313 resultados para Bankruptcy.
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The financial crisis of 2007-2008 led to extraordinary government intervention in firms and markets. The scope and depth of government action rivaled that of the Great Depression. Many traded markets experienced dramatic declines in liquidity leading to the existence of conditions normally assumed to be promptly removed via the actions of profit seeking arbitrageurs. These extreme events motivate the three essays in this work. The first essay seeks and fails to find evidence of investor behavior consistent with the broad 'Too Big To Fail' policies enacted during the crisis by government agents. Only in limited circumstances, where government guarantees such as deposit insurance or U.S. Treasury lending lines already existed, did investors impart a premium to the debt security prices of firms under stress. The second essay introduces the Inflation Indexed Swap Basis (IIS Basis) in examining the large differences between cash and derivative markets based upon future U.S. inflation as measured by the Consumer Price Index (CPI). It reports the consistent positive value of this measure as well as the very large positive values it reached in the fourth quarter of 2008 after Lehman Brothers went bankrupt. It concludes that the IIS Basis continues to exist due to limitations in market liquidity and hedging alternatives. The third essay explores the methodology of performing debt based event studies utilizing credit default swaps (CDS). It provides practical implementation advice to researchers to address limited source data and/or small target firm sample size.
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Prior research has been divided regarding how firms respond to bankruptcy risk, largely revolving around two competing forces. On the one hand, asset substitution encourages firms to increase the riskiness of assets to extract value from creditors. On the other, firms want to minimize bankruptcy risk, either by reducing cash flow risk or through increasing the size of the firm. I test these two theories using a natural experiment of chemicals used in production processes being newly identified as carcinogenic to explore how firms may respond to potential negative cash flow resulting from litigation risk. I use plantlevel chemical data to study firm exposure to risk. I examine how responses between firms of differing levels of chemical exposure may vary within the industry, how firm financial distress affects firm response and whether public and private firms respond differently. In general, my research provides support for the asset substitution theory. My first paper studies how investment response varies based on level of carcinogenic exposure. I find that firms with moderate levels of exposure make efforts to mitigate their cash flow risk and reduce their exposure. At the same time, firms with high levels of exposure increase their exposure and riskiness of future cash flows. These findings are consistent with asset substitution theory. My second paper analyzes the interaction of financial distress and risk exposure. I find that firms in a stronger financial position are more likely to limit their exposure by reducing the number of exposed facilities. On the other hand, not only do firms in weaker financial position not decrease their exposure, I find that, in some instances, they increase their exposure to carcinogens. This work again supports the theory of asset substitution. Finally, in my third paper, I explore if public firms respond differently to a potential negative cash flow shock than do private firms. I test whether existing public firms are more likely to attempt to minimize their cash flow risk and thus reduce their carcinogen exposure than are private firms. I do not find evidence that public firms respond differently to this shock than do private firms.
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Mestrado em Auditoria
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Doutoramento em Gestão.
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Facility location concerns the placement of facilities, for various objectives, by use of mathematical models and solution procedures. Almost all facility location models that can be found in literature are based on minimizing costs or maximizing cover, to cover as much demand as possible. These models are quite efficient for finding an optimal location for a new facility for a particular data set, which is considered to be constant and known in advance. In a real world situation, input data like demand and travelling costs are not fixed, nor known in advance. This uncertainty and uncontrollability can lead to unacceptable losses or even bankruptcy. A way of dealing with these factors is robustness modelling. A robust facility location model aims to locate a facility that stays within predefined limits for all expectable circumstances as good as possible. The deviation robustness concept is used as basis to develop a new competitive deviation robustness model. The competition is modelled with a Huff based model, which calculates the market share of the new facility. Robustness in this model is defined as the ability of a facility location to capture a minimum market share, despite variations in demand. A test case is developed by which algorithms can be tested on their ability to solve robust facility location models. Four stochastic optimization algorithms are considered from which Simulated Annealing turned out to be the most appropriate. The test case is slightly modified for a competitive market situation. With the Simulated Annealing algorithm, the developed competitive deviation model is solved, for three considered norms of deviation. At the end, also a grid search is performed to illustrate the landscape of the objective function of the competitive deviation model. The model appears to be multimodal and seems to be challenging for further research.
