932 resultados para financial markets credit rating agencies


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Considering the importance of the proper detection of bubbles in financial markets for policymakers and market agents, we used two techniques described in Diba and Grossman (1988b) and in Phillips, Shi, and Yu (2015) to detect periods of exuberance in the recent history of the Brazillian stock market. First, a simple cointegration test is applied. Secondly, we conducted several augmented, right-tailed Dickey-Fuller tests on rolling windows of data to determine the point in which there’s a structural break and the series loses its stationarity.

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Vector error-correction models (VECMs) have become increasingly important in their application to financial markets. Standard full-order VECM models assume non-zero entries in all their coefficient matrices. However, applications of VECM models to financial market data have revealed that zero entries are often a necessary part of efficient modelling. In such cases, the use of full-order VECM models may lead to incorrect inferences. Specifically, if indirect causality or Granger non-causality exists among the variables, the use of over-parameterised full-order VECM models may weaken the power of statistical inference. In this paper, it is argued that the zero–non-zero (ZNZ) patterned VECM is a more straightforward and effective means of testing for both indirect causality and Granger non-causality. For a ZNZ patterned VECM framework for time series of integrated order two, we provide a new algorithm to select cointegrating and loading vectors that can contain zero entries. Two case studies are used to demonstrate the usefulness of the algorithm in tests of purchasing power parity and a three-variable system involving the stock market.

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The recent deregulation in electricity markets worldwide has heightened the importance of risk management in energy markets. Assessing Value-at-Risk (VaR) in electricity markets is arguably more difficult than in traditional financial markets because the distinctive features of the former result in a highly unusual distribution of returns-electricity returns are highly volatile, display seasonalities in both their mean and volatility, exhibit leverage effects and clustering in volatility, and feature extreme levels of skewness and kurtosis. With electricity applications in mind, this paper proposes a model that accommodates autoregression and weekly seasonals in both the conditional mean and conditional volatility of returns, as well as leverage effects via an EGARCH specification. In addition, extreme value theory (EVT) is adopted to explicitly model the tails of the return distribution. Compared to a number of other parametric models and simple historical simulation based approaches, the proposed EVT-based model performs well in forecasting out-of-sample VaR. In addition, statistical tests show that the proposed model provides appropriate interval coverage in both unconditional and, more importantly, conditional contexts. Overall, the results are encouraging in suggesting that the proposed EVT-based model is a useful technique in forecasting VaR in electricity markets. (c) 2005 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

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Whilst financial markets are not strangers to academic and professional scrutiny, they still remain epistemologically contested. For individuals trying to profit by trading shares, this uncertainty is manifested in the varying trading styles which they are able to utilize. This paper examines one trading style commonly used by non-professional share traders-technical analysis. Using research data obtained from individuals who identify themselves as technical analysts, this paper seeks to explain the ways in which individuals understand and use the technique in an attempt to make trading profits. In particular, four distinct subcategories or ideal types of technical analysis can be identified, each providing an alternative perceptual form for participating in financial markets. Each of these types relies upon a particular method for seeing the market, these visualization techniques highlighting the existence of forms of professional vision (as originally identified by Goodwin (1994)) in the way the trading styles are comprehended and acted upon.

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The roiling financial markets, constantly changing tax law and increasing complexity of planning transaction increase the demand of aggregated family wealth management (FWM) services. However, current trend of developing such advisory systems is mainly focusing on financial or investment side. In addition, these existing systems lack of flexibility and are hard to be integrated with other organizational information systems, such as CRM systems. In this paper, a novel architecture of Web-service-agents-based FWM systems has been proposed. Multiple intelligent agents are wrapped as Web services and can communicate with each other via Web service protocols. On the one hand, these agents can collaborate with each other and provide comprehensive FWM advices. On the other hand, each service can work independently to achieve its own tasks. A prototype system for supporting financial advice is also presented to demonstrate the advances of the proposed Webservice- agents-based FWM system architecture.

