VictorJuiz/thesis huggingface dataset:
Advances in Portfolio Selection Under Discrete Choice Constraints: A Mixed-integer Programming Approach and Heuristics

Over the last year or so, we have witnessed the global effects and repercussions related to the field of finance. Supposed blue chip stocks and well-established companies have folded and filed for bankruptcy, an event that might have thought to been absurd two years ago. In addition, finance and investment science has grown over the past few decades to include a plethora of investment options and regulations. Now more than ever, developments in the field are carefully examined and researched by potential investors. This thesis involves an investigation and quantitative analysis of key money management problems. The primary area of interest is Portfolio Selection, where we develop advanced financial models that are designed for investment problems of the 21st century. Portfolio selection is the process involved in making large investment decisions to generate a collection of assets. Over the years the selection process has evolved dramatically. Current portfolio problems involve a complex, yet realistic set of managing constraints that are coupled to general historic risk and return models. We identify three well-known portfolio problems and add an array of practical managing constraints that form three different types of Mixed-Integer Programs. The product is advanced mathematical models related to risk-return portfolios, index tracking portfolios, and an integrated stock-bond portfolio selection model. The numerous sources of uncertainty are captured in a Stochastic Programming framework, and Goal Programming techniques are used to facilitate various portfolio goals. The designs require the consideration of modelling elements and variables with respect to problem solvability. We minimize trade-offs in modelling and solvability issues found in the literature by developing problem specific algorithms. The algorithms are tailored to each portfolio design and involve decompositions and heuristics that improve solution speed and quality. The result is the generation of portfolios that have intriguing financial outcomes and perform well with respect to the market. Portfolio selection is as dynamic and complex as the recent economic situation. In this thesis we present and further develop the mathematical concepts related to portfolio construction. We investigate the key financial problems mentioned above, and through quantitative financial modelling and computational implementations we introduce current approaches and advancements in field of Portfolio Optimization.

Keywords: Optimization
Mathematical Programming
Stochastic Programming
Portfolio Optimization
Advisor: Kwon, Roy H.
Adaptation and Perfomance of Greek Drama in Post-Apartheid South Africa

In my dissertation I examine how adaptations of Greek tragedy in South Africa after the fall of apartheid (1994) address the transitional stage of the country and mediate in the formation and apprehension of post-apartheid national identities and the formation of a new communitas. Drawing particularly from Raymond Williams and Jean-Pierre Vernant, I approach tragedy as a paradigmatic model for analyzing the dialectical relationship between cultural text and social context. The examination of this paradigm in the context of post-apartheid South Africa is grounded in postcolonial theory defined as an ongoing project of addressing the politics of identity representation in conjunction with the underlying conditions of cultural and material inequalities in a neo-colonial context. I am focusing on three plays that provide distinct perspectives on the problem of national identity in the post-apartheid era and distinct artistic approaches to the process of adaptation. My examination of each play consists of two, interrelated parts: in the first part, I conduct a structural analysis of the text and an examination of the ways it relates to and reworks the major themes and concepts of the Greek tragedy it adapts. In the second part, I examine the connections between the country’s dominant discourses on national identities and the plays’ representations of these.

Keywords: South Africa
adaptation
tragedy
performance
Advisor: Quayson, Ato
'Wash Me Black Again': African Nationalism, the Indian Diaspora, and Kwa-Zulu Natal, 1944-60

