Dissertations / Theses: 'Business forecasting'

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Haensly, Paul J. "The Application of Statistical Classification to Business Failure Prediction." Thesis, University of North Texas, 1994. https://digital.library.unt.edu/ark:/67531/metadc278187/.

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Bankruptcy is a costly event. Holders of publicly traded securities can rely on security prices to reflect their risk. Other stakeholders have no such mechanism. Hence, methods for accurately forecasting bankruptcy would be valuable to them. A large body of literature has arisen on bankruptcy forecasting with statistical classification since Beaver (1967) and Altman (1968). Reported total error rates typically are 10%-20%, suggesting that these models reveal information which otherwise is unavailable and has value after financial data is released. This conflicts with evidence on market efficiency which indicates that securities markets adjust rapidly and actually anticipate announcements of financial data. Efforts to resolve this conflict with event study methodology have run afoul of market model specification difficulties. A different approach is taken here. Most extant criticism of research design in this literature concerns inferential techniques but not sampling design. This paper attempts to resolve major sampling design issues. The most important conclusion concerns the usual choice of the individual firm as the sampling unit. While this choice is logically inconsistent with how a forecaster observes financial data over time, no evidence of bias could be found. In this paper, prediction performance is evaluated in terms of expected loss. Most authors calculate total error rates, which fail to reflect documented asymmetries in misclassification costs and prior probabilities. Expected loss overcomes this weakness and also offers a formal means to evaluate forecasts from the perspective of stakeholders other than investors. This study shows that cost of misclassifying bankruptcy must be at least an order of magnitude greater than cost of misclassifying nonbankruptcy before discriminant analysis methods have value. This conclusion follows from both sampling experiments on historical financial data and Monte Carlo experiments on simulated data. However, the Monte Carlo experiments reveal that as the cost ratio increases, robustness of linear discriminant rules improves; performance appears to depend more on the cost ratio than form of the distributions.

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DICKHUT, LENA. "BUSINESS CASE DEVELOPMENT : CATEGORIZATION AND CHALLENGES." Thesis, KTH, Nationalekonomi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-199203.

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Every new product launching industrial company faces the difficulties of forecasting future success or failure of a new product before launch. Before launch it is common to develop a business case in order to estimate future quantities and set prices. In the present paper the challenges of developing a standardized business case tool for a large industrial construction and mining company are presented. Few academic studies have been conducted on the challenges and complexities of developing business cases. The research question under which this study is done is: What are the challenges associated with developing an effective standardized business case tool for a large industrial construction and mining company? Due to the different subject areas of the business case for new product launch, the challenges are categorized by topics developed by the researcher in the course of this project: process and team, data gathering and validation, quantity forecast and price forecast. The main challenges found in these categories by the researcher are: finding and motivating experts for the project of developing a standardized business case, gathering and selecting all data necessary without including redundant data, ensuring that different potential new products can be forecasted and designing the price forecast to be profit-maximizing. Solutions to these challenges are provided in the context of a case company by using methods suggested by the academic literature and the evaluation of expert interviews inside the case company

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Koottatep, Pakawkul, and Jinqian Li. "Promotional forecasting in the grocery retail business." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/36142.

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Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2006.
Includes bibliographical references (leaves 84-85).
Predicting customer demand in the highly competitive grocery retail business has become extremely difficult, especially for promotional items. The difficulty in promotional forecasting has resulted from numerous internal and external factors that affect the demand patterns. It has also resulted from multiple levels of hierarchy that involve different groups in the organization as well as different methods and systems. Moreover, judgments from the forecasters are critical to the accuracy of the forecasts, while the value of tweaking the forecast results is yet to be determined. In this business, the forecasters generally have a high incentive to over-forecast in order to meet the corporate goal of maximizing customer satisfaction. The main objective of this thesis is to analyze the effectiveness of promotional forecasting, identify the factors contributing to forecast accuracy, and propose suggestions for improving forecasts. In light of this objective, we used WMPE and WMAPE as the measures of forecast accuracy, and conducted analysis of promotional forecast accuracy from different point of views.
(cont.) We also verified our results with regression analysis, which helped identify the significance of each forecasting attribute so as to support the promotion planning without compromising forecast accuracy. We suggest several approaches to improve forecast accuracy. First, to improve store forecasts, we recommend three models: the bias correction model, the adaptive bias correction model, and the regression model. Second, to improve replenishment forecasts, we propose a new model that combines the top-down and bottom-up approaches. Lastly, we suggest a framework for measuring accuracy that emphasizes the importance of comparing the accuracy of forecasts generated from systems and from judgments.
by Pakawkul Koottatep and Jinqian Li.
M.Eng.in Logistics

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Feng, Ning. "Essays on business cycles and macroeconomic forecasting." HKBU Institutional Repository, 2016. https://repository.hkbu.edu.hk/etd_oa/279.

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This dissertation consists of two essays. The first essay focuses on developing a quantitative theory for a small open economy dynamic stochastic general equilibrium (DSGE) model with a housing sector allowing for both contemporaneous and news shocks. The second essay is an empirical study on the macroeconomic forecasting using both structural and non-structural models. In the first essay, we develop a DSGE model with a housing sector, which incorporates both contemporaneous and news shocks to domestic and external fundamentals, to explore the kind of and the extent to which different shocks to economic fundamentals matter for driving housing market dynamics in a small open economy. The model is estimated by the Bayesian method, using data from Hong Kong. The quantitative results show that external shocks and news shocks play a significant role in this market. Contemporaneous shock to foreign housing preference, contemporaneous shock to terms of trade, and news shocks to technology in the consumption goods sector explain one-third each of the variance of housing price. Terms of trade contemporaneous shock and consumption technology news shocks also contribute 36% and 59%, respectively, to the variance in housing investment. The simulation results enable policy makers to identify the key driving forces behind the housing market dynamics and the interaction between housing market and the macroeconomy in Hong Kong. In the second essay, we compare the forecasting performance between structural and non-structural models for a small open economy. The structural model refers to the small open economy DSGE model with the housing sector in the first essay. In addition, we examine various non-structural models including both Bayesian and classical time-series methods in our forecasting exercises. We also include the information from a large-scale quarterly data series in some models using two approaches to capture the influence of fundamentals: extracting common factors by principal component analysis in a dynamic factor model (DFM), factor-augmented vector autoregression (FAVAR), and Bayesian FAVAR (BFAVAR) or Bayesian shrinkage in a large-scale vector autoregression (BVAR). In this study, we forecast five key macroeconomic variables, namely, output, consumption, employment, housing price inflation, and CPI-based inflation using quarterly data. The results, based on mean absolute error (MAE) and root mean squared error (RMSE) of one to eight quarters ahead out-of-sample forecasts, indicate that the non-structural models outperform the structural model for all variables of interest across all horizons. Among the non-structural models, small-scale BVAR performs better with short forecasting horizons, although DFM shows a similar predictive ability. As the forecasting horizon grows, DFM tends to improve over other models and is better suited in forecasting key macroeconomic variables at longer horizons.

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Liao, Kua-ping. "Feedforward neural network forecasting model building evaluation : theory and application in business forecasting." Thesis, Lancaster University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310532.

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Yenilmez-Dramali, Demet. "Moderating effect of forecasting methods between forecasting criteria and export sales forecasting effectiveness : an empirical model for UK organizations." Thesis, Kingston University, 2013. http://eprints.kingston.ac.uk/26591/.

