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1. The Excel file contains daily closes for the S&P/TSX composite index from January 2, 2008 to December 31, 2010. Assuming that December 31, 2010 is the current day. A) Using the Exponentially Weighted Moving Average (EWMA) method to forecast tomorrow's volatility (standard deviation). Do it for two cases: λ=0.95 and λ=0.995. Compare the forecast with the sample volatility. Discuss. (Assuming 252 days in a year.) Hint: the forecast and the weights are
B) Using the maximum likelihood method (as we did in class) to estimate GARCH(1, 1) model. In other words, estimate ω, α and β. Report the maximum likelihood value. Also calculate the log-run volatility (both daily and annualized). C) Repeat B) using the variance targeting method. Here please set the annual target variance at such a level so that the annual volatility is 16.5%. (Note: the usual method based on the sample variance won't converge since the recent variance in the sample is too low.) D) Using the parameter estimates from B), forecast the future daily variance for the next 200 days. Report forecasts only for the first 20 days and days 50, 100, 150 and 200. E) Calculate the average daily variance for the next 200 days using the parameter estimates from B). Report the average variance only for the first 20 days and days 50, 100, 150 and 200. Plot the daily forecast and the average in one chart for the entire 200 days. Discuss. Note: for accuracy, when doing parts B), C), D) and E), please copy cell and paste values for the GARCH parameters. In other words, keep all the decimal places for the parameters.
You are required to implement below shift system in MATLAB, t0 is the amount of shift towards left or right. y(t)= x(t-t0) Implement MATLAB code, where shift should be taken as
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Using the coefficients obtained for the noisy signal and the FIR filter in Q1(c)(i) implement on the TMS320VC5510DSK. You can use and modify any of the files provided in the Board
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write a note on vulcanization
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