Advances in statistical inference for econometric diffusion models

• Autores: Alejandra María López Pérez
• Directores de la Tesis: Wenceslao González Manteiga (dir. tes.) , Manuel Febrero Bande (dir. tes.)
• Lectura: En la Universidade de Santiago de Compostela ( España ) en 2022
• Idioma: español
• Tribunal Calificador de la Tesis: Eva Ferreira García (presid.) , Juan Carlos Reboredo Nogueira (secret.) , Nuno Miguel Baptista Brites (voc.)
• Enlaces
  • Tesis en acceso abierto en: MINERVA
• Resumen

  • 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.