We say that a~graph admits a~nowhere-zero k-flow if we can assign a~direction and a~positive integer (<k) as a~flow to each edge so that total in-flow into $v$ and total out-flow from $v$ are equal for each vertex $v$. In 1954, Tutte conjectured that every bridgeless graph admits a~nowhere-zero 5-flow and the conjecture is still open. Kochol in his recent papers introduces a~computational method how to prove that a~minimal counterexample cannot contain short circuits (up to length 10). In this Thesis, we provide a~comprehensive view on this method. Moreover, since Kochol does not share his implementation and in order to independently verify the method, we provide our source code that validates Kochol's results and extend them: we prove that any minimal counterexample to the conjecture does not contain any circuit of length less than 12. Powered by TCPDF (www.tcpdf.org)

The contemporary world landscape is epitomised by a highly globalised world economy, where neo-liberal agendas push for ultimate competitiveness and much of the manufacturing and production processes have been relocated from core to semi-peripheral countries. To be able to compete in the global arena, many developing nations and newly emerging economies have sacrificed an approach to sustainable development by neglecting social and ecological aspects. A showcase of such unsustainable growth in recent years can be observed in Tirupur, South India. Tirupur’s heavy export orientation of ready-knitted garments transformed it into a major textiles cluster for fashion retailers and buyer groups worldwide. However, the substantial pollution of water resources due to the discharge of raw effluents by processing units into the Noyyal river and the overexploitation of groundwater cast a shadow on the city’s economic expansion. In order to tackle these challenges, a number of regulatory directives were issued from the mid 1990’s onwards, leading to the enforcement of strict Zero Liquid Discharge norms in the cluster. This study investigates whether intervention efforts directed at Tirupur’s textiles sector have been able to address inherent challenges impacting the local environment and population. The findings gathered from an extensive literature review and a field study to Tirupur suggest that while some problems of the past have been attended to, major sustainability issues remain. Serious concerns such as a shift in pollution and economical uncertainty in the cluster have been identified as consequences from the policy interventions.

In this paper we present a simple combinatorial approach for the derivation of zero avoiding transition probabilities in a Markovian r- node series Jackson network. The method we propose offers two advantages: first, it is conceptually simple because it is based on transition counts between the nodes and does not require a tensor representation of the network. Second, the method provides us with a very efficient technique for numerical computation of zero avoiding transition probabilities. / Series: Forschungsberichte / Institut für Statistik

As instituições financeiras que pretendem utilizar a IRB (Internal Ratings Based) avançada precisam desenvolver métodos para estimar a componente de risco LGD (Loss Given Default). Desde a década de 1950 são apresentadas propostas para modelagem da PD (Probability of default), em contrapartida, a previsão da LGD somente recebeu maior atenção após a publicação do Acordo Basileia II. A LGD possui ainda uma literatura pequena, se comparada a PD, e não há um método eficiente em termos de acurácia e interpretação como é a regressão logística para a PD. Modelos de regressão para LGD desempenham um papel fundamental na gestão de risco das instituições financeiras. Devido sua importância este trabalho propõe uma metodologia para quantificar a componente de risco LGD. Considerando as características relatadas sobre a distribuição da LGD e na forma flexível que a distribuição beta pode assumir, propomos uma metodologia de estimação da LGD por meio do modelo de regressão beta bimodal inflacionado em zero. Desenvolvemos a distribuição beta bimodal inflacionada em zero, apresentamos algumas propriedades, incluindo momentos, definimos estimadores via máxima verossimilhança e construímos o modelo de regressão para este modelo probabilístico, apresentamos intervalos de confiança assintóticos e teste de hipóteses para este modelo, bem como critérios para seleção de modelos, realizamos um estudo de simulação para avaliar o desempenho dos estimadores de máxima verossimilhança para os parâmetros da distribuição beta bimodal inflacionada em zero. Para comparação com nossa proposta selecionamos os modelos de regressão beta e regressão beta inflacionada, que são abordagens mais usuais, e o algoritmo SVR , devido a significativa superioridade relatada em outros trabalhos. / Financial institutions willing to use the advanced Internal Ratings Based (IRB) need to develop methods to estimate the LGD (Loss Given Default) risk component. Proposals for PD (Probability of default) modeling have been presented since the 1950s, in contrast, LGDs forecast has received more attention only after the publication of the Basel II Accord. LGD also has a small literature, compared to PD, and there is no efficient method in terms of accuracy and interpretation such as logistic regression for PD. Regression models for LGD play a key role in the risk management of financial institutions, due to their importance this work proposes a methodology to quantify the LGD risk component. Considering the characteristics reported on the distribution of LGD and in the flexible form that the beta distribution may assume, we propose a methodology for estimation of LGD using the zero inflated bimodal beta regression model. We developed the zero inflated bimodal beta distribution, presented some properties, including moments, defined estimators via maximum likelihood and constructed the regression model for this probabilistic model, presented asymptotic confidence intervals and hypothesis test for this model, as well as selection criteria of models, we performed a simulation study to evaluate the performance of the maximum likelihood estimators for the parameters of the zero inflated bimodal beta distribution. For comparison with our proposal we selected the beta regression models and inflated beta regression, which are more usual approaches, and the SVR algorithm, due to the significant superiority reported in other studies.

