No description available.

No description available.

No description available.

No description available.

This research investigated the effects of Scientifically Estimated Environmental Risks (SEERs) and perceived risks of floods, hurricanes, and hazardous material releases, and hazard mitigation measures with other locational and neighborhood amenities on housing prices. This study also tested the relationship between demographic characteristics and SEERs as well as demographic characteristics and environmental risk perceptions. The relationships among these different types of variables were examined by means of statistical analyses such as correlational analyses, ANOVA, MANOVA, and hedonic price regression analyses. Major findings of this research are as follows: There were no statistically significant relationships between most of the demographic characteristics (age, sex, household size, marital status, tenure at the present home) and SEERs of the two natural hazards (a flood and a hurricane). By contrast, SEER of hazardous materials was correlated with all demographic characteristics. There were little differences in risk perceptions of natural and technological hazards across demographic groups. Specifically, the respondents' risk perceptions of both natural and technological hazards did not differ by age, household size, and marital status. By contrast, educational level, gender (male = 1), and median household income were negatively related to perceived risk of the natural hazards, whereas educational attainment and gender were negatively related to perceived risk of hazardous material releases. SEERs of floods and hurricanes were positively related to respondents' perception of property damage, but not related to injury or heath problems from those natural hazards. SEER of hazardous materials was related to all three categories of risk perception of a hazardous material release. Neither the SEERs of natural hazards nor risk perceptions of these hazards had impacts on housing prices. However, the SEER of hazardous material releases and risk perceptions of this hazard were significant housing price determinants. None of the variables representing household hazard mitigation measures contributed to the explanation of housing prices.

Stock prices are dynamic and changing frequently whenever the financial markets are opened. Many people aspire to know where prices are likely to be at future times. One of the basic problems, connected with stock valuation is to create an appropriate model of stock prices dynamics. This paper deals with the stock valuation models, such as binomial, additive, multiplicative, Brownian motion and etc. These models appeals to hypothesis, declaring that returns of stock follows by normal distribution and stock prices by lognormal one. The aim of this work is to test these hypothesis. The research of this paper discloses the basic tendency, announcing that stock is not applicable for a real adaptability of methods in Lithuanian companies because the returns of stock do not follow by the normal distribution. Disputed situation is opposite in companies of the USA. The returns of stocks are calculated by the following ways. They are numbered in the area of MS Excel. In order to review the conditions of normality, the SAS software was chosen. Finally, Delphi 10 programming language was selected for realization of the binomial tree.

Produsente van landboukommoditeite, veral in ontwikkelende lande, word blootgestel aan prysrisiko's. Markte vir landboukommoditeite in Suid-Afrika, soos in die res van die wêreld, is die afgelope aantal jare gekenmerk deur prosesse van deregulering. Die bemarkingsrade wat aanvanklik verantwoordelik was vir die bemarking van landbouprodukte, het ontbind en produsente van landbouprodukte moes nuwe metodes vind om hulle produkte te bemark. Een van die metodes wat gebruik word, is termynkontrakte. Witmielies en geelmielies is die twee landboukommoditeite wat in die grootste hoeveelhede geproduseer word in Suid-Afrika. Witmielies en geelmielies word as twee afsonderlike kommoditeite verhandel op die termynbeurs. Witmielies word hoofsaaklik aangewend vir menslike verbruik en geelmielies vir dierevoer. Hierdie studie fokus hoofsaaklik op witmielies. Die prys van mielies word beïnvloed deur veranderinge in die vraag daarna en aanbod daarvan. Faktore wat die vraag en aanbod van mielies beïnvloed is, onder andere, oesskattings, reënval, die wisselkoers en die pryse van mielies op die buitelandse mark, veral die markte in die VSA. In Suid-Afrika vorm die invoerpariteit en uitvoerpariteit 'n band waarbinne die prys van mielies varieer. Die doel van hierdie studie is om 'n regressievergelyking te konstrueer ten einde prys van die witmielietermynkontrakte te verklaar. Die regressie-analise word deur middel van 'n foutherstellende model met outoregressiewe foutterme behartig. Die regressie-analise slaag daarin om die prys van witmielietermynkontrakte te verklaar. / Thesis (M.Com. (Economics))--North-West University, Potchefstroom Campus, 2004.

We present a tree algorithm, called the willow tree, for financial derivative pricing. The setup of the tree uses a fixed number of spatial nodes at each time step. The transition probabilities are determine by solving linear programming problems. The willow tree method is radically superior in numerical performance when compared to the binomial tree method.

In 2003, the Centre for Operations Excellence at the University of British Columbia's Sauder School of Business worked on a project for a company in the resort industry. The project was an initial attempt to develop and implement a pricing management practice for the ski lift ticket business of that company. Our main deliverable was the development of an Excel-based tool with a user-friendly interface that could help the company in their budgeting of the ski lift ticket business. After completing the project, we did some further investigation relative to pricing management techniques that could be applied to this sort of business, namely a congestible service industry. In this thesis we argue that a revenue management system could bring substantial benefits if implemented in this industry. We also identify the requirements and main features of a revenue management system applied to congestible service industries. Although revenue management is a very popular system in fields such as the airline, hotel and car rental industry, none of them can be classified as congestible industries. The ski lift ticket industry and similar industries possess one characteristic that differentiates them from the ones previously mentioned, there is no fixed capacity. This is the reason why we considered important to study the application of revenue management in congestible service industries.

This dissertation analyzes the complex relationships between language, immigration, and labor and housing market outcomes. First, I model the urban labor market as segmented by language barriers. The prediction of this segmentation theory is confirmed by Canadian Census data, which allow me to identify a worker's labor market segment by her work language. Second, I explore whether the housing market reflects people's willingness to pay for higher quality social-ethnic interactions. By combining housing transaction data and Census information, I am able to test such a relationship with positive results. Finally, I ask what properties housing price series have if some people have better knowledge of the future immigration/migration flows to a city. Under this setup, the price series become serially correlated and the price volatility varies over time. The model also explains the long-standing price-volume relationship in housing transaction data.