Conditional Density Models Integrating Fuzzy and Probabilistic Representations of Uncertainty


Rui Jorge de Almeida e Santos Nogueira
Rui Jorge de Almeida e Santos Nogueira
  • Speaker
Industrial Engineering & Innovation Sciences, Eindhoven University of Technology

Event Information

Type
PhD Defence
Programme
Logistics
Date
Thu. 26 Jun. 2014
Contact
Kim Harte
Time
11:30-13:00
Location
Senate Hall, A-Building, Woudestein Campus


Abstract

Conditional density estimation is an important problem in a variety of areas such as system identification, machine learning, artificial intelligence, empirical economics, macroeconomic analysis, quantitative finance and risk management.

This work considers the general problem of conditional density estimation, i.e., estimating and predicting the density of a response variable as a function of covariates. The semi-parametric models proposed and developed in this work combine fuzzy and probabilistic representations of uncertainty, while making very few assumptions regarding the functional form of the response variable's density or changes of the functional form across the space of covariates. These models possess sufficient generalization power to approximate a non-standard density and the ability to describe the underlying process using simple linguistic descriptors despite the complexity and possible non-linearity of this process.

These novel models are applied to real world quantitative finance and risk management problems by analyzing financial time-series data containing non-trivial statistical properties, such as fat tails, asymmetric distributions and changing variation over time.

Uzay Kaymak
Uzay Kaymak
Professor of Intelligence and Computation in Economics
  • Promotor
da Costa Sousa
  • Co-promotor
Patrick Groenen
Professor of Statistics
  • Member Doctoral Committee
Trevor Martin
Trevor Martin
  • Member Doctoral Committee
Jaap Spronk
Jaap Spronk
Academic Dean MBA Programmes & Professor of Financial Management Science
  • Member Doctoral Committee
Kim Harte
Kim Harte
  • Coordinator