| dc.contributor | Díaz-Ruelas, Álvaro P. | |
| dc.creator | Lozano-Orozco, Gabriela | |
| dc.date | 2023-01-26T20:16:32Z | |
| dc.date | 2023-01-26T20:16:32Z | |
| dc.date | 2022-11 | |
| dc.date.accessioned | 2023-07-21T21:59:20Z | |
| dc.date.available | 2023-07-21T21:59:20Z | |
| dc.identifier | Lozano-Orozco, G. (2022). Markov Chain Monte Carlo Approach to the Analysis and Forecast of Grain Prices and Volatility Monitoring. Trabajo de obtención de grado, Maestría en Ciencia de Datos. Tlaquepaque, Jalisco: ITESO. | |
| dc.identifier | https://hdl.handle.net/11117/8437 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/7756830 | |
| dc.description | Public studies on the dynamics of food staples as important as cereals (grains) are relatively scarce. Here we undertake a preliminary analysis of the time series for corn, wheat, soybean, and oat prices first via classical ARIMA/GARCH models, and later complementing with the more complex Stochastic Volatility (SV) models. The goal is to improve upon the classical results by implementing a Bayesian analysis through the construction of a suitable Markov Chain Monte Carlo Model with improved volatility analysis and forecasting capabilities. The performance of the SV model is benchmarked against the classical ARMA/GARCH approach, and both are discussed as monitoring tools for the volatility prices. | |
| dc.format | application/pdf | |
| dc.language | eng | |
| dc.publisher | ITESO | |
| dc.rights | http://quijote.biblio.iteso.mx/licencias/CC-BY-NC-2.5-MX.pdf | |
| dc.subject | Mcmc | |
| dc.subject | Markov Chain Monte Carlo | |
| dc.subject | Grains | |
| dc.subject | Stochastic Volatility Models | |
| dc.title | Markov Chain Monte Carlo Approach to the Analysis and Forecast of Grain Prices and Volatility Monitoring | |
| dc.type | info:eu-repo/semantics/masterThesis | |
| dc.type | info:eu-repo/semantics/acceptedVersion | |
