Thesis topic proposal
István Berkes
A gazdaságtan és a pénzügy nemlineáris idősorainak statisztikai elemzése. (Statistical Analysis of Nonlinear Time Series in Economy and Finance.)


Institute: Budapest University of Technology and Economics
mathematics and computing
Doctoral School of Mathematics and Computer Science

Thesis supervisor: István Berkes
Location of studies (in Hungarian): BME Matematika Intézet/MTA Rényi
Abbreviation of location of studies: BME

Description of the research topic:

Statistical analysis of financial data has received considerable attention in the literature during the last 20 years. Several models have been suggested to capture special features of
financial processes and most of these models have the property that the conditional variance (or the conditional scaling) of the considered process depends on the past. The best known and most
often used examples are the autoregressive conditionally heteroscedastic (ARCH) process introduced by Engle (1982) and its generalizations, like the GARCH, exponential GARCH, augmented GARCH models and their variations serving special purposes. ARCH
processes and their generalizations have been a crucial tool to model asset returns, exchange rates and to describe time-varying volatility and the lasting effect of shocks in financial time series.
Besides their economical importance, these models are very important for the 'pure' mathematical theory as well: the study of ARCH and related processes gives a profound insight into the structure of nonlinear times series, in particular to processes exhibiting strong dependence. We suggest various topics in this field such as parameter estimation, asymptotic properties, dependence structure, change point problems and inference for functional data sets.

Required language skills: angol
Number of students who can be accepted: 1

Deadline for application: 2016-12-31

2017. XI. 23.
ODT ülés
Az ODT következő ülésére 2017. december 8-án 10.00 órakor kerül sor a Semmelweis Egyetem II. Belgyógyászati Klinika tetőterében levő MSD teremben (Bp. Szentkirályi u. 46., a rektori épület mellett).

All rights reserved © 2007, Hungarian Doctoral Council. Doctoral Council registration number at commissioner for data protection: 02003/0001. Program version: 2.2358 ( 2017. X. 31. )