Obtaining and Transforming the Data

A. Obtaining
and Transforming the Data:

1.
Download daily and monthly adjusted closing prices for 12 years for
the same company you used for the first team project Annualize the
daily data. See
pages 2 – 6 of your textbook.

2.
Annualize the Monthly data. See
pages 2 – 6 of your textbook.

3.
Plot the daily prices versus time (days)

4.
Plot the annualized prices (obtained from daily prices) versus time
(years).

5.
Plot the monthly prices versus time (months).

6.
Plot the annualized prices (obtained from monthly prices) versus time
(years).

7.
Describe, Explain, Compare and Contrast.

B. Calculating
Simple and Logarithmic (Continuously Compounded) Returns:

Daily
Simple and Logarithmic Returns:

1.
Calculate (simple) returns as percentage changes in daily prices. See
pages 2 – 6 of your textbook. [This
is equal to (p(t) – p(t-1))/(p(t-1)].

2.
Calculate daily logarithmic
returns (continuously compounded). See
pages 2 – 6 of your textbook. [This
is equal to Ln((p(t)/(p(t-1))].

Monthly
Simple and Logarithmic Returns:

3.
Calculate (simple)
returns as percentage changes in monthly prices.

4.
Calculate monthly logarithmic returns
(continuously compounded).

5.
Describe, Explain, Compare and Contrast.

C. Distributional
Properties of Returns (See pages 20-27 of your textbook):

1.
Compute the moments for the continuously compounded
(logarithmic) daily returns.

2.
Do these daily logarithmic
returns come from a normal distribution? Present JB test results.

3.
Compute the moments for the continuously compounded
(logarithmic) monthly returns.

4.
Do these monthly logarithmic
returns come from a normal distribution? Present JB test results.

5.
Describe, Explain, Compare and Contrast.

D. Working
with Autocorrelation Functions (See pages 40 – 50 of your
textbook):

1.
Obtain and Plot the Autocorrelation Functions (acf)
for daily percentage
(simple) returns.

2.
At the 95% Confidence Level, and using the daily percentage
(simple)
returns,

a.
Perform the Box Pierce and the Ljung-Box tests for autocorrelations.

b.
What are your conclusions?

3.
Obtain and Plot the Autocorrelation Functions (acf)
for daily logarithmic returns.

4.
At the 95% Confidence Level, and using the daily logarithmic returns,

a.
Perform the Box Pierce and the Ljung-Box tests for autocorrelations.

b.
What are your conclusions?

5.
Obtain and Plot the Autocorrelation Functions (acf)
for monthly percentage
(simple)
returns.

6.
At the 95% Confidence Level, and using the monthly percentage
(simple)
returns,

a.
Perform the Box Pierce and the Ljung-Box tests for autocorrelations.

b.
What are your conclusions?

7.
Obtain and Plot the Autocorrelation Functions (acf)
for monthly logarithmic returns.

8.
At the 95% Confidence Level, and using
the monthly logarithmic returns,

a.
Perform the Box Pierce and the Ljung-Box tests for autocorrelations.

b.
What are your conclusions?

9. What
do your ACF analyses tell you about:

a. Stationarity
of the individual time series of daily and monthly returns? EXPLAIN.

b. Efficient
Market Hypothesis with respect to the time series of individual daily
and monthly returns? EXPLAIN.

c. Are
the daily and monthly returns “White Noise”? EXPLAIN.

Very
Important:

1.
Absolute maximum of 2 pages in WORD for all the descriptive portions
of Sections A, B, C and D.

2.
All graphs, Charts, R results, etc, should NOT be part of the 2
pages!! They should be presented in an APPENDIX.

Theory
Questions

1.
State and prove the 3 properties of an ARIMA(2,0,0). For credit,
PLEASE show ALL the
steps of your proof,

2.

3. State
and prove the 3 properties of an ARIMA(0,0,2). For credit, PLEASE
show ALL the
steps of your proof

Extra
Credit:

4.
State and prove the 3 properties of an ARIMA(1,0,1). For credit,
PLEASE show ALL the
steps of you

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