The thesis has for objective to study new statistical methods to correct temperature predictionsthat may be implemented on the ensemble prediction system (EPS) of Meteo France so toimprove its use for the electric system management, at EDF France. The EPS of Meteo Francewe are working on contains 51 members (forecasts by time-step) and gives the temperaturepredictions for 14 days. The thesis contains three parts: in the first one we present the EPSand we implement two statistical methods improving the accuracy or the spread of the EPS andwe introduce criteria for comparing results. In the second part we introduce the extreme valuetheory and the mixture models we use to combine the model we build in the first part withmodels for fitting the distributions tails. In the third part we introduce the quantile regressionas another way of studying the tails of the distribution.

歷經國內外多起知名企業的財務弊案後，各國政府及投資人開始關注公司的資訊透明度，企業也意識到資訊透明度對於企業永續經營的重要性，因此，本研究主要探討資訊透明度對於企業價值之影響。研究貢獻在於以具有專業和分析能力之分析師預測行為作為判斷企業資訊透明度之依據，進而探究其與企業價值之關聯性。本研究以2008年到2013年台灣上市(櫃)公司為樣本，以企業價值(Tobin’s Q)為應變數，資訊透明度相關之變數(分析師追蹤意願、分析師盈餘預測偏誤與分析師盈餘預測離散性)為主要解釋變數，在控制公司成長面、獲利面、風險面與公司規模因素，並固定產業和年份，利用追蹤資料迴歸模型(panel regression)來進行分析。 實證結果分為兩部分，（1）代表資訊透明度之變數－分析師預測意願、分析師預測精準度及分析師預測離散性與企業價值具有顯著正向關係。另利用前述之結果，本研究自行建立一個衡量企業透明度的模型，以整合性資訊探討資訊透明度對於企業價值的影響，實證結果顯示（2）資訊透明度與企業價值間確實具有顯著正向關係，結果支持良好的資訊透明度，有助於公司治理，長期間更能夠提升企業價值與永續經營。此外，本研究以整合資訊衡量企業資訊透明度，相較於單一資訊更為完善，也提供企業利害關係人及一般大眾不同面相去了解企業的資訊透明度，進而保護其權益。 / Since the occurrences of financial scandal, issues surrounding corporate governance and information disclosure have been widely discussed in these few years. Not only have government and investors started paying more attention on information transparency, but more and more firms have noticed that well corporate governance could help its sustainable development. The main purpose of this study is to examine the influences of information transparency on corporate value. Based on the samples of Taiwan listed firms for the period from 2009 to 2013, this study employs panel regression model with Corporate value (Tobin’s Q) as the dependent variable against various combinations of explanatory variables (analysts following, analysts’ earnings forecast bias and analysts’ earnings forecast derivation). The results of this research reveal that (1) the firms with high corporate value significantly have more analysts following, less analyst's earning forecast error and the greater forecast derivation. And by using an integrated model to do further analysis, the evidence shows that (2) higher information transparency could improve the corporate governance, gain more corporate value and benefit sustainable development in the long term. What’s more, instead of unitary source, this research measures corporate information transparency via integrated sources to ensure credibility, and provides various angles for corporate stakeholders and the general public to learn further more about corporate information transparency and be able to protect their rights.