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Over the last three decades important advances have been made in developing sales forecasting methods that more accurately reflect market place conditions. However, surveys of sales forecasting practice continue to report only marginal gains in sales forecasting effectiveness. This gap between theory and practice has been identified as a significant issue for sales forecasting research. The literature suggests that this gap should be addressed by examining new factors in sales forecasting. Accuracy, bias, timeliness, cost and environmental turbulence are the most studied forecasting criteria in sales forecasting effectiveness. There are some literatures which address how these factors are affected by the forecast methods the firm uses. Empirical evidence on such a role of the forecasting method is lacking, and existing literature does not take into account whether forecasting criteria's influence on export sales forecasting effectiveness vary depending on the forecasting methods used by the firm. This is the first research gap identified during the literature review. Furthermore, the role of export sales forecasting. effectiveness on export market performance have received only limited attention to date. Linking the forecasting effectiveness to the business performance was reported to be critical in evaluating and improving the firm's sales forecasting capability and sales forecasting climate. However, empirical evidence of this linkage is missing and this is the second gap this study addresses. A conceptual model is proposed and multivariate analysis technique is used to investigate the relationship between dependent (forecasting effectiveness and export performance) and independent variables (forecasting criteria, forecasting methods, managerial characteristics, organizational characteristics and export market orientation). Our finding revealed the impact of bias, timeliness and cost on forecasting effectiveness varies depending on the forecasting methods used by the firm. But no moderating impact of forecasting methods has been found for accuracy and environmental turbulence. Moreover, this study reported the linkage between forecasting effectiveness and export performance when composite forecasting method is used. Identifying the relative importance of all the factors (i.e. accuracy, bias, cost, timeliness, forecasting methods, etc) it becomes possible to set priorities directly reflecting managerial preferences for different forecast criteria. If implementation of such priorities is seen to contradict principles of good forecasting practice, action can be taken to inform managers of the potential negative consequences.

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Lannsjö, Fredrik. "Forecasting the Business Cycle using Partial Least Squares." Thesis, KTH, Matematisk statistik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-151378.

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Partial Least Squares is both a regression method and a tool for variable selection, that is especially appropriate for models based on numerous (possibly correlated) variables. While being a well established modeling tool in chemometrics, this thesis adapts PLS to financial data to predict the movements of the business cycle represented by the OECD Composite Leading Indicators. High-dimensional data is used, and a model with automated variable selection through a genetic algorithm is developed to forecast different economic regions with good results in out-of-sample tests.
Partial Least Squares är både en regressionsmetod och ett verktyg för variabelselektion som är specielltlämpligt för modeller baserade på en stor mängd (möjligtvis korrelerade) variabler.Medan det är en väletablerad modelleringsmetod inom kemimetri, anpassar den häruppsatsen PLS till finansiell data för att förutspå rörelserna av konjunkturen,representerad av OECD's Composite Leading Indicator. Högdimensionella dataanvänds och en model med automatiserad variabelselektion via en genetiskalgoritm utvecklas för att göra en prognos av olika ekonomiska regioner medgoda resultat i out-of-sample-tester

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Queen, Catriona M. "Bayesian graphical forecasting models for business time series." Thesis, University of Warwick, 1991. http://wrap.warwick.ac.uk/4321/.

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This thesis develops three new classes of Bayesian graphical models to forecast multivariate time series. Although these models were originally motivated by the need for flexible and tractable forecasting models appropriate for modelling competitive business markets, they are of theoretical interest in their own right. Multiregression dynamic models are defined to preserve certain conditional independence structures over time. Although these models are typically very non-Gaussian, it is proved that they are simple to update, amenable to practical implementation and promise more efficient identification of causal structures in a time series than has been possible in the past. Dynamic graphical models are defined for multivariate time series for which there is believed to be symmetry between certain subsets of variables and a causal driving mechanism between these subsets. They are a specific type of graphical chain model (Wermuth & Lauritzen, 1990) which are once again typically non- Gaussian. Dynamic graphical models are a combination of multiregression dynamic models and multivariate regression models (Quintana, 1985,87, Quintana & West, 1987,88) and as such, they inherit the simplicity of both these models. Partial segmentation models extend the work of Dickey et al. (1987) to the study of models with latent conditional independence structures. Conjugate Bayesian anaylses are developed for processes whose probability parameters are hypothesised to be dependent, using the fact that a certain likelihood separates given a matrix of likelihood ratios. It is shown how these processes can be represented by undirected graphs and how these help in its reparameterisation into conjugate form.

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Shirahatti, Murughendra. "Business planning and forecasting application for Synopsys, Inc." [Chico, Calif. : California State University, Chico], 2009. http://csuchico-dspace.calstate.edu/xmlui/handle/10211.4/176.

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Pacce, Matías José. "Essays on Business Cycles Fluctuations and Forecasting Methods." Doctoral thesis, Universidad de Alicante, 2017. http://hdl.handle.net/10045/71346.

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This doctoral dissertation proposes methodologies which, from a linear or a non-linear approach, accommodate to the information flow and can deal with a large amount of data. The empirical application of the proposed methodologies contributes to answer some of the questions that have emerged or that it has potentiated after the 2008 global crisis. Thus, essential aspects of the macroeconomic analysis are studied, like the identification and forecast of business cycles turning points, the business cycles interactions between countries or the development of tools able to forecast the evolution of key economic indicators based on new data sources, like those which emerge from search engines.

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PARKASH, MOHINDER. "THE IMPACT OF A FIRM'S CONTRACTS AND SIZE ON THE ACCURACY, DISPERSION AND REVISIONS OF FINANCIAL ANALYSTS' FORECASTS: A THEORETICAL AND EMPIRICAL INVESTIGATION." Diss., The University of Arizona, 1987. http://hdl.handle.net/10150/184093.

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The evidence presented in this study suggests that the dispersion, accuracy and transitory component in revisions of financial analysts' forecasts (FAF) are determined by production/investment/financing decisions, accounting choices as well as firm specific characteristics including the type of control, debt to equity ratio and size of the firm. Firms with managers control (owners control), high (low) debt to equity ratio and large (small) size are hypothesized to have higher (lower) dispersion, forecast error and transitory components in revisions of FAF. These hypotheses are motivated by the contracting cost and political visibility theories. The information availability theory is included as a contrast to the political visibility hypothesis. The information availability hypothesis predicts large (small) firms to have lower (higher) dispersion, forecast error and transitory component in revisions of FAF. The regression results are sensitive to deflated and undeflated measures of the dispersion and accuracy of FAF and size of the firm. The appropriateness of the two measures of firm's size, the book value of total assets and the market value of common stock plus long-term debt, as well as the deflated and undeflated measures of dispersion and accuracy of FAF are investigated. It is concluded that deflated measures of the dispersion and forecast errors and the market value as measure of firm size are misspecified in the present context. The current year forecast revisions are assumed to consist of the transitory and permanent components. The second year forecast revisions are used to represent the long-term forecast revisions and are used as a control for the permanent component of forecast revisions. The regression results are consistent with the contracting and political visibility hypotheses. The firm specific characteristics are hypothesized to influence forecast errors and dispersion directly and indirectly through business risk and accounting policy choices. The links between firm characteristics and business risk, accounting policy choices, dispersion and forecast errors are established and path analysis is used to test these relationships. These relationships are observed to be consistent with predictions and significant.