My dissertation combines a critical history of the Indian diaspora’s political and intellectual impact on the development of African nationalism in South Africa with an analysis of African/Indian racial dynamics in Natal. Beginning in the 1940s, tumultuous debates among black intellectuals over the place of the Indian diaspora in Africa played a central role in the emergence of new and antagonistic conceptualizations of a South African nation. The writings of Indian political figures (particularly Gandhi and Nehru) and the Indian independence struggle had enormous influence on a generation of African nationalists, but this impact was mediated in complex ways by the race and class dynamics of Natal. During the 1930s and 40s, rapid and large-scale urbanization generated a series of racially-mixed shantytowns surrounding Durban in which a largely Gujarati and Hindi merchant and landlord class provided the ersatz urban infrastructure utilized by both Tamil-speaking workers and Zulu migrants. In Indian-owned buses, stores, and movie theatres, a racial hierarchy of Indian over African developed based on the social grammars of property, relationship with land, family structure, and different gender roles. In such circumstances, practices integral to maintaining diasporic identities—such as religious festivals, marriage, caste (jati), language, and even dress and food—became signifiers of ranked status and perceived exclusion. Despite the destruction of this urban landscape by forced removals beginning in the late 1950s, these social relationships powerfully shaped African and Indian identities in Natal, the popular memory of different communities, and the later politics of the anti-apartheid struggle. Although a few recent publications have attempted to break down the bifurcation that characterizes Natal’s historiography, the majority of academic writing on the province employs a race-based framework that focuses on either Indians or Zulu-speaking Africans. As a result, Natal’s African/Indian racial dynamic plays, at most, a secondary role in most scholarship on the region. In turn, Natal itself generally appears in histories of the anti-apartheid struggle as either an exception or a momentary interruption to a “national” narrative overwhelmingly centered on events, organizations, and individuals in the Transvaal. Rejecting a “race relations” approach that hypostatizes coherent racial groups, my dissertation examines how segregationist policies, African and Indian political organizations, and everyday social practices continuously reproduced an “African/Indian divide” despite both the enormous heterogeneity of each group and the quotidian intimacies of urban life. At the same time, it explores the ways in which this division shaped the development of the anti-apartheid struggle in Natal and the consequences of Natal’s politics for South Africa as a whole.

Keywords: South Africa
Natal
African National Congress
South African Indians
Diaspora
Postcolonial Theory
Advisor: Hawkins, Sean
On Small Mammal Sympatry in the Southeastern Amazon and Ecological Relationships with Brazil Nut Dispersal and Harvesting

The Amazon rainforest harbors the planet's highest biodiversity among terrestrial ecosystems; however, the biology and ecology of most of its species are unknown. Niche partitioning is considered a key factor allowing species co-existence, especially for morphological similar species such as spiny rats of the genus Proechimys. I examined the extent to which habitat differentiation, species body mass, and diet could explain the community composition of small mammals at a site in the southeastern Amazon. Moreover, I radio-tagged sympatric species of Proechimys spp. and Mesomys stimulax (an arboreal spiny rat) to obtain detailed autoecology information, including habitat use and use of space. I found support for niche partitioning among species and associated small mammal species with distinct successional phases of gap dynamics. I also observed among Proechimys spp. a typical polygynous organization: females appeared to be territorial against females of any species of their genus; but male territories overlapped with those of several females. Mesomys stimulax showed evidence of monogamy and possible sociality, although sample sizes were small. To identify the importance of small mammals as seed disperser of Brazil nut seeds, I conduct experiments using a combination of fluorescent powder, seed exclosures, and track plates in forests with and without Brazil nut groves, and in forests with and without Brazil nut harvesting. Among small mammals, only Proechimys spp. removed, dispersed, and preyed upon Brazil nut seeds. Proechimys spp. sometimes scatterhoarded these seeds, and hence have the potential to play a significant role in recruiting new Brazil nut trees. I also trapped small mammals and measured forest structures on the same sites used for the seed dispersal experiment, to determine the ecological effects of Brazil nut harvest on small mammal communities; however, my results showed little evidence of changes associated with the seed exploitation. My results highlight the importance of habitat heterogeneity in structuring small mammal communities, and indicate that forest management practices that alter habitats, such as partial logging, also can be expected to alter small mammal composition and diversity. Proechimys spp. have the potential to play an important role in the ecological restoration of intensive exploited Brazil nut groves.

Keywords: Small Mammals
Autoecology
Brazil nut
NTFPs
Seed Dispersal
Sympatry
Autoecology
Radio Telemetry
Muridae
Echimyidae
Spiny rat
Proechimys cuvieri
Proechimys goeldii
Proechimys roberti
Mesomys stimulax
Bertholletia excelsa
Lecythidaceae
Exclosures
Track plate
Live-trap
Advisor: Malcolm, Jay R.
Error Control for Network Coding