協同規劃、預測與補貨（Collaborative Planning, Forecasting and Replenishment; CPFR）是協同商務中一個新發展的應用實務，主要強調供應鏈上買賣雙方協同合作流程的概念，以提升供應鏈上流程的處理效率。企業需要利用協同合作所獲得之即時資訊來進行預測，減少不確定性因素之影響，提高預測之準確性。CPFR流程下協同預測階段分為銷售預測與訂單預測，兩者之預測項目與目的並不相同且所需要之資訊亦有所差異。銷售預測著重在市場需求部份的預測；訂單預測則是依據銷售預測、存貨狀況與生產面因素來做實際訂單之預測。由於訂單預測作為下個階段之實際補貨的參考，其預測準確性的要求就格外重要。然而研究文獻多偏向CPFR流程架構與導入效益等管理議題，雖有少數針對預測模型之研究，但亦以企業內部銷售預測為主，並未有文獻提出跨企業之協同訂單預測模型，故CPFR流程下訂單預測方法之研究探討有其必要性。本研究以CPFR流程中接續銷售預測之訂單預測階段為研究主題，蒐集近年來國內外研究CPFR與訂單預測之相關文獻為基礎，歸納出協同合作下訂單預測所須具備之屬性與影響因素，並作為模型解釋變數，透過時間序列、多元迴歸與演化策略法（Evolution Strategies）的結合，建構一個統整供應鏈上、下游協同資訊與符合CPFR流程下訂單預測特性之預測模型。最後以國內某製造業公司與其顧客（一國際大型零售商）之訂單資料進行模型驗證，與單純使用時間序列方法或統計迴歸分析的預測結果作績效評比，實驗顯示本研究所提出之訂單預測方法較傳統使用單一時間序列或統計回歸方法之預測結果佳。 / Collaborative Planning, Forecasting and Replenishment (CPFR) is nowadays a practice of collaborative commerce, emphasizing buyers and sellers’ coordination for the efficiency of the process in supply chain. Enterprises utilize instant information obtained from coordinate processes to forecast in order to reduce the influence of the uncertain factor and improve forecasting accuracy. The stage of the collaborative forecasting in CPFR process is divided into sales forecasting and order forecasting which make differences on forecasting objective, subject, and information needed. Sales forecasting focuses on the prediction of the market demand; order forecasting is the prediction of the real orders according to sales forecasting, stock state and productive factor. The accuracy of order forecasting is extremely important because it is regarded as the reference of the replenishment at next stag. The literatures about CPFR mostly probe into manage topics like benefits of implementation or process structures though there are some researches on the forecasting model which mainly discuss sales forecasting inside enterprises. Therefore, it is necessary to investigate into the coordinative order forecasting model under CPFR process. This paper regards order forecasting following sales forecasting in CPFR as the theme. Besides generalizing the necessary parameter of order forecasting based on literatures review, the research presents a hybrid forecasting model which considers coordinative information and order forecasting requirements. It integrates the time series model, regression model, and use evolution strategies to determine its coefficients efficiently. The validity of the forecasting model is verified by experiment on order datum from one manufacturer in Taiwan and its international retailer. The results show that the order forecasting model has better forecasting performance than not only the time series model but also the ordinary regression model.

The thesis deals with the issue of long-term strategy for the development of social services in the municipality with extended scope Světlá nad Sázavou to r. 2030. The aim was to describe the current situation in selected municipalities in terms of facilities and related social services to handle the forecast population on a given territory by 2030 and ratify the lessons learned in terms of the need for social services in the interviews with key players in the field of social and related services. The theoretical part is focused mainly on the concept and characteristics of social services and related issues with regard to demographic changes. The practical part is divided into three parts. In the case study, I firstly describe the current state of social and health services in the municipality with extended powers Světlá. In the second part of the thesis, I compiled the forecast population of the selected area by 2030. In the final part in order to achieve the objective I conducted interviews with key personnel in social services in the studied area. The conducted research has revealed several recommendations for the town Světlá. In the future, it would be appropriate to support outreach and outpatient services, and increasingly develop cooperation with existing non-profit organization that operate in the selected area. It is also necessary to resolve the issue in an appropriate manner of people at risk of social exclusion. By 2030, the increase in the number of people older than 65 years in the studied area almost doubled. With that will surely come the need to extend existing capabilities of social services. For the city, it follows in the next 15 years to take appropriate action in response to the social policy of the state. The current system of financing social services and the care allowance is assessed as ineffective and requires appropriate legislative adjustment, so that the network of social services in the Czech Republic in the future, is prepared for the expected demographic trends.

