M.Comm. / The object of this study is to critically appraise the fundamental models, technical methods and statistical techniques that constitute the bulk of exchange rate forecasting methodology. Specifically, can any single approach, or combination of techniques, predict or explain the volatile currency movements characterising exchange rate behaviour in the modern international currency market? International currency markets are indeed complex in nature, and the layperson may be excused for not grasping the distinction between the fundamental, technical and statistical techniques described in the hypothesis. It is vital, however, for the comprehension of this study that the distinction between these approaches be explained, and the logic underlying their individual methodologies examined. It may prima facie seem that this study is based on a contradiction. Surely if one wants to predict an economic variable of any kind, one should refer to the economic theory upon which it is based as the starting point of an analysis. Consequently, if the objective is to forecast the future value of a currency, surely there are a great many economic texts that deal with this very question in voluminous detail. Why, then, should yet another paper be written when so much literature already exists? The answer lies not so much in the scope as in the purpose of this work. The aim of this study can be paraphrased. as follows: to provide a comprehensive and critical examination of the various methods of exchange rate forecasting and to explain why economic theory is still deficient in this important area. The question of whether or not short-term' exchange rates are able to be forecast at all will also be critically examined. This study will attempt to elucidate that while fundamental currency speculation models do provide a certain degree of guidance to currency-traders in their daily prognostications, these models are, in the context of modern capital markets, inadequate. At best, these models will be shown as trackers of long-term exchange rate trends, and not always accurate ones at that. Further, it will be demonstrated that the modern trading floors are characterised (if not defined) by split-second price changes, where the long-term'' can mean a minute, and he who hesitates is lost. It is in this setting that traders must do battle for profit, and where the fundamental models that seem to serve so well in textbooks are anachronisms. The study then shifts its focus to a subset of technical analysis known as charting, the objective being to fill the void which arises due to the fundamental models' inadequacies in the short-term. The charting techniques utilised in this study deviate from their fundamental counterparts in that they attempt to explain future exchangerate trends in terms of past performance. That is, exogenous changes are factored out of the forecasting equation, to give way to a methodology based on trendextrapolation. The performance of these models, especially as they pertain to the medium- and short-term., will then be determined. Finally, in an attempt to supplement the use of charts as a forecasting tool, statistical analysis will be considered. The model utilised in this section will be a rudimentary auto-regressive process. Its simplicity, however, belies its consequence. That is, considering that no ubiquitous statistical model dominates exchange rate theory, it is reasonable to assume that an auto-regressive process, such as the one contributed by this study, will not be subordinate to other, more complex, quantitative offerings. Thus this study attempts to provide the necessary insights in order to perspicaciously 1 It should be noted here that the terms "short-term" and "short run" are interchangeable. For the purposes of consistency, only the former term shall be employed throughout this study. 2 The terms "long-term" and "long run" are also interchangeable. For the purposes of consistency, only the former term shall be employed throughout this study. ascertain the proficiency of statistical analysis as an accurate forecaster of exchange rate fluctuations. All of the models and methods examined in this study adopt a pragmatic acid-test. That is to say, if the predictions made as a result of adherence to the models do not comply accurately and consistently with real findings, then the models themselves should be revised. This revision can be in terms of the time-frame to which the model pertains, the application of the model, or the model itself. It must, however, be stressed that a model whose very raison d'etre lies in its ability to predict exchange rate movements must be able to do so without qualifications or exceptions. The methodology adopted in analysing the models themselves is therefore positive as opposed to normative. Thus, even in the "organised chaos" of the modern exchange rate markets, the application of the models should yield satisfactory results. In other words, despite the unprecedented volumes, speed and volatility of the currencies that are traded in the modern arena, the models themselves should still be able to achieve their purpose - to forecast the extent and direction of changes in the par value of a currency. The next logical question is: what is meant by the "organised chaos", and specifically why should this influence the predictive ability of the fundamental, technical and statistical methods of exchange rate forecasting? The answer to this can be introduced as follows. On an almost daily basis, currency traders move an excess of one trillion dollars throughout the world. Adding to the gravity of this somewhat overwhelming statistic is that most of these are intercomputer transactions occurring instantaneously via inter-bank wire-transfers. In fact, the volume of currency