Network coding has emerged as a new paradigm for communication in networks, allowing packets to be algebraically combined at internal nodes, rather than simply routed or replicated. The very nature of packet-mixing, however, makes the system highly sensitive to error propagation. Classical error correction approaches are therefore insufficient to solve the problem, which calls for novel techniques and insights. The main portion of this work is devoted to the problem of error control assuming an adversarial or worst-case error model. We start by proposing a general coding theory for adversarial channels, whose aim is to characterize the correction capability of a code. We then specialize this theory to the cases of coherent and noncoherent network coding. For coherent network coding, we show that the correction capability is given by the rank metric, while for noncoherent network coding, it is given by a new metric, called the injection metric. For both cases, optimal or near-optimal coding schemes are proposed based on rank-metric codes. In addition, we show how existing decoding algorithms for rank-metric codes can be conveniently adapted to work over a network coding channel. We also present several speed improvements that make these algorithms the fastest known to date. The second part of this work investigates a probabilistic error model. Upper and lower bounds on capacity are obtained for any channel parameters, and asymptotic expressions are provided in the limit of long packet length and/or large field size. A simple coding scheme is presented that achieves capacity in both limiting cases. The scheme has fairly low decoding complexity and a probability of failure that decreases exponentially both in the packet length and in the field size in bits. Extensions of the scheme are provided for several variations of the channel. A final contribution of this work is to apply rank-metric codes to a closely related problem: securing a network coding system against an eavesdropper. We show that the maximum possible rate can be achieved with a coset coding scheme based on rank-metric codes. Unlike previous schemes, our scheme has the distinctive property of being universal: it can be applied on top of any communication network without requiring knowledge of or any modifications on the underlying network code. In addition, the scheme can be easily combined with a rank-metric-based error control scheme to provide both security and reliability.

Keywords: network coding
error control
information-theoretic security
rank-metric codes
matrix channels
Advisor: Kschischang, Frank R.
Utility Indifference Pricing of Credit Instruments

While the market for credit instruments grew continuously in the decade before 2008, its liquidity has dried up significantly in the current crisis, and investors have become aware of the possible consequences of being exposed to credit risk. In this thesis we address these issues by pricing credit instruments using utility indifference pricing, a method that takes into account the investor's personal risk aversion and which is not affected by the lack of liquidity. Through stochastic optimal control methods, we use indifference pricing with exponential utility to determine corporate bond prices and CDS spreads. In the first part we examine how these quantities are affected by risk aversion under different models of default. The emphasis lies on a hybrid model, in which a regime switch of the reference entity is triggered by a creditworthiness index correlated to its stock price. The second part generalizes this setup by introducing uncertainty in the model parameters. Robust optimal control has been used independently in the literature to address model uncertainty for portfolio selection problems. Here, we incorporate this approach with utility indifference and derive some analytical and numerical results on how model uncertainty affects credit spreads.

Keywords: utility indifference pricing
credit instruments
risk aversion
model uncertainty
stochastic optimal control
Advisor: Jaimungal, Sebastian
Machine Learning in Computational Biology: Models of Alternative Splicing

Alternative splicing, the process by which a single gene may code for similar but different proteins, is an important process in biology, linked to development, cellular differentiation, genetic diseases, and more. Genome-wide analysis of alternative splicing patterns and regulation has been recently made possible due to new high throughput techniques for monitoring gene expression and genomic sequencing. This thesis introduces two algorithms for alternative splicing analysis based on large microarray and genomic sequence data. The algorithms, based on generative probabilistic models that capture structure and patterns in the data, are used to study global properties of alternative splicing. In the first part of the thesis, a microarray platform for monitoring alternative splicing is introduced. A spatial noise removal algorithm that removes artifacts and improves data fidelity is presented. The GenASAP algorithm (generative model for alternative splicing array platform) models the non-linear process in which targeted molecules bind to a microarray’s probes and is used to predict patterns of alternative splicing. Two versions of GenASAP have been developed. The first uses variational approximation to infer the relative amounts of the targeted molecules, while the second incorporates a more accurate noise and generative model and utilizes Markov chain Monte Carlo (MCMC) sampling. GenASAP, the first method to provide quantitative predictions of alternative splicing patterns on large scale data sets, is shown to generate useful and precise predictions based on independent RT-PCR validation (a slow but more accurate approach to measuring cellular expression patterns). In the second part of the thesis, the results obtained by GenASAP are analysed to reveal jointly regulated genes. The sequences of the genes are examined for potential regulatory factors binding sites using a new motif finding algorithm designed for this purpose. The motif finding algorithm, called GenBITES (generative model for binding sites) uses a fully Bayesian generative model for sequences, and the MCMC approach used for inference in the model includes moves that can efficiently create or delete motifs, and extend or contract the width of existing motifs. GenBITES has been applied to several synthetic and real data sets, and is shown to be highly competitive at a task for which many algorithms already exist. Although developed to analyze alternative splicing data, GenBITES outperforms most reported results on a benchmark data set based on transcription data.