Submitted by Marcia Bacha (marcia.bacha@fgv.br) on 2011-04-12T19:42:27Z No. of bitstreams: 1 000406591.pdf: 5825955 bytes, checksum: a09d43a0b53cba39f568bd3b137cef16 (MD5) / Approved for entry into archive by Marcia Bacha(marcia.bacha@fgv.br) on 2011-04-12T19:44:07Z (GMT) No. of bitstreams: 1 000406591.pdf: 5825955 bytes, checksum: a09d43a0b53cba39f568bd3b137cef16 (MD5) / Made available in DSpace on 2011-04-12T19:44:32Z (GMT). No. of bitstreams: 1 000406591.pdf: 5825955 bytes, checksum: a09d43a0b53cba39f568bd3b137cef16 (MD5) Previous issue date: 2008-05-01 / Com a entrada do regime cambial flutuante no Brasil a partir de 1999, o mercado de derivativos cambiais se desenvolveu muito. A crescente demanda das empresas e instituições financeiras pelos produtos de hedge cambial junto a um novo panorama econômico mundial foram as causas desse desenvolvimento. Esse trabalho procura encontrar tendências para o mercado de derivativos cambiais brasileiro estimando parâmetros através de regressões entre séries não-estacionárias, porém cointegradas. E utilizado o modelo de correção de erros para fazer as previsões. Os resultados mostram que o crescimento do mercado ocorre em função da corrente de comércio exterior e PIB, que os produtos mais utilizados para operações de curto e longo prazos tendem a ser o dólar futuro e as opções cambiais e que, no futuro, algumas outras moedas terão participação significativa no mercado brasileiro.

The thesis presents the results of a study on the impact of International Financial Reporting Standards on the analysts information environment. The analysis is concentrated on the role of specific IFRSs and corporate disclosure. The effect of IFRS adoption on the information asymmetry between firms and outsiders is examined through properties of analysts earnings forecasts. A contribution to the existing academic literature is made by examining the role of goodwill, intangible assets and acquisitions before and after IFRS adoption in Europe. The results show that the IFRSs for goodwill, acquisitions and intangible assets are related to improvements in the analysts information environment. Another contribution to knowledge is made by investigating the effect of corporate disclosure quantity on the analysts information environment before and after IFRS adoption. For this purpose, a new approach and text analysis technique to assess the impact of corporate disclosure quantity is developed. This involves the creation of a new custom dictionary and the collection of an extensive set of qualitative data. The results show that corporate disclosure quantity under IFRS, is related to improvements in the analysts information environment but that there are differences in this effect across European countries. The results also demonstrate that the improvements in the accuracy of analysts earnings forecasts are related particularly to disclosure concerning financial instruments and operating segments. Overall, the findings of the thesis suggest that the adoption of IFRS resulted in an increase in the quality of reported earnings, which is likely to derive from higher comparability of financial statements, enhanced transparency and an improved analysts information environment. It is also established that fundamental differences across countries remain after IFRS adoption and that the development and harmonisation of financial reporting standards alone are not sufficient to increase the quality of financial information and decrease information asymmetry between market participants.

Submitted by Geandra Rodrigues (geandrar@gmail.com) on 2018-01-17T11:13:15Z No. of bitstreams: 1 samuelbelinidefilippo.pdf: 2610291 bytes, checksum: 6c4f48d00a0649b56977f6c8a7ada4e0 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2018-01-22T16:33:53Z (GMT) No. of bitstreams: 1 samuelbelinidefilippo.pdf: 2610291 bytes, checksum: 6c4f48d00a0649b56977f6c8a7ada4e0 (MD5) / Made available in DSpace on 2018-01-22T16:33:53Z (GMT). No. of bitstreams: 1 samuelbelinidefilippo.pdf: 2610291 bytes, checksum: 6c4f48d00a0649b56977f6c8a7ada4e0 (MD5) Previous issue date: 2017-09-20 / Todo a produção, transmissão e distribuição de energia elétrica ocorre concomitantemente com o consumo da energia. Isso é necessário porque ainda não existe hoje uma maneira viável de se estocar energia em grandes quantidades. Dessa forma, a energia gerada precisa ser consumida quase que instantaneamente. Isso faz com que as previsões de demanda sejam fundamentais para uma boa gestão dos sistemas de energia. Esse trabalho focaliza métodos de previsão de demanda a curto prazo, até um dia à frente. Nos métodos mais