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Niu, Mu. "Supply chain dynamics and forecasting." Thesis, Northumbria University, 2009. http://nrl.northumbria.ac.uk/1606/.

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Nowadays, the global supply chain system needs to respond promptly to changes in customer demand and adapt quickly to advancements in technology. Supply chain management becomes an integral approach which links together producers, distributors and customers in collaborative management of the whole system. The variability in orders or inventories in supply chain systems is generally thought to be caused by exogenous random factors such as uncertainties in customer demand or lead time. Studies have shown, however, that orders or inventories may exhibit significant variability, even if customer demand and lead time are deterministic. Most researchers have concentrated on the effects of the ordering policy on supply chain behaviour, while not many have paid attention to the influences of applying different forecasting to supply chain planning. This thesis presents an analysis of the behaviour of a model of a centralised supply chain. The research was conducted within the manufacturing sector and involved the breathing equipment manufacturer Draeger Safety, UK. The modelling process was embedded in the organization and was focused on the client's needs. A simplified model of the Draeger Safety, UK centralised supply chain was developed and validated. The dynamics of the supply chain under the influence of various factors: demand pattern, ordering policy, demand-information sharing, and lead time were observed. Simulation and analysis were performed using system dynamics, non-linear dynamics and control theory. The findings suggest that destructive oscillations of inventory could be generated by internal decision making practices. To reduce the variation in the supply chain system, the adjustment parameters for both inventory and supply line discrepancies should be more comparable in magnitude. Counter- intuitively, in certain fields of decision, sharing demand information can do more harm than good. The linear forecasting ARMA (autoregression and moving average) model and the nonlinear forecasting model Wavelet Neural Network were applied as the supply chain forecasting methods. The performance was tested against supply chain costs. A management microworld was developed, allowing managers to experiment with different decision policies and learn how the supply chain performs.

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Matsumoto, Dawn Aiko. "Management's incentives to influence analysts' forcasts /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/8742.

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Harrington, Robert P. "Forecasting corporate performance." Diss., Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/54515.

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For the past twenty years, the usefulness of accounting information has been emphasized. In 1966 the American Accounting Association in its State of Basic Accounting Theory asserted that usefulness is the primary purpose of external financial reports. In 1978 the State of Financial Accounting Concepts, No. 1 affirmed the usefulness criterion. "Financial reporting should provide information that is useful to present and potential investors and creditors and other users..." Information is useful if it facilitates decision making. Moreover, all decisions are future-oriented; they are based on a prognosis of future events. The objective of this research, therefore, is to examine some factors that affect the decision maker's ability to use financial information to make good predictions and thereby good decisions. There are two major purposes of the study. The first is to gain insight into the amount of increase in prediction accuracy that is expected to be achieved when a model replaces the human decision-maker in the selection of cues. The second major purpose is to examine the information overload phenomenon to provide research evidence to determine the point at which additional information may contaminate prediction accuracy. The research methodology is based on the lens model developed by Eyon Brunswick in 1952. Multiple linear regression equations are used to capture the participants’ models, and correlation statistics are used to measure prediction accuracy.
Ph. D.

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Theobald, Thomas [Verfasser]. "Essays on Business Cycle Forecasting and Banking Regulation / Thomas Theobald." Berlin : Freie Universität Berlin, 2014. http://d-nb.info/1054951047/34.

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Hii, Teck K. "Reducing the redundancy of financial ratios and assessing the stability of financial patterns." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2000. https://ro.ecu.edu.au/theses/1343.

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The purpose of this study was to examine the financial patterns of Australian industrial firms along the lines of Pinches et al.’s (1973; 1975) study. The financial ratios used in prior Australian corporate failure studies were used to derive a reduced set of factors that was predictive of corporate failure (e.g., Castagna & Matolesy, 1981: Booth, 1983). These factors were examined for the short – and long-term stability of these factors. The set of firms used was selected from FINSELECT database, which covered the period from 1989 to 1997. A random list of 199 Australian industrial firms that survived between 1989 and 1997 was selected. A total of thirty-one unique financial ratios were calculated based on the models derived in prior Australian failure prediction studies. These financial rations were factor analysed. The financial factors that were predictive of corporate failure were Return on Investment, Short-Term Liquidity (I and II), Financial Leverage (I and II) and Decomposition Measure.

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Laxmidhar, Mohammad, and Dnyanesh Sarang. "Exploratory Investigation of Sales Forecasting Process and Sales Forecasting System : Case Study of Three Companies." Thesis, Jönköping University, JIBS, Business Administration, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-718.

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The future has always caught the attention of the human being. The thirst of exploring the future and to know the unknown has driven the human being toward innovativeness.

Companies are expanding their operations worldwide since the past few decades. Profit growth coupled with an effective strategy has become the primary need of global companies. Research in this area has given rise to optimization of the supply chain for higher profitability. Considering the overall strategy the company needs to plan production well in advance. The operational planning comes in picture at this moment. In order to reduce excessive inventory at each stage of the production; one should know the demand of the next stage and preferably the end customer demand. The process of sales forecasting is undertaken to predict demand at different stages. It is a complex managerial function and hence needed to be undertaken by a scientific way. The sales forecasting the function includes process of forecasting, administration, hardware, software, users and developers of forecast.

Historically sales forecasting has been considered as a side activity by most of the companies. Sales forecasting has not been considered as an important function of marketing and finance. Very few companies have seen sales forecasting by a scientific management point of view. Less research has been reported in sales forecasting in comparison to other managerial functions. Planning based on sales forecasting; may be part of a selected strategy for growth and profitability. These facts have attracted us to study sales forecasting as a managerial function.

The purpose of this study is to describe and analyze the sales forecasting process, sales forecasting system, sales forecasting methods and techniques. Further proposing possibilities of improvements in existing forecasting process is also purpose of this study.

We have selected three manufacturing companies for this study based on purposive sampling. Considering research interest in phenomenon study; we have selected a qualitative research strategy for this study. We have selected a case study method for our research as it is the most appropriate tool to study the relation between theory and phenomenon. For this research, we have collected the data by semistructured interviews based on a pre formed questionnaire. The questionnaire has been prepared with respect to our research purpose and open ended questions were used to gather extensive data. The data gathered during interviews, have been analyzed by the use of ‘Flow model’ suggested by Miles and Huberman (1994).

Results from this study shows that there is a need to see ‘sales forecasting’ as a management function rather than a computer activity. To achieve the best information integration throughout the supply chain, increased information visibility is needed. To achieve accuracy in both forecasting and planning; collaborative forecasting may be used. Forecasting software needs to have a suite of methods towards product specific forecasting. The need of customized softwares has also been indicated by this study. The need to measure performance of forecasting by means of accuracy, cost and customer relationship has been concluded.

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Sanders, Nada R. "Forecasting short term demand in the physical distribution environment /." Connect to resource, 1986. http://rave.ohiolink.edu/etdc/view.cgi?acc%5Fnum=osu1262198594.

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Burger, S. (Stephan). "Managing the forecasting function within the fast moving consumer goods industry." Thesis, Stellenbosch : Stellenbosch University, 2003. http://hdl.handle.net/10019.1/53494.

