none

none

On a basis of the development of credit risk models, this study aims to help managers of financial institutions understand the development of the models so as to develop their own model that will provide objective and reasonable references for banks to decide the lending rate. Furthermore, this study used "Utilization of Long-Term Funding" as the object and studied individual cases of approved loans. By using risk neutral evaluation method to study the difference between the lending rate of loans and the risk-free interest rate of public bonds, to extract implied probabilities of default and required credit risk premiums form actual market data on interest rates. These credit risk premiums of model were used to be compared with the actual markups of banks and the results are as follows: 1.Most values stated in credit risk premium are lower than the actual markups for banks usually consider the burden of other capital costs and the factor of liquidity premium when they set the rating for markup. 2.After a loan is approved, the assumed recovery rate upon application will adjust according to the market value of the collateral. When the recovery rate decreases, the expected loss rate on the loan will gradually increase. Moreover, the higher the assumed recovery rate, the larger the corrected expected loss rate after the loan is approved. 3.In recent years, the non-performing rate for banks in Taiwan has reached a record high. Even though banks face less credit risks when they make long-term loans in "Utilization of Long-Term Funding", the probability of default has increased in recent years, which has contributed to the increase of expected loss rate on the long-term loan. In sum, banks still face credits risks that should not be ignored when they manage long-term loans. Thus, it is necessary to improve loan review to enhance the quality of loans and to increase the efficiency of utilization of long-term fund.

Farmers will supply the raw ingredients for the emerging cellulosic ethanol industry. The long-term relationship between a farmer and a processing firm is expected to be contractual. A processing firm has an incentive to sign long-term contracts to ensure a cost-efficient level of raw ingredient supply. However, farmers generally prefer to operate with either no contract or a short-term contract in order to maintain options for adjustments in future acreage allocations due to changes in relative prices. Of interest in this research is to understand the incentives of farmers and calculating the efficient level of the “inflexibility premium”, which a processing firm must provide to a farmer when a long term contract is signed. A stochastic dynamic programming model is solved and with the help of Microsoft Excel numerically evaluated to illustrate the marginal inflexibility premium is increasing with contract length and the level of price variability, and is decreasing with the size of acreage adjustment costs.

Farmers will supply the raw ingredients for the emerging cellulosic ethanol industry. The long-term relationship between a farmer and a processing firm is expected to be contractual. A processing firm has an incentive to sign long-term contracts to ensure a cost-efficient level of raw ingredient supply. However, farmers generally prefer to operate with either no contract or a short-term contract in order to maintain options for adjustments in future acreage allocations due to changes in relative prices. Of interest in this research is to understand the incentives of farmers and calculating the efficient level of the “inflexibility premium”, which a processing firm must provide to a farmer when a long term contract is signed. A stochastic dynamic programming model is solved and with the help of Microsoft Excel numerically evaluated to illustrate the marginal inflexibility premium is increasing with contract length and the level of price variability, and is decreasing with the size of acreage adjustment costs.

Zugl.: Hamburg, Univ., Diss., 2009

Farmers will supply the raw ingredients for the emerging cellulosic ethanol industry. The long-term relationship between a farmer and a processing firm is expected to be contractual. A processing firm has an incentive to sign long-term contracts to ensure a cost-efficient level of raw ingredient supply. However, farmers generally prefer to operate with either no contract or a short-term contract in order to maintain options for adjustments in future acreage allocations due to changes in relative prices. Of interest in this research is to understand the incentives of farmers and calculating the efficient level of the “inflexibility premium”, which a processing firm must provide to a farmer when a long term contract is signed. A stochastic dynamic programming model is solved and with the help of Microsoft Excel numerically evaluated to illustrate the marginal inflexibility premium is increasing with contract length and the level of price variability, and is decreasing with the size of acreage adjustment costs. / Land and Food Systems, Faculty of / Graduate

