This dissertation analyzes key features of credit derivatives market, basic risks of the products and trends the market has experienced for several years since its inception, discusses regulatory issues of the market with regard to the Basel II treatment and key reasons for investors using credit derivatives. Dissertation also examines whether and how credit derivatives affected current financial turmoil, analyzes credit derivatives losses of selected institutions on the financial markets and compares them with total losses of these institutions. The main result of the work is that there was no substantial effect of the credit derivatives market on the current financial crisis. Dissertation also examines whether there is any connection between U.S. banks credit derivatives trades and their capital adequacy ratio. According to the analysis, there is no evidence for credit derivatives to essentially affect capital adequacy ratio of U.S. banks. A potential explanation for the higher values of U.S. banks' capital adequacy ratio may be that there are sophisticated risk management strategies banks have been implicating for many years.

This thesis deals with the current financial crisis and its solutions. In the first part of this work are analyzed the main causes underlying the emergence of contemporary global crisies. Described are also the methods and financial products through which the crisies spread from the United States of America to the rest of the world, mentioned are main negative impacts of the crisis in the Czech Republic and anti-crisis measures taken by the czech government in context of crisis. In the second part of the work proposed recommendations that could reduce the likelihood of further crises in the future or measures, which could help to solve the current economic crisis. The conclusion summarizes the results of the analysis and answer the question if it is possible to avoid a financial crisis and the resulting economic recession or will come again and again?

A topical issue in financial economics is the development of appropriate stochastic dynamic models for banking items and behavior. The issue here is to fulfil the need to generalize the more traditional discrete-time models of banking activity to a Levy process setting. In this thesis, under the assumption that the loan market is imperfectly competitive, we investigate the evolution of banking items such as bank assets (cash, bonds, shares, Treasuries, reserves, loans and intangible assets), liabilities (demand deposits) and bank capital (bank equity, subordinate debt and loan loss reserves). Here we consider the influence of macroeconomic factors and profitability as well as its indicators return on assets (ROA) and return on equity (ROE). As far as bank assets are concerned, we note that loan pricing models usually reflect the financial funding cost, risk premium to compensate for the risk of default by the borrower, a premium reflecting market power exercised by the bank and the sensitivity of the cost of capital raised to changes in loans extended. On the other hand, loan losses can be associated with an offsetting expense called the loan loss provision (LLP), which is charged against Nett profit. This offset will reduce reported income but has no impact on taxes, although when the assets are finally written off, a tax-deductible expense is created. An important factor influencing loan loss provisioning is regulation and supervision. Measures of capital adequacy are generally calculated using the book values of assets and equity. The provisioning of loans and their associated write-offs will cause a decline in these capital adequacy measures, and may precipitate increased regulation by bank authorities. Greater level of regulation generally entail additional costs for the bank. Currently, this regulation mainly takes the form of the Basel II Capital Accord that has been implemented on the worldwide basis since 2008. It is clear that bank profitability is a major indicator of financial crises for households, companies and financial institutions. An example of this from the 2007-2008 subprime mortgage crisis (SMC) is the U.S. bank, Wachovia Corp., who reported a big loss as from the first quarter of 2007 and eventually was bought by the world's largest bank, Citigroup, on 29 September 2008. A further example from the SMC is that both the failure of the Lehman Brothers investment bank and the acquisition in September 2008 of Merrill Lynch and Bear Stearns by Bank of America and JP Morgan Chase, respectively, were preceded by a decrease in profitability and an increase in the price of loans and loan losses. The subprime mortgage crisis is characterized by contracted liquidity in the global credit markets and banking system. The level of liquidity in the banking sector affects the ability of banks to meet commitments as they become due without incurring substantial losses from liquidating less liquid assets. Liquidity, therefore, provides the defensive cash or near-cash resources to cover banks' liability. An undervaluation of real risk in the subprime market is cascading, rippling and ultimately severely adversely affecting the world economy. The downturn in the U.S. housing market, risky lending and borrowing practices, and excessive individual and corporate debt levels have caused multiple adverse effects tumbled as the US housing market slumped. Banks worldwide are hoarding cash and showing a growing reluctance to lend, driving rates that institutions charge to each other on loans to record highs. Also, global money markets are inoperative, forcing increased injections of cash from central banks. The crisis has passed through various stages, exposing pervasive weaknesses in the global financial system and regulatory framework. The stochastic dynamics of the aforementioned banking items assist in formulating a maximization problem that involves endogenous variables such as profit consumption, the value of the bank's investment in loans and provisions for loan losses as control variants. In particular, we demonstrate that the bank is able to maximize its expected utility of discounted profit consumption over a random time interval, [t,r], and terminal profit at time r. Here the term profit consumption refers to the consumption of the bank's profits by dividend payments on equity and interest and principal payments on subordinate debt. The associated Hamilton-Jacobi-Bellman (HJB) equation has a smooth solution when the optimal controls are computed by means of power, logarithmic and exponential utility functions. This enables us to make a direct comparison between the economic properties of the solutions for different choices of the utility function. In keeping with the main theme of this thesis, we simulate the financial indices ROE and ROA that are two measures of bank profitability. We further discuss optimization with power utility where we show the convergence of the Markov Chain Approximation Method (MCAM) and the impact of varying the model parameters in the form of loan loss severity, P, and loan loss frequency, <f>. We investigate the connections between the banking models and Basel II capital accord as well as the current subprime mortgage crises. As a way of conclusion, we provide remarks about the main issues discussed in the thesis and speculate about future research directions. The contents of this thesis is based on 3 peer-reviewed journal articles (see [105], [106] and [107]) and 1 peer-reviewed conference proceedings paper (see [104]). In addition, the paper [108] is currently being prepared for submission to an accredited journal. / Thesis (Ph.D. (Applied Mathematics))--North-West University, Potchefstroom Campus, 2009.