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Thesis (MBA)--Stellenbosch University, 2003.
ENGLISH ABSTRACT: Forecasting the future has always been one of the man's strongest desires. The aim to determine the future has resulted in scientifically based forecasting models of human health, behaviour, economics, weather, etc. The main purpose of forecasting is to reduce the range of uncertainty within which management decisions must be made. Forecasts are only effective if they are utilized by those who have decisionmaking authority. Forecasts need to be understood and appreciated by decision makers so that they find their way into management of the firm. Companies still predominantly rely on judgemental forecasting methods, most often on an informal basis. There is a large literature base that point to the numerous biases inherent in judgemental forecasting. Most companies know that their forecasts are incorrect but don't know what to do about it and choose to ignore the issue, hoping that the problem will solve itself. The collaborative forecasting process attempts to use history as a baseline, but supplement current knowledge about specific trends, events and other items. This approach integrates the knowledge and information that exists internally and externally into a single, more accurate forecast that supports the entire supply chain. Demand forecasting is not just a matter of duplicating or predicting history into the future. It is important that one person should lead and manage the process. Accountability needs to be established. An audit on the writer's own organization indicated that no formal forecasting process was present. The company's forecasting process was very political, since values were entered just to add up to the required targets. The real gap was never fully understood. Little knowledge existed regarding statistical analysis and forecasting within the marketing department who is accountable for the forecast. The forecasting method was therefore a top-down approach and never really checked with a bottom up approach. It was decided to learn more about the new demand planning process prescribed by the head office, and to start implementing the approach. The approach is a form of a collaborative approach which aims to involve all stakeholders when generating the forecast, therefore applying a bottom up approach. Statistical forecasting was applied to see how accurate the output was versus that of the old way of forecasting. The statistical forecast approach performed better with product groups where little changed from previous years existed, while the old way performed better where new activities were planned or known by the marketing team. This indicates that statistical forecasting is very important for creating the starting point or baseline forecast, but requires qualitative input from all stakeholders. Statistical forecasting is therefore not the solution to improved forecasting, but rather part of the solution to create robust forecasts.
AFRIKAANSE OPSOMMING: Vooruitskatting van die toekoms was nog altyd een van die mens se grootste begeertes. Die doel om die toekoms te bepaal het gelei tot wiskundige gebaseerde modelle van die mens se gesondheid, gedrag, ekonomie, weer, ens. The hoofdoel van vooruitskatting is om die reeks van risikos te verminder waarbinne bestuur besluite moet neem. Vooruitskattings is slegs effektief as dit gebruik word deur hulle wat besluitnemingsmag het. Vooruitskattings moet verstaan en gewaardeer word deur die besluitnemers sodat dit die weg kan vind na die bestuur van die firma. Maatskappye vertrou nog steeds hoofsaaklik op eie oordeel vooruitskatting metodes, en meestal op 'n informele basis. Daar is 'n uitgebreide literatuurbasis wat daarop dui dat heelwat sydigheid betrokke is by vooruitskattings wat gebaseer is op eie oordeel. Baie organisasies weet dat hulle vooruitskattings verkeerd is, maar weet nie wat daaromtrent te doen nie en kies om die probleem te ignoreer, met die hoop dat die probleem vanself sal oplos. Die geïntegreerde vooruitskattingsproses probeer om die verlede te gebruik as 'n basis, maar voeg huidige kennis rakende spesifieke neigings, gebeurtenisse, en ander items saam. Hierdie benadering integreer die kennis en informasie wat intern en ekstern bestaan in 'n enkele, meer akkurate vooruitskatting wat die hele verskaffingsketting ondersteun. Vraagvooruitskatting is nie alleen 'n duplisering of vooruitskatting van die verlede in die toekoms in nie. Dit is belangrik dat een persoon die proses moet lei en bestuur. Verantwoordelikhede moet vasgestel word. 'n Oudit op die skrywer se organisasie het getoon dat geen formele vooruitskattingsprosesse bestaan het nie. Die maatskappy se vooruitskattingsproses was hoogs gepolitiseerd, want getalle was vasgestel wat in lyn was met die nodige teikens. Die ware gaping was nooit werklik begryp nie. Min kennis was aanwesig rakende statistiese analises en vooruitskatting binne die bemarkingsdepartement wat verantwoordelik is vir die vooruitskatting. Die vooruitskatting is dus eerder gedoen op 'n globale vlak en nie noodwendig getoets deur die vooruitskatting op te bou uit detail nie. Daar is besluit om meer te leer rakende die nuwe vraagbeplanningsproses, wat voorgeskryf is deur hoofkantoor, en om die metode te begin implementeer. Die metode is 'n vorm van 'n geïntegreerde model wat beoog om alle aandeelhouers te betrek wanneer die vooruitskatting gedoen word, dus die vooruitskatting opbou met detail. Statistiese vooruitskatting was toegepas om te sien hoe akkuraat die uitset was teenoor die ou manier van vooruitskatting. Die statistiese proses het beter gevaar waar die produkgroepe min verandering van vorige jare ervaar het, terwyl die ou manier beter gevaar het waar bemarking self die nuwe aktiwiteite beplan het of bewus was daarvan. Dit bewys dat statistiese vooruitskatting baie belangrik is om die basis vooruitskatting te skep, maar dit benodig kwalitatiewe insette van all aandeelhouers. Statistiese vooruitskattings is dus nie die oplossing vir beter vooruitskattings nie, maar deel van die oplossing om kragtige vooruitskattings te skep.

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Tam, Yat-hung Terence. "Forecasting models on residential property price /." [Hong Kong : University of Hong Kong], 1993. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13731208.

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Field, K. F. "Input-output technology forecasting : A micro-foundation approach." Thesis, University of Strathclyde, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.382318.

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Postiglioni, Renato. "Sales forecasting within a cosmetic organisation : a managerial approach." Thesis, Stellenbosch : Stellenbosch University, 2006. http://hdl.handle.net/10019.1/21980.

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Thesis (MBA)--Stellenbosch University, 2006.
Although most businesses require accurate sales forecasts in order to survive and to be successful, very little attention has been devoted to examine how sales forecasting processes should be managed, and the behavioural factors associated with the management of forecasting. Sales forecasting activities and research have by and large concentrated on the techniques or on the systems used, rather than on the forecasting management philosophy, which considers the organisational, procedural, and personnel aspects of the process. Both forecasting modelling and IT systems form the basis for the forecasting process, but the third element, namely the organisation, is potentially the most important one. Researchers have argued that improvements in this area could have a greater impact on the level of forecasting accuracy than improvements with regard to other aspects. After developing predetermined forecasting standards and principles, an audit on the author's organisation was conducted. This revealed that no formal forecasting --- existed, and that a number of business practices were in effect contaminating procedures and possibly affecting the integrity of the data. Very little forecasting knowledge existed, sales were predicted very sporadically, and simple averaging techniques were adopted. Life cycles of products, trends, seasonality or any other cyclical activity were never modelled. This obviously resulted in a very poor level of forecast accuracy, affecting a number of business activities. A decision was made to research the topic of forecasting management, develop a best practice model, and apply it to the organisation. The best practice model was based predominantly on the research work of Armstrong and Mentzer. This model requires the forecasting process to be developed in two specific phases, namely a strategic phase, in which the forecast is aligned to the organisation, the internal processes and the people, and the operational phase, in which more tangible aspects of the forecasting process are identified and constructed. This new forecasting approach and a dedicated forecasting software programme were successfully implemented, improving the overall accuracy level of the forecast.

