Thesis (Ph. D.)--University of Washington, 2006. / Vita. Includes bibliographical references (leaves 130-144).

Could the analysts¡¦ forecasting be the important investment decision of the naive investors? This is the significant issue of the study. The study shows the following, in the short run, recommendations have information value; in the long run, forecasting earnings have information value. And electronic industry is the most valuable of all industries in the long run and short run. Although recommendations also have information value in the long run, but the industry returns aren¡¦t consistent. In addition, analysts over predict about the forecasting earnings. Finally, the study also shows the following, forecasting price or recommendation has negative coefficient and statistically significant in large scale company. Because large scale companies are more attentive than small scale companies, and information superiority trader already get the information before analysts¡¦ release. So they can trade the stocks before analysts¡¦ release, naive investors can¡¦t get returns with the analysts¡¦ forecasting.

Fashion and the contemporary environment as a whole, is a complex environment that requires retailers and wholesalers to adapt to the changes that constantly occurring. This adaptation is in a bid to ensure that more profits than loses are realized by the company. For this reason, companies have to use various methods to determine the best ways to improve their products. Companies resolve to introduction of new product to the market but the acceptance of new products to the fashion industry is not an assured factor but rather a gamble. This is mainly because of the industry’s characteristics. The main aim of this thesis is to analyze the methods that may be used to improve the accuracy of new products. The fashion industry has characteristics that may be considered as challenges because for instance, when a product is launched, one has to determine whether it is by a reputable designer or whether it is a trend, and with the fashion industry, trends are mainly turned into such by celebrities who introduce a certain design to the world for adoption. These challenges or characteristics are carefully analyzed and examined with the necessity of the introduction of new products analyzed. Data collection, being the main backbone of this thesis and multiple-case study method, is used to answer the research question as “How can structured analogy method be used to improve the forecast accuracy for the footwear products in the fashion industry “.Samples for case study have been chosen from footwear category. Structured analogy method is used to determine the accuracy of the information gathered from literature review.

published_or_final_version / Statistics / Master / Master of Social Sciences

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This thesis examines the predictive ability of models for forecasting inflation and financial market volatility. Emphasis is put on evaluation of forecasts and the usage of large data sets. Variety of models are used to forecast inflation, including diffusion indices, artificial neural networks, and traditional linear regressions. Financial market volatility is forecast using various GARCH-type and high-frequency based models. High-frequency data are also used to obtain ex-post estimates of volatility, which is then used to evaluate forecasts. All forecast are evaluated using recently proposed techniques that can account for data snooping bias, nested, and nonlinear models.

No description available.

Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves 49-53). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves 49-53). Also available on the Internet.