Advances in statistical inference for econometric diffusion models
Due to their analytical tractability, continuous-time models have become a centerpiece in the financial literature. The goal of this thesis is the development of new goodness-of-fit test for continuous-time diffusion models, considering stochastic differential equations with deterministic and stocha...
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| Tipo de recurso: | tesis doctoral |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad de Santiago de Compostela (USC) |
| Repositorio: | Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela |
| Idioma: | inglés |
| OAI Identifier: | oai:minerva.usc.gal:10347/29802 |
| Acceso en línea: | http://hdl.handle.net/10347/29802 |
| Access Level: | acceso abierto |
| Palabra clave: | Materias::Investigación::12 Matemáticas::1209 Estadística::120911 Teoría estocástica y análisis de series temporales Materias::Investigación::12 Matemáticas::1209 Estadística::120913 Técnicas de inferencia estadística Materias::Investigación::12 Matemáticas::1209 Estadística::120902 Calculo en estadística |
| Sumario: | Due to their analytical tractability, continuous-time models have become a centerpiece in the financial literature. The goal of this thesis is the development of new goodness-of-fit test for continuous-time diffusion models, considering stochastic differential equations with deterministic and stochastic volatility and Itô diffusions as functional time series. Notwithstanding the importance of goodness-of-fit tools, latent factors and a continuous-time setting with observations occurring at discrete time points challenge the estimation of the models. Therefore, the estimation problem is addressed, as it hinders the goodness-of-fit procedures, discussing the intricacies of different estimation implementations prior to the methodological contribution of the test procedures. |
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