High-quality short-term forecasts of wind speed are vital to making wind power a more reliable energy source. Gneiting et al. (2006) have introduced a model for the average wind speed two hours ahead based on both spatial and temporal information. The forecasts produced by this model are accurate, and subject to accuracy, the predictive distribution is sharp, i.e., highly concentrated around its center. However, this model is split into nonunique regimes based on the wind direction at an off-site location. This work both generalizes and improves upon this model by treating wind direction as a circular variable and including it in the model. It is robust in many experiments, such as predicting at new locations. This is compared with the more common approach of modeling wind speeds and directions in the Cartesian space and use a skew-t distribution for the errors. The quality of the predictions from all of these models can be more realistically assessed with a loss measure that depends upon the power curve relating wind speed to power output. This proposed loss measure yields more insight into the true value of each model's predictions. One method of evaluating time series forecasts, such as wind speed forecasts, is to test the null hypothesis of no difference in the accuracy of two competing sets of forecasts. Diebold and Mariano (1995) proposed a test in this setting that has been extended and widely applied. It allows the researcher to specify a wide variety of loss functions, and the forecast errors can be non-Gaussian, nonzero mean, serially correlated, and contemporaneously correlated. In this work, a similar unconditional test of forecast accuracy for spatial data is proposed. The forecast errors are no longer potentially serially correlated but spatially correlated. Simulations will illustrate the properties of this test, and an example with daily average wind speeds measured at over 100 locations in Oklahoma will demonstrate its use. This test is compared with a wavelet-based method introduced by Shen et al. (2002) in which the presence of a spatial signal at each location in the dataset is tested.

Accurate determination of the tropopause is important for applications such as dynamical analysis and forecasting, radiative transfer calculations, and the diagnosis of chemical transport in the atmosphere. In this paper, we examine how well the extratropical tropopause is determined in the National Centers for Environmental Prediction (NCEP) high-resolution Global Forecast System (GFS) model analysis over the continental United States using high-resolution aircraft and radiosonde data. The GFS analyses and sounding data compare well, with r.m.s. differences of approximately 600m, which is comparable to the vertical resolution of the model. The GFS tropopause is a good proxy in areas without in situ observations, but near the subtropical jet the GFS analysis often mistakenly identifies the secondary rather than the primary tropopause. We also explore an alternative method to identify the tropopause by fitting a smoothed step-function to the static stability profile. This new approach provides a measure of the depth of the troposphere-stratosphere transition and facilitates the study of the dynamical behavior of the tropopause region. In particular, using the transition depth, we are able to identify the statistical behavior of temperature in profiles with deep or shallow tropopause transition layers.

This paper studies the quality of mandatory financial forecasts which announced by Taiwan lists and OTC companies ¡]hereinafter called ¡§the companies¡¨¡^. Does outside financial analyst can offer the public users more useful financial forecast than the companies¡H What¡¦s the difference on precision between financial forecasts issued from the companies and outside analysts¡HBesides, this paper also tests if the companies would perform earnings management for meeting the public expectation. The empirical results indicate that for public investors, the mandatory financial forecasts issued by the companies didn¡¦t show better accrual precision than the financial forecast issued by outside analysts. There wasn¡¦t any significant difference on degree of differential between financial forecast prepared by outside analysts and the companies. The risk for using both of the financial forecasts are the same. That means the investors can rely on none of the companies and outside analysts¡¦ forecasts to do investment decision. And the companies performed earning management to meet the consistent expectation of earning arose from market which can avoid the bad result when the actual financial report differ from forecast. In summary, the mandatory financial forecasts in Taiwan can not offer timely useful information to investors. Most of them only increase the preparation cost and control cost. Some of the companies even use them as the tool to collect money from public for personal welfare. We recommend the government authorities to consider the benefit of voluntary financial forecast system in UAS when they are reviewing the mandatory financial forecast system. The voluntary financial forecast system may solve the problems of incomplete predictability of financial forecast and asymmetry of information, finally increase the usefulness of financial forecasts.

For the last half century, financial forecast has been undergone numerous discussions among AICPA, authority agencies, and experts. Generally, scholars and researchers use either general financial ratios or cash-flow ratios or both to predict if enterprises will bankrupt or fail. As a matter of fact, there is no concurrent conclusion as for which one is better. Some believe that the former is more accurate than the latter, while some claim that it is the vice versa. Still, some assert that it is more accurate to use them both, and some even believe that cash forecast sheet is the most effective. Usually, it has been some time since financial forecast was submitted to board of directors for approval prior to fiscal year, and moreover, some unpredictable information might occur during fiscal year given the information asymmetry. Therefore, the most important is to find funds gap as early as possible so as to respond quickly. From the perspective of an enterprise insider, the researcher regards financial forecast as a necessary tool for professional managers to cope with current information, utilizing models conforming to business¡¦s needs to introduce various situations for predicting possible funds gap in the near future. The information for the development of financial forecasts is highly complex, involving all departments in a company. Using Excel as a tool and a case company as a basis, this study developed a model which could be used for predictions with several single variables or multi-variables. Also, the validity of this model was verified by virtue of about twenty times of simulation tests. II Given that this case company, which engages in basic metal industry, is small and middle business, the model developed based on this case can only be used by similar businesses. This model which employs a MIS approach and is developed based on financial and accounting procedures often acquires inputs of enormous amount of time, manpower, and resources to become an effective tool for planning and management. Due to the limited resources and talented, it takes researcher a lot of efforts to successfully establish this model. Moreover, the operation of this model which uses Excel as a tool is not as easy as that of other systems written with programming languages. Finally, because the case company is small and middle business which has possible crises different from that of large companies, the prediction the model can make is limited. This study is mainly concerned with a system model which is not able to be shown in the text. Therefore, it is suggested to first recognize the framework of this study, and then pair with related tables to better understand this study.

<p>Businesses use forecasts in order to gather information concerning phenomena that are important to them. Since electronic commerce has grown in importance for businesses, forecasts concerning this area are becoming increasingly important. The work presented in this report aims at gathering information useful when improving forecast quality. In practice the report presents a collection of forecasts, concerning business-to-consumer electronic commerce, and a collection of factors affecting electronic commerce forecast outcomes. A categorisation and evaluation of the collected forecasts is performed, this evaluation is done by comparing the forecasts in the categories to the actual outcomes. Problems that occur during the evaluation process, such as problems with forecast wording and scope, are described, and suggestions of how to avoid these problems are provided. Structured methods to categorise and evaluate the forecasts are also presented. Finally, the outcome from the evaluation is analysed using the compiled factors and indications are given of how to use the results in order to improve future forecasting.</p>

Application Service Providing (ASP) is a recently emerged software delivery model under which an Application Service Provider hosts, manages and delivers software as a service to customers via the Internet or a private network. The ASP model offers benefits from cost savings, specialized expertise, a faster time to market, and a reduced risk due to a lower capital investment. However, customers who are unsure about the value of ASP services and their demands may be reluctant to commit to ASP contracts. Many are also concerned with security, performance and loss of control. The underlying research identifies determinants influencing adoption intentions in the early technology stages of ASP within electric utilities. The tested model includes characteristics of the innovation, such as relative (dis-) advantage of ASP, as well as characteristics of the environment, the adopting company and importance of social influence. After a broad qualitative study a quantitative web-based survey generated 158 data sets. Multiple linear regression and logistic regression were used to analyze the relationships between multi-item constructs. Results show that the perceived improved service provided by ASP, the perceived calculation accuracy of load and price forecasts, the perceived benefits from the provision of external competence, and the trust in the reliability of the service provider as well as the image gains a company has by using ASP are significant factors influencing the formation of attitude for or against ASP solutions. Furthermore, the dependent variable in this research-the intention to adopt-is determined by the behavioral intention to try, the attitude towards ASP, the perceived cost of ASP, and the company size of the adopting firm. All constructs rank high in measurement quality and the overall model reveals food for an improved conception of ASP as well as managerial practices. Results also indicate the lapse of the diffusion curve of ASP in the electric utilities industry in Austria and Germany. (author's abstract)

Βασικός στόχος αυτής τη εργασίας είναι να παρουσιάσει με λεπτομερή και τεκμηριωμένο τρόπο την διαδικασία που ακολουθεί ένας χρηματοοικονομικός αναλυτής έτσι ώστε να προσδιορίσει την σχέση απόδοσης και κινδύνου κάποιων χρεογράφων με απώτερο σκοπό να καταλήξει σε ορθολογικά συμπεράσματα που μπορούν να τον οδηγήσουν στις βέλτιστες αποφάσεις. Οι αποφάσεις αυτές θα αφορούν την δόμηση ενός βέλτιστου χαρτοφυλακίου χρεογράφων το οποίο για δεδομένο κίνδυνο θα αποφέρει την μέγιστη αναμενόμενη απόδοση η αντίστροφα με δεδομένη την επιθυμητή απόδοση θα ενέχει το ελάχιστο ρίσκο . Η χρήση του απλού γραμμικού υποδείγματος , της μεθόδου ελαχίστων τετραγώνων (OLS) , των διαστημάτων εμπιστοσύνης και της στατιστικής συμπερασματολογίας είναι κάποιες από τις μεθόδους που θα εφαρμόσουμε για να προσδιορίσουμε με ακρίβεια την σχέση απόδοσης και κινδύνου χρεογράφων των οποίων έχουμε επιλέξει για τις εφαρμογές μας . Οι διαταράξεις των υποθέσεων του απλού γραμμικού υποδείγματος , όπως η αυτοσυσχέτιση και η ετεροσκεδαστικότητα είναι επίσης αντικείμενα προς εξέταση ,παράγοντες οι οποίοι αλλοιώνουν τις οικονομετρικές εκτιμήσεις της μεθόδου των ελαχίστων τετραγώνων και πρέπει να άρονται από τον αναλυτή, έτσι ώστε να καταλήγει η ανάλυση και η έρευνα των χρηματοοικονομικών εφαρμογών σε αξιόπιστες εκτιμήσεις . Ιδίως στην αντιμετώπιση της ετεροσκεδαστικότητας, η χρήση των μοντέλων ARCH/GARCH, μπορεί να μας οδηγήσει στο ζητούμενο ,το οποίο είναι η εκτίμηση και η πρόβλεψη του μελλοντικού κινδύνου αγοράς ενός χρεογράφου όπως η μετοχή . / The basic goal of this paper is to present in an analytic and trustworthy way, the process that a financial analyst follows so as to evaluate the relationship between risk and return of stocks. This kind of process will lead the analyst to rational conclusions and effective decisions which concern the structure of optimal portfolios of stocks. The optimal portfolio structure offers a maximum expected return if the risk is known and vice versa (minimum risk when the return is known).The use of the simple linear model, least square method and statistical conclusion function, are some of the methods that will help us to measure the relationship between risk and return of the stocks that we have chose to use for our applications. The disorders of the simple linear model assumptions, autocorrelation and heteroscedasticity, are parameters who are making the estimations of least squares method spurious. The analyst has to detect these problems so as the analysis and research of financial applications to conclude rational and effective estimations.Specialy in coping with heteroscedasticity, the use of ARCH/GARCH models can lead us to the objective, the estimation and forecast of the future risk of the stock being studied.

