| dc.contributor.advisor | Díaz-Ruelas, Álvaro P. | |
| dc.contributor.author | Lozano-Orozco, Gabriela | |
| dc.date.accessioned | 2023-01-26T20:16:32Z | |
| dc.date.accessioned | 2023-03-10T18:11:44Z | |
| dc.date.available | 2023-01-26T20:16:32Z | |
| dc.date.available | 2023-03-10T18:11:44Z | |
| dc.date.issued | 2022-11 | |
| dc.identifier.citation | 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. | es_MX |
| dc.identifier.uri | https://hdl.handle.net/20.500.12032/71354 | |
| 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. | es_MX |
| dc.language.iso | eng | es_MX |
| dc.publisher | ITESO | es_MX |
| dc.rights.uri | http://quijote.biblio.iteso.mx/licencias/CC-BY-NC-2.5-MX.pdf | es_MX |
| dc.subject | Mcmc | es_MX |
| dc.subject | Markov Chain Monte Carlo | es_MX |
| dc.subject | Grains | es_MX |
| dc.subject | Stochastic Volatility Models | es_MX |
| dc.title | Markov Chain Monte Carlo Approach to the Analysis and Forecast of Grain Prices and Volatility Monitoring | es_MX |
| dc.type | info:eu-repo/semantics/masterThesis | es_MX |
