Financial Econometrics (R Studio)
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Provide a short description for the concepts addressed in the following questions:
(a.) Why study an asset return and not its price?
(b.) Let denote the daily log return of an asset. Describe a procedure for testing the existence of serial correlations in .
(c.) What is a white noise process?
(d.) Describe a nice feature and a drawback of using ARCH model to modeling asset volatility.
(e.) What is a stationary time series? What is a non-stationary process?
(f.) Describe the different steps involved in performing a GARCH analysis.
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Consider the return time series for the DJIA index.
(a.) Download the DJIA data from Yahoo! Finance using quantmod (the index ticker is ^DJI) from 1991-01-01 to 2018-12-31 and calculate the daily return time series.
(b.) Write down the AR model for the series. Remove insignificant coefficient estimates (based
on t-ratio in absolute value of 1.645). Provide model checking to confirm that the model is adequate.
(c.) Use the fitted model to obtain 1-step to 5-step ahead predictions series (forecast origin is the last data point). Also, compute the corresponding 95% interval forecasts.
(d.). Does the series exhibit GARCH effects? If yes, why?
(e.) Provide the volatility equation and perform model checking. Consider both a normal innovation and a Student-t innovation.
(f.) Write the full model for the series.
DETAILED ASSIGNMENT
