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Title: Modelling nonlinear stochastic dynamics in financial time series
Author: Lesch, Ragnar H.
ISNI:       0000 0001 3608 3352
Awarding Body: Aston University
Current Institution: Aston University
Date of Award: 2000
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For analysing financial time series two main opposing viewpoints exist, either capital markets are completely stochastic and therefore prices follow a random walk, or they are deterministic and consequently predictable. For each of these views a great variety of tools exist with which it can be tried to confirm the hypotheses. Unfortunately, these methods are not well suited for dealing with data characterised in part by both paradigms. This thesis investigates these two approaches in order to model the behaviour of financial time series. In the deterministic framework methods are used to characterise the dimensionality of embedded financial data. The stochastic approach includes here an estimation of the unconditioned and conditional return distributions using parametric, non- and semi-parametric density estimation techniques. Finally, it will be shown how elements from these two approaches could be combined to achieve a more realistic model for financial time series.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Phd
EThOS ID:  DOI: Not available
Keywords: Mathematics not elsewhere classified ; Information Management ; Information Systems Economics