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    Energy Market (EEM) • 25-27 May 2011 • Zagreb‚ Croatia Electricity price forecasting – ARIMA model approach Tina Jakaša #1‚ Ivan Andročec #2‚ Petar Sprčić *3 Hrvatska elektroprivreda Ulica grada Vukovara 37‚ Zagreb‚ Croatia 2 # tina.jakasa@hep.hr ivan.androcec@hep.hr 1 * HEP Trade Ulica grada Vukovara 37‚ Zagreb‚ Croatia 2 petar.sprcic@hep.hr Abstract— Electricity price forecasting is becoming more important in everyday business of power utilities. Good forecasting models

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    running a business. Objectives The aim of this section is to help you to prepare financial forecasts. It will enable you to: • Understand costing and pricing; • Use break-even analysis as a way of setting sales targets; • Understand financial forecasting; and‚ • Assess working capital requirements. Assignment The purpose of these assignments is to ensure that you are able to prepare the necessary financial forecasts for your business. Satisfactory completion of the set of assignments

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    Eight Steps to Forecasting •  Determine the use of the forecast □ What objective are we trying to obtain? •  Select the items to be forecast •  Determine the time horizon of the forecast □ Short time horizon – 1 to 30 days □ Medium time horizon – 1 to 12 months □ Long time horizon – more than 1 year •  Select the forecasting model(s) |Description |Qualitative Approach |Quantitative Approach

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    UNIT 6 DEMAND ESTIMATION AND FORECASTING Objectives By studying this unit‚ you should be able to: identify a wide range of demand estimation and forecasting methods; apply these methods and to understand the meaning of the results; understand the nature of a demand function; identify the strengths and weaknesses of the different methods; understand that demand estimation and forecasting is about minimising risk. Structure 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8 6.9 Introduction Estimating Demand Using

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    The Policy Process Part II Lenue Richardson HCS/455 March 14‚ 2013 University of Phoenix The Policy Process Part II Introduction The development of policy is not something that can be done in an efficient manner. However; there are times when policies are very burdensome and can be a very big challenge‚ one that is loaded with all sorts of committees and everything else‚ it is truly an experience. Although the creating of a policy is a very different experience it is necessary

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    1) Raw data‚ not seasonalized 2) Seasonal Adjustment used: Census II X-12 multiplicative (MASA): Used because of the presence of seasonal variations that are increasing with the level of my series. Increasing degree of variability overtime… TX non seasonalized and seasonalized 3) Combined seasonally adjusted with non-seasonally adjusted De-seasonalizing the data helped with the removal of seasonal component that creates higher volatility in model. Now‚ variations

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    Manager’s Guide to Forecasting by David M. Georgoff and Robert G. Murdick Harvard Business Review Reprint 86104 J A N U A RY– F E B R U A RY 1 9 8 6 HBR Manager’s Guide to Forecasting David M. Georgoff and Robert G. Murdick E arly in 1984‚ the Houston-based COMPAQ Computer Corporation‚ manufacturer of IBMcompatible microcomputers‚ faced a decision that would profoundly affect its future. Recognizing that IBM would soon introduce its version of the portable computer and threaten

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    ANC Introduction: Headlines: • Typhoon ‘Lawin’ gets stronger‚ heads far northern Luzon • Eye of ’Lawin’ to spare northern Luzon: PAGASA • CebuPac cancels 4 Caticlan flights • ’Lawin’ slightly weakens Reporter 1: Typhoon ‘Lawin’ gets stronger‚ heads far northern Luzon Typhoon “Lawin” sped up slightly as it continued its movement towards the northern Philippines‚ the state weather bureau said. At 4 p.m. Wednesday‚ the eye of the supertyphoon was plotted by satellite and surface data at

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    LECTURE 3 CASH BUDGETING CLASS QUESTION 1 Alberta Limited needs a cash budget for the month of November.  The following information is available: The cash balance on November 1 is $6‚000. Sales for October and November are $80‚000 and $60‚000 respectively.  Cash collections on sales are 30 percent in the month of sale‚ 65 percent in the following month‚ and 5 percent uncollectible. General expenses are budgeted to be $23‚000 for November. Inventory purchases will total $30‚000 in October and

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    Issues 1.1 What is forecasting? Forecasting is the process of making statements about future happenings based on the previous data collected. Forecasting usually is an estimation of the future data‚ happenings‚ trends‚ values‚ etc for the specified date. A commonplace example is estimation of the expected value for some variable of interest at some specified future data. The forecasting is similar to the prediction‚ but more general term. However‚ as the term implies‚ forecasting is not necessarily

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