traded is so great that if one were to sum the trading of all the Saudi oil, American wheat, European aircraft and Japanese cars, the monetary result would seem pithy in comparison (Millman, 1995:xxi). It is, however, not only the sheer volumes of currencies traded that characterise the international money markets. It is perhaps more importantly the unanticipated and unparalleled volatility of the markets themselves which provides the greatest quandary for those who conform to 'traditional' methods of exchange rate determination. It is all too common, in fact, for currency prices to change on a minute-to-minute or even second-to-second basis. Exchange rates are thus in a constant state of flux. The significant though infrequent changes of past years have been terminally disposed of. The inception of the microcomputer and the floating exchange rate system currently dominating the greater world economy has irrevocably altered what was considered a flawed order. It is this very metamorphosis which will be examined in detail, specifically how fundamental models have assumed a differing purpose to those used by modern speculators, hedgers and arbitrageurs in their specific fields of application. Thus it will be shown how the changing paradigm of the world economy and consequently the currency trading floors themselves necessitate neoteric predictive powers, that is, the power to forecast currency changes not in terms of years, months or even weeks, but rather in terms of days, minutes and seconds. The object of this thesis will therefore be to show that a definite dichotomy has developed between the exchange rate models espoused in economic textbooks and the techniques upon which the de facto day-to-day buying and selling of currencies depend. The efficacy of this study consequently hinges on one decisive question - is there truly a consistent and precise method of forecasting exchange rates?

The purpose of this research is to investigate current company business process from sales forecasting perspective and provide potential improvements of how to deal with unstable market demand and increase overall precision of forecasting. The problem which company face is an unstable market demand and not enough precision in sales forecasting process. Therefore the research questions are:  How current forecasting process can be improved?  What methods, can be implemented in order to increase the precision of forecasting? Study can be described as an action research using an abductive approach supported by combination of quantitative and qualitative analysis practices. In order to achieve high degree of reliability the study was based on verified scientific literature and data collected from the case company while collaborating with company’s COO. Research exposed the current forecasting process of the case company. Different forecasting methods were chosen according to the existing circumstances and analyzed in order to figure out which could be implemented in order to increase forecasting precision and forecasting as a whole. Simple exponential smoothing showed the most promising accuracy results, which were measured by applying MAD, MSE and MAPE measurement techniques. Moreover, trend line analysis was applied as well, as a supplementary method. For the reason that the case company presents new products to the market limited amount of historical data was available. Therefore simple exponential smoothing technique did not show accurate results as desired. However, suggested methods can be applied for testing and learning purposes, supported by currently applied qualitative methods.

M.Ing. (Electrical and Electronic Engineering Science) / Scientific workflows (SWFs) and artificial neural networks (ANNs) have attracted the attention of researchers in many fields and have been used to solve a variety of problems. Examples of these are (a) the use of scientific workflows for the sensor web in the hydrology domain and (b), the use of ANNs for the prediction of a number of water resource variables such as rainfall, flow, water level and various other water quality variables. ANNs have proved to be a powerful tool for prediction when compared with statistical methods. The aims of this research are to develop ANNs that act as predictive models for water resources and to deploy these models as predictive tools in a scientific workflow environment. While there are guidelines in the literature relating to the factors affecting network performance, there is no standard approach that is universally accepted for determining the optimum architecture of a neural network for a given problem. The parameters of a neural network and for the learning algorithm have a major effect on the performance of the neural network. We consider various recurrent and feed-forward neural network architectures for predicting changes in the water levels of dams. We explore various' hidden layer dimensions in learning the characteristics of the training data using the back propagation learning algorithm. Trained networks are deployed as predictive model in a scientific workflows environment called VisTrails. ': We review and discuss the use of SWFs and ANNs in the hydrology domain with emphasis on the development of neural network architecture that will give the best predictions for water resources. A number of architectures are employed to examine the best accurate predictive network for historical rainfall data. The findings of training experiments are promising in terms of the use of ANNs as a water resources predictive tool. Experimental results showed how the architecture of a neural network impacts on its predictive performance. This study shows that the number of hidden nodes is important factor for the improvement of the quality of the predictions.

