on the importance of forecasting. The presentation would be done along the following lines. * THE MEANING OF FORECASTING * STEPS USED TO DEVELOP A FORECASTING SYSTEM * QUALITATIVE FORECASTING * QUANTITATIVE FORECASTING * BENEFITS OF FORECASTING THE MEANING OF FORECASTING A planning tool that helps management in its attempts to cope with the uncertainty of the future‚ relying mainly on data from the past and present and analysis of trends. Forecasting entails the use of
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Forecasting Trends in Time Series Author(s): Everette S. Gardner‚ Jr. and Ed. McKenzie Reviewed work(s): Source: Management Science‚ Vol. 31‚ No. 10 (Oct.‚ 1985)‚ pp. 1237-1246 Published by: INFORMS Stable URL: http://www.jstor.org/stable/2631713 . Accessed: 20/12/2012 02:05 Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use‚ available at . http://www.jstor.org/page/info/about/policies/terms.jsp . JSTOR is a not-for-profit service that helps scholars‚ researchers
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TIME SERIES AND FORECASTING McGrawHill/Irwin Copyright © 2010 by The McGrawHill Companies‚ Inc. All rights reserved. Time Series and its Components TIME SERIES is a collection of data recorded over a period of time (weekly‚ monthly‚ quarterly)‚ an analysis of history‚ that can be used by management to make current decisions and plans based on long-term forecasting. It usually assumes past pattern to continue into the future Components of a Time Series 1. 2. 3. 4. Secular Trend – the smooth
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Neurocomputing 55 (2003) 307 – 319 www.elsevier.com/locate/neucom Financial time series forecasting using support vector machines Kyoung-jae Kim∗ Department of Information Systems‚ College of Business Administration‚ Dongguk University‚ 3-26‚ Pil-dong‚ Chung-gu‚ Seoul 100715‚ South Korea Received 28 February 2002; accepted 13 March 2003 Abstract Support vector machines (SVMs) are promising methods for the prediction of ÿnancial timeseries because they use a risk function consisting of the
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Forecasting Models: Associative and Time Series Forecasting involves using past data to generate a number‚ set of numbers‚ or scenario that corresponds to a future occurrence. It is absolutely essential to short-range and long-range planning. Time Series and Associative models are both quantitative forecast techniques are more objective than qualitative techniques such as the Delphi Technique and market research. Time Series Models Based on the assumption that history will repeat itself‚
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Time Series Models for Forecasting New One-Family Houses Sold in the United States Introduction The economic recession felt in the United States since the collapse of the housing market in 2007 can be seen by various trends in the housing market. This collapse claimed some of the largest financial institutions in the U.S. such as Bear Sterns and Lehman Brothers‚ as they held over-leveraged positions in the mortgage backed securities market. Credit became widely available to unqualified borrowers
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TIME SERIES ANALYSIS Introduction Economic and business time series analysis is a major field of research and application. This analysis method has been used for economic forecasting‚ sales forecasting‚ stock market analysis and company internal control. In this paper‚ we will talk about time series and review techniques that are useful for analyzing time series data. Definition of Time Series and Time Series Analysis Time series is an ordered sequence of values of a variable at equally spaced
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TIME SERIES ANALYSIS Chapter Three Univariate Time Series Models Chapter Three Univariate time series models c WISE 1 3.1 Preliminaries We denote the univariate time series of interest as yt. • yt is observed for t = 1‚ 2‚ . . . ‚ T ; • y0‚ y−1‚ . . . ‚ y1−p are available; • Ωt−1 the history or information set at time t − 1. Call such a sequence of random variables a time series. Chapter Three Univariate time series models c WISE 2 Martingales Let {yt} denote
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Question 5 - 10 marks (Equity Options) It is January 2nd‚ 2014 and Google Inc. (GOOG) stock is currently trading on the Nasdaq at a price of $1‚105.00 US dollars. Using the information provided below‚ please answer the following questions: (Note: ’Last’ means the last traded price of the put or call option. Use this number for your calculations). Call options: Put options: a) Based on the current stock price‚ which one of the two options is in the money? by how much? (1 marks) b)
Free Call option Strike price Options
TIME SERIES MODELS Time series analysis provides tools for selecting a model that can be used to forecast of future events. Time series models are based on the assumption that all information needed to generate a forecast is contained in the time series of data. The forecaster looks for patterns in the data and tries to obtain a forecast by projecting that pattern into the future. A forecasting method is a (numerical) procedure for generating a forecast. When such methods are not based upon
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