Influência do risco de incumprimento nos retornos de capital

Sempre foi do interesse das instituições financeiras de crédito determinar o risco de incumprimento associado a uma empresa por forma a avaliar o seu perfil. No entanto, esta informação é útil a todos os stakeholders de uma empresa, já que também estes comprometem uma parte de si ao interagirem com esta. O aumento do número de insolvências nos últimos anos tem reafirmado a necessidade de ampliar e aprofundar a pesquisa sobre o stress financeiro. A identificação dos fatores que influenciam a determinação do preço dos ativos sempre foi do interesse de todos os stakeholders, por forma a antecipar a variação dos retornos e agir em sua conformidade. Nesta dissertação será estudada a influência do risco de incumprimento sobre os retornos de capital, usando como indicador do risco de incumprimento a probabilidade de incumprimento obtida segundo o modelo de opções de Merton (1974). Efetuou-se esta análise durante o período de Fevereiro de 2002 a Dezembro de 2011, utilizando dados de empresas Portuguesas, Espanholas e Gregas. Os resultados evidenciam uma relação negativa do risco de incumprimento com os retornos de capital, que é devida a um efeito momentum e à volatilidade. A par disso, também se demonstra que o tamanho e o book-to-market não são representativos do risco de incumprimento na amostra aqui utilizada, ao contrário do que Fama & French (1992; 1996) afirmavam.

Optimal alarms systems and its application to financial time series

This thesis focuses on the application of optimal alarm systems to non linear time series models. The most common classes of models in the analysis of real-valued and integer-valued time series are described. The construction of optimal alarm systems is covered and its applications explored. Considering models with conditional heteroscedasticity, particular attention is given to the Fractionally Integrated Asymmetric Power ARCH, FIAPARCH(p; d; q) model and an optimal alarm system is implemented, following both classical and Bayesian methodologies. Taking into consideration the particular characteristics of the APARCH(p; q) representation for financial time series, the introduction of a possible counterpart for modelling time series of counts is proposed: the INteger-valued Asymmetric Power ARCH, INAPARCH(p; q). The probabilistic properties of the INAPARCH(1; 1) model are comprehensively studied, the conditional maximum likelihood (ML) estimation method is applied and the asymptotic properties of the conditional ML estimator are obtained. The final part of the work consists on the implementation of an optimal alarm system to the INAPARCH(1; 1) model. An application is presented to real data series.

Hotel Valuation Software, Version 4.0

[Updated August 2016] The Hotel Valuation Software, freely available from Cornell’s Center for Hospitality Research, has been updated to reflect the many changes in the 11th Edition of the Uniform System of Accounts for the Lodging Industry (USALI). Version 4.0 of the Hotel Valuation Software provides numerous enhancements over the original tool from 2011. In addition to a significant increase in functionality and an update to reflect the 11th edition of the USALI, Version 4.0 takes advantage of the power of the latest release of Microsoft Excel®. Note that Version 4.0 works only on a PC running Microsoft Windows, it does not work on a Mac running OS X. Users desiring an OS X compatible version should click here (Labeled as Version 2.5). 酒店评估软件手册和三个程序（点击这里 ) Users desiring a Mandarin version of the Hotel Valuation Software should click here The Hotel Valuation Software remains the only non-proprietary computer software designed specifically to assist in the preparation of market studies, forecasts of income and expense, and valuations for lodging property. The software provides an accurate, consistent, and cost-effective way for hospitality professionals to forecast occupancy, revenues and expenses and to perform hotel valuations. Version 4.0 of the Hotel Valuation Software includes the following upgrades – a complete update to reflect the 11th edition of the USALI – the most significant change to the chart of accounts in a generation, an average daily rate forecasting tool, a much more sophisticated valuation module, and an optional valuation tool useful in periods of limited capital liquidity. Using established methodology, the Hotel Valuation Software is a sophisticated tool for lodging professionals. The tool consists of three separate software programs written as Microsoft Excel files and a software users' guide. The tool is provided through the generosity of HVS and the School of Hotel Administration. The three software modules are: Room Night Analysis and Average Daily Rate: Enables the analyst to evaluate the various competitive factors such as occupancy, average room rate, and market segmentation for competitive hotels in a local market. Calculates the area-wide occupancy and average room rate, as well as the competitive market mix. Produce a forecast of occupancy and average daily rate for existing and proposed hotels in a local market. The program incorporates such factors as competitive occupancies, market segmentation, unaccommodated demand, latent demand, growth of demand, and the relative competitiveness of each property in the local market. The program outputs include ten-year projections of occupancy and average daily rate. Fixed and Variable Revenue and Expense Analysis: The key to any market study and valuation is a supportable forecast of revenues and expenses. Hotel revenue and expenses are comprised of many different components that display certain fixed and variable relationships to each other. This program enables the analyst to input comparable financial operating data and forecast a complete 11-year income and expense statement by defining a small set of inputs: The expected future occupancy levels for the subject hotel Base year operating data for the subject hotel Fixed and variable relationships for revenues and expenses Expected inflation rates for revenues and expenses Hotel Capitalization Software: A discounted cash flow valuation model utilizing the mortgage-equity technique forms the basis for this program. Values are produced using three distinct underwriting criteria: A loan-to-value ratio, in which the size of the mortgage is based on property value. A debt coverage ratio (also known as a debt-service coverage ratio), in which the size of the mortgage is based on property level cash flow, mortgage interest rate, and mortgage amortization. A debt yield, in which the size of the mortgage is based on property level cash flow. By entering the terms of typical lodging financing, along with a forecast of revenue and expense, the program determines the value that provides the stated returns to the mortgage and equity components. The program allows for a variable holding period from four to ten years The program includes an optional model useful during periods of capital market illiquidity that assumes a property refinancing during the holding period