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Resumen La intensificación de la crisis a nivel global, luego de la bancarrota de Lehman Brothers en septiembre del 2008, ha provocado que el actual entorno económico y financiero sea complicado para la economía mundial, el sector financiero a nivel global y para los bancos centrales. La actual crisis deriva de muchas causas; no obstante las principales son tres: primero, aspectos macroeconómicos; segundo, la inadecuada regulación de los entes encargados, y tercero, los reguladores estimularon el rápido crecimiento de los derivados en el mercado OTC. Abstract The amplification of the global financial crisis, following the bankruptcy of Lehman Brothers in September 2008, has made the present economic and financial environment a not easy time for the world economy, the global financial system and for central banks. There are many causes from the recent financial crisis. Main could be three. First, there were macroeconomic components. Second, the inadequate oversight/regulation provided by financial market regulators. And third, federal regulators have actively encouraged the rapid growth of over-the-counter (OTC) derivatives and securities by all types of financial institutions.
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We consider a situation in which agents have mutual claims on each other, summarized in a liability matrix. Agents' assets might be insufficient to satisfy their liabilities leading to defaults. In case of default, bankruptcy rules are used to specify the way agents are going to be rationed. A clearing payment matrix is a payment matrix consistent with the prevailing bankruptcy rules that satisfies limited liability and priority of creditors. Since clearing payment matrices and the corresponding values of equity are not uniquely determined, we provide bounds on the possible levels equity can take. Unlike the existing literature, which studies centralized clearing procedures, we introduce a large class of decentralized clearing processes. We show the convergence of any such process in finitely many iterations to the least clearing payment matrix. When the unit of account is sufficiently small, all decentralized clearing processes lead essentially to the same value of equity as a centralized clearing procedure. As a policy implication, it is not necessary to collect and process all the sensitive data of all the agents simultaneously and run a centralized clearing procedure.
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¿What have we learnt from the 2006-2012 crisis, including events such as the subprime crisis, the bankruptcy of Lehman Brothers or the European sovereign debt crisis, among others? It is usually assumed that in firms that have a CDS quotation, this CDS is the key factor in establishing the credit premiumrisk for a new financial asset. Thus, the CDS is a key element for any investor in taking relative value opportunities across a firm’s capital structure. In the first chapter we study the most relevant aspects of the microstructure of the CDS market in terms of pricing, to have a clear idea of how this market works. We consider that such an analysis is a necessary point for establishing a solid base for the rest of the chapters in order to carry out the different empirical studies we perform. In its document “Basel III: A global regulatory framework for more resilient banks and banking systems”, Basel sets the requirement of a capital charge for credit valuation adjustment (CVA) risk in the trading book and its methodology for the computation for the capital requirement. This regulatory requirement has added extra pressure for in-depth knowledge of the CDS market and this motivates the analysis performed in this thesis. The problem arises in estimating of the credit risk premium for those counterparties without a directly quoted CDS in the market. How can we estimate the credit spread for an issuer without CDS? In addition to this, given the high volatility period in the credit market in the last few years and, in particular, after the default of Lehman Brothers on 15 September 2008, we observe the presence of big outliers in the distribution of credit spread in the different combinations of rating, industry and region. After an exhaustive analysis of the results from the different models studied, we have reached the following conclusions. It is clear that hierarchical regression models fit the data much better than those of non-hierarchical regression. Furthermore,we generally prefer the median model (50%-quantile regression) to the mean model (standard OLS regression) due to its robustness when assigning the price to a new credit asset without spread,minimizing the “inversion problem”. Finally, an additional fundamental reason to prefer the median model is the typical "right skewness" distribution of CDS spreads...
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The uncertainty about the future of firms must be modeled and incorporated in the valuation of enterprises outside the explicit period of analysis, i.e., in the continuing or terminal value (TV). There is a multiplicity of factors that influence the TV of firms which are not being considered within current evaluation models. This aspect leads to the incurring of unrecoverable errors, thus leading to values of goodwill or bad will far away from the substantial value of intrinsic assets. As a consequence, the evaluation results will be presented markedly different from market values. There is no consensus in the scientific community about the method of computation of the TV as a forecast in an infinite horizon. The size of the terminal, or non-explicit period, assumed as infinite, is never called into question by scientific literature, or the probability of business bankruptcy. This paper aims to promote a study of the existing literature on the TV, to highlight the fragility of the evaluation models of companies that have been used by the academic community and by financial analysts, and to point out lines for future research to minimize these errors.