Keywords: Machine Learning
Graphical Models
Computational Biology
Alternative Splicing
Advisor: Frey, Brendan J.
Mediators and Moderators in the Relative Deprivation – Crime/Counter-normative Actions Relationship

Researchers have failed to specify when crime and counter-normative actions, as opposed to other responses may occur as a consequence of relative deprivation. To clarify this issue, a mediational model was developed that specified the causal processes leading from the recognition of deprivation to crime and counter-normative actions. This model hypothesizes that the recognition of deprivation (cognitive relative deprivation) leads to feelings associated with this recognition (affective relative deprivation) which in turn leads to crime and counter-normative actions. This model applies to both personal and group deprivation. In both cases, the feelings associated with deprivation include anger, resentment, dissatisfaction, and discontent. Data from a sample of 950 males between the ages of 16 to 30 supported the mediational model. Moderator variables were hypothesized to influence the causal processes in the mediational model, and were thus employed to specify the conditions under which the recognition of deprivation became more likely to lead to intense emotional reactions, and the conditions under which these emotional reactions became more likely to lead to crime and counter-normative actions. Personal deprivation was found to lead to stronger emotional responses if persons were pessimistic about their deprivation being relieved in the future, while at the group level, higher levels of optimism were related to stronger emotional responses. Both types of deprivation also lead to stronger emotional responses when persons believe that financial success and wealth are important. The emotive responses for both personal and group deprivation, in turn, were more likely to lead to crime and counter-normative actions if deprived persons had criminal peers. It was also found that the recognition of personal deprivation was more likely to lead to depression and lower self-esteem if people blamed themselves for their deprivation than if they did not. Persons who were not optimistic that their deprivation would be relieved in the future were more depressed than persons who were optimistic. Persons whose in-group was deprived were more likely to have lower self-esteem if they blamed the in-group for its deprivation than if they did not.

Keywords: Relative Deprivation
Crime
Counter-normative actions
mediators
moderators
Advisor: Wortley, Scot
Doob, Anthony N.
Gartner, Rosemary
Family Matters: An Examination of the Association between Family Structure and Youth Injury

Injury is the leading cause of morbidity and mortality among Canadian youth. In order to develop successful prevention strategies for this major public health problem, it is necessary to determine injury risk factors. Despite reasons to believe that family structure (parents’ marital and living arrangements) may be associated with youth injury, this link has been largely overlooked in injury research. The objectives of this thesis were to determine whether family structure was associated with youth injury in a manner described by theory, after considering alternative explanations for the observed association and to explore how engaging in high risk behaviour mediated the impact of family structure on youth injury. The association was explored using cross-sectional and longitudinal data. This study was based on a representative, cross-sectional World Health Organization, Health Behaviour in School-aged Children (2006) survey of 9, 068 Canadian students, aged 11–15 years, from 186 schools. A sub-sample of 1, 885 Ontario students surveyed in 2006 and again in 2007 comprised the longitudinal sample. The associations were assessed using generalized estimating equations with classroom clusters and Poisson distribution, adjusting for identified potential confounders and examining mediation by high-risk behaviours. There were three main findings: 1) Family structure was associated with medically treated injury in females, after accounting for confounding. Results showed that females from non-intact families had slightly increased risk of any injury than those from intact families (PR=1.11; 95% CI: 1.04-1.19). However, they had a greater risk of non-sports (PR=1.30; 95% CI: 1.16-1.77) and severe, non-sports (PR=1.46; 95% CI: 1.12-1.91) injury. 2) Only a small portion of the association between family structure and injury was explained by engaging in high risk behaviour. 3) There was an inconsistent relationship between family structure and male non-sports injury (Canadian cross-sectional, PR=1.05; 95% CI: 0.94-1.16; Ontario longitudinal, PR=1.58; 95% CI: 1.20-2.07). The findings of this thesis call attention to the importance of non-intact family structures as a risk factor for youth injury. More research is needed to improve our understanding of the mechanisms through which family structure influences youths' risk of injury in order to guide policy development.

Keywords: youth injury
family structure
Advisor: Chipman, Mary
té, Pierre Cô