Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 60 for “"Dependence Structure"”.
-
Analyzing the dependence structure of microarray data: a copula–based approach
… tool in each field where the multivariate dependence is of great interest and their use in clustering has not been still investigated. The first part of this work contains the review of the literature of clustering methods, copula functions and microarray experiments. The attention focuses …
-
Investigation on the efficient frontier based on CVaR under copula dependence structure with applications to South African JSE stocks
… must satisfy. Using copula to describe the dependence structure between the instruments in our portfolio, we implement and backtest a CVaR optimization algorithm and compare the backtested results to those obtained using parametric and non-parametric/Monte Carlo VaR. Finally we optimise the …
-
Applications of Copula Theory and Regime Switching in Finance
There is well-documented evidence that the dependence structure of financial assets is often characterized by considerable time variation. Financial markets are repeatedly subjected to episodes of rapid growth and dramatic decline of asset prices, and the recent financial crisis reinforced the need …
-
Three Essays on Extremes and Non-Linearities in Asset Pricing
… can be further characterized by a non-linear dependence structure. The second essay "Credit Cycle Dependent Spread Determinants in Emerging Sovereign Debt Markets", empirically estimates non-linear dependence structures of determinants of changes in sovereign bond spreads. Empirical results of …
-
Symbolic analysis for parallelizing compilers
The notion of dependence captures the most important properties of a program for efficient execution on parallel computers. The dependence structure of a program defines the necessary constraints of the order of execution of the program components, and provides sufficient information for the …
-
Bayesian prediction of functions with applications to manufacturing and marketing
… which satisfy a certain condition on their dependence structure (a chainlike dependence structure) will be considered. In the first chapter, Bayesian updating of these probability distributions will be discussed. In particular, we will show that the updated marginal distributions for any …
-
Data-Driven Polynomial Chaos Expansions for Uncertainty Quantification
… inputs impose strong assumptions on the dependence structure of the inputs or lack interpretability. Although recent studies proposed fully data-driven PCEs without strong assumptions on inputs, these PCEs are generally inefficient because the minimally required number of observations …
-
Vine copula modelling of dependence and portfolio optimization with application to mining and energy stock return series from the Australian market
This thesis models the dependence risk profile, investment risk and portfolio allocation features of seven 20-stock portfolios from the mining, energy, retail and manufacturing sectors of the Australian market in the context of the 2008-2009 global financial crisis (2008-2009 GFC) and pre-GFC, GFC, …
-
Essays in Multivariate Modelling in Finance
Modelling the dependence structure of financial variables is of paramount importance for a wide range of financial applications. Financial variables exhibit various forms of dependence and tail dependence whereas the magnitude of dependence is not constant over time but rather time-varying and can …
-
Modulo Scheduling for Control-Intensive General-Purpose Programs
… that is sustainable for the given resources and dependence structure. Third, with the appropriate architectural support, modulo scheduling results in less code expansion because unrolling is required only for optimization, but not to amortize the loss of overlap across the back edge.
-
Structure learning in high-dimensional graphical models
… provably consistent algorithms for learning the structure of undirected and directed (causal) graphical models in the high-dimensional setting. Structure learning in graphical models is a central problem in statistics with numerous applications including learning gene regulatory networks from …
-
Dependence testing in high dimension
"The study of dependence for high dimensional data originates in many different areas of contemporary research. While a lot of existing work focuses on measuring the linear dependence and monotone dependence for fixed dimensional data, comparatively less is concerned for more complex dependence …
-
Topics in Bayesian sample size determination and Bayesian model selection.
… used for estimation. After accounting for the dependence structure, the required sample size will be larger than that assuming independence between the tests. The second topic is also concerned with Bayesian sample size calculation with a misclassified binary response variable. Differing from …
-
STATISTICAL MODELING FOR COMPLEX FUNCTIONAL AND NETWORK TIME SERIES DATA
… problems. On the other hand, the complex structure presents challenges to conventional statistical analytical tools in terms of estimation and prediction. We developed three statistical modeling to investigate the dynamic behaviors of high dimensional data with either seasonality …
-
Modeling End-User Behavior In Data Networks
… distributions of size, duration and rate, dependence structure between the marginals, and distribution of the difference between consecutive initiation times. We group sessions according to peak transfer rate in the second problem, and network application in the third problem. The ultimate …
-
Risk management and solvency: mathematical methods in theory and practice
… (Federal Financial Supervisory Authority). The dependences between risks play an essential role in Solvency II since their negligence can lead to a substantial misestimation of the solvency capital. This is particularly critical when looking at natural catastrophes where dependencies can occur …
-
An alternative model for multivariate stable distributions
… data without using the spectral measure as a dependence structure. From our investigation, firstly, we echo that the assumption of "Gaussianity" must be rejected, as a model for, particularly, high frequency financial data based on evidence from the Johannesburg Stock Exchange (JSE). Secondly, …
-
Bayesian Model Selection for Spatial Data and Cost-constrained Applications
… tool for identifying an appropriate model class, dependence structure, and valuable predictors for a wide variety of applications. In this work we consider objective Bayesian model selection where no subjective information is available to inform priors on model parameters a priori, specifically in …
-
Stochastic Orders Applied to Insurance and Economics
… this fact, we must model risks considering the dependence structure of a random vector whose components are interrelated risks. Copula Theory serves as a fundamental instrument to model dependence among these components. This Ph.D. dissertation aims to provide contributions in the scientific …
-
RESEARCH ON THE MEASUREMENT AND INFLUENCING FACTORS OF SYSTEMIC RISKS IN CHINESE FINANCIAL INSTITUTIONS IN CASE OF MAJOR PUBLIC EMERGENCIES
… uses the DTW-MST network model to describe the dependence structure between financial institutions and between industries. It explores important institutional nodes of risk dependence from a network perspective. Then, it uses the time-varying Copula-CoVaR model to measure financial institutions' …
Page 1 of 3