The paper develops a global vector auto-regressive model with time varying pa- rameters and stochastic volatility to analyse whether international spillovers of US monetary policy have changed over time. The model proposed enables us to assess whether coefficients evolve gradually over time or are better characterized by infrequent, but large, breaks. Our find- ings point towards pronounced changes in the international transmission of US monetary policy throughout the sample period, especially so for the reaction of international output, equity prices and exchange rates against the US dollar. In general, the strength of spillovers has weakened in the aftermath of the global financial crisis. Using simple panel regressions, we link the vari- ation in international responses to measures of trade and financial globalization. We find that a broad trade base and a high degree of financial integration with the world economy tend to cushion risks stemming from a foreign shock such as US tightening of monetary policy, whereas a reduction in trade barriers and/or a liberalization of the capital account increase these risks.

by Luk Wai Shing. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves 44-45). / ABSTRACT --- p.i / ACKNOWLEDGMENTS --- p.ii / Chapter CHAPTER 1. --- INTRODUCTION --- p.1 / Chapter CHAPTER 2. --- DRAWBACKS OF CLASSICAL THEORY --- p.4 / Chapter 2.1 --- Review of Sequential Iterative Methods --- p.4 / Chapter 2.2 --- Visualization Techniques --- p.8 / Chapter 2.3 --- Review of Deflation --- p.10 / Chapter CHAPTER 3. --- THE IMPROVEMENT OF THE ABERTH METHOD --- p.11 / Chapter 3.1 --- The Durand-Kerner method and the Aberth method --- p.11 / Chapter 3.2 --- The generalized Aberth method --- p.13 / Chapter 3.3 --- The modified Aberth Method for multiple-zero --- p.13 / Chapter 3.4 --- Choosing the initial approximations --- p.15 / Chapter 3.5 --- Multiplicity estimation --- p.16 / Chapter CHAPTER 4. --- THE HIGHER-ORDER ITERATIVE METHODS --- p.18 / Chapter 4.1 --- Introduction --- p.18 / Chapter 4.2 --- Convergence analysis --- p.20 / Chapter 4.3 --- Numerical Results --- p.28 / Chapter CHAPTER 5. --- PARALLEL DEFLATION --- p.32 / Chapter 5.1 --- The Algorithm --- p.32 / Chapter 5.2 --- The Problem of Zero Component --- p.34 / Chapter 5.3 --- The Problem of Round-off Error --- p.35 / Chapter CHAPTER 6. --- HOMOTOPY ALGORITHM --- p.36 / Chapter 6.1 --- Introduction --- p.36 / Chapter 6.2 --- Choosing Q(z) --- p.37 / Chapter 6.3 --- The arclength continuation method --- p.38 / Chapter 6.4 --- The bifurcation problem --- p.40 / Chapter 6.5 --- The suggested improvement --- p.41 / Chapter CHAPTER 7. --- CONCLUSION --- p.42 / REFERENCES --- p.44 / APPENDIX A. PROGRAM LISTING --- p.A-l / APPENDIX B. COLOR PLATES --- p.B-l

