Question

What is the variance and expectation functions of the ARMA(2,1) model?

Answer #1

Solution:

What are the stationarity conditions for a mixed seasonal ARMA
model?

Explain the following terms briefly
(a) The mixed seasonal ARMA model.
(b) The ACF and the sample ACF.
(c) The stationarity condition for a mixed seasonal ARMA
model.
(d) Akaike Information Criterion.

If we use the mean as a model, what does the variance
represent?

We cannot say an expectation is rational if ________?
the expectation is different from what the Fed expects.
only some people have this expectation.
not all the information is used to form the expectation.
the expectation ends up to be wrong.
What kind of monetary policy can be used to reduce the rate of
inflation?
Selling bonds
Lowering the interest rate
Any expansionary monetary policy would work.
None of the above would work.
Suppose we hold money velocity constant, which...

a. If variance of asset A is 0.04 and variance of asset B is
0.02, what is the correlation between the two assets? Assume
covariance between the 2 assets to be 0.015. Show how you found the
values.
b. Suppose a portfolio has expected return of 15% and volatility
of 30%. How can you combine this portfolio with the risk-free asset
to create a portfolio with 10% expected return? Risk-free asset has
expected return of 3%. Show how you found the...

What is inflation expectation and how can we measure it?

What is expectation of E[n-X] in binomial distribution?

5. Variance Covariance Matrix and Asset
Allocation Model (Markowitz Portfolio Model): Suppose the variance
covariance matrix for two stocks is given as:
Stock 1
Stock 2
Stock 1
0.025
0.015
Stock 2
0.030
The expected rate of returns on Stocks 1 and 2 are 10% and 12%,
respectively. The average return to risk-free treasury is 5%. Given
that the objective of the investor is a minimum-risk portfolio,
find the optimum weights of each stock in the portfolio.

Consider the linear regression model ? = ? +?? + ? Suppose the
variance of e increases as X increases. What implications, if any,
does this have for the OLS estimators and how would you proceed to
estimate β in this case.

In the General Linear Model the actual statistical model (e.g.
linear regression, analysis of variance, etc.) performed is
determined by:
A) The user indicating the specific model to be run by entering
a key word: “regression”, “analysis_of_variance”, etc.
B) The number and type of the explanatory variables
C) The number (but not the type) of the explanatory
variables
D) The total number of data points included in the model

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