In this dissertation, I examine the changes to the nature of the accounting paradigms of U.S. GAAP and International Financial Reporting Standards (IFRS) over the course of the U.S. GAAP and IFRS convergence project. I further examine whether the changes to the nature of IFRS following convergence impacts the financial reporting quality. The motivation for this study is to provide an initial review of the progress of the convergence process between U.S. GAAP and IFRS that aims to converge both sets of standards towards more principles-based paradigms. The ultimate goal of the convergence process was the development of globally recognized high quality financial reporting standards (FASB, 2002) and the development of principles-based accounting standards was identified as an essential component of such a goal. Extant literature and professional practice agree that U.S. GAAP is more rules-based whereas IFRS is more principles-based. Thus, both the International Accounting Standards Board (IASB) and the U.S. Financial Accounting Standards Board (FASB) agreed that the convergence process would be an ideal vehicle to converge both sets of standards towards more principles-based paradigm. I document that over the course of the convergence project, the underlying accounting paradigm of U.S. GAAP has remained consistent whereas the accounting paradigm of IFRS has become more rules-based. Amendments to existing International Standards and newer standards added over the course of the convergence have moved IFRS towards a more rules-based nature which was not the intended outcome of the convergence process. I further examine if the changes in rules vs. principles-based nature of IFRS has impacted the accounting quality. Using a firm level instrument developed in Folsom et al. (2016) that measures the extent to which firms rely on principles-vs –rules-based accounting, standards I find a relation between firm reliance on principles-based standards and earnings persistence. I also find an association between firm reliance on principles-based standards and earnings ability to predict future cash flows as well as concurrent returns. More, importantly the results of my study provide initial evidence that these associations are significantly manifested in the post-convergence period.

The principles versus rules debate has long since been a conversation in the accounting world, but the conversation heated up in the early part of the 21st century on the heels of a few highly publicized accounting frauds. In an increasingly globalized business environment, convergence between the more rules-oriented US GAAP and more principles-oriented IFRS is becoming more and more relevant. This study attempts to better inform that debate, exploring the accounting conceptual framework, United States legal environment, and the costs and benefits of adopting a more principles-oriented set of accounting standards. This study concludes that, though there would likely be some costs initially, principles-oriented standards give managers the ability to produce more relevant, comparable, and reliable financial statements, and can even serve to deincentivize fraudulent behavior. By adjusting the incentive structure, managers would no longer be offered protection by bright-line rules, instead required to more faithfully represent the economic reality of their firm. However, though rules-oriented standards like lease accounting are in need of improvement, due to the complex nature of some transactions, not all standards can be solely principles-oriented. As such, the FASB should develop a propensity away from rules, detailed guidance, and exceptions whenever possible.

Failure diagnosis in large and complex systems is a critical task. In the realm of discrete event systems, Sampath et al. proposed a language based failure diagnosis approach. They introduced the diagnosability for discrete event systems and gave a method for testing the diagnosability by first constructing a diagnoser for the system. The complexity of this method of testing diagnosability is exponential in the number of states of the system and doubly exponential in the number of failure types. In this thesis, we give an algorithm for testing diagnosability that does not construct a diagnoser for the system, and its complexity is of 4th order in the number of states of the system and linear in the number of the failure types. In this dissertation we also study diagnosis of discrete event systems (DESs) modeled in the rule-based modeling formalism introduced in [12] to model failure-prone systems. The results have been represented in [43]. An attractive feature of rule-based model is it's compactness (size is polynomial in number of signals). A motivation for the work presented is to develop failure diagnosis techniques that are able to exploit this compactness. In this regard, we develop symbolic techniques for testing diagnosability and computing a diagnoser. Diagnosability test is shown to be an instance of 1st order temporal logic model-checking. An on-line algorithm for diagnosersynthesis is obtained by using predicates and predicate transformers. We demonstrate our approach by applying it to modeling and diagnosis of a part of the assembly-line. When the system is found to be not diagnosable, we use sensor refinement and sensor augmentation to make the system diagnosable. In this dissertation, a controller is also extracted from the maximally permissive supervisor for the purpose of implementing the control by selecting, when possible, only one controllable event from among the ones allowed by the supervisor for the assembly line in automaton models.

This thesis compares and contrasts rules-based and principles-based approaches to the regulation of derivative securities and examines these approaches in the context of derivative securities regulation in Thailand and Québec. It highlights the importance of derivatives regulation by briefly noting the role of derivatives in the 2007-2008 financial crisis. Context is provided by briefly noting the complexity and riskiness of derivatives, and the function of intermediaries in derivatives markets. With this context in mind, literature on rules-based regulation and principles-based regulation is examined. The two approaches are described and the advantages and disadvantages of each approach are highlighted. The thesis posits that the approach in Thailand is predominantly rules-based while the approach in Québec is predominantly principles-based. The thesis then argues that Québec may have been better positioned than Thailand to adopt a principles-based approach, given its longer experience with trading in public securities markets, its greater degree of specialization in derivatives markets, and the significantly higher volume of derivatives trading in Québec. These factors may have promoted a greater degree of regulatory expertise and self-regulatory organization experience. It is then argued that even though Thailand, and countries at a similar stage of derivatives market development, may not be in as good a position as Québec to adopt a principles-based regulatory approach, once the derivatives market has been established, a shift to principles-based regulation is, nonetheless, likely to better serve the regulatory goals of risk management and innovation.