Meteorologists working for the state government in Ceara, Northeast Brazil claim that the kinds of forecasts they can currently produce are not useful for subsistence farmers, who lack resources to act on forecast-based decisions. I argue that scientific predictions do have meaning and consequences in rural communities. Official forecasts inform policies that affect farmers; therefore, farmers hold government accountable for predictions, even if they do not directly influence the farmers' own decision-making.My investigation takes the discussion beyond notions of "usefulness" as I demonstrate that prediction is more than a projection of the future based on the past and the present. In prediction discourse, people create understandings of their place in the social world, including their relationship to government. While government discourse constructs farmers as "non-users" and removes its responsibility to them, traditional "rain prophets" motivate farmers with optimistically-framed predictions and encourage autonomy from government.Prediction is a meaning-making endeavor&amp;#8213;not just of ecological and atmospheric processes, but of who people are and how they live. Drawing on linguistic theories of performance and performativity, I analyze strategic language use within a cultural models framework, taking into account the emotions and motivations associated with experiences of living in a particular environment (both natural and material), and how these are crucial to understanding the meanings of prediction. Through prediction, people test the limits of their knowledge, judgement and faith. My examination of the connections between cultural models of 'prediction' and 'lie' explains how traditional predictions motivate farmers and build solidarity in opposition to exclusionary systems of government and science.This research furthers our understanding of how locally marginalized groups engage with government and the knowledge systems it privileges. After tracing constructions of "rain prophet" and "scientist" in the media, I show how rain prophets both oppose themselves to and align themselves with media representations of science, as they establish their authority and challenge meteorologists' expertise. Meanwhile, meteorologists work to authenticate science as the only legitimate authority. Thus, in prediction performances, meteorologists and rain prophets position themselves within local and global discourses about science and traditional knowledge.

The forecast control for the heating system tries to maintain the buildings’ indoor temperature at a desired level, by using technical building characteristics, data on its mode of operation, data on the building location and meteorological parameters. By forecasting the conditions of the building and calculating the free energies (solar radiation and internal heat generation) it is possible to know the amount of additional heat that should be supplied to the building every moment, avoiding heat surpluses or deficits. By applying the theory developed by Roger Taesler to buildings 92911 and 92917 placed in Sandvik AB, it is seen that if the desired temperature was 21ºC it would be possible to save a 16.3% of energy, 15518 SEK/year, and that the payback time for the installation of such a system is 3 years. Other efficiency measures as changing the ventilation schedule or installing a heat exchanger are also discussed in the present report.

This Master’s Degree is a futurology that aims to analyse how the Chinese stock market might develop for a period of ten years, i.e. between the years 2005-2015. Since the future never with certainty can be predicted, scenarios will be presented displaying other possible outcomes. Naturally these scenarios are built upon given assumptions which otherwise could be as many as one’s imagination allows. The thought is to present the results as an index so the reader easily can see the possible development and scenarios. The methodology used to collect necessary data is through the classical Delphi method, by which one interviews the selected “experts” that have the knowledge needed of the Chinese stock market. Moreover, the authors have collected further information through literature, the Internet, articles, reports and other written sources needed to continue further investigation. Further, the forecast was measured by two steps. The first step was to calculate the value at the start point. The second step was to create tow types of scenarios, added as a frame of the forecast outcomes. To transform the analysis and the scenarios in to a numerical index, a technical measurement of Quasi Monte Carlo Simulation was applied. The theories applied when creating the index is foremost the Arbitrage Pricing Theory, which makes it possibly to measure several factors at the same time, including macro economical effects on the stock market. According to the result, four factors were identified as the driving forces when finding a balanced economy, which affect the stock exchange: the investment structure; equal standard of living; the state of the financial sector and increased transparency. The result also indicates that the Chinese stock market will not stay in parity with the earlier development. A healthier and more efficient market will occur, due to structural reforms and the expected improvements within the financial sector including the stock exchange. It is with great anticipation that the authors await a bright and successful future for the Chinese stock market. A new direction has been settled, although there are many difficult challenges.