A topical issue in financial economics is the development of appropriate stochastic dynamic models for banking items and behavior. The issue here is to fulfil the need to generalize the more traditional discrete-time models of banking activity to a Levy process setting. In this thesis, under the assumption that the loan market is imperfectly competitive, we investigate the evolution of banking items such as bank assets (cash, bonds, shares, Treasuries, reserves, loans and intangible assets), liabilities (demand deposits) and bank capital (bank equity, subordinate debt and loan loss reserves). Here we consider the influence of macroeconomic factors and profitability as well as its indicators return on assets (ROA) and return on equity (ROE). As far as bank assets are concerned, we note that loan pricing models usually reflect the financial funding cost, risk premium to compensate for the risk of default by the borrower, a premium reflecting market power exercised by the bank and the sensitivity of the cost of capital raised to changes in loans extended. On the other hand, loan losses can be associated with an offsetting expense called the loan loss provision (LLP), which is charged against Nett profit. This offset will reduce reported income but has no impact on taxes, although when the assets are finally written off, a tax-deductible expense is created. An important factor influencing loan loss provisioning is regulation and supervision. Measures of capital adequacy are generally calculated using the book values of assets and equity. The provisioning of loans and their associated write-offs will cause a decline in these capital adequacy measures, and may precipitate increased regulation by bank authorities. Greater level of regulation generally entail additional costs for the bank. Currently, this regulation mainly takes the form of the Basel II Capital Accord that has been implemented on the worldwide basis since 2008. It is clear that bank profitability is a major indicator of financial crises for households, companies and financial institutions. An example of this from the 2007-2008 subprime mortgage crisis (SMC) is the U.S. bank, Wachovia Corp., who reported a big loss as from the first quarter of 2007 and eventually was bought by the world's largest bank, Citigroup, on 29 September 2008. A further example from the SMC is that both the failure of the Lehman Brothers investment bank and the acquisition in September 2008 of Merrill Lynch and Bear Stearns by Bank of America and JP Morgan Chase, respectively, were preceded by a decrease in profitability and an increase in the price of loans and loan losses. The subprime mortgage crisis is characterized by contracted liquidity in the global credit markets and banking system. The level of liquidity in the banking sector affects the ability of banks to meet commitments as they become due without incurring substantial losses from liquidating less liquid assets. Liquidity, therefore, provides the defensive cash or near-cash resources to cover banks' liability. An undervaluation of real risk in the subprime market is cascading, rippling and ultimately severely adversely affecting the world economy. The downturn in the U.S. housing market, risky lending and borrowing practices, and excessive individual and corporate debt levels have caused multiple adverse effects tumbled as the US housing market slumped. Banks worldwide are hoarding cash and showing a growing reluctance to lend, driving rates that institutions charge to each other on loans to record highs. Also, global money markets are inoperative, forcing increased injections of cash from central banks. The crisis has passed through various stages, exposing pervasive weaknesses in the global financial system and regulatory framework. The stochastic dynamics of the aforementioned banking items assist in formulating a maximization problem that involves endogenous variables such as profit consumption, the value of the bank's investment in loans and provisions for loan losses as control variants. In particular, we demonstrate that the bank is able to maximize its expected utility of discounted profit consumption over a random time interval, [t,r], and terminal profit at time r. Here the term profit consumption refers to the consumption of the bank's profits by dividend payments on equity and interest and principal payments on subordinate debt. The associated Hamilton-Jacobi-Bellman (HJB) equation has a smooth solution when the optimal controls are computed by means of power, logarithmic and exponential utility functions. This enables us to make a direct comparison between the economic properties of the solutions for different choices of the utility function. In keeping with the main theme of this thesis, we simulate the financial indices ROE and ROA that are two measures of bank profitability. We further discuss optimization with power utility where we show the convergence of the Markov Chain Approximation Method (MCAM) and the impact of varying the model parameters in the form of loan loss severity, P, and loan loss frequency, <f>. We investigate the connections between the banking models and Basel II capital accord as well as the current subprime mortgage crises. As a way of conclusion, we provide remarks about the main issues discussed in the thesis and speculate about future research directions. The contents of this thesis is based on 3 peer-reviewed journal articles (see [105], [106] and [107]) and 1 peer-reviewed conference proceedings paper (see [104]). In addition, the paper [108] is currently being prepared for submission to an accredited journal. / Thesis (Ph.D. (Applied Mathematics))--North-West University, Potchefstroom Campus, 2009.

