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The impact of the intensity of firm's intangible assets on the volatility of their stock pricesFred Tambong, Takoeta January 2008 (has links)
The volatility of share prices is an important variable in most asset pricing models and option pricing formulas.Valuation of volatility of share prices have become a major challenge with the development of the knowledge-driven economy as evidence suggest that not all elements of company wealth are physical in nature. The purpose of this project entitled “The intensity of the firm’s intangible asset on the volatility of their stock price” is to check if the intensity of intangible assets in a firm’s balance sheet affects the volatility of their stock price. A brief overview of intangible assets is also included in this study. An OLS regression was run and the results of the entire data set gives a negative correlation between intensity of intangible assets and volatility of stock prices probably due to the fact that the volatility of the firm share prices are driven by uncertainty and expectation of future growth. An industry-grouping regression was carried out, the results shows that for basic pharmaceuticals there is a positive correlation between the intensity of intangible assets and their price volatility while the other three industry groups produce a negative correlation. The study relies on secondary data of randomly selected fourty (40) publicly traded companies in Europe from four different industry groupings namely: manufacture of basic pharmaceuticals, manufacture of food products and beverages, information technology and manufacture of basic metals.
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Applications of adaptive Fourier decomposition to financial dataShi, Rong January 2012 (has links)
University of Macau / Faculty of Science and Technology / Department of Mathematics
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Decision making framework for managers : Profit by forecasting, costs and price managementAnema, Jens, Fraga, Fernando January 2009 (has links)
Forecasting, cost management and pricing policies are topics which have beenwidely investigated over time. Due to a lack of scientific research about therelationships between each of those subjects, these methods have beeninvestigated in combination with their outcomes. The purpose of this work was todevelop a framework which can be used by managers who want to make adecision in either of the subjects mentioned before. By the use of a qualitative, interpretive research design, a literature review was performed which led to some interesting findings. Generally, it can be said that the methods are not related directly, although the outcomes are linked and can often be used as a criterion for the decision making process for the other methods.
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Housing market and urban growth in China: what are the factors affecting housing prices?Liu, Danyuan January 2012 (has links)
A rapid urbanization process facilitated an enormous expansion of the cities and stimulated the development of the urban housing markets in China. The primary purpose of this thesis is to find factors influencing the urban housing prices. Based on the supply and demand theory, I examine housing prices in 95 cities in 2010 related to population growth, wages, manufacturing employment, human capital, pollution, and housing investment using a cross section data analysis. The empirical results indicate that all those factors are significantly related to the housing prices. I focus on population growth, a proxy for the urbanization process, as the core determinant to analyze housing prices in China. In addition, the results also find that cities located in the eastern area have averagely a higher productivity than the ones located in the mid-west, and the higher housing prices in the eastern area are explained by the higher level of population growth and wages.
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Essays in financial economics and risk managementZou, Lin 15 May 2009 (has links)
No description available.
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Application of price uncertainty quantification models and their impacts on project evaluationsFariyibi, Festus Lekan 30 October 2006 (has links)
This study presents an analysis of several recently published methods for quantifying the
uncertainty in economic evaluations due to uncertainty in future oil prices. Conventional
price forecasting methods used in the industry typically underestimate the range of
uncertainty in oil and gas price forecasts. These forecasts traditionally consider
pessimistic, most-likely, and optimistic cases in an attempt to quantify economic
uncertainty.
The recently developed alternative methods have their unique strengths as well as
weaknesses that may affect their applicability in particular situations. While stochastic
methods can improve the assessment of price uncertainty they can also be tedious to
implement. The inverted hockey stick method is found to be an easily applied alternative
to the stochastic methods. However, the primary basis for validating this method has
been found to be unreliable. In this study, a consistent and reliable validation of
uncertainty estimates predicted by the inverted hockey stick method is presented.
Verifying the reliability of this model will ensure reliable quantification of economic
uncertainty.
Although we cannot eliminate uncertainty from investment evaluations, we can
better quantify the uncertainty by accurately predicting the volatility in future oil and gas
prices. Reliably quantifying economic uncertainty will enable operators to make better
decisions and allocate their capital with increased efficiency.
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Housing prices dynamics in China : A case study of Shanghai, Tianjin and HefeiLing, Chen, Xie, Tao January 2010 (has links)
<p>This paper studies the fundamental determinants of housing prices in three different developedcities in China. The main question addressed is whether fluctuations in the fundamentaldeterminants of housing prices around the world have an impact on housing prices inChina. The theoretical framework shows that housing prices in China are determined to alarge extent by stipulated factors that affect other big cities. They are: income per capita, interestrate, land price, construction cost and population and stock price.We use a linear regression model in our article. The empirical testing shows that these sixdeterminants used in Western countries are also applicable to Chinese real estate market.Most of them succeed in explaining the dynamics of housing prices. However, the resultsof the empirical testing are different among the three cities, so specific economic environmentof the three cities are necessary to understand the results.In our opinion, although some of the determinants fail to explain the fluctuations of housingprices, it is early to say there are bubbles due to the short history of Chinese real estatemarket. However, if policies are not implemented to calm down the overheating market insome first-tier cities, the consequences are hard to identify.</p>
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Essays on the nonlinear modeling of real exchange rates and price differentials /Lo, Ming Chien, January 2000 (has links)
Thesis (Ph. D.)--University of Washington, 2000. / Vita. Includes bibliographical references (leaves 98-101).
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Studies in Chinese price historyWilkinson, Endymion Porter. January 1970 (has links)
Thesis (Ph. D.)--Princeton University, 1970. / eContent provider-neutral record in process. Description based on print version record.
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Cost considerations when purchasing from China /Måttgård, Erik. Håkansson, Marcus. Svensson, Rikard. January 2008 (has links)
Master's thesis. / Format: PDF. Bibl.
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