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As ações de maior liquidez do índice IBOVESPA, refletem o comportamento das ações de um modo geral, bem como a relação das variáveis macroeconômicas em seu comportamento e estão entre as mais negociadas no mercado de capitais brasileiro. Desta forma, pode-se entender que há reflexos de fatores que impactam as empresas de maior liquidez que definem o comportamento das variáveis macroeconômicas e que o inverso também é uma verdade, oscilações nos fatores macroeconômicos também afetam as ações de maior liquidez, como IPCA, PIB, SELIC e Taxa de Câmbio. O estudo propõe uma análise da relação existente entre variáveis macroeconômicas e o comportamento das ações de maior liquidez do índice IBOVESPA, corroborando com estudos que buscam entender a influência de fatores macroeconômicos sobre o preço de ações e contribuindo empiricamente com a formação de portfólios de investimento. O trabalho abrangeu o período de 2008 a 2014. Os resultados concluíram que a formação de carteiras, visando a proteção do capital investido, deve conter ativos com correlação negativa em relação às variáveis estudadas, o que torna possível a composição de uma carteira com risco reduzido.

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It is well known that one of the obstacles to effective forecasting of exchange rates is heteroscedasticity (non-stationary conditional variance). The autoregressive conditional heteroscedastic (ARCH) model and its variants have been used to estimate a time dependent variance for many financial time series. However, such models are essentially linear in form and we can ask whether a non-linear model for variance can improve results just as non-linear models (such as neural networks) for the mean have done. In this paper we consider two neural network models for variance estimation. Mixture Density Networks (Bishop 1994, Nix and Weigend 1994) combine a Multi-Layer Perceptron (MLP) and a mixture model to estimate the conditional data density. They are trained using a maximum likelihood approach. However, it is known that maximum likelihood estimates are biased and lead to a systematic under-estimate of variance. More recently, a Bayesian approach to parameter estimation has been developed (Bishop and Qazaz 1996) that shows promise in removing the maximum likelihood bias. However, up to now, this model has not been used for time series prediction. Here we compare these algorithms with two other models to provide benchmark results: a linear model (from the ARIMA family), and a conventional neural network trained with a sum-of-squares error function (which estimates the conditional mean of the time series with a constant variance noise model). This comparison is carried out on daily exchange rate data for five currencies.

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This paper studies the behaviour of returns for a sample of cross-listed stocks, listed on both the Paris Bourse and SEAQ-International in London. The aim of the paper is to discover which market adjusts to fundamental news more quickly, the home market of Paris or SEAQ-International. We find that prices in London adjust to changes in their fundamental value more slowly than Paris prices, despite the ability to quickly arbitrage between the two markets. We suggest that this finding may reflect the type of trading, which takes place in the two markets and differences associated with the reporting of large trades. We also estimate the amount of noise present in the two markets and show that the Paris market is more noisy than London. © 2003 Published by Elsevier B.V.

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Purpose - To provide a framework of accounting policy choice associated with the timing of adoption of the UK Statement of Standard Accounting Practice (SSAP) No. 20, "Foreign Currency Translation". The conceptual framework describes the accounting policy choices that firms face in a setting that is influenced by: their financial characteristics; the flexible foreign exchange rates; and the stock market response to accounting decisions. Design/methodology/approach - Following the positive accounting theory context, this paper puts into a framework the motives and choices of UK firms with regard to the adoption or deferment of the adoption of SSAP 20. The paper utilises the theoretical and empirical findings of previous studies to form and substantiate the conceptual framework. Given the UK foreign exchange setting, the framework identifies the initial stage: lack of regulation and flexibility in financial reporting; the intermediate stage: accounting policy choice; and the final stage: accounting choice and policy review. Findings - There are situations where accounting regulation contrasts with the needs and business objectives of firms and vice-versa. Thus, firms may delay the adoption up to the point where the increase in political costs can just be tolerated. Overall, the study infers that firms might have chosen to defer the adoption of SSAP 20 until they reach a certain corporate goal, or the adverse impact (if any) of the accounting change on firms' financial numbers is minimal. Thus, the determination of the timing of the adoption is a matter which is subject to the objectives of the managers in association with the market and economic conditions. The paper suggests that the flexibility in financial reporting, which may enhance the scope for income-smoothing, can be mitigated by the appropriate standardisation of accounting practice. Research limitations/implications - First, the study encompassed a period when firms and investors were less sophisticated users of financial information. Second, it is difficult to ascertain the decisions that firms would have taken, had the pound appreciated over the period of adoption and had the firms incurred translation losses rather than translation gains. Originality/value - This paper is useful to accounting standards setters, professional accountants, academics and investors. The study can give the accounting standard-setting bodies useful information when they prepare a change in the accounting regulation or set an appropriate date for the implementation of an accounting standard. The paper provides significant insight about the behaviour of firms and the associated impacts of financial markets and regulation on the decision-making process of firms. The framework aims to assist the market and other authorities to reduce information asymmetry and to reinforce the efficiency of the market. © Emerald Group Publishing Limited.

