Applied Modeling & Forecasting QMIS 320 Chapter 1

Similar documents
Applied Modeling & Forecasting. Chapter 1

Introduction to Forecasting

Chapter 8 - Forecasting

Forecasting Practice: Decision Support System to Assist Judgmental Forecasting

Econometrics in a nutshell: Variation and Identification Linear Regression Model in STATA. Research Methods. Carlos Noton.

AUTO SALES FORECASTING FOR PRODUCTION PLANNING AT FORD

Empirical Project, part 1, ECO 672

Industrial Engineering Prof. Inderdeep Singh Department of Mechanical & Industrial Engineering Indian Institute of Technology, Roorkee

STAT 115: Introductory Methods for Time Series Analysis and Forecasting. Concepts and Techniques

Forecasting. Copyright 2015 Pearson Education, Inc.

The TransPacific agreement A good thing for VietNam?

Business Cycle Dating Committee of the Centre for Economic Policy Research. 1. The CEPR Business Cycle Dating Committee

Warwick Business School Forecasting System. Summary. Ana Galvao, Anthony Garratt and James Mitchell November, 2014

AN ECONOMETRICAL MODEL FOR CALCULATING THE ROMANIAN GROSS DOMESTIC PRODUCT

Chapter 5: Forecasting

Chapter 7 Forecasting Demand

A Comparison of Time Horizon Models to Forecast Enrollment

Business Statistics. Chapter 14 Introduction to Linear Regression and Correlation Analysis QMIS 220. Dr. Mohammad Zainal

A Summary of Economic Methodology

Research Brief December 2018

Assistant Prof. Abed Schokry. Operations and Productions Management. First Semester

Source: US. Bureau of Economic Analysis Shaded areas indicate US recessions research.stlouisfed.org

Forecasting: Methods and Applications

A Multistage Modeling Strategy for Demand Forecasting

Chapter 3 Multiple Regression Complete Example

2 Functions and Their

Topic 4 Forecasting Exchange Rate

Global and China Sodium Silicate Industry 2014 Market Research Report

Economics 390 Economic Forecasting

LATVIAN GDP: TIME SERIES FORECASTING USING VECTOR AUTO REGRESSION

QMT 3001 BUSINESS FORECASTING. Exploring Data Patterns & An Introduction to Forecasting Techniques. Aysun KAPUCUGİL-İKİZ, PhD.

Chapter 14 Student Lecture Notes Department of Quantitative Methods & Information Systems. Business Statistics. Chapter 14 Multiple Regression

Dennis Bricker Dept of Mechanical & Industrial Engineering The University of Iowa. Forecasting demand 02/06/03 page 1 of 34

Putting the U.S. Geospatial Services Industry On the Map

The Benchmarking in the official data in Mexico

NOWCASTING REPORT. Updated: April 15, 2016

NOWCASTING REPORT. Updated: May 20, 2016

Chapter 13: Forecasting

Time Series and Forecasting

FORECASTING. Methods and Applications. Third Edition. Spyros Makridakis. European Institute of Business Administration (INSEAD) Steven C Wheelwright

Time Series Econometrics For the 21st Century

Simple Regression Model. January 24, 2011

SHORT TERM LOAD FORECASTING

h Edition Money in Search Equilibrium

Forecasting Using Time Series Models

Lecture 4 Forecasting

14. Time- Series data visualization. Prof. Tulasi Prasad Sariki SCSE, VIT, Chennai

Forecasting: Principles and Practice. Rob J Hyndman. 1. Introduction to forecasting OTexts.org/fpp/1/ OTexts.org/fpp/2/3

CP:

TRANSMISSION BUSINESS LOAD FORECAST AND METHODOLOGY

On the Directional Predictability of Eurostoxx 50

Stationarity Revisited, With a Twist. David G. Tucek Value Economics, LLC

SAN DIEGO GAS AND ELECTRIC COMPANY SOUTHERN CALIFORNIA GAS COMPANY 2013 TRIENNIAL COST ALLOCATION PROCEEDING (A ) (DATA REQUEST DRA-MPS-2)

Time Series and Forecasting

The Central Bank of Iceland forecasting record

Dynamics and Monetary Policy in a Fair Wage Model of the Business Cycle

MA Advanced Macroeconomics: Solving Models with Rational Expectations

Vol. 5, No. 5 May 2014 ISSN Journal of Emerging Trends in Computing and Information Sciences CIS Journal. All rights reserved.