n the electrical power grid, the power load is not constant but continuouslychanging. This depends on many different factors, among which the habits of theconsumers, the yearly seasons and the hour of the day. The continuous change inenergy consumption requires the power grid to be flexible. If the energy provided bygenerators is lower than the demand, this is usually compensated by using renewablepower sources or stored energy until the power generators have adapted to the newdemand. However, if buffers are depleted the output may not meet the demandedpower and could cause power outages. The currently adopted practice in the indus-try is based on configuring the grid depending on some expected power draw. Thisanalysis is usually performed at a high level and provide only some basic load aggre-gate as an output. In this thesis, we aim at investigating techniques that are able topredict the behaviour of loads with fine-grained precision. These techniques couldbe used as predictors to dynamically adapt the grid at run time. We have investigatedthe field of time series forecasting and evaluated and compared different techniquesusing a real data set of the load of the Swedish power grid recorded hourly throughyears. In particular, we have compared the traditional ARIMA models to a neuralnetwork and a long short-term memory (LSTM) model to see which of these tech-niques had the lowest forecasting error in our scenario. Our results show that theLSTM model outperformed the other tested models with an average error of 6,1%.

The problem of this study is to predict how basic design will be taught in the year 2000 in the United States of America according to the perceptions of design educators who were polled using a Delphi exercise. Basic design is an introductory course in design disciplines covering fundamental principles, components, and applications of design. This study has a twofold purpose. The first is to predict how basic design will be taught in the year 2000 to allow design educators to better prepare for the future. The second is to provide a basis for further research that might address specific areas in the future of teaching design.

A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophy. July 2014. / South Africa’s climate is highly variable, implying that the national agricultural sector should make provision to have early warning services in place in order to reduce the risks of disasters. More than 70% of natural disasters worldwide are caused by weather and climate or weather and climate related hazards. Reliable Seasonal Climate Forecasting (SCF) for South Africa would have the potential to be of great benefit to users in addressing disaster risk reduction. A disaster is a serious disruption of the functioning of a community or a society, causing widespread human, material, economic or environmental losses, which exceed the ability of the affected community or society to cope when using their own resources. The negative impacts on agricultural production in South Africa due to natural disasters including disasters due to increasing climate variability and climate change are critical to the sector. The hypothesis assumed in the study is the improved early warning service and better SCF dissemination lead to more effective and better decision making for subsequent disaster risk reduction in the agricultural sector. The most important aspect of knowledge management in early warning operations is that of distributing the most useful service to the target group that needs it at the right time. This will not only ensure maximum performance of the entity responsible for issuing the early warnings, but will also ensure the maximum benefit to the target group. South Africa is becoming increasingly vulnerable to natural disasters that are afflicted by localised incidents of seasonal droughts, floods and flash floods that have devastating impacts on agriculture and food security. Such disasters might affect agricultural production decisions, as well as agricultural productivity. Planting dates and plant selection are decisions that depend on reliable and accurate meteorological and climatological knowledge and services for agriculture. Early warning services that could be used to facilitate informed decision making includes advisories on iv future soil moisture conditions in order to determine estimated planting times, on future grazing capacity, on future water availability and on forecasts of the following season’s weather and climate, whenever that is possible. The involvement of government structures, obviously, is also critical in immediate responses and long term interventions. The importance of creating awareness, of offering training workshops on climate knowledge and SCF, and of creating effective early warning services dissemination channels is realized by government. This is essential in order to put effective early warning services in place as a disaster-risk coping tool. Early warning services, however, can only be successful if the end-users are aware of what early warning systems, structures and technologies are in place, and if they are willing that those issuing the early warning services become involved in the decision-making process. Integrated disaster-risk reduction initiatives in government programmes, effective dissemination structures, natural resource-management projects and communityparticipation programmes are only a few examples of actions that will contribute to the development