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We review briefly the literature on international financial integration, especially as it pertains to bond market integration. This contextualizes the review we than provide of a number of papers contained in a special issue of this Journal. © 2005 Elsevier B.V. All rights reserved.

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Financial prediction has attracted a lot of interest due to the financial implications that the accurate prediction of financial markets can have. A variety of data driven modellingapproaches have been applied but their performance has produced mixed results. In this study we apply both parametric (neural networks with active neurons) and nonparametric (analog complexing) self-organisingmodelling methods for the daily prediction of the exchangerate market. We also propose acombinedapproach where the parametric and nonparametricself-organising methods are combined sequentially, exploiting the advantages of the individual methods with the aim of improving their performance. The combined method is found to produce promising results and to outperform the individual methods when tested with two exchangerates: the American Dollar and the Deutche Mark against the British Pound.

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The aim of this study is to determine if nonlinearities have affected purchasing power parity (PPP) since 1885. Also using recent advances in the econometrics of structural change we segment the sample space according to the identified breaks and look at whether the PPP condition holds in each sub-sample and whether this involves linear or non-linear adjustment. Our results suggest that during some sub-periods, PPP holds, although whether it holds or not and whether the adjustment is linear or non-linear, depends primarily on the type of exchange rate regime in operation at any point in time.

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This paper demonstrates that the conventional approach of using official liberalisation dates as the only existing breakdates could lead to inaccurate conclusions as to the effect of the underlying liberalisation policies. It also proposes an alternative paradigm for obtaining more robust estimates of volatility changes around official liberalisation dates and/or other important market events. By focusing on five East Asian emerging markets, all of which liberalised their financial markets in the late, and by using recent advances in the econometrics of structural change, it shows that (i) the detected breakdates in the volatility of stock market returns can be dramatically different to official liberalisation dates and (ii) the use of official liberalisation dates as breakdates can readily entail inaccurate inference. In contrast, the use of data-driven techniques for the detection of multiple structural changes leads to a richer and inevitably more accurate pattern of volatility evolution emerges in comparison with focussing on official liberalisation dates.

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The role of interest and agency in the creation and transformation of institutions, in particular the “paradox of embedded agency” (Seo & Creed, 2002) have long puzzled institutional scholars. Most recently, Lawrence and Suddaby (2006) coined the term “institutional work” to describe various strategies for creating, maintaining and disrupting institutions. This label, while useful to integrate existing research, highlights institutionalists’ lack of attention to work as actors’ everyday occupational tasks and activities. Thus, the objective of this study is to take institutional work literally and ask: How does practical work come to constitute institutional work? Drawing on concepts of “situated change” (Orlikowski, 1996) I supplement existing macro-level perspectives of change with a microscopic, practice-based alternative. I examine the everyday work of English and German banking lawyers in a global law firm. Located at the intersection of local laws, international financial markets, commercial logics and professional norms, banking lawyers’ work regularly bridges different normative settings. Hence, they must constructively negotiate contradictory meanings, practices and logics to develop shared routines that resonate with different normative frameworks and facilitate task accomplishment. Based on observation and interview data, the paper distils a process model of banking transac-tions that highlights the critical interfaces forcing English and German banking lawyers into cross-border sensemaking. It distinguishes two accounts of cross-border sensemaking: the “old story” in which contradictory practices and norms collide and the “new story” of a synthetic set of practices for collaboratively “editing” (Sahlin-Andersson, 1996) legal documentation. Data show how new practices gain shape and legitimacy over a series of dialectic contests unfolding at work and how, in turn, these contests shift institutional logics as lawyers ‘get the deal done’. These micro-mechanisms suggest that as practical and institutional work blend, everyday work-ing practices come to constitute a form of institutional agency that is situated, emergent, dialectic and, therefore, embedded.