Thesis (B.A.)--Haverford College, Dept. of Economics, 2009. / Includes bibliographical references.

The goal of my thesis is to analyze anti-crisis measures of the hotel Westside located in the United States of America. The first chapter explains theoretical approaches to crisis and its impacts. It depicts crisis management approaches to successful crisis managing. In the next part of my thesis I look closer at the U.S. subprime mortgage crisis. I tried to show details of subprime mortgage crisis spreading into the financial sector and also its impacts on tourism industry. The last chapter of my thesis compares theoretical approaches with the real steps in the crisis. After analyzing the real hotel behavior, I can conclude the hotel managed the crisis successfully. Right identification of the crisis, choosing effective price strategy and additional financial resource utilization contributed to smooth managing of the crisis. There were mistakes made by human resources department. They made the impact of the crisis on the hotel bigger but their realizing taught the management of the hotel how to behave in the future.

Despite being governed by several laws aimed at preventing racial inequality in access to housing and credit resources, the mortgage lending market remains a contributor to racial and place-based disparities in homeownership rates, wealth, and access to high-quality community resources. Scholarship has identified persistent disparities in mortgage loan approval rates and subprime lending between white borrowers and those from other racial and ethnic groups, and between white neighborhoods and neighborhoods with high levels of non-white residents. Against this backdrop, the mortgage lending industry is undergoing rapid, technology-driven changes in risk assessment and application processing. Traditional borrower risk-assessment methods including face-to-face discussions between lenders and applicants and the prominent use of FICO credit scores have been replaced or supplemented by automated decision-making tools at a new generation of institutions known as fintech lenders. Little is known about the relationship between lenders using these new tools and the racial and spatial disparities that have long defined the wider mortgage market. Given the well-documented history of discrimination in lending along with findings of technology-driven racial inequality in other economic sectors, fintech lending’s potential for racial discrimination warrants increased scrutiny. This dissertation compares the lending outcomes of traditional and fintech mortgage lenders in the United States depending on applicant and neighborhood racial characteristics. Using data from the Home Mortgage Disclosure Act, an original dataset classifying lenders as fintech or traditional, and an array of complimentary administrative data sources, it provides an assessment of the salience of race and place in the rates at which mortgage loans from each lender type are approved and assigned subprime terms. Results from a series of regression-based quantitative analyses suggest fintech mortgage lenders, like traditional mortgage lenders, approve and deny loans and distribute subprime credit at disparate rates to white borrowers and neighborhoods relative to nonwhite borrowers and neighborhoods. Findings suggest that policymakers and regulators must increase their oversight of fintech lenders, ensuring that further advances in lending technology do not concretize longstanding racial and spatial disparities.