U.S. GAAP and the software industry in particular, are on the verge of a major alteration in revenue-recognition accounting standards. The IASB-FASB joint revenue-recognition project is due to be finalized over the next year with the result being a shift from a rules-based set of accounting standards to a principles-based standard. The purpose of this research is to examine financial statement preparers' software revenue-recognition decisions under a principles-based accounting standard compared to a rules-based accounting standard both with and without a personal incentive to maximize revenue. The 2 X 2 between-subjects experiment examines the revenue-recognition judgments and decisions of financial statement preparers involved in applying rules-based standards (U.S. GAAP) and a principles-based standard (IASB-FASB Exposure Draft: Revenue from Contracts with Customers) with and without a personal incentive to maximize revenue. The study included 127 experienced financial statement preparers with an average of 20 years of experience and 82% at a manager/director level or above. The results indicate financial statement preparers applying rules-based standards in a revenue-recognition scenario provide less accurate revenue decisions than when applying a principles-based standard. Moreover, the results did not show that a personal incentive influenced the financial statement preparers in their revenue-recognition decisions. Surprisingly, in the rules-based and principles-based scenarios where a personal incentive was not present, the arithmetic mean recommended revenue amounts were higher. In providing the amount of judgment required to determine the revenue to be recognized, there was not a statistically significant difference in the amount of judgment required between subjects applying rules-based standards and subjects applying principles-based standards. The arithmetic means for rules-based subjects and principles-based indicated some judgment however not significant judgment was required. This is interesting to note as so few subjects correctly answered the revenue amount and neglected to fully apply the guidance.

Titel: K2 eller K3 : Motiv till att redovisa enligt K3  Författare: Adrian Zhubi och Albert Zhubi  Färdigställt: Våren 2016  Handledare: Eva Berggren Bakgrund: BFN har sedan 2004 gett ut allmänna råd, vilket har medfört att K-projektet skapats där företag delas in i fyra olika kategorier beroende på företagsstorlek. K-projektets vanligaste regelverk är huvudregelverket principbaserade K3 och alternativregelverket regelbaserade K2. Sedan 2015 är det obligatoriskt för samtliga aktiebolag och ekonomiska föreningar att tillämpa ett av dessa två regelverk. Företag bör därmed reflektera över dess verksamhet och intressenter vid val av regelverk. Valet kan ställa krav på att årsredovisningen ska vara relevant för intressenter. Vi vill därför med studien undersöka vilka väsentliga skillnader som förklarar att företag väljer K3 framför K2. Detta utifrån redovisningsrådgivares perspektiv.  Syfte: Syftet med studien är att förklara vilka skillnader som ligger bakom att företag föredrar K3 istället för K2 utifrån redovisningsrådgivares perspektiv.  Problemformulering: Vad anser redovisningsrådgivare förklarar företags val av K3 framför K2?  Metod: Studien består av en kvalitativ ansats. Den empiriska datan består av totalt fem intervjuer, varav en är pilotintervju. Studiens respondenter består av tre revisorer, en redovisningsexpert samt en redovisningsspecialist. Respondenterna har olika erfarenheter och är från olika revisionsbyråer. Resultat: Studien visar att redovisningsrådgivare anser skillnader i materiella, immateriella och finanisella anläggningstillgångar i K2 och K3 gör att företag föredrar K3. Avsättningar, uppskjuten skatt och intressenter är även påverkande faktorer. Samtliga respondenter var eniga om att K2 är enklare att tillämpa då regelverket innehåller handfasta regler för redovisning. K3 ställer större krav på kunskap vid professionell bedömning då regelverket tar hänsyn till en komplex verksamhet med fler företagsintressenter. / Title: K2 or K3 : Reasons to account according to K3  Authors: Adrian Zhubi and Albert Zhubi  Published: Spring 2016  Tutor: Eva Berggren  Background: Since 2004 BFN has given accounting standards, which started the K-project that divides companies into four different categories based on company size. The K-project's most common regulations are the main regulation principles-based K3 and the alternative regulation rules-based K2. Since 2015 it became mandatory for all joint-stock companies and economic associations to apply one of these two regulations. Companies should therefore reflect on its business and stakeholders when making a choice of regulation. This requires that the annual report should be relevant to the stakeholders. With the study we therefore want to examine the main differences that explains why companies choose K3 instead of K2 from accounting advisors’ perspective.  Aim: The aim of the study is to describe why companies prefer K3 instead of K2 according to accounting advisors.  Formulation of the problem: What do accounting advisors consider explains the companies’ choice of K3 instead of K2?  Methodology: The study is based on a qualitative approach. The empirical data contains a total of five interviews, one of those is a pilot interview. The study's respondents are three auditors, an accounting expert and an accounting specialist. The respondents have different experiences and are from different accounting firms. Results: The study shows that accounting advisors consider differences in tangible, intangible and financial assets between K2 and K3 makes companies prefer K3. Factors as depositions, deferred taxes and stakeholders also affects the choice. According to the study’s respondents, K2 is easier to apply because the regulation contains robust rules for accounting. K3 require greater knowledge at professional judgement, because the regulation includes companies with a complex business with many stakeholders.