simples, as previsões são feitas por modelos lineares que utilizam dados históricos da demanda de energia. Contudo, modelos baseados em inteligência computacional têm sido estudados para este fim, por explorarem a relação não-linear entre a demanda de energia e as variáveis climáticas. Em geral, estes modelos conseguem melhores previsões do que os métodos lineares. Seus resultados, porém, são instáveis e sensíveis a erros de medição, gerando erros de previsão discrepantes, que podem ter graves consequências para o processo de produção. Neste estudo, empregamos redes neurais artificiais e algoritmos genéticos para modelar dados históricos de carga e de clima, e combinamos estes modelos com métodos lineares tradicionais. O objetivo é conseguir previsões que não apenas sejam mais acuradas em termos médios, mas que também menos sensíveis aos erros de medição. / The production, transmission and distribution of electric energy occurs concomitantly with its consumption. This is necessary because there is yet no feasible way to store energy in large quantities. Therefore, the energy generated must be consumed almost instantaneously. This makes forecasting essential for the proper management of energy systems. This thesis focuses on short-term demand forecasting methods up to one day ahead. In simpler methods, the forecasts are made by linear models, which use of historical data on energy demand. However, computer intelligence-based models have been studied for this end, exploring the nonlinear relationship between energy demand and climatic variables. In general, these models achieve better forecasts than linear methods. Their results, however, are unstable and sensitive to measurement errors, leading to outliers in forecasting errors, which can have serious consequences for the production process. In this thesis, we use artificial neural networks and genetic algorithms for modelling historical load and climate data, and combined these models with traditional linear methods. The aim is to achieve forecasts that are not only more accurate in mean terms, but also less sensitive to measurement errors.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-03-02T12:24:39Z No. of bitstreams: 1 annaclaudiamancinidasilvacarneiro.pdf: 1333903 bytes, checksum: a7b3819bb5b0e1adb8efd07bca0f9aa2 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-03-06T19:35:55Z (GMT) No. of bitstreams: 1 annaclaudiamancinidasilvacarneiro.pdf: 1333903 bytes, checksum: a7b3819bb5b0e1adb8efd07bca0f9aa2 (MD5) / Made available in DSpace on 2017-03-06T19:35:55Z (GMT). No. of bitstreams: 1 annaclaudiamancinidasilvacarneiro.pdf: 1333903 bytes, checksum: a7b3819bb5b0e1adb8efd07bca0f9aa2 (MD5) Previous issue date: 2014-09-26 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A previsão de cargas elétricas é fundamental para o planejamento das empresas de energia. O foco deste estudo são as previsões a curto prazo; assim, aplicamos métodos univariados de previsão de séries temporais a uma série real de cargas elétricas de 104 semanas no Rio de Janeiro, nos anos de 1996 e 1997, e experimentamos várias combinações dos métodos de melhor desempenho. As combinações foram feitas pelo método outperformance, uma combinação linear simples, com pesos fixos. Os resultados das combinações foram comparados ao de simulações de redes neurais artificiais que solucionam o mesmo problema, e ao resultado de um método de amortecimento de dupla sazonalidade aditiva. No geral, este método de amortecimento obteve os melhores resultados, e talvez seja o mais adequado e confiável para aplicações práticas, embora necessite de melhorias para garantir a extração completa da informação contida nos dados. / Forecasting the demand for electric power is crucial for the production planning in energy utilities. The focus of this study are the short-term forecasts. We apply univariate time series methods to the forecasting of a series containing observations of the energy consumption of 104 weeks in Rio de Janeiro, in 1996 and 1997, and experiment with several combinations of the methods which have the best performance. These combinations are done by the outperformance method, a simple linear combination with fixed weights. The results were compared to those obtained by neural networks on the same problem, and with the results of a exponential smoothing method for dual additive seasonality. Overall, the exponential smoothing method achieved the best results, and was shown to be perhaps the most reliable and suitable for practical applications, even though it needs improvements to ensure complete extraction of the information contained in the data.