The subprime mortgage crisis and the resultant inflationary monetary policy in the USA have left the Chinese economy subject to four risks in particular. First, China's exports to the USA might continue to decline. Second, in the medium term, the higher US inflation rate will lead to a weak dollar, which will negatively affect China's exports. Third, in the long term, when the US Federal Reserve decreases money supply to control inflation, the US economy might enter another recession, hurting China's exports further. Fourth, China's foreign exchange reserve assets might suffer heavy losses when the US inflation rate rises. Conventional foreign exchange investment strategies are insufficient for dealing with these four risks. Investment by China in the major US banks is suggested in the present paper. This strategy would mitigate if not eliminate all four risks. China could gain considerable financial returns on investments with only moderate risk.

Over the last decade, the United States had experienced a boom and bust in the subprime mortgage market. The ups and downs of the subprime mortgage market became a primary factor triggering the most severe global economic recession since the Great Depression. The dissertation contributes to the literature by inquiring whether the subprime lending has exacerbated social inequity between subprime neighborhoods and other neighborhoods, through analyzing the subprime mortgage market in the Philadelphia MSA from 2000 through 2010, and focusing on two research questions: (1) the spatial distribution of subprime mortgages across census tracts; (2) the relationship between subprime intensities and housing price variations across zip-code areas. As the dissertation's study area expands from an urban to a MSA, spatial heterogeneity merits attention in this relative huge area. As a result, this dissertation not only employs a global, Ordinary Least Squares (OLS) model, but also a local, Geographically Weighted Regression (GWR) model to examine spatial variations across different neighborhoods. For the first research question, the dissertation finds: (1) a higher concentration of higher-priced mortgage for purchase and refinance in tracts with higher proportion of African-American and Hispanic residents, lower median household incomes, higher-unemployment rates, lower self-employment rates, and higher capitalization rates, after controlling for other variables; (2) the association between higher-priced mortgages and explanatory variables varies across census tracts. Because the dynamics of neighborhood subprime originations are heterogamous, the association between subprime mortgage origination and socioeconomic characteristics may be stronger in some neighborhoods than other neighborhoods. For the second research question, the dissertation finds: (1) subprime mortgage shares have a significant negative association with housing price appreciations during the housing boom period (2001-2006); (2) subprime mortgage shares have a significant positive association with housing price depreciations during the housing bust period (2006-2010); and (3) the association between housing price variations and explanatory variables differs across geographic submarkets within the Philadelphia region. The result confirms that areas where more residents obtained subprime mortgages have suffered more severely than other from the housing market's ups and downs over the last decade. The empirical results can draw broad policy implications. The primary implication is that it is time for the federal government to rethink its homeownership policy. Increased homeownership levels arising from the expansion of subprime mortgages are not sustainable, and subprime lending has exacerbated social inequity between subprime neighborhoods and other neighborhoods. The second implication is that the government needs to enforce the fair lending laws, because the cluster of subprime mortgage origination reflects the unequal opportunities of prime mortgage accessibility across different neighborhoods. The third implication is that the government needs to promote place-based policy making. As the GWR demonstrates, the dynamics of the mortgage market and housing market are uneven across different neighborhoods. Therefore, place-based making can increase the efficiency of public policy. These implications based on the dissertation's empirical results are helpful for designing more efficient, effective, and sustainable housing policies of the United States. / Urban Studies

Thesis (MBA)--Stellenbosch University, 2012. / The use of leading indicators provides a valuable method to predict changes in macro-economic variables. However, the accuracy of the various models using leading indicators is a topic of constant debate. This study aimed to identify whether leading indicator models predicting residential house price changes performed as well during the recent global financial crisis (fourth quarter 2007 to second quarter 2012) as during the period directly before the crisis. Several potential drivers of the South African property market were identified with the help of previous studies on this topic. Following that, a quantitative analysis was done and single leading indicator models were built using regression analysis to evaluate the importance of each independent variable. This information was used to create a composite leading index for the South African housing market. The accuracy of these models were then compared to predict the changes in house prices during the period preceding the recent global economic crisis.It was found that the ability of these leading indicator models to predict house price changes during the recent global economic crisis decreased significantly.