Taxation and Household Financial Decisions: Evidence from the Bush Tax Acts

Thesis (Ph.D.)--University of Washington, 2013

Waiting for Godot? Welfare Attitudes in Portugal Before and After the Financial Crisis

Do attitudes towards the welfare state change in response to economic crises? Addressing this question is sometimes difficult because of the lack of longitudinal data. This article deals with this empirical challenge using survey data from the 2008 European Social Survey and from our own follow-up survey of Spring 2013 to track welfare attitudes at the brink and at the peak of the socio-economic crisis in one of the hardest hit countries: Portugal. The literature on social policy preferences predicts an increased polarization in opinions towards the welfare state between different groups within society – in particular between labour market insiders and outsiders. However the prediction has scarcely been tested empirically. A notoriously dualized country, Portugal provides a critical setting in which to test this hypothesis. The results show attitudinal change and this varies according to labour market vulnerability. However, we observe no polarisation and advance alternative explanations for why this is so.

How can economic and political liberalisation improve financial development in African countries?

The objective of this paper is to study the interactions between Economic liberalisation, Political liberalisation and Financial development in African countries. More specifically, we seek to establish the impact of Economic, Political and institutional openness on financial deepening. The empirical approach will be two-step procedure, first using a difference in difference method to show the various aspect of financial liberalisation on economic and political freedom while the second step will be using panel data techniques from period 1990 to 2005. The estimation results can be summarised as the following, first, Economic and financial liberalisation did account significantly for the financial development performance. While political stability show a positive overall effect on financial development, the association with Political freedom is consistent only after controlling the endogeneity of Political freedom on financial development. This result indicates that the transformation of the political and economic environment has improved the performance of the financial sector.

Financial development and income inequality: evidence from African countries

This paper present empirical evidence on how financial development is related to income distribution in a panel data set covering 22 African countries for the period between 1990 to 2004. A dynamic panel estimation technique (GMM) is employ and the findings indicate that income inequality decrease as economies develop their financial sector, which is consistent with the bulk of theoretical and empirical research. The result also confirm that educational attainment play a significant role in making income distribution more equal. We also find no evidence supporting the Greenwood-Jovanovic hypothesis of an inverted-U- shaped relationship between financial sector development and inequality.

Diversification, size and risk: The case of bank acquisitions of nonbank financial firms

We investigate the risk effects of bank acquisitions of insurance companies and securities firms between 1991 and 2012 using a newly constructed dataset of M&A deals. We examine risk changes before and after deal announcements by decomposing risk into systematic and idiosyncratic components. Subsequently, we investigate the relationship between risk and diversification by modelling the determinants of risks. We find that bank combinations with securities firms yield higher risks than combinations with insurance companies. Bank size is an important and consistent determinant of risk whereas diversification is not. Our results inform the continuing debate on diversification versus functional separation of bank activities.