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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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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tactics implemented by management in order to become more competitive and world-class in their operations. Hard Rock Café has clearly made great strides in modernizing their business venue by utilizing sophisticated POS systems with the latest forecasting trends. Some tactics they have implemented include an extensive Point-of-sale system (POS)‚ which captures transaction data on nearly every person who walks through a cafe’s door. The sale of each entrée represents one customer. They forecast monthly
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fashion forecasting “Forecasting provides a way for executives to expand their thinking about changes‚ through anticipating the future‚ and projecting the likely outcomes.” (Lavenback and Cleary 1981) Long term forecasting (over 2 years ahead) is used by executives for planning purposes. It is also used for marketing managers to position products in the marketplace in relationship to competition. (http://www.fibre2fashion.com/industry-article/free-fashion-industry-article/fashion-forecasting/fashion-forecasting5
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The CFO can forecast exchange rates by using either of two approaches‚ fundamental forecasting or technical forecasting. Fundamental forecasting uses trends in economic variables to predict future rates. The data can be plugged into an econometric model or evaluated on a more subjective basis. Technical forecasting uses past trends in exchange rates themselves to spot future trends in rates. Technical forecasters‚ or chartists‚ assume that if current exchange rates reflect all facts in the market
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Demand Forecasting Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase. Demand forecasting involves techniques including both informal methods‚ such as educated guesses‚ and quantitative methods‚ such as the use of historical sales data or current data from test markets. Demand forecasting may be used in making pricing decisions‚ in assessing future capacity requirements‚ or in making decisions on whether to enter a new market.
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ITM UNIVERSITY ECONOMICS DETERMINANTS OF DEMAND SUBMITTED TO: Miss. Surti Dahuja SUBMITTED BY : SHUMYLA KHAN‚ KINNI KANSANA‚ SAGAR VYAS‚ Shibu lijack DEMAND “Demand for a commodity refers to the quantity of the commodity which an individual consumer or a household is willing to purchase per unit of time at a particular price”. Demand for a commodity implies – a) Desire of the consumer to buy the product‚ b) His willingness to buy the product‚ and c) Sufficient purchasing power in his pocket
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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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WEATHER ANALYSIS & FORECASTING ** Weather Analysis: process of collecting‚ compiling‚ analyzing and transmitting the observational data of atmospheric conditions *this data & analysis is then used to forecast future weather conditions * Types of data: * Each weather station‚ 10‚000 around the world‚ collects the same data at the same time‚ at least 4 times per day(0000‚ 0600‚1200‚ 1800 GMT) * Most US stations also collect data continuously or at least every hour
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