O presente trabalho busca identificar bull e bear markets para o mercado financeiro brasileiro, especificamente para o índice Ibovespa, através das principais metodologias existentes na literatura: regras não paramétricas e modelos de mudança de regime markoviano. A primeira abordagem foi utilizada como benchmark para comparação com melhor modelo econométrico estimado pela segunda abordagem, visto que trata-se de um método ex-post de identificação. No tange aos modelos de mudança de regime markoviano, constatou-se que permitir regimes distintos também para a variância da série contribui para a identificação dos mesmos. Desta forma, o melhor modelo obtido fora o MSARMA(2,1)-2 para a série de retornos semanais do índice Ibovespa. O modelo foi capaz de identificar os principais eventos que impactaram a economia e o mercado financeiro brasileiro no período. Além disto, o modelo se mostrou útil para a tomada de decisão, visto que a estratégia de investimento, baseada na previsão um passo à frente do estado do mercado, foi capaz de preservar o capital do investidor, gerando um melhor desempenho do que na estratégia buy-and-hold de longo prazo. / This paper seeks to identify bull and bear markets in the brazilian stock market, specifically to the time series of the Ibovespa index, through the main methodologies present in literature: identification based on rules and Markov switching models. The first method was used as a benchmark to compare with the best regime switching model, since it is an ex-post method of identification. Modelling a Markov switching model with two regimes also for the variance of the process resulted in a better identification of the markets. Thus, the best Markov switching model estimated was theMSARMA(2,1)-2 to the time series of the Ibovespa weekly returns. The model was able to identify the main events that have impacted the brazilian economy and also the stock market in the period. Furthermore, the model proved its value in decision making, since in a investment strategy, based on the models one step ahead forecast about the regime of the market, it was able to preserve investor capital, generating a better performance than the buy-and-hold strategy.

O presente trabalho busca identificar bull e bear markets para o mercado financeiro brasileiro, especificamente para o índice Ibovespa, através das principais metodologias existentes na literatura: regras não paramétricas e modelos de mudança de regime markoviano. A primeira abordagem foi utilizada como benchmark para comparação com melhor modelo econométrico estimado pela segunda abordagem, visto que trata-se de um método ex-post de identificação. No tange aos modelos de mudança de regime markoviano, constatou-se que permitir regimes distintos também para a variância da série contribui para a identificação dos mesmos. Desta forma, o melhor modelo obtido fora o MSARMA(2,1)-2 para a série de retornos semanais do índice Ibovespa. O modelo foi capaz de identificar os principais eventos que impactaram a economia e o mercado financeiro brasileiro no período. Além disto, o modelo se mostrou útil para a tomada de decisão, visto que a estratégia de investimento, baseada na previsão um passo à frente do estado do mercado, foi capaz de preservar o capital do investidor, gerando um melhor desempenho do que na estratégia buy-and-hold de longo prazo. / This paper seeks to identify bull and bear markets in the brazilian stock market, specifically to the time series of the Ibovespa index, through the main methodologies present in literature: identification based on rules and Markov switching models. The first method was used as a benchmark to compare with the best regime switching model, since it is an ex-post method of identification. Modelling a Markov switching model with two regimes also for the variance of the process resulted in a better identification of the markets. Thus, the best Markov switching model estimated was theMSARMA(2,1)-2 to the time series of the Ibovespa weekly returns. The model was able to identify the main events that have impacted the brazilian economy and also the stock market in the period. Furthermore, the model proved its value in decision making, since in a investment strategy, based on the models one step ahead forecast about the regime of the market, it was able to preserve investor capital, generating a better performance than the buy-and-hold strategy.

