudinal data | 0.511 | 2 | 1 | 100% |
| kass1995bayes | unmatched citation key kass1995bayes | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 68 scored citations. 1 of these could not be matched to a bibliography entry, so only the citation key is shown.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | GARCHX-NoVaS: A Model-free Approach to Incorporate Exogenous Variables | 0.405 | 1 | 1 |