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Jessen, Andreas, and Carina Kellner. "Forecasting Management." Thesis, University of Kalmar, Baltic Business School, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hik:diva-1868.

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In a world that is moving faster and faster, a company’s ability to align to market changes is becoming a major competitive factor. Forecasting enables companies to predict what lies ahead, e.g. trend shifts or market turns, and makes it possible to plan for it. But looking into the future is never an easy task.

“Prediction is very difficult, especially if it’s about the future.” (Niels Bohr, 1885-1962)

However, progress in the field of forecasting has shown that it is possible for companies to improve on forecasting practices. This master thesis looks at the sales forecasting practices in MNCs primarily operating in emerging and developing countries. We examine the whole process of sales forecasting, also known as forecasting management, in order to develop a comprehensive model for forecasting in this type of companies. The research is based on a single case study, which is then later generalized into broader conclusions.

The conclusion of this master thesis is that forecasting is a four-step exercise. The four stages we have identified are: Knowledge creation, knowledge transformation, knowledge use and feedback. In the course of these four stages a company’s sales forecast is developed, changed and used. By understanding how each stage works and what to focus on, companies will be able to improve their forecasting practices.

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Qiang, Fu. "Bayesian multivariate time series models for forecasting European macroeconomic series." Thesis, University of Hull, 2000. http://hydra.hull.ac.uk/resources/hull:8068.

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Research on and debate about 'wise use' of explicitly Bayesian forecasting procedures has been widespread and often heated. This situation has come about partly in response to the dissatisfaction with the poor forecasting performance of conventional methods and partly in view of the development of computational capacity and macro-data availability. Experience with Bayesian econometric forecasting schemes is still rather limited, but it seems to be an attractive alternative to subjectively adjusted statistical models [see, for example, Phillips (1995a), Todd (1984) and West & Harrison (1989)]. It provides effective standards of forecasting performance and has demonstrated success in forecasting macroeconomic variables. Therefore, there would seem a case for seeking some additional insights into the important role of such methods in achieving objectives within the macroeconomics profession. The primary concerns of this study, motivated by the apparent deterioration of mainstream macroeconometric forecasts of the world economy in recent years [Wallis (1989), pp.34-43], are threefold. The first is to formalize a thorough, yet simple, methodological framework for empirical macroeconometric modelling in a Bayesian spirit. The second is to investigate whether improved forecasting accuracy is feasible within a European-based multicountry context. This is conducted with particular emphasis on the construction and implementation of Bayesian vector autoregressive (BVAR) models that incorporate both a priori and cointegration restrictions. The third is to extend the approach and apply it to the joint-modelling of system-wide interactions amongst national economies. The intention is to attempt to generate more accurate answers to a variety of practical questions about the future path towards a united Europe. The use of BVARs has advanced considerably. In particular, the value of joint-modelling with time-varying parameters and much more sophisticated prior distributions has been stressed in the econometric methodology literature. See e.g. Doan et al. (1984). Kadiyala and Karlsson (1993, 1997), Litterman (1986a), and Phillips (1995a, 1995b). Although trade-linked multicountry macroeconomic models may not be able to clarify all the structural and finer economic characteristics of each economy, they do provide a flexible and adaptable framework for analysis of global economic issues. In this thesis, the forecasting record for the main European countries is examined using the 'post mortem' of IMF, DECO and EEC sources. The formulation, estimation and selection of BVAR forecasting models, carried out using Microfit, MicroTSP, PcGive and RATS packages, are reported. Practical applications of BVAR models especially address the issues as to whether combinations of forecasts explicitly outperform the forecasts of a single model, and whether the recent failures of multicountry forecasts can be attributed to an increase in the 'internal volatility' of the world economic environment. See Artis and Holly (1992), and Barrell and Pain (1992, p.3). The research undertaken consolidates existing empirical and theoretical knowledge of BVAR modelling. It provides a unified coverage of economic forecasting applications and develops a common, effective and progressive methodology for the European economies. The empirical results reflect that in simulated 'out-of-sample' forecasting performances, the gains in forecast accuracy from imposing prior and long-run constraints are statistically significant, especially for small estimation sample sizes and long forecast horizons.

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Renner, Nancy A. (Nancy Ann). "Forecasting Quarterly Sales Tax Revenues: A Comparative Study." Thesis, North Texas State University, 1986. https://digital.library.unt.edu/ark:/67531/metadc501220/.

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The purpose of this study is to determine which of three forecasting methods provides the most accurate short-term forecasts, in terms of absolute and mean absolute percentage error, for a unique set of data. The study applies three forecasting techniques--the Box-Jenkins or ARIMA method, cycle regression analysis, and multiple regression analysis--to quarterly sales tax revenue data. The final results show that, with varying success, each model identifies the direction of change in the future, but does not closely identify the period to period fluctuations. Indeed, each model overestimated revenues for every period forecasted. Cycle regression analysis, with a mean absolute percentage error of 7.21, is the most accurate model. Multiple regression analysis has the smallest absolute percentage error of 3.13.

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Conway, Miles V. "An empirical study of South African business forecasting practices in the context of Western benchmarks." Thesis, Stellenbosch : Stellenbosch University, 2008. http://hdl.handle.net/10019.1/1273.

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Hersey, J. Michael Rowlett James M. Thompson Shannon P. "Forecasting the demand of the F414-GE-400 at NAS Lemoore." Monterey, Calif. : Naval Postgraduate School, 2008. http://edocs.nps.edu/npspubs/scholarly/MBAPR/2008/Dec/08Dec%5FHersey%5FMBA.pdf.

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"Submitted in partial fulfillment of the requirements for the degree of Master of Business Administration from the Naval Postgraduate School, December 2008."
Advisor(s): Ferrer, Geraldo ; Apte, Aruna U. "December 2008." "MBA professional report"--Cover. Description based on title screen as viewed on January 28, 2009. Includes bibliographical references (p. 61-63). Also available in print.

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Eroglu, Cuneyt. "An investigation of accuracy, learning and biases in judgmental adjustments of statistical forecasts." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1150398313.

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Clarke, Roddy N. "A managerial approach to forecasting for the construction industry." Thesis, Queen's University Belfast, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.292594.

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Stoll, Robert G. "Collaborative Planning Forecasting Replenishment (CPFR): Successful Implementation Attributes." Cleveland State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=csu1292517604.

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Choi, Jeong-Gil. "The Restaurant Industry: Business Cycles, Strategic Financial Practices, Economic Indicators, and Forecasting." Diss., Virginia Tech, 1999. http://hdl.handle.net/10919/27181.