O presente trabalho busca identificar bull e bear markets para o mercado financeiro brasileiro, especificamente para o índice Ibovespa, através das principais metodologias existentes na literatura: regras não paramétricas e modelos de mudança de regime markoviano. A primeira abordagem foi utilizada como benchmark para comparação com melhor modelo econométrico estimado pela segunda abordagem, visto que trata-se de um método ex-post de identificação. No tange aos modelos de mudança de regime markoviano, constatou-se que permitir regimes distintos também para a variância da série contribui para a identificação dos mesmos. Desta forma, o melhor modelo obtido fora o MSARMA(2,1)-2 para a série de retornos semanais do índice Ibovespa. O modelo foi capaz de identificar os principais eventos que impactaram a economia e o mercado financeiro brasileiro no período. Além disto, o modelo se mostrou útil para a tomada de decisão, visto que a estratégia de investimento, baseada na previsão um passo à frente do estado do mercado, foi capaz de preservar o capital do investidor, gerando um melhor desempenho do que na estratégia buy-and-hold de longo prazo. / This paper seeks to identify bull and bear markets in the brazilian stock market, specifically to the time series of the Ibovespa index, through the main methodologies present in literature: identification based on rules and Markov switching models. The first method was used as a benchmark to compare with the best regime switching model, since it is an ex-post method of identification. Modelling a Markov switching model with two regimes also for the variance of the process resulted in a better identification of the markets. Thus, the best Markov switching model estimated was theMSARMA(2,1)-2 to the time series of the Ibovespa weekly returns. The model was able to identify the main events that have impacted the brazilian economy and also the stock market in the period. Furthermore, the model proved its value in decision making, since in a investment strategy, based on the models one step ahead forecast about the regime of the market, it was able to preserve investor capital, generating a better performance than the buy-and-hold strategy.

Submitted by Izabel Franco (izabel-franco@ufscar.br) on 2016-09-06T20:33:16Z No. of bitstreams: 1 DissFJJS.pdf: 1581721 bytes, checksum: f878dcc392455f0f3956326282aabe6a (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-09-12T14:27:05Z (GMT) No. of bitstreams: 1 DissFJJS.pdf: 1581721 bytes, checksum: f878dcc392455f0f3956326282aabe6a (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-09-12T14:27:10Z (GMT) No. of bitstreams: 1 DissFJJS.pdf: 1581721 bytes, checksum: f878dcc392455f0f3956326282aabe6a (MD5) / Made available in DSpace on 2016-09-12T14:27:36Z (GMT). No. of bitstreams: 1 DissFJJS.pdf: 1581721 bytes, checksum: f878dcc392455f0f3956326282aabe6a (MD5) Previous issue date: 2009-11-30 / Não recebi financiamento / The use of fuzzy logic and fuzzy sets theory applied to decision making process was initially proposed by Bellman and Zadeh (1970). Since then, the arisen of unstructured problems associated with multi-criteria characteristics and group decision making changed the way of dealing with these problems. The evolution of Decision Support Systems (DSS) allowed them, not only to provide data and information, but also to propose solutions to these problems. The goal of this work is to present a framework for the development of DSS that deal with Multi-Criteria Group Decision Making (MCGDM) problems through fuzzy rules. In this approach, we propose a method capable of automatically generating a Fuzzy Rule Base with multi-criteria characteristics for group decision making, that is, different influence degrees for each decider and different importance degrees assigned to each variable are considered in the model. This framework also contains a structural model of a Fuzzy System for Group Decision Support aiming at adding DSS characteristics found in literature to Fuzzy Systems. These characteristics include user/system interactivity and Model Management Subsystem (MMS) described in this work. Finally, a case study designed to validate the model is presented. / O uso da lógica fuzzy e da teoria de conjuntos fuzzy aplicadas ao processo de tomada de decisão foi proposto inicialmente por Bellman e Zadeh (1970). Desde então, os problemas não estruturados associados às características multicritério e de tomada de decisão em grupo alteraram sua forma de tratamento. A evolução presente nos Sistemas de Apoio à Decisão (SAD) fez com que estes sistemas deixassem de fornecer somente dados e informações e passassem também a propor soluções aos problemas analisados. O objetivo deste trabalho é apresentar um framework para o desenvolvimento de SAD que tratem problemas classificados como Multi-Criteria Group Decision Making (MCGDM) com o uso de regras fuzzy. Dentro desta abordagem é apresentado um método capaz de gerar automaticamente uma Base de Regras Fuzzy com características multicritério para tomada de decisão em grupo, ou seja, os diferentes graus de influência de cada decisor e os diferentes graus de importância atribuídos por eles a cada variável são considerados no modelo. Este framework ainda contempla um modelo estrutural de um Sistema Fuzzy para Apoio à Decisão em Grupo com o objetivo de agregar aos sistemas fuzzy as características dos SAD descritas na literatura como, por exemplo, a capacidade de interatividade usuário/sistema e a presença do Subsistema de Gestão de Modelos (SGM), descritos neste trabalho. Por fim, um estudo de caso é realizado para validar o modelo apresentado.