代做ECON339 Applied Financial Modelling Mid-Semester Examination Paper Spring 2022代做留学生SQL语言程序

日期：2024-04-29 04:03

ECON339

Applied Financial Modelling

Mid-Semester Examination Paper

Spring 2022

Q1. Briefly describe the criterion used to obtain the ordinary least square estimator. [2]

The model must be linear in the parameters.The Gauss-Markov theorem is applied and the estimator for ols is the best linear unbiased estimate (BLUE).

Q2. When estimating a regression in a sample why is a large sample observations preferred to a small sample? [2]

This means that the estimates will converge to their true values when the sample size is larger.

Q3. Why is an efficient estimator a desirable property of the OLS estimator? [2]

When the estimate is valid and can minimise the probability of it being far from the true value.

Q4. State the assumption(s) under the classical linear regression model giving rise to a biased standard error of the coefficient estimates when violated. [2]

The bias is due to the omission of any of the variables associated with the dependent and independent variables.

Tt  = a + bTM,t  + ut                                                                                         (1)

Tt  = c + dTM,t  + evolt  + vt                                                                   (2)

where Tt  is stock returns, TM,t   is market returns, and volt   is market volatility. State the null hypothesis if regression (1) is nested in regression (2). [2]

H0: b=d=e=0

Q6. Holding other things constant, what is the effect of (a) sample size and (b) variation in x on the variance of the OLS estimator? [2]

a ：An increase in sample size will lead to a decrease in the OLS estimator. b：An increase in variation in x will result in an increase in the OLS estimator.

Use the following information to answer Q7-Q9.

A researcher runs the following regression with the Eviews output presented below.

nettfa = b0  + b1 inc + b2 age + b3marr + b4male + e                               (3)

where

nettfa = the net financial wealth (measured in $’000)

inc = income

age = the age of the respondent

marr = a dummy variable equals 1 if the respondent is married and 0 otherwise. male = a dummy variable equals 1 if the respondent is male and 0 otherwise.

Dependent Variable: NETTFA

Method: Least Squares

Date: 08/23/22   Time: 19:06

Sample: 1 9275

Included observations: 9275

Q7. Interpret the coefficient of age. [2]

Net financial wealth increases by 1.041951 * 1000 per age increase.

Q8.State the independent variable whose estimate is not statistically significant at the 5% significance level. [2]

MALE,   p-value ＞0.05.

Q9. On average is there any gendre bias in the net financial wealth in the sample? [2]

There are biases and men have more wealth

Use the following information to answer Q10-Q12.

The researcher estimated a log-log regression and the output is reported below:

log (nettfa) = b0  + b1 log (inc) + b2 age + b3marr + b4male + e          (4)

Dependent Variable: LNETTFA

Method: Least Squares

Date: 08/23/22   Time: 19:04

Sample: 1 9275

Included observations: 6029

Q10. Between equations (3) and (4), which model do you prefer? Explain. [2]

[Hint: the included observations in regression 4 are far lesser than the sample in regression 3]

equations (4) Because in (4) the square of r and the square of the adjusted r are higher

Q11. Interpret the coefficient of log(inc) . [2]

Net financial wealth increases by $1,898 with every $1,000 increase in income.

Q12. Interpret the coefficient of marr . [2]

For each unit increase in marr ，nettfa will decrease by 0.31% .

Use the following information to answer Q13-Q14.

The researcher performed diagnostic tests on the residuals of regression (3).

Breusch-Godfrey Serial Correlation LM Test:

Null hypothesis: No serial correlation at up to 2 lags

Q13. Based on the Breusch and Godfrey test, what is the order of the lag of the serial correlation in the null hypothesis? [2]

Second-order autocorrelation.

Q14. What can you infer from the Breusch and Godfrey test results? [2]

There is an autocorrelation problem because the p-value is not significant and reject Null hypothesis

Use the information below to answer Q15 to Q17.

The researcher is interested in a nonlinear relationship between nettfa and age. The squared of age (denoted agesq) is incorporated in regression (3) and the regression output is shown  below.

nettfa = b0  + b1 inc + b2 age + b3 age2  + b4marr + b5male + e                                       (5)

Dependent Variable: NETTFA

Method: Least Squares

Date: 08/23/22   Time: 20:14

Sample: 1 9275

Included observations: 9275

Q15. Between models (3) and (5), which is the preferred model? Explain. [2]

I chose 3 because 3 has fewer independent variables than 5 and they are significantly correlated

Q16. At what age is the net financial wealth maximised? Show your working. [2]

Q17. State the name of the test that you can perform. to determine whether a linear regression or a nonlinear regression is a better fit for the data. [2]

T-test

Use the information below to answer Q18 to Q20.

The researcher performed a test for heteroskedasticity on residuals of equation (3). The table below shows the results.

Heteroskedasticity Test: White

Null hypothesis: Homoskedasticity

Test Equation:

Dependent Variable: RESID^2

Method: Least Squares

Date: 08/23/22   Time: 20:24

Sample: 1 9275

Included observations: 9275

Q18. What can you infer from the White test result? [2]

There is no heteroscedasticity.

Q19. Which property of the OLS estimator is violated based on the White test result? [2]

MALE^2

Q20. State an alternative method of estimating regression (3) that will address the concern of Q19. [2]

Weight Least Square （WLS) Replacing the original model with a logarithmic model