3.1A small regional trucking company has experienced steady growth. Use time series regression to forecast capital needs for the next 2 years. The company's recent capital needs have been:
══════════════════════════════════════════════
Capital Needs Capital Needs
(Thousands Of (Thousands Of
Year Dollars)Year Dollars)
------------------------------------------- --------------------------------------------
1100 3130
2110 4140
5160
══════════════════════════════════════════════ perform a regression analysis and forecast sales for the next two years:

Exponential Smoothing

3.33The Sporting Charge Company buys large quantities of copper that is used in its manufactured products. Bill Bray is developing a forecasting system for copper prices. He has accumulated this historical data:

a.Use exponential smoothing to forecast monthly copper prices. Compute what the forecasts would have been for all the months of historical data for = 0.1, = 0.3, and = 0.5 if the forecast for all ’s in the first month was $0.99.

b.Which alpha () value results in the least mean absolute deviation over the 16-month period?

c.Use the alpha () from Part b to compute the forecasted copper price for Month 17.

Integrated Products Corporation (IPC) needs to estimate its sales for next year. The most recent six years of revenue data for the company’s line of XT computers are found in the table below:

...Regression with TimeSeries Data Week 10
Main features of Timeseries Data
Observations have temporal ordering
Variables may have serial correlation, trends and seasonality
Timeseries data are not a random sample because the observations in timeseries are collected from the same objects at different points in time
For time...

...report on the time-series analysis of continuously compounded returns for Ford and GM for the periods January 2002 till April 2007 using monthly stock prices. This analysis is aimed at estimating the ARIMA model that provides the best forecast for the series. This paper will be divided into 2 sections; the first section showing the Ford analysis and the second the GM analysis.
Section 1: Ford
Figure 1: Timeseries plot...

...SECTION A (You should attempt all 10 questions)
A1. Regression analysis is ____________________________________.
A) describes the strength of this linear relationship.
B) describes the mathematical relationship between two variables.
C) describes the pattern of the data.
D) describes the characteristic of independent variable.
A2. __________________ is used to illustrate any relationship between two variables.
A) Histogram
B) Pie chart
C)...

...Timeseries analysis
(Session – I)
Commands and syntax for data analysis using STATA
1. Open and Run the STATA application
• Click on the Data on the task bar and open Data editor
• Copy the data from Excel sheet and paste it on the data editor
• Preserve the data
• Close Data Editor
2. Type “describe” in the command space- Software will show the description of the
data set.
3. Graphs...

....2.3 Timeseries models
Timeseries is an ordered sequence of values of a variable at equally spaced time intervals. Timeseries occur frequently when looking at industrial data. The essential difference between modeling data via timeseries methods and the other methods is that Timeseries analysis accounts for the fact that data points...

...TimeSeries 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...

...Forecast Error, TimeSeries Models, Tracking Signals ) NAME____________________ Solution True or False 1. T F According to the textbook, a short-term forecast typically covers a 1-year time horizon. 2. T F Regression is always a superior forecasting method to exponential smoothing. 3. T F The 3 categories of forecasting models are timeseries,...

...A timeseries analysis for Chinese Electricity Demand
1. Introduction
Electricity is the basic demand for peoples’ daily life, and relate to the Industrial production. It is also be a very important indexer to indicate the economic growth because the electricity demand and the economic growth always highly related. Thus the prediction of the electricity demand is very important. The government of a country must be able to forecasting the electricity demand in...

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