of effective early warning services, and the subsequent response to and adoption of the advices/services strategies by the people most affected. The effective distribution of the most useful early warning services to the end-user, who needs it at the right time through the best governing structures, may significantly improve decision making in the agricultural, food security and other water-sensitive sectors. Developed disaster-risk policies for extension and farmers as well as other disaster prone sectors should encourage self-reliance and the sustainable use of natural resources, and will reduce the need for government intervention. The SCF producers (e.g. the South African Weather Service (SAWS)) have issued new knowledge to intermediaries for some years now, and it is important to determine whether this knowledge has been used in services, and if so whether these services were applied effectively in coping with disaster-risks and in disaster v reduction initiatives and programmes. This study for that reason also intends to do an evaluation of the knowledge communication processes between forecasters, and intermediaries at national and provincial government levels. It therefore, aims to assess and evaluate the current knowledge communication structures within the national agricultural sector, seeking to improve disaster-risk reduction through effective early warning services. A boundary organisation is an organization which crosses the boundary between science, politics and end-users as they draw on the interests and knowledge of agencies on both sides to facilitate evidence base and socially beneficial policies and programmes. Reducing uncertainty in SCF is potentially of enormous economic value especially to the rural communities. The potential for climate science to deliver reduction in total SCF uncertainty is associated entirely with the contributions from internal variability and model uncertainty. The understanding of the limitations of the SCFs as a result of uncertainties is very important for decision making and to end-users during planning. Disappointing, however, is that several studies have shown a fairly narrow group of potential users actually receive SCFs, with an even a smaller number that makes use of these forecasts In meeting the objectives of the study the methodology to be followed is based on knowledge communication. For that reason two types of questionnaires were drafted. Open and closed questionnaires comprehensively review the knowledge, understanding, interpretation of SCFs and in early warning services distribution channels. These questionnaires were administered among the SCF producers and intermediaries and results analysed. Lastly the availability of useful SCFs knowledge has important implications for agricultural production and food security. Reliable and accurate climate service, as one of the elements of early warning services, will be discussed since they may be used to improve agricultural practices such as crop diversification, time of planting vi and changes in cultivation practices. It was clear from the conclusions of the study that critical elements of early warning services need to receive focused attention such as the SCF knowledge feedback programme should be improved by both seasonal climate producers and intermediaries, together with established structures through which reliable, accurate and timely early warning services can be disseminated. Also the relevant dissemination channels of SCFs are critical to the success of effective implementation of early warning services including the educating and training of farming communities. The boundary organisation and early warning structures are important in effective implementation of risk reduction measures within the agricultural sector and thus need to be prioritised. Enhancing the understandability and interpretability of SCF knowledge by intermediaries will assist in improving action needed to respond to SCFs. Multiple media used by both SCF producers and intermediaries in disseminating of SCFs should be accessible by all users and end-users. The Government should ensure that farming communities are educated, trained and well equipped to respond to risks from natural hazards.

Data was provided by researchers of the Einstein Aging Study (EAS) of the Albert Einstein College of Medicine, Yeshiva University whom statistically analyzed data from the Bronx Aging Study cohort, concluding that participation in cognitive leisure activities and one physical activity, dancing, were associated with a reduced risk of dementia [1]. We explore data from a second (the EAS) cohort, utilizing Cox Proportional-Hazards and extended Cox regression [13]. Cognitive leisure activities in general, and particularly doing crossword puzzles, reading books, watching television, and emailing are associated with a reduced risk of dementia. Doing aerobics, learning computer programming, babysitting, dancing, jogging singing, and weight training are associated with an increased risk of dementia. Participation in cognitive leisure activities in general, and reading books in particular, remains highly significant even after adjustment for well-known risk factors [14] such as: age, cognitive status, depression, medical illnesses, gender, ethnicity, education and economic status. / by Carrie Stevens. / Thesis (M.S.)--Florida Atlantic University, 2011. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2011. Mode of access: World Wide Web.