The aim of this thesis is to determine the marketing strategies used in the luxury industry differentiate luxury from premium and research the motivations values and beliefs of luxury consumers. Research was done on five main luxury activities: fashion and leather goods jewelry and watches and perfumes and cosmetics spirits and automobiles. The literature part has been structured in a way to present the evolution of the luxury industry and its development over the course of years. The section then goes onto clearly defining what luxury is and stating the different industries found in the luxury market. The secondary research identified the use of five different marketing strategies in the luxury industry. A survey was then conducted in order to understand consumer s motivations for purchasing luxury goods and their beliefs values and view s on luxury products. Results showed that the majority of survey participants agreed there existed a difference between premium and luxury and that quality and craftsmanship are the biggest motivators for purchasing luxury goods. The survey was carried out worldwide but there was a greater focus on consumers from North America and Europe. Survey participants were categorized into three target groups: management students managers with high disposable income and regular luxury consumers. Based on the findings the author made recommendations for new entrants into the luxury industry according to each marketing strategy.

<div>In models of stock returns where investors with extrapolative beliefs on future stocks (e.g., Barberis and Shleifer (2003)), price momentum and the value premium both arise naturally. The key insight from these models is that, the strength and timing of these cross- sectional return anomalies will be conditional on the degree of extrapolative bias. More specifically, higher (lower) degree of over-extrapolation leading to stronger value premium (momentum).</div><div> Using the time-series variation in the degree of over-extrapolation documented in Cassella and Gulen (2018), I first directly test the hypothesis that both value and momentum stem from over-extrapolation in financial markets. I find that the average momentum return is 1.00% (0.10%) per month when the degree of over-extrapolation is low (high), whereas the average value premium is 0.51% (1.29%) per month following low (high) levels of over- extrapolation.</div><div> Furthermore, I extend the model in Barberis and Shleifer (2003) by having both within- equity extrapolators and across asset-class extrapolator. The extension is based on the idea that when extrapolators move capital in and out of the equity market, they disproportionately buy growth stocks in good times and sell value stocks in bad times. The model predicts that the cross-sectional value premium should be stronger following states of large market- wide over- or undervaluation due to additional extrapolative demand to buy or sell. This prediction is tested empirically and I find strong support for it. The value premium is 3.42% per month following market-wide undervaluation and 1.70% per month following market overvaluation. In the remainder 60% to 80% of the sample, when the market is neither significantly over or under-valued, there is no significant value premium in a monthly horizon and the value premium is only 0.54% per month in an annual horizon. I provide some suggestive evidence regarding portfolio return dynamics, investor expectation errors and fund flows that supports the extrapolative demand channel. Overall, this work examines more closely at the effect of extrapolative beliefs on the cross-section of asset prices and offers some support for extrapolation-based asset-pricing theories.</div><div><br></div>

Size premium puzzle, also known as the size effect, is one of the most studied anomalies in asset pricing literature. It refers to the observation that, on average, smaller firms have higher risk-adjusted returns than larger firms over a long period of time. While many studies have debated the existence of the size effect, the question of why it exists has become a subject of heated debate. Thus, this dissertation aims to examine if previously overlooked factors can, at least partially, explain the size effect. Essay 1 examines if merger and acquisition activity can explain a part of the size effect. I find that merger and acquisition activity explain a part of the size effect. The size effect is found to be stronger during merger waves but is not consistent across industries. Further, the size effect tends to be stronger when acquisition activity is concentrated among smaller firms. Essay 2 investigates if expectational errors explain the higher return of small firms. Several empirical studies show that stocks that investors underestimate yield higher returns. However, I do not find support for the underestimation explanation in explaining the higher returns of small firms. Instead, I find that investors are overly optimistic about the growth of small firms. In essay 3, I examine if the size effect can be explained by perceived risk. Using the implied cost of capital (ICC) as a measure of perceived risk, I find that small firms are perceived to be riskier by the market, and the perceived risk explains the size effect.