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The essential characteristic of the future is uncertainty. A basic feature of the economy, and life in general, is that decisions are made under conditions of uncertainty-the future is unknowable. Having reliable guidelines or indicators that provide discipline and signposts to the future is required for the process of successful investing. Conditions are constantly changing, and there are no rewards for replaying the same old game over and over. To answer for this demand, continued from the previous studies (Choi, 1996; Choi et al., 1997a; Choi et al., 1997b; Choi et al., 1999), this study developed the restaurant industry business cycle models and examined financial practices of the high and low performing firms over the industry cycles. The U.S. restaurant industry demonstrated three cycles (peak to peak or trough to trough) for the period of 1970 through 1998. The restaurant industry peaked in 1973, 1979, and 1989. The industry troughed in 1970, 1974, 1980, and 1991. The mean duration of the restaurant industry cycles is 8 years (SD: 2) calculated by peak to peak and 6.5 years (SD: 2.08) calculated by trough to trough. Expansion takes an average of 6 years in the restaurant industry but declines sharply after it reaches the peak taking average 1.33 years. The restaurant industry experienced high growth (boom) every five years on average. The troughs of the growth cycles, contrasted to the peaks of the growth cycles, coincided with those of the restaurant industry business cycles in each case except one (1985). During that year a low growth phase interrupted industry business expansion but did not terminate it. Restaurant industry growth cycles, then, tend to be relatively symmetrical: since 1970 the average duration was about 2.25 years for both expansion (L-H) and contraction (H-L). In contrast, the restaurant industry business cycles in the same period show a strong asymmetry: the expansions lasted on the average 6 years; the contractions, 1.33 years. The expansions have varied in duration much more than the high growth phases have (the respective standard deviations are 2.58 and 0.95 years). This study supports the view that the cyclical fluctuations of the growth of the restaurant industry can be projected by measuring and analyzing series of economic indicators and each economic indicator has specific characteristics in terms of time lags, and thus can be classified into leading, coincident, and lagging indicators. This study formed a set of composite indices with twelve indicators classified in the leading category, six as coincident, and twenty as lagging. The high performing firms' financial practices regarding investment decisions measured by capital spending, and price earning ratio, and part of financing and dividend decisions measured by market value of common share outstanding are independent of the cyclical fluctuations of the industry cycles. But, their practices regarding dividend decisions measured by the earning per share, investment decision measured by cash flow per share, and financing decisions measured by asset value per share and long term debt level are dependent on the events (Expansion/Contractions) in the Restaurant Industry Cycles. Conclusively, high performers exercise their capital investment (reflected by capital spending) and equity management (reflected by common share outstanding and P/E ratio) independently while being less influenced by the industry swings. They exercise, however, their working capital management (reflected by cash flow per share), earning management (reflected by EPS), asset management, and long term debt management quite dependently while being more influenced by the industry swings. The financial practices exercised by the low performing firms are independent from the events in the industry cycle. Although some financial practices are related to the events in the industry cycle, the directions are opposite to the events in the industry cycle. Specifically, for all of the selected financial strategies except common share outstanding and long-term debt, the low performers practice them independently from the cyclical fluctuations of the industry cycles. Even for common share outstanding and long-term debt strategies, they practiced their strategies in opposite directions to the events (Expansion/Contractions) in the Restaurant Industry Cycles. It is expected that the above results can be used for improving investment performance through understanding the cyclical behavior of the economy and the restaurant industry. With that model, investors should be able to take part in the upswings while avoiding the cyclical downturns, and to structure a portfolio that keeps risk to a minimum. This should then presumably result in competitive investment decisions of firms, thereby improving the effectiveness of resource allocation.
Ph. D.

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Berny, Jan. "Forecasting and risk analysis applied to management planning and control." Thesis, Aston University, 1988. http://publications.aston.ac.uk/10851/.

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The aim of this research was to improve the quantitative support to project planning and control principally through the use of more accurate forecasting for which new techniques were developed. This study arose from the observation that in most cases construction project forecasts were based on a methodology (c.1980) which relied on the DHSS cumulative cubic cost model and network based risk analysis (PERT). The former of these, in particular, imposes severe limitations which this study overcomes. Three areas of study were identified, namely growth curve forecasting, risk analysis and the interface of these quantitative techniques with project management. These fields have been used as a basis for the research programme. In order to give a sound basis for the research, industrial support was sought. This resulted in both the acquisition of cost profiles for a large number of projects and the opportunity to validate practical implementation. The outcome of this research project was deemed successful both in theory and practice. The new forecasting theory was shown to give major reductions in projection errors. The integration of the new predictive and risk analysis technologies with management principles, allowed the development of a viable software management aid which fills an acknowledged gap in current technology.

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Pacella, Claudia. "Essays on Forecasting." Doctoral thesis, Universite Libre de Bruxelles, 2020. https://dipot.ulb.ac.be/dspace/bitstream/2013/307579/4/CP_ToC.pdf.

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In this thesis I apply modern econometric techniques on macroeconomic time series. Forecasting is here developed along several dimensions in the three chapters. The chapters are in principle self-contained. However, a common element is represented by the business cycle analysis. In the first paper, which primarily deals with the problem of forecasting euro area inflation in the short and medium run, we also compute the country-specific responses of a common business cycle shock. Both chapters 2 and 3 deal predominately with business cycle issues from two different perspectives. The former chapter analyses the business cycle as a dichotomous non-observable variable and addresses the issue of evaluating the euro area business cycle dating formulated by the CEPR committee, while the latter chapter studies the entire distribution of GDP growth.
Doctorat en Sciences économiques et de gestion
info:eu-repo/semantics/nonPublished

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Moore, Ronald K. (Ronald Kenneth). "Prediction of Bankruptcy Using Financial Ratios, Information Measures, National Economic Data and Texas Economic Data." Thesis, North Texas State University, 1987. https://digital.library.unt.edu/ark:/67531/metadc331133/.

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The main purpose of this study is to develop a bankruptcy prediction model for the small business firm. Data was collected from the Dallas Small Business Administration (SBA), making this study specific to its decision makers. Existing research has produced models which predominately use financial ratios and information measures either independently or combined, and a few research models have used economic trends. This study varies from past studies in that it includes regional economic variables from the states of Texas. A sample of three-year data for 138 firms included fifteen bankrupt firms. This proportion of bankrupt/nonbankrupt firms approximates the proportion of repayed/defaulted loans in the SBA. Stepwise regression, set at the .15 level of significance, reduced a total of fifty-three variables to nine. These nine variables were then used to test twelve predictive models. All twelve models tested improved the SBA repayment rate and only two of the twelve would have caused the SBA to deny loans to applicants who eventually repaid. The study determined the model that included financial ratios, information measures, and Texas economic variables as best. It was also demonstrated that some of the variables used in this model could be eliminated without decreasing the predictive power of the model. The best of twelve models improved the SBA default rate by 40 percent without denying a loan to any applicant that eventually repaid.

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Tanwari, Anwar Uddin. "Impact of business forecasting on demand planning : a strategy for improving business forecasting and reducing inventories throughout the supply chain for fast moving consumer goods in the Middle East market." Thesis, University of Bradford, 1999. http://hdl.handle.net/10454/4336.

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Poor quality of information and forecasting create a number of problems for manufacturing companies, such as poor planning of products and insufficient service levels, which leads to increased inventory and stock holding or stockouts and increased total costs. Cussons (UK) Limited is experiencing precisely these problems. Apart from these problems normally associated with forecasting demand for fast moving consumer goods there is an additional problem of reconciling the Western calendar with the Muslim calendar, and a recognition of the effects that Muslim religious holidays, as opposed to Christian religious holidays, have on demand. Muslim religious holidays rotate backwards with regard to the Western calendar, but in fact they occur at known dates and therefore the effect they have on demand for products can be taken into consideration when attempting to forecast demand. An additional problem that influences Cussons' sales in the market is the seasonal pattern of demand. Due to this, there is an increase in demand for Cussons' products during summer months. From the analysis of both data sets it was identified that the warehouse movement data is less variable and more reliable for business forecasting than order data. In this thesis, these forecasting problems are examined as a case study, focusing on these particular problems. To overcome these problems and to improve business forecasting of Cussons' products in the Middle East market, a forecasting strategy has been suggested which will enable Cusson's to reduce the inventories throughout the supply chain and to improve their customer's service.