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One of the ways the South Carolina State Housing Finance and Development Authority fulfills this mission is through the purchase and servicing of mortgage loans. The 2007 Recession resulted in decreased revenues for the department while higher default, foreclosure and bankruptcy rates increased the department's manpower cost. The agency has since acquired different servicing software which complies with current industry regulations and is once again servicing the loans that it purchases. This project is to see if the department could improve any of their overall processes by using existing technologies and software to better utilize the new servicing system while minimizing manual tasks. This paper explores whether the existing Kofax Document Recognition system could improve this process and reduce overall employee time and effort?
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Esta investigación busca desde la logística inversa, mostrar como un producto tan implementado y desechado por la sociedad, puede generar un nuevo uso, e incluso la reintegración total de sus materias primas a la cadena de suministro, mostrando la estrecha relación que existe entre la logística inversa y la reutilización de productos fuera de uso. Para esto se analizara el manejo actual que tienen las llantas en Bogotá, planteando su flujo y dando a conocer el principal punto de falencia, que es la recolección y los diferentes sitios de acopio de estas. Los neumáticos o llantas son desechados anualmente en Bogotá sin medir las consecuencias ambientales que esto trae consigo, pues las quemas a cielo abierto de estos materiales y su almacenamiento inadecuado generan altos riesgos para su entorno y el medio ambiente. Además, el manejo inapropiado de llantas es una de las principales razones por la cual pasan a ser obsoletas al poco tiempo de uso. El proceso de fabricación de llantas es muy similar al proceso de cualquier producto, pues en resumen este cuenta con la implementación de sus materias primas, proceso de manufactura, una inspección final y como resultado un producto terminado, que al ser vendido muchas compañías se libran de la disposición final de las llantas. Pero ahí radica un punto a favor para la logística inversa, donde esta buscara la manera de darle un nuevo ciclo de vida a este producto, a través del reciclaje y la reutilización. Mediante esta investigación, se busca captar los principales lugares de acopio de llantas usadas en Bogotá, de manera que estos serán nuestros principales puntos de información para el proyecto, que permita plantear y definir de manera clara estrategias y conclusiones cualitativas.
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Las organizaciones y sus entornos son sistemas complejos. Tales sistemas son difíciles de comprender y predecir. Pese a ello, la predicción es una tarea fundamental para la gestión empresarial y para la toma de decisiones que implica siempre un riesgo. Los métodos clásicos de predicción (entre los cuales están: la regresión lineal, la Autoregresive Moving Average y el exponential smoothing) establecen supuestos como la linealidad, la estabilidad para ser matemática y computacionalmente tratables. Por diferentes medios, sin embargo, se han demostrado las limitaciones de tales métodos. Pues bien, en las últimas décadas nuevos métodos de predicción han surgido con el fin de abarcar la complejidad de los sistemas organizacionales y sus entornos, antes que evitarla. Entre ellos, los más promisorios son los métodos de predicción bio-inspirados (ej. redes neuronales, algoritmos genéticos /evolutivos y sistemas inmunes artificiales). Este artículo pretende establecer un estado situacional de las aplicaciones actuales y potenciales de los métodos bio-inspirados de predicción en la administración.
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Based on four samples of Portuguese family-owned firmsdi) 185 young, low-sized family-owned firms; ii) 167 young, high-sized familyowned firms; iii) 301 old, low-sized family-owned firms; and iv) 353 old, high-sized family-owned firms d we show that age and size are fundamental characteristics in family-owned firms’ financing decisions. The multiple empirical evidence obtained allows us to conclude that the financing decisions of young, low-sized family-owned firms are quite close to the assumptions of Pecking Order Theory, whereas those of old, high-sized family-owned firms are quite close to what is forecast by Trade-Off Theory. The lesser information asymmetry associated with greater age, the lesser likelihood of bankruptcy associated with greater size, as well as the lesser concentration of ownership and management consequence of greater age and size, may be especially important in the financing decisions of family-owned firms. In addition, we find that GDP, interest rate and periods of crisis have a greater effect on the debt of young, low-sized family-owned firms than on that of family-owned firms of the remainder research samples.