Sogeti is an IT consulting company that’s active in large parts of the world. One of their biggest clients in Sundsvall is SCA Skog. In case of fire risk, SCA parti- cipates in consultation meetings with contractors to determine fire prevention measures. SMHI’s fire forecasts and warnings are a few of the bases that deter- mine when a consultation meeting is to begin. The problem is that the contractor today does not receive an automatic indication of fire risk. The purpose of the project was therefore to investigate SMHI’s services and find a solution to the problem and to find a limit for when a consultation meeting should be initia- ted based on the risk within an area. The solution presented is illustrated by a proof-of-concept model. The work has been carried agile in sprinting. Data has been taken from SMHI for a more detailed documentation over warnings and against MSB for the raw data that is behind fire forecasts so that those can be included in the solution. The project has resulted in an application that supports indication of risk based on a list of coordinates as well as automatic indication to the user’s position. An implementation guide was also created to facilitate a possible further development of the solution. The investigation shows that fire forecasts give a more precise indication of danger, but warnings should not be overlooked, as they indicate a risk of other warnings than fire risk. The solution is only intended to give the contractor an additional tool when making a deci- sion. The responsibility remains with the contractor, but the tool will hopefully allow the right decision to be made. / Sogeti är ett IT-konsultföretag med kontor i många länder. En av deras största klienter i Sundsvall är SCA Skog. Vid brandrisk deltar SCA tillsammans deras entreprenörer i samrådsmöten för att bestämma brandförebyggande åtgärder. SMHI:s brandprognoser och varningar är ett par av de underlag som avgör när ett samrådsmöte ska inledas. Problemet är att entreprenören idag inte får en automatisk indikation för brandrisk. Syftet med projektet blev därför att undersöka SMHI:s tjänster och finna en automatisk lösning samt att hitta en gräns för när ett samrådsmöte bör inledas baserat på brandrisken inom ett område. Den lösning som tagits fram illustreras genom en Proof-of-Concept modell. Arbetet har utförts agilt i sprintar. En datainsamling har utförts mot SMHI för en mer detaljerad dokumentation och mot MSB för den rådata som ligger bakom brandprognoser så att detta kan inkluderas i lösningen. Projektet har resulterat i en applikation som stödjer indikation av risk baserat på geografiska positioner samt automatisk indikation av risk vid en användares position. En implementationsguide togs även fram för att underlätta en möjlig vidareutveckling av lösningen. Undersökningen visar att brandprognoser ger en mer precis indikation på fara däremot bör varningar inte helt förbises då dessa kan indikera risk vid andra varningar än just brandrisk. Lösningen är enbart avsedd att ge entreprenören ett extra verktyg när denne ska ta ett beslut. Ansvaret ligger fortfarande hos entreprenören men en implementation möjliggör att beslut kan tas med gott un- derlag.

SMHI:s hydrologiska prognos- och varningstjänst använder sig av meteorologiska ensembleprognoser som indata i hydrologiska modeller. De hydrologiskaensembleprognoserna tar därmed hänsyn till framtida osäkerhet i temperatur och nederbördoch används som underlag vid utfärdandet av risker och varningar för höga flöden. För närvarande beaktas dock inte osäkerheten i modellens starttillstånd, vilket består av de tillståndsvariabler i modellen som beskriver bland annat markvattenhalt och snötäcke. I dennastudie undersöktes hur starttillståndet i den hydrologiska modellen HYPE inverkar på prognoser i syfte att kvantifiera osäkerheten och på sikt möjliggöra säkrare prognoser.Studien hade tre mål: 1) Ta fram ett förslag på hur starttillståndet kan varieras för att ge en god uppskattning av prognososäkerheten relaterat till det hydrologiska starttillståndet. 2) Undersöka sambandet mellan starttillståndens spridning och det hydrologiska prognosfelet. 