by Wong Yiu Fai, James. / Bibliography: leaves 61-62 / Thesis (M.Ph.)--Chinese University of Hong Kong, 1984

by Li, Man-kong, Vincent, Yee, Yat-pui, Yvonne. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1990. / Bibliography: leaves 92-94. / Library's copy:Disk for circulation (3.5 in.) / TABLE OF CONTENTS / ABSTRACT --- p.ii / TABLE OF CONTENTS --- p.iii / LIST OF TABLES --- p.v / ACKNOWLEDGEMENTS --- p.vi / CHAPTER / Chapter I. --- INTRODUCTION --- p.1 / Importance of Earnings Forecast --- p.1 / Previous Research Findings --- p.3 / Objective --- p.5 / Chapter II. --- AN OVERVIEW OF EARNING FORECASTING --- p.6 / Methods of Forecasting --- p.6 / Financial Analyst's Model --- p.7 / Time-series Model --- p.9 / Common Belief Regarding Forecast Superiority --- p.10 / Chapter III. --- RESEARCH DESIGN AND METHOD OF ANALYSIS --- p.12 / General Framework --- p.12 / Choice of Companies and Time Period --- p.13 / Data Preparation --- p.16 / Actual Earning Data --- p.16 / Forecast Data by Financial Analyst --- p.17 / Adjustment of Data --- p.18 / Time Series Model Data --- p.20 / Generation of Time-series Data --- p.20 / The Time-series Model --- p.20 / Data Analysis --- p.25 / Definition of Forecast Error --- p.25 / Comparison of Forecast Accuracy --- p.26 / Grouping of Companies --- p.26 / Method of Comparison --- p.27 / Chapter IV. --- RESULTS OF ANALYSIS AND IMPLICATIONS --- p.30 / General Data Manipulation --- p.30 / Data For Analysis --- p.30 / Input Data --- p.30 / Computed Forecast Errors --- p.31 / Comparison of Forecast Accuracy --- p.31 / First Time Friedman Test Results --- p.31 / Full Cross-Sectional Dependence --- p.32 / Sectorial Dependence --- p.34 / Cross-Sectional Independence --- p.37 / Wilcoxon Signed Rank Test and Second Time Friedman Test --- p.41 / Full Cross-Sectional Dependence. --- p.42 / Sectorial Dependence --- p.43 / Cross-Sectional Independence --- p.44 / Chapter V. --- CONCLUSION AND DISCUSSION --- p.45 / Findings From Results of Study --- p.45 / Limitation of Study --- p.48 / Cost of Forecast --- p.48 / Sample Size and Length of Study Period --- p.48 / Limited Past Earning Data --- p.49 / Accounting Income Manipulation --- p.50 / Suggested Further Study --- p.50 / APPENDIX A --- p.52 / APPENDIX B --- p.53 / APPENDIX C --- p.56 / BIBLIOGRAPHY --- p.92

Cheng Yuen Chung Armstrong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves 146-150). / Acknowledgements --- p.i / Abstract --- p.ii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- South China Orography --- p.2 / Chapter 1.2 --- Winter Monsoon Surges in Southern China --- p.3 / Chapter 1.3 --- Forecasts on the Northerly Surges and Effects on Local Weather --- p.5 / Chapter 1.4 --- Motivations and Objectives --- p.6 / Chapter 2 --- The Numerical Model --- p.8 / Chapter 2.1 --- Model Domain and Grid Structure --- p.10 / Chapter 2.1.1 --- Model domain --- p.10 / Chapter 2.1.2 --- Grid structure --- p.11 / Chapter 2.2 --- Governing