Griffin, JE;
Mitrodima, G;
(2020)
A Bayesian Quantile Time Series Model for Asset Returns.
Journal of Business & Economic Statistics
10.1080/07350015.2020.1766470.
(In press).
Preview |
Text
BayesianJQTSmodels_revision_21_4_20.pdf - Accepted Version Download (680kB) | Preview |
Abstract
We consider jointly modeling a finite collection of quantiles over time. Formal Bayesian inference on quantiles is challenging since we need access to both the quantile function and the likelihood. We propose a flexible Bayesian time-varying transformation model, which allows the likelihood and the quantile function to be directly calculated. We derive conditions for stationarity, discuss suitable priors, and describe a Markov chain Monte Carlo algorithm for inference. We illustrate the usefulness of the model for estimation and forecasting on stock, index, and commodity returns.
| Type: | Article |
|---|---|
| Title: | A Bayesian Quantile Time Series Model for Asset Returns |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/07350015.2020.1766470 |
| Publisher version: | https://doi.org/10.1080/07350015.2020.1766470 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Bayesian nonparametrics, Predictive density, Stationarity, Transformation models |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10097063 |
Archive Staff Only
 |
View Item |