3) Analysera hur årstider, avrinningsområdens area, sjöprocent, skogsprocent och höjd över havet inverkar på prognososäkerheten. En central hypotes var att mindre skillnad mellan starttillståndets vattenföring och den observerade vattenföringen vid prognosstart resulterar i mer träffsäkra prognoser. Studien begränsades av att starttillstånden endast genererades med hjälp av störningar i drivdata.Indata till HYPE-modellen var femton temperatur- och nederbördsserier som manipulerats i syfte att skapa en ensemble av olika starttillstånd. Denna ensemble användes sedan för att göra vattenföringsprognoser med observerad temperatur och nederbörd som drivdata. Studien omfattade 76 avrinningsområden från hela Sverige med data för perioden 1999-2008. Prognoser utfördes varje dygn och ensemblespridningen utvärderades 2, 4 och 10 dygn in i prognosen. Samma utvärderingar utfördes även på autoregressiva prognoser, vilket innebär att modellerad rättas utefter observerad vattenföring.Resultaten indikerade ett samband mellan ensemblespridning och prognosfel, vilket innebär att spridning kan användas som ett mått på starttillståndets osäkerhet. Prognosfelet korrelerade positivt med skogsprocent och negativt med avrinningsområdenas area, sjöprocent och höjd över havet. Samma samband uppvisades mellan dessa områdesvariableroch spridning. Spridningen var störst på vintern och våren då normalisering skett med medelvattenföring över tio år, och under vår och sommar då normalisering skett med medelvattenföring per månad. Hypotesen att mindre skillnad mellan starttillståndets vattenföring och den observerade vattenföringen vid prognosstart resulterar i mer träffsäkraprognoser bekräftades av resultaten. Implementering av en ensemble av olika starttillstånd i operationella prognoser vid SMHIs hydrologiska prognos- och varningstjänst föreslås i syfte att kvantifiera osäkerheten och därigenom utöka bedömningsunderlaget vid utfärdande av risker och varningar. / The Hydrological Forecast and Warning Service of The Swedish Meteorological and Hydrological Institute (SMHI) use meteorological ensemble forecasts as input in hydrological models. The hydrological ensemble forecasts take the uncertainty of future temperature and precipitation into account and serve as the basis of issued risks and warnings of high flows. Currently not considered is the uncertainty of the initial state, which consists of state variables in the model describing for instance soil water content and snow pack. This study assessed the impact of the initial state on forecasts in the hydrological model HYPE aiming to quantify the uncertainty and eventually enable more accurate forecasts.There were three aims of this study : 1) Evaluate a suggestion about how the initial state can be varied to give a good estimation of forecast uncertainty related to the hydrological initial state. 2) Examine the relationship between the spread of initial states and the hydrological forecast error. 3) Analyze the impact of seasons, catchment area, lake percentage, forest percentage and elevation on forecast uncertainty. A central hypothesis was that a smaller difference between the discharge of the initial state and the observed discharge results in more accurate forecasts. A restriction of the study was that the initial states only could be generated by disturbances of forcing data in before the forecast.Input data to the HYPE model were fifteen temperature and precipitation series, manipulated to generate an ensemble of different initial states. This ensemble was then used to make discharge forecasts with observed temperature and precipitation as forcing data. The study was performed on 76 catchments all over Sweden with data from the time period 1999-2008. Forecasts were made every day and the ensemble spread was evaluated 2, 4 and 10 days into the forecast. Autoregressive forecasts where the modelled discharge is corrected after the observed discharge were executed and evaluated as well. The results indicated a relationship between ensemble spread and forecast error, which implies that the spread can be used as a measure of the uncertainty of the initial state. The forecast error and ensemble spread correlated positively to forest percentage and negatively to catchment area, lake percentage and elevation. The same trend was detected between spread and catchment characteristics. The spread was biggest in winter and spring when normalization was made with mean discharge for the ten-year period and in spring and summer when normalization was done with mean discharge per month. The hypothesis that a smaller difference between the discharge of the initial state and the observed discharge results in more accurate forecasts was confirmed by the results. An implementation of an ensemble of different initial states in operational forecasts at SMHI’s Hydrological Forecast and Warning Service is suggested in order to further quantify the uncertainty of hydrological forecasts, and thereby improve the basis of judgment when issuing risks and warnings.