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Time Series and Prediction Computing - R Programming Assignment Help

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R Programming Assignment Help

Task:  Write a function in R called “my.first.app”. The function
  • requires no input arguments and
  • returns as output the text string “Hello World!”.
Stationarity. Carry out an ADF test to assess the evidence of nonstationarity. Q1. ADF test stat: - 7 Q2. Do you reject the null of nonstationarity?
  • Moments of the return time series
Q3. Mean: Q4. Variance: Q5. Skewness: Q6. Kurtosis: Q7. Inspection of the skewness reveals that the empirical distribution of returns is negatively skewed positively skewed Q8. Inspection of the kurtosis reveals that the empirical distribution of returns is thin tailed fat tailed
  • Extremes.
Q9. What are the max and min returns of the series? Q10. What is the percentage of days with a return larger than 5% in absolute value?
  • Return distribution. Carry out a Jarque-Bera test to assess the evidence of normality.
Q11. JB stat: Q12. JB p-value: Q13. Do you reject the null of normality?
  • Annualized Volatility
Q14. Ann. Volatility over the full sample: Q15. Ann. Volatility in 2007 (if the stock did not trade over the entire year, enter NA): Q16. Ann. Volatility in 2009 (if the stock did not trade over the entire year, enter NA): Q17. Ann. Volatility in 2014 (if the stock did not trade over the entire year, enter NA):
  • Return Dynamics. Compute the sample auto correlation function from lag 1 to lag 126.
Q18. What are the values of the sample auto correlation function from lag 1 to 5? Q19. What is the number of auto correlations outside the zero confidence bands? Q20. What is the number of auto correlations larger than 0.05 in absolute value?
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