by Kwok, Wong-chuen Tony. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves [85-86]). / Acknowledgement / Abstract / Chapter I --- Laguerre's Method in Polynomial Zero-finding / Chapter 1 --- Background --- p.1 / Chapter 2 --- Introduction and Problems of Laguerre´ةs Method --- p.3 / Chapter 2.1 --- Laguerre´ةs Method in Symmetrie-Cluster Problem / Chapter 2.2 --- Cyclic Behaviour / Chapter 2.3 --- Supercluster Problem / Chapter 3 --- Proposed Enhancement to Laguerre 's Method --- p.9 / Chapter 3.1 --- Analysis of Adding a Zero or Pole / Chapter 3.2 --- Proposed Algorithm / Chapter 4 --- Conclusion --- p.17 / Chapter II --- Homotopy Methods applied to Polynomial Zero-finding / Chapter 1 --- Introduction --- p.18 / Chapter 2 --- Overcoming Bifurcation --- p.22 / Chapter 3 --- Comparison of Homotopy Algorithms --- p.27 / Chapter 4 --- Conclusion --- p.29 / Appendices / Chapter I --- Laguerre's Method in Polynomial Zero-finding / Chapter 0 --- Naming of Testing Polynomials / Chapter 1 --- Finding All Zeros using Proposed Laguerre's Method / Chapter 2 --- Experiments: Selected Pictures of Comparison of Proposed Strategy with Other Strategy / Chapter 3 --- Experiments: Tables of Comparison of Proposed Strategy with Other Strategy / Chapter 4 --- Distance Colorations and Target Colorations / Chapter II --- Homotopy Methods applied to Polynomial Zero-finding / Chapter 1 --- Comparison of Algorithms using Homotopy Method / Chapter 2 --- Experiments: Selected Pictorial Comparison / Chapter III --- An Example Demonstrating Effect of Round-off Errors References

There are two main features in this thesis. The first is a study of the role of "tracts" of finite determination on the growth of integral functions. Such a study is of importance, since most of the known results in this field are based on the extreme case where the tracts of finite determination reduce to single lines. The second is the construction of functions, meromorphic and integral, bounded in tracts of positive angular measure, where the tracts are not confined to radial sectors.