Equations --- p.11 / Chapter 2.3 --- Finite Differencing Schemes and Lateral Boundaries --- p.14 / Chapter 2.3.1 --- Spatial differencing scheme --- p.15 / Chapter 2.3.2 --- Time integration scheme --- p.16 / Chapter 2.3.3 --- Choice of time step --- p.17 / Chapter 2.3.4 --- Lateral boundary conditions --- p.20 / Chapter 2.4 --- Development of Unevenly Spaced Vertical Levels --- p.20 / Chapter 2.4.1 --- Differencing scheme in vertical direction --- p.22 / Chapter 2.4.2 --- Integration of the hydrostatic equation --- p.26 / Chapter 2.4.3 --- Consideration of consistency in vertical and horizontal resolution --- p.27 / Chapter 2.5 --- Boundary Layer Physics --- p.30 / Chapter 2.5.1 --- Basic theory --- p.31 / Chapter 2.5.2 --- Turbulence closure --- p.33 / Chapter 2.5.3 --- Budget equation for turbulent kinetic energy --- p.36 / Chapter 2.5.4 --- Static and dynamic stability --- p.38 / Chapter 2.5.5 --- The logorithmic wind profile --- p.40 / Chapter 2.5.6 --- Bulk aerodynamics --- p.42 / Chapter 2.5.7 --- Boundary layer parameterization schemes of the model --- p.44 / Chapter 2.6 --- Parameterization of Precipitations --- p.48 / Chapter 3 --- Numerical Experiments --- p.53 / Chapter 3.1 --- Simulations From the Original Version --- p.54 / Chapter 3.2 --- Simulations From the Unevenly Spaced Version --- p.67 / Chapter 3.2.1 --- 10unevenly spaced levels simulation --- p.67 / Chapter 3.2.2 --- 17unevenly spaced levels simulation with enhanced PBL resolution --- p.71 / Chapter 3.3 --- Simulations With the Modified Boundary Layer Parameterization Schemes --- p.73 / Chapter 4 --- Case Studies of Northerly Cold Surges --- p.77 / Chapter 4.1 --- Lag-correlation Analysis --- p.78 / Chapter 4.2 --- Case Study I --- p.80 / Chapter 4.2.1 --- General descriptions --- p.81 / Chapter 4.2.2 --- Forecasts in ROHK --- p.84 / Chapter 4.2.3 --- 500hPa vorticity --- p.84 / Chapter 4.2.4 --- Numerical simulations --- p.87 / Chapter 4.3 --- Case Study II --- p.90 / Chapter 4.3.1 --- General descriptions --- p.90 / Chapter 4.3.2 --- Potential temperature advection --- p.90 / Chapter 5 --- A Forecast Index for Northerly Cold Surges --- p.99 / Chapter 5.1 --- The Internal Froude Number --- p.100 / Chapter 5.2 --- Case Investigations of a Critical Internal Froude Number over Nan Ling Ranges --- p.102 / Chapter 5.2.1 --- Case study I --- p.103 / Chapter 5.2.2 --- Case study II --- p.104 / Chapter 5.2.3 --- Case study on other events --- p.105 / Chapter 6 --- Conclusion --- p.112 / Appendices --- p.115 / Chapter A --- Computational Dispersion of Shallow Water Equation in f-Plane --- p.115 / Chapter B --- Rossby Radius in a Continuously Stratified Fluid --- p.119 / Chapter C --- Boussinesq Approximation of Navier-Stokes Equation --- p.123 / Chapter D --- Depth of the Neutral Boundary Layer --- p.125 / Chapter E --- Lag-correlation Analysis --- p.128 / Chapter F --- Fortran Source Code of the Numerical Model --- p.131 / Bibliography --- p.146