Endogenous information acquisition

Barnabas Chipindu, Department of Physics, University of Zimbabwe

Regression Models REVISED TEACHING SUGGESTIONS ALTERNATIVE EXAMPLES

Ch 13 & 14 - Regression Analysis

THE APPLICATION OF GREY SYSTEM THEORY TO EXCHANGE RATE PREDICTION IN THE POST-CRISIS ERA

ECON 427: ECONOMIC FORECASTING. Ch1. Getting started OTexts.org/fpp2/

Lecture 2 Differences and Commonalities among Developing Countries

Real Business Cycle Model (RBC)

Population and Employment Forecast

Toulouse School of Economics, Macroeconomics II Franck Portier. Homework 1. Problem I An AD-AS Model

Part A: Answer question A1 (required), plus either question A2 or A3.

INTRODUCTORY REGRESSION ANALYSIS

Graceway Publishing Company, Inc.

Forecasting: principles and practice. Rob J Hyndman 1.1 Introduction to Forecasting

Asitha Kodippili. Deepthika Senaratne. Department of Mathematics and Computer Science,Fayetteville State University, USA.

Business Statistics:

Bahrain Meteorological Services Structure For The Future. Shukry Jaffar Senior Meteorologist

NSP Electric - Minnesota Annual Report Peak Demand and Annual Electric Consumption Forecast

WP6 Early estimates of economic indicators. WP6 coordinator: Tomaž Špeh, SURS ESSNet Big data: BDES 2018 Sofia 14.,

Forecasting with Expert Opinions

Business Statistics. Chapter 6 Review of Normal Probability Distribution QMIS 220. Dr. Mohammad Zainal

NOWCASTING REPORT. Updated: August 17, 2018

NOWCASTING REPORT. Updated: May 5, 2017

Ørsted. Flexible reporting solutions to drive a clean energy agenda

Is economic freedom related to economic growth?

NOWCASTING REPORT. Updated: September 7, 2018

Types of economic data

IA_Core Curriculum Social Studies (2010) High School

Analysis of Gross National Product (GNP) in the form of time series

BEFORE THE PUBLIC UTILITIES COMMISSION OF THE STATE OF COLORADO * * * * *

NOWCASTING REPORT. Updated: September 14, 2018

CAN SOLAR ACTIVITY INFLUENCE THE OCCURRENCE OF RECESSIONS? Mikhail Gorbanev January 2015

Prentice Hall World Studies: Latin America 2005 Correlated to: Missouri Social Studies Grade Level Expectations (Grade 7)

Euro-indicators Working Group

Macroeconomics Field Exam. August 2007

ESRI Research Note Nowcasting and the Need for Timely Estimates of Movements in Irish Output

GDP growth and inflation forecasting performance of Asian Development Outlook

RBC Model with Indivisible Labor. Advanced Macroeconomic Theory

MS-E2140. Lecture 1. (course book chapters )

ES103 Introduction to Econometrics

THEORIES OF GLOBAL INTERCONNECTIONS. APWH Unit 6 Part to Present

Assignment #5. 1 Keynesian Cross. Econ 302: Intermediate Macroeconomics. December 2, 2009

Transcription:

DEPARTMENT OF QUANTITATIVE METHODS & INFORMATION SYSTEMS Applied Modeling & Forecasting QMIS 320 Chapter 1 Fall 2010 Dr. Mohammad Zainal 2 What is Forecasting? It is the process of analyzing current and historical data to determine future trends. It isthe process of calculating l or estimating i something inadvance. It is the process of predicting the future. The History of Forecasting Forecasting techniques are developed in the 19th century Regression analysis, time series analysis, and Box Jenkins procedures. Appearance of computers Developments in computer and software gave forecasting techniques more attention and gave managers the ability to utilize data analysis techniques. QM-120, M. Zainal 1