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36

Tanwari, Anwar U. "Impact of business forecasting on demand planning. A strategy for improving business forecasting and reducing inventories throughout the supply chain for fast moving consumer goods in the Middle East market." Thesis, University of Bradford, 1999. http://hdl.handle.net/10454/4336.

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Poor quality of information and forecasting create a number of problems for manufacturing companies, such as poor planning of products and insufficient service levels, which leads to increased inventory and stock holding or stockouts and increased total costs. Cussons (UK) Limited is experiencing precisely these problems. Apart from these problems normally associated with forecasting demand for fast moving consumer goods there is an additional problem of reconciling the Western calendar with the Muslim calendar, and a recognition of the effects that Muslim religious holidays, as opposed to Christian religious holidays, have on demand. Muslim religious holidays rotate backwards with regard to the Western calendar, but in fact they occur at known dates and therefore the effect they have on demand for products can be taken into consideration when attempting to forecast demand. An additional problem that influences Cussons' sales in the market is the seasonal pattern of demand. Due to this, there is an increase in demand for Cussons' products during summer months. From the analysis of both data sets it was identified that the warehouse movement data is less variable and more reliable for business forecasting than order data. In this thesis, these forecasting problems are examined as a case study, focusing on these particular problems. To overcome these problems and to improve business forecasting of Cussons' products in the Middle East market, a forecasting strategy has been suggested which will enable Cusson's to reduce the inventories throughout the supply chain and to improve their customer's service.
Ministry of Education, Government of Pakistan, Cussons (UK)Limited.

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Famy, George. "Forecasting Reurns to Pure Factors: A Study of Time Varying Risk Premia." restricted, 2006. http://etd.gsu.edu/theses/available/etd-04282006-162928/.

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Thesis (Ph.D.)--Georgia State University, 2006.
Stephen D. Smith, committee chair; Jason Greene, James Owens, Alok Srivastava, committee members. Electronic text (132 p. : ill. (some co.)) : digital, PDF file. Description based on contents viewed July 12, 2007. Includes bibliographical references (p. 91-97).

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38

Vassilopoulos, Angelos. "Development and evaluation of alternative methods for multi-item short-term business forecasting." Thesis, London Business School (University of London), 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.408195.

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39

Domenichelli, Daniele. "A procedure for modular forecasting at scale with constraints for business time series." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24782/.

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Nowadays artificial intelligence algorithms are capable to achieve impressive results with a reduced amount of physical and time resources. They cover many different topics with a discrete success, but one of the most challenging subject to model is the prediction of future trends in complex and mutable environments, such as market sales. From a deterministic point of view, the knowledge of the exact state and the rules of a system in a certain period intrinsically brings the faculty to forecast any future state. This perspective yields an exact prediction, but it lays its foundation on the assumption that its possible to model every aspect of the system, a premise that is usually satisfied only in simple cases. The difficulty of predicting time-series is amenable to many factors, one of the most important is the drastically instable and mutable domain subjected to the competitiveness of its constituents, vendors and buyers, as described by the principles of the game theory; in such system, the rules are constantly changing, hardening the predictions of future states. Furthermore, financial studies produced a variety of economic models which help to understand the market behaviour. By applying specific constraints to the prediction, it is possible to exploit these models to reach better and more explainable results and relate their components to the relative sources. The aim of this work is to propose a procedure capable of inject domain constraints in the prediction in a declarative fashion, addressing different economic models. This procedure helps the analysts to better express their domain expertise while keeping a completely explainable approach to describe their outcomes.

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Hossari, Ghassan, and hossari7@bigpond net au. "A ratio-based multi-level modelling approach for signalling corporate collapse a study of Australian corporations." Swinburne University of Technology. Australian Graduate School of Entrepreneurship, 2006. http://adt.lib.swin.edu.au./public/adt-VSWT20060320.114422.

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The objective of this study is to introduce a more refined methodological approach for signalling corporate collapse. The proposed methodological approach provides informed stakeholders in a corporation with a tool that would help them signal impending collapse with a higher degree of accuracy than the existing mainstream methodology. By doing so, the proposed methodological approach helps stakeholders take appropriate measures, if possible, to save their company from collapse. The motivation behind this study emanates from a need in the literature in relation to coming up with a new methodological approach that is superior to what is available. For example, Jones and Hensher (2004), one of the most recent studies in the field, stated that over the past three decades there has been a conspicuous absence of modelling innovation in the literature on financial distress prediction, as well as a failure to keep abreast of important methodological developments emerging in other fields of the social sciences. Specifically, this study introduces a new ratio-based multivariate methodological approach for signalling corporate collapse, called Multi-Level Modelling (MLM). Moreover, this study demonstrated that MLM provides informed stakeholders in a corporation with a tool that would help them signal impending collapse with a higher degree of accuracy than Multiple Discriminant Analysis (MDA), which is the mainstream benchmark methodological approach. By doing so, MLM helps stakeholders take appropriate measures, if possible, to save their company from collapse. The empirical results depicted the superiority of MLM over MDA. MLM generated better overall predictive power and dramatically reduced the occurrence of Type I error (classifying a collapsed company as non-collapsed). Moreover, MLM achieved those results while at the same time capturing variations in industry sectors among the data sample of companies. This is something that MDA was not capable of.

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Liu, Wenxian. "Interpreting and forecasting the semiconductor industry cycle." free to MU campus, to others for purchase, 2002. http://wwwlib.umi.com/cr/mo/fullcit?p3060119.

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Pan, Youqin Pavur Robert J. "Impact of forecasting method selection and information sharing on supply chain performance." [Denton, Tex.] : University of North Texas, 2009. http://digital.library.unt.edu/ark:/67531/metadc12176.

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43

Xue, Xiang. "Determinants of Consumer Behavior in an e-Commerce Environment." Fogler Library, University of Maine, 2002. http://www.library.umaine.edu/theses/pdf/XueX2002.pdf.

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Lin, Lee-Hsuan. "An examination of the stability of forecasting in failure prediction models." Thesis, University of Warwick, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.385071.

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Bjurgert, Johan, and Marcus Edstrand. "Forecasting the Equity Premium and Optimal Portfolios." Thesis, Linköping University, Department of Mathematics, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-11795.

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The expected equity premium is an important parameter in many financial models, especially within portfolio optimization. A good forecast of the future equity premium is therefore of great interest. In this thesis we seek to forecast the equity premium, use it in portfolio optimization and then give evidence on how sensitive the results are to estimation errors and how the impact of these can be minimized.

Linear prediction models are commonly used by practitioners to forecast the expected equity premium, this with mixed results. To only choose the model that performs the best in-sample for forecasting, does not take model uncertainty into account. Our approach is to still use linear prediction models, but also taking model uncertainty into consideration by applying Bayesian model averaging. The predictions are used in the optimization of a portfolio with risky assets to investigate how sensitive portfolio optimization is to estimation errors in the mean vector and covariance matrix. This is performed by using a Monte Carlo based heuristic called portfolio resampling.

The results show that the predictive ability of linear models is not substantially improved by taking model uncertainty into consideration. This could mean that the main problem with linear models is not model uncertainty, but rather too low predictive ability. However, we find that our approach gives better forecasts than just using the historical average as an estimate. Furthermore, we find some predictive ability in the the GDP, the short term spread and the volatility for the five years to come. Portfolio resampling proves to be useful when the input parameters in a portfolio optimization problem is suffering from vast uncertainty.

