FORECASTING FORECASTING The Role of the Manager Planning Organizing Staffing Leading Controlling Future ? Data Information • Short-range • Medium-range • Long-range Features Common to All Forecasts Forecasting techniques generally assume that same underlying causal system that existed in the past will continue to exist in the future. Forecasts are rarely perfect. Forecasts for groups of items tend to be more accurate than forecasts for individual items. Forecast
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Forecasting Why forecast? Features Common to all Forecasts • Conditions in the past will continue in the future • Rarely perfect • Forecasts for groups tend to be more accurate than forecasts for individuals • Forecast accuracy declines as time horizon increases Elements of a Good Forecast • Timely • Accurate • Reliable (should work consistently) • Forecast expressed in meaningful units • Communicated in writing • Simple to understand and use Steps in Forecasting Process
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FINANCIAL MODELING The materials in this book are intended for instructional and educational purposes‚ to illustrate situations similar to those encountered in the real world. The reader will understand that MIT Press and its authors do not guarantee the accuracy or completeness of any information published in this book. Neither MIT Press nor its authors is responsible for the consequences of the implementation of models or information presented in this book. FINANCIAL MODELING Simon Benninga
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FORECASTING Q1: Moving averages are often used to identify movements of stock prices. Weekly closing prices (in $ per share) for Toys Я Us for 22 September‚ 1997‚ through December 8‚ 1997‚ are as follows (Prudential Securities Inc); Month Sept 22 Sept 29 Oct 6 Oct 13 Oct 20 Oct 27 Nov 3 Nov 10 Nov 17 Nov 24 Dec 1 Dec 8 Fund Price 37.8750 35.6250 34.6875 33.5625 32.6250 34.0000 33.6250 35.0625 34.0625 34.1250 33.2500 32.0625 a. Use a 3-month simple moving average
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Portfolio optimization - a practical approach Andrzej Palczewski Institute of Applied Mathematics Warsaw University June 29‚ 2008 1 Introduction The construction of the best combination of investment instruments (investment portfolio) is a principal goal of investment policy. This is an optimization problem: select the best portfolio from all admissible portfolios. To approach this problem we have to choose the selection criterion first. The seminal paper of Markowitz [8] opened a new era
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Scilab Datasheet Optimization in Scilab Scilab provides a high-level matrix language and allows to define complex mathematical models and to easily connect to existing libraries. That is why optimization is an important and practical topic in Scilab‚ which provides tools to solve linear and nonlinear optimization problems by a large collection of tools. Overview of the industrial-grade solvers available in Scilab and the type of optimization problems which can be solved by Scilab. Objective
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understand the nature of demand and competition in order to develop realistic business plans‚ determine a strategic vision for the organization‚ and determine technology and infrastructure needs. To address these challenges‚ forecasting is used. According to Makridakis (1989)‚ forecasting future events can be characterized as the search for answers to one or more of the following questions: X What new economic‚ technical‚ or sociological forces is the organization likely to face in both the near and long
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Forecasting Techniques Forecasting is the methodology utilized in the translation of past experiences in an estimation of the future. The German market presents challenges for forecasting techniques especially for its retail segment. Commercially oriented organizations are used to help during forecasting as general works done by academic scientists are not easy to come across (Bonner‚ 2009). The qualitative method of forecasting is one in which an educated opinion of relevant individuals
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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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Solutions to suggested cases WARNING: Good studying practice suggests that you attempt the problems before looking at the solutions. You learn and retain more from making mistakes than merely referring to pro forma solutions Problem 1-16 1-16. Instructors might want to mention that this problem asks students to consider the accounting information needs of a subset of not-for-profit organizations‚ and to note that the accounting data required by them often does not differ much from for-profit
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