HTime series using Holt-Winters Forecasting Procedure Summary The Holt-Winters forecasting procedure is a simple widely used projection method which can cope with trend and seasonal variation. We can apply this method to lots of fields such as banking data analysis‚ investment forecasting‚ inventory controlling and so on. This paper shows us a practical banking credit card example using Holt-Winter method in Java programming for data forecasting. The reason we use Holt-Winter is that
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changed easily by using certain accounting methods or manipulating accruals. When discovered‚ this information will have a negative effect on a company ’s share price and its reputation in general. Methods of Income Smoothing In order to present a more positive result to shareholders and a more favorable view of company’s results‚ numerous methods exist that can be used by accountants. Most methods are achieved by using book entries. The Depreciation Method The Depreciation Method is one of the
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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 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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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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on data from the past and present and analysis of trends. Forecasting entails the use of historic data to determine the direction of future trends. Forecasting is used by companies to determine how to allocate their budgets for an upcoming period of time. This is typically based on demand for the goods and service it offers compared to the cost of producing them. Investors utilize forecasting to determine if events affecting a company‚ such as sales expectations will increase or decrease the price
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Time Series Analysis: The Multiplicative Decomposition Method Table of Contents Page Abstract………………………………………………………………………………………………………………………………………….3 Introduction………………………………………………………………………………………………………………………...…4-5 Methodology: Multiplicative Decomposition……………………………………………….…5-7 Advantages/Disadvantages of Multiplicative Method………………………………7-8 Conclusion…………………………………………………………………………………………………………………………………..8 Abstract One of the most essential pieces
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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)
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Competition environment 4.9.2 How –simulation method There are many ways to create a forecast for a certain goods that a planner can use just one or combine many methods together. According to Chopra and Meindl define these methods as follows: 1. Qualitative methods Rely upon a person’s intuition or subjective opinions about a market. These methods are most appropriate when there is not much historical data to work with. 2. Causal methods assume that demand is strongly related to a particular
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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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