3 New forecasting techniques continue to be developed as management concern with the forecasting process continues to grow. Why Forecasting is Necessary? All organizations operate in an atmosphere of uncertainty so that decisions must be made today to affect the future organization. Educated guess versus pure guess. The most effective forecasting is to combine both quantitative and qualitative techniques. Who needs Forecasting and why? Almost every organization needs explicit or implicit forecasting, because every organization must plan to meet the conditions of future for which it has imperfect knowledge. 4 All business and economics branches need forecasting because: Some people want to increase their budget and to know what affects their sales. Some people want to recover the fixed investment t in production equipment by predicting the number of units to be sold. Some people want to predict what factors explain the variability in monthly unit sells. What is the purpose of forecasting? Predictions of forecasting are rarely precise, we can only minimize inevitable errors. So the purpose of forecasting is to reduce the range of uncertainty within which management judgments must be made. QM-120, M. Zainal 2

5 This purpose suggests two primary rules to which the forecasting process must adhere: Rule 1: The forecast must be technically correct and produce forecasts accurate enough to meet the firmʹs need. Rule 2: The forecasting procedure and its results must be effectively presented to management so that the forecasts are used in the decisionmaking process to the firmʹs advantage; results must also be justified on a cost benefit basis. Remark: Forecasters often pay particular attention to the first rule and expend less effort on the second. 6 What Types of Forecasts are available? I. Long term or short term forecasts. In this case forecasts can be classified in term of their timescale on longterm or short term forecasts. Long term forecasts are used by top management are necessary to set the general course of an organization for the long. Short term forecasts which are used by middle and first line management to design immediate strategies to meet the needs of the immediate future. Forecasting method that is used to forecast sales next month would probably be an inappropriate method to forecast sales in five years. Term Timescale Type of decision Example Short Up to 3-6 months Operating Inventory control, Production planning, and distribution Medium 3-6 months to 2 yrs Tactical Leasing of plant or equipment Long Above 2 yrs Strategic R & D, acquisitions, mergers, and product changes QM-120, M. Zainal 3

7 II. III. A micro or macro forecasts In this case forecasts can be classified in term of their position on micromacro continuum. Different levels of management in an organization tend to focus on different levels of micro macro continuum. The basic reason for the above classification is that different forecasting methods apply in each situation. A forecasting method that is used to forecast number of workers needed for the next several months for a plant manager (micro) would probably be an inappropriate method to forecast the total number of people employed in the entire country for the government (macro). Quantitative or qualitative forecasts. In this case forecasts can be classified according to whether forecasts are no formal mathematical model (because of lack of data) versus forecasts are of formal mathematical model. A forecasting method based on forecaster judgment as a result of the mental manipulation of past historical data is a qualitative forecast. 8 A forecasting method using a mechanical procedures based on the manipulation of numerical data such as business data is a quantitative forecast. What do wemeanby Macroeconomic Forecasting? A macroeconomic forecasting is the forecasting methods that concern in forecasting important variables for the entire economy of a country or for the global economy. Examples: Forecasting unemployment rate. Gross domestic product (GDP). Large changes in Oil prices. Inflation. QM-120, M. Zainal 4

9 What are the forecasting steps? There are five steps in the forecasting process, these are as follows: 1. Problem formulation and data collection It is a process of understanding the problem to determine the appropriate collection of data and considering the related forecasting methodology (qualitative or quantitative) in view of the availability and the correctness of the existed data. 2. Data manipulation and cleaning It is the process of checking the data whether it is small or large and cleaning data from missing observations using appropriate estimation techniques. 3. Model building and evaluation It is the process of fitting the collected data into an appropriate forecasting model with minimum forecasting errors to be used for predicting the future. 10 4. Model implementation (actual forecast) It is the process of generating the actual model forecasts using the appropriate forecasting model that have been chosen. 5. Forecast evaluation It is the process of evaluating the accuracy of the model forecasts and the adequacy of the fitted model using different methods defined on the forecasting errors. How to manage the forecasting process? It is the process of involving the ability and the common sense of managers in the forecasting process to help forecasters to introduce their advices using some quantitative tools to be used by managers in arriving at better decisions. What are the available computer forecasting packages? There are a lot of computer packages with forecasting tools included are available such as: SPSS, Minitab, SAS, Eviews, Excel etc QM-120, M. Zainal 5