Chapter 11 - ECMT1020 Chapter 11 Time Series Analysis Dr...

Info iconThis preview shows pages 1–12. Sign up to view the full content.

View Full Document Right Arrow Icon
ECMT1020: Chapter 11 Dr Boris Choy 1 ECMT1020 Chapter 11 Time Series Analysis Dr Boris Choy for ECMT1020
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
ECMT1020: Chapter 11 Dr Boris Choy 2 Topics covered 1. Introduction to Time Series 2. Time Series Forecasting 3. Moving averages 4. Exponential Smoothing 5. Seasonal Indices References Black 16.1, 16.2, 16.4 Excel file: Chapter 11.xls Must read Black Chapter 16: Opening Case Forecasting inflation (p.644- 645)
Background image of page 2
ECMT1020: Chapter 11 Dr Boris Choy 3 Learning Objectives Understand time series data Understand the basic concepts of time series forecasting Able to compare different forecasting techniques Able to apply different smoothing techniques for forecasting Understand seasonality and apply decomposition technique to isolate seasonal effects
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
ECMT1020: Chapter 11 Dr Boris Choy 4 Time Series Data & Time Series Forecasting
Background image of page 4
ECMT1020: Chapter 11 Dr Boris Choy 5 Time Series Q: What is a time series? A: A time series (TS) is a collection of observations collected at regular time intervals. Examples: [1] Daily petrol price [2] Monthly sales of a DFO outlet [3] Supply and demand of a certain resource (e.g. copper) [4] Daily value (opening, closing, maximum, minimum or trading volume) of AORD (or ASX 200) index [5] Unemployment rate [6] Inventory level
Background image of page 5

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
ECMT1020: Chapter 11 Dr Boris Choy 6 Time Series Q: What is time series analysis (TSA)? A: TSA consists of statistical methods and techniques to analyse TS data in order to extract meaningful statistics and characteristics of the data. Q: What is time series forecasting (TSF)? A: TSF is to use a statistical model to predict the future observations before they are observed. Such a model is built based on the past observations. TSF is the art or science of predicting the future and is widely used in decision-making process.
Background image of page 6
ECMT1020: Chapter 11 Dr Boris Choy 7 Time Series Q: Which TS methods are commonly used? A: Averaging, smoothing, regression analysis for trend, decomposition, etc. Q: Where can we get Australian economic data? A: www.rba.gov.au - Reserve Bank of Australia website www.abs.gov.au Australian Bureau of Statistics
Background image of page 7

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
ECMT1020: Chapter 11 Dr Boris Choy 8 Time Series Data CPI From 1990 100.0 110.0 120.0 130.0 140.0 150.0 160.0 170.0 180.0 Mar-90 Mar-91 Mar-92 Mar-93 Mar-94 Mar-95 Mar-96 Mar-97 Mar-98 Mar-99 Mar-00 Mar-01 Mar-02 Mar-03 Mar-04 Mar-05 Mar-06 Mar-07 Mar-08 Mar-09 Mar-10 Quarter CPI
Background image of page 8
ECMT1020: Chapter 11 Dr Boris Choy 9 Time Series Data Weekly high, low and closing prices of AORD (2005 to now)
Background image of page 9

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon