5 resultados para [JEL:D46] Microeconomics - Market Structure and Pricing - Value Theory

em Digital Commons at Florida International University


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Extreme stock price movements are of great concern to both investors and the entire economy. For investors, a single negative return, or a combination of several smaller returns, can possible wipe out so much capital that the firm or portfolio becomes illiquid or insolvent. If enough investors experience this loss, it could shock the entire economy. An example of such a case is the stock market crash of 1987. Furthermore, there has been a lot of recent interest regarding the increasing volatility of stock prices. ^ This study presents an analysis of extreme stock price movements. The data utilized was the daily returns for the Standard and Poor's 500 index from January 3, 1978 to May 31, 2001. Research questions were analyzed using the statistical models provided by extreme value theory. One of the difficulties in examining stock price data is that there is no consensus regarding the correct shape of the distribution function generating the data. An advantage with extreme value theory is that no detailed knowledge of this distribution function is required to apply the asymptotic theory. We focus on the tail of the distribution. ^ Extreme value theory allows us to estimate a tail index, which we use to derive bounds on the returns for very low probabilities on an excess. Such information is useful in evaluating the volatility of stock prices. There are three possible limit laws for the maximum: Gumbel (thick-tailed), Fréchet (thin-tailed) or Weibull (no tail). Results indicated that extreme returns during the time period studied follow a Fréchet distribution. Thus, this study finds that extreme value analysis is a valuable tool for examining stock price movements and can be more efficient than the usual variance in measuring risk. ^

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Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubblelike deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the nonfundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

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This case study examines the factors that shaped the identity and landscape of a small island-urban-village between the north and south forks of the Middle River and north of an urban area in Broward County, Florida. The purpose of the study is to understand how Wilton Manors was transformed from a “whites only” enclave to the contemporary upscale, diverse, and third gayest city in the U.S. by positing that a dichotomy for urban places exists between their exchange value as seen by Logan and Molotch and the use value produced through everyday activity according to Lefebvre. Qualitative methods were used to gather evidence for reaching conclusions about the relationship among the worldview of residents, the tension between exchange value and use value in the restructuration of the city, and the transformation of Wilton Manors at the end of the 1990s. Semi-structured, in-depth interviews were conducted with 21 contemporary participants. In addition, thirteen taped CDs of selected members of founding families, previously taped in the 1970s, were analyzed using a grounded theory approach. My findings indicate that Wilton Manors’ residents share a common worldview which incorporates social inclusion as a use value, and individual agency in the community. This shared worldview can be traced to selected city pioneers whose civic mindedness helped shape city identity and laid the foundation for future restructuration. Currently, residents’ quality of life reflected in the city’s use value is more significant than exchange value as a primary force in the decisions that are made about the city’s development. With innovative ideas, buildings emulating the new urban mixed-use design, and a reputation as the third gayest city in the United States, Wilton Manors reflects a worldview where residents protect use value as primary over market value in the decisions they make that shape their city but not without contestation.^

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For producers motivated by their new status as self-employed, landowning, capitalist coffee growers, specialty coffee presents an opportunity to proactively change the way they participate in the international market. Now responsible for determining their own path, many producers have jumped at the chance to enhance the value of their product and participate in the new "fair trade" market. But recent trends in the international coffee price have led many producers to wonder why their efforts to produce a certified Fair Trade and organic product are not generating the price advantage they had anticipated. My study incorporates data collected in eighteen months of fieldwork, including more than 45 interviews with coffee producers and fair trade roasters, 90 surveys of coffee growers, and ongoing participant observation to understand how fair trade certification, as both a market system and development program, meets the expectations of the coffee growers. By comparing three coffee cooperatives that have engaged the Fair Trade system to disparate ends, the results of this investigation are three case studies that demonstrate how global processes of certification, commodity trade, market interaction, and development aid effect social and cultural change within communities. This study frames several lessons learned in terms of (1) socioeconomic impacts of fair trade, (2) characteristics associated with positive development encounters, and (3) potential for commodity producers to capture value further along their global value chain. Commodity chain comparisons indicate the Fair Trade certified cooperative receives the highest per-pound price, though these findings are complicated by costs associate with certification and producers' perceptions of an "unjust" system. Fair trade-supported projects are demonstrated as more "successful" in the eyes of recipients, though their attention to detail can just as easily result in "failure". Finally, survey results reveal just how limited is the market knowledge of producers in each cooperative, though fair trade does, in fact, provide a rare opportunity for producers to learn about consumer demand for coffee quality. Though bittersweet, the fair trade experiences described here present a learning opportunity for a wide range of audiences, from the certified to the certifiers to the concerned public and conscientious consumer.

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Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubble-like deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the non-fundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.