Data can be collected in the form of counts in many situations. In other words, the number of deaths from an accident, the number of days until a machine stops working or the number of annual visitors to a city may all be considered as interesting variables for study. This study is motivated by two facts; first, the vital role of the continuous Weibull distribution in survival analyses and failure time studies. Hence, the discrete Weibull (DW) is introduced analogously to the continuous Weibull distribution, (see, Nakagawa and Osaki (1975) and Kulasekera (1994)). Second, researchers usually focus on modeling count data, which take only non-negative integer values as a function of other variables. Therefore, the DW, introduced by Nakagawa and Osaki (1975), is considered to investigate the relationship between count data and a set of covariates. Particularly, this DW is generalised by allowing one of its parameters to be a function of covariates. Although the Poisson regression can be considered as the most common model for count data, it is constrained by its equi-dispersion (the assumption of equal mean and variance). Thus, the negative binomial (NB) regression has become the most widely used method for count data regression. However, even though the NB can be suitable for the over-dispersion cases, it cannot be considered as the best choice for modeling the under-dispersed data. Hence, it is required to have some models that deal with the problem of under-dispersion, such as the generalized Poisson regression model (Efron (1986) and Famoye (1993)) and COM-Poisson regression (Sellers and Shmueli (2010) and Sáez-Castillo and Conde-Sánchez (2013)). Generally, all of these models can be considered as modifications and developments of Poisson models. However, this thesis develops a model based on a simple distribution with no modification. Thus, if the data are not following the dispersion system of Poisson or NB, the true structure generating this data should be detected. Applying a model that has the ability to handle different dispersions would be of great interest. Thus, in this study, the DW regression model is introduced. Besides the exibility of the DW to model under- and over-dispersion, it is a good model for inhomogeneous and highly skewed data, such as those with excessive zero counts, which are more disperse than Poisson. Although these data can be fitted well using some developed models, namely, the zero-inated and hurdle models, the DW demonstrates a good fit and has less complexity than these modifed models. However, there could be some cases when a special model that separates the probability of zeros from that of the other positive counts must be applied. Then, to cope with the problem of too many observed zeros, two modifications of the DW regression are developed, namely, zero-inated discrete Weibull (ZIDW) and hurdle discrete Weibull (HDW) models. Furthermore, this thesis considers another type of data, where the response count variable is censored from the right, which is observed in many experiments. Applying the standard models for these types of data without considering the censoring may yield misleading results. Thus, the censored discrete Weibull (CDW) model is employed for this case. On the other hand, this thesis introduces the median discrete Weibull (MDW) regression model for investigating the effect of covariates on the count response through the median which are more appropriate for the skewed nature of count data. In other words, the likelihood of the DW model is re-parameterized to explain the effect of the predictors directly on the median. Thus, in comparison with the generalized linear models (GLMs), MDW and GLMs both investigate the relations to a set of covariates via certain location measurements; however, GLMs consider the means, which is not the best way to represent skewed data. These DW regression models are investigated through simulation studies to illustrate their performance. In addition, they are applied to some real data sets and compared with the related count models, mainly Poisson and NB models. Overall, the DW models provide a good fit to the count data as an alternative to the NB models in the over-dispersion case and are much better fitting than the Poisson models. Additionally, contrary to the NB model, the DW can be applied for the under-dispersion case.

This research complements and combines market microstructure theory and mechanism design to optimize the market structure of financial markets systematically. We develop an agent-based model featuring near-zero-intelligence traders operating in a call market with a wide range of trading rules governing the determination of prices, which orders are executed as well as a range of parameters regarding market intervention by market makers and the presence of informed traders. The market structure which generates the best market performance is determined by applying the search technique Population-based Incremental Learning, guided by a number of performance measures, including maximizing trading volume or price, minimizing bid-ask spread or return volatility. We investigate the credibility of our model by observing the trading behavior of near-zero-intelligence traders with stylized facts in real markets. Based on computer simulations, we conform that the model is capable to reproduce some of the most important stylized facts found in financial markets. Thereafter, we investigate the best found market structure using both single-objective optimization and multi-objective optimization techniques. Our results suggest that the best-found combination of trading rules used to enhance trading volume may not be applied to achieve other objectives, such as reducing bid-ask spread. The results of single-objective optimization experiments show that significantly large tick sizes appear in the best market structures in most cases, except for the case of maximizing trading volume. The tick size is always correlated with the selection of multi-price rules. Though there is no particular combination of priority rule and multiprice rule achieving the best market performance, the time priority rule and the closest multi-price rule are the most frequently obtained rules. The level of market transparency and the extend of market maker intervention show ambiguous results as their representative parameter values change in a wide range. We also nd that the results of multi-objective optimization experiments are much similar to those obtained in the single-objective optimization experiments, except for the market transparency represented by the fraction of informed trader, which shows a clear trend in the multi-objective optimization. Using the results obtained from this research we can derive recommendations for exchanges and regulators on establishing the optimal market structure; for securities issuers on choosing the best exchange for their listing; and for investors on choosing the most suitable exchange for trading.