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De, Boyrie Maria Eugenia. "Out-of-sample exchange rate forecasting structural and non-structural nonlinear approaches." FIU Digital Commons, 1994. http://digitalcommons.fiu.edu/etd/2727.

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Forecasting foreign exchange rates is a perennial dilemma for exporters, importers, foreign exchange rate traders, and the business community as a whole. Foreign exchange rate models using popular linear and non-linear specifications do not produce particularly accurate forecasts. In point of fact, these models have not improved much upon the random walk model, especially in out-of-sample forecasting. Given these results, this dissertation constructs and evaluates new forecasting models to generate as accurate as possible out-of-sample forecasts of foreign exchange rates. The information content of futures contracts on foreign exchange rates is investigated and used to forecast future exchange rates using alternative techniques, both structural (econometric) and non-structural (fuzzy) models. The results of two specifications of a structural model are compared against the well-known random walk model. The first specification assumes future exchange rates are determined by futures prices and a lagged structure of spot rates. The second specification assumes that future spot rates are a function of only a lagged structure of the futures prices. The forecasting accuracy of the models is tested for both in-sample and out-of-sample periods; out-of-sample tests range from the short term to the long term (30- to 180-day forecasts). The results indicate that the random walk model remains a competitive alternative. In out-of-sample predictions, however, we can improve upon it in certain cases. The results also show that the predictive accuracy of the models is better in the short term (30 to 60 days) than in the longer term (180 days).

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Dwyer, Michael Edward. "Impact of implementing a self-managed work team on high sales force turnover and low productivity : a field experiment." Thesis, Swansea University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.607454.

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Brinca, Pedro Soares. "Essays in Quantitative Macroeconomics." Doctoral thesis, Stockholms universitet, Nationalekonomiska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-92861.

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In the first essay, Distortions in the Neoclassical Growth Model: A Cross Country Analysis, I show that shocks that express themselves as total factor productivity and labor income taxes are comparably more synchronized than shocks that resemble distortions to the ability of allocating resources across time and states of the world. These two shocks are also the most important to model. Lastly, I document the importance of international channels of transmission for the shocks, given that these are spatially correlated and that international trade variables, such as trade openness correlate particularly well with them. The second essay is called Monetary Business Cycle Accounting for Sweden. Given that the analysis is focused in one country, I can extend the prototype economy to include a nominal interest rate setting rule and government bonds. As in the previous essay, distortions to the labor-leisure condition and total factor productivity are the most relevant margins to be modeled, now joined by deviations from the nominal interest rate setting rule. Also, distortions do not share a structural break during the Great Recession, but they do during the 1990’s. Researchers aiming to model Swedish business cycles must take into account the structural changes the Swedish economy went through in the 1990’s, though not so during the last recession. The third essay, Consumer Confidence and Consumption Spending: Evidence for the United States and the Euro Area, we show that, the consumer confidence index can be in certain circumstances a good predictor of consumption. In particular, out-of-sample evidence shows that the contribution of confidence in explaining consumption expenditures increases when household survey indicators feature large changes, so that confidence indicators can have some increasing predictive power during such episodes. Moreover, there is some evidence of a confidence channel in the international transmission of shocks, as U.S. confidence indices help predicting consumer sentiment in the euro area.

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Katerna, Olga, and Ольга Костянтинівна Катерна. "Modern information technology in business." Thesis, National aviation university, 2021. https://er.nau.edu.ua/handle/NAU/53437.

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Катерна О. Сучасні інформаційні технології в бізнесі // Сучасні проблеми менеджменту: матеріали XVII Міжнародної науково-практичної конференції. – Національний авіаційний університет. – Київ, 2021. - С. 19-20
In recent decades, the amount of information in society in general and information used in the enterprise in particular has increased dramatically. This is due to the growing rates of development of science and technology, the emergence of new technologies, and their rapid replacement. In the markets of raw materials and products, conditions have developed that require constant monitoring of the state of the market, its changes, trends in its development, it is necessary to be able to foresee the further development of the situation and be ready to change the strategy, style of activity, production technology for the fastest adaptation to new external conditions.
В останні десятиліття обсяг інформації в суспільстві в цілому та інформації, використовуваної на підприємстві, зокрема, різко зріс. Це пов'язано зі зростаючими темпами розвитку науки і техніки, появою нових технологій і їх швидкою заміною. На ринках сировини і продукції склалися умови, що вимагають постійного моніторингу стану ринку, його змін, тенденцій в його розвитку, необхідно вміти передбачити подальший розвиток ситуації і бути готовим змінити стратегію, стиль діяльності, технологію виробництва для максимально швидкої адаптації до нових зовнішніх умов.

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Boshoff, Willem Hendrik. "The properties of cycles in South African financial variables and their relation to the business cycle." Thesis, Stellenbosch : University of Stellenbosch, 2006. http://hdl.handle.net/10019.1/1733.

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Thesis (MComm (Economics)--University of Stellenbosch, 2006.
The goal of this thesis is twofold: it aims, firstly, at a description of cycles in South African financial variables and, secondly, at the evaluation of the relationship between cycles in financial variables and the South African business cycle. The study is based on the original business cycle framework of Arthur Burns and Wesley Mitchell, but incorporates recent contributions by Australian economists Don Harding and Adrian Pagan, as well as the work of the Economic Cycle Research Institute in New York. Part I of the thesis is concerned with the characteristics of cycles in financial variables within the South African context. The first chapter presents a taxonomy of the concepts of classical, deviation and growth rate cycles in order to establish a simple reference framework for cycle concepts. At this point the concept of a ‘turning point cycle’ is introduced, with particular focus on the non-parametric method of turning point identification, following Harding and Pagan’s recent translation of the original work of Burns and Mitchell into a modern version with a sound statistical basis. With the turning points identified the dissertation proceeds to an exposition of descriptive measures of expansion and contraction phases. The second chapter entails an empirical report on descriptive results for amplitude and duration characteristics of cycle phases in the different financial variables, with separate reports for classical cycles and growth rate cycles. Chapter two concludes with a series of tables in which the behaviour of cycle phases are compared for different financial variables. Part II considers financial variables as potential leading indicators of the business cycle in South Africa. Chapter 3 introduces the concept ‘leading indicator’ to this end and distinguishes the original concept from modern, econometric versions. The chapter then introduces a framework for evaluating potential leading indicators, which emphasises two requirements: firstly, broad co-movement between cycles in the proposed leading indicator and the business cycle and, secondly, stability in the number of months between turning points in cycles of the proposed indicator and business cycle turning points. The capacity of potential indicators to meet these criteria is measured via the concordance statistic and the ‘lead profile’ respectively. Chapter four provides the statistical basis for the concordance statistic, after which the empirical results (presented separately for classical and growth rate cycles) are presented. The fifth chapter presents the statistical test for the stability of the interval by which cyclical turning points in the potential indicator lead turning points in the business cycle. Empirical results are presented in both tabular form (the ‘lead profile’) and graphical form (the ‘lead profile chart’). As far as can be determined, this analysis represents the first application of the ‘lead profile’ evaluation to financial variables. Chapter six concludes by presenting a summary of the results and a brief comparison with findings from an econometric study of leading indicators for South Africa.

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