• July 26th, 2015

The idea of this assignment is to practice every piece of techniques learned in this course by applying them to a single time series.

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The idea of this assignment is to practice every piece of techniques learned in this course by applying them to a single time series.

 

Course Project

The course project will concentrate on the application of the techniques taught during the term a time series of your own choice. You are required to apply the statistical techniques and econometric methods taught in the course to a time‑series of your own area of research interest. Select a time‑series, collect data (preferably quarterly) for the selected variable and the related variables, and apply the techniques as course proceeds.  You are required to report a summary of your work and the results as they progress. The idea of this assignment is to practice every piece of techniques learned in this course by applying them to a single time series.  You start with plotting a scatter diagram of your data and by eyeballing it for trend, seasonality, cyclicality, auto-regression and other components of a time series and proceed to hypothesis testing and estimating a single-equation linear regression model.  Finally, you use your regression model for in-sample and out-of-sample forecasting. At every stage you are required to make a summary of the results and report it. At the end of the term you are required to submit the portfolio of your work, including all the computer print outs and individual summary reports. Your final paper will include a summary of all the work done.

 

 

Use Eviews to do the project.

There’s 2 models, #1 is CPI model where is CPI=β01 X1+β2X2(X1 is unemployment rate, X2 is money growth rate), inflation rate=β01 X1, just as the project introduction (step1-step16)

 

Download one company’s monthly data from yahoo finance website (for example Apple)

 

#2 is business model where is Y=β01 X1( y is Apple’s adj price, X is “S&P 500”) (not sure about this part), and for the return, Y=β01 X1( y is Apple’s return minus “CBOE Interest Rate 10 Year T No” return, X is “S&P500” return minus “CBOE Interest Rate 10 Year T No” return). Follow the similarly step1-step16, Do MAD,MAPE, MSE, Dummy, and Gauss-Markov Theorem.

 Ra-Rf==β0+β1(Rs&p500-Rf)

 

Choose one model, there’s two video which is a sample project of #2, her sample is The Kroger Co. from 2004.1-2009.12, use the sample project to check the requirement and answers.

 

Prof. Safarzadeh

Assignment #1

I- Download the monthly data on CPI for the period 2004.1-2009.12, find the following estimates and do the following tests.

  1. Plot the variable over time. Explain the movements in your variable and mark the outliers and structural break, if any. Comment on the existence of time trend, seasonal trend, cyclical trend, and randomness in the variable.
  2. Do the histogram of the CPI data and comment on the distribution of data.
  3. Plot the natural logarithm of the variable. Explain movements in the natural log of the variable and mark the outliers and structural breaks.
  4. Plot the histogram of the log of the variable and comment on its distribution.
  5. Comment on the differences between the behavior of the variable and the natural log of the variable.
  6. Find the summary statistics of the CPI variable.
  7. Do a hypothesis test that the mean CPI during the 2004.1-2006.12 is statistically no different from the mean CPI during the 2007.1-2009.12.
  8. Do a hypothesis test that the variation of CPI during the 2004.1-2006.12 is statistically no different from the mean CPI during the 2007.1-2009.12.
  9. Create the lag of the CPI variable and use it as a naive forecast of your variable. Find the mean absolute deviation (MAD), mean absolute percentage error (MAPE), and mean squared error (MSE)for your forecast.
  10. Divide the CPI data to three equal-size periods. Find the means and the variances of the first and the last periods.
  11. Do a hypothesis test that the mean of the first period is the same as the mean of the third period.
  12. Do a hypothesis testing that the variance of the first period is the same as the variance of the Third period.
  13. Find the correlation coefficient between the first period and the third period data. Comment on the correlation coefficient.
  14. Take time as an explanatory variable. Find the correlation between the CPI and the time. Comment on the correlation.

 

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