代写ECMT3130留学生、代做R程序、代做natural logarithms、代写R代写

日期：2018-10-24 09:52

ECMT3130: Forecasting for Economics and Business

Group Project with Individual Component?

For this project, you should work—individually and in groups—with the

monthly time series of the assigned commodity prices. The project consists

of a set of time series estimation and forecasting exercises, as outlined below.

You should address all these items. You should upload the reports and the

R file containing all the coding for your project by the due dates. Questions

1–4 belong to the Individual Component of the assignment. You should

address these by the due date of the mid-semester test. The remaining

questions belong to the Group Project. You should address these by the

group project submission date.

1. Transform the prices to their natural logarithms, and work with these

transformed series, denoted by pt

, henceforth.

2. Divide the series into the in-sample estimation environment (observations

up to and including Dec 2010) and the out-of-sample forecasting

environment (observations beginning from Jan 2011 and onward).

3. Using data from the estimation environment, obtain and report parameter

estimates of the following models:

(a) polynomial deterministic trend model with seasonal component

(use AIC to decide on the polynomial order);

(b) autoregressive model of order p (use AIC to decide on the autoregressive

order)

(c) autoregressive model of order p with linear trend and seasonal

component (use AIC to decide on the autoregressive order).

4. For the same set of models as in the previous question, as well as the

random walk model (i.e., four models in total), obtain and plot point

forecasts for the duration of the out-of-sample window size (i.e., for

periods from January 2011 to December 2017).

The individual component will be assessed as part of the mid-semester test

1

5. Based on the category of commodities, prices of which have been assigned

to your group, briefly (no more than 500 words) motivate the

topic (as if you were preparing a research report). This will serve as

an ”introduction” of your report.

6. Present a table with descriptive statistics (that lists mean, standard

deviation, minimum and maximum values of the times series), and

another table with unit root test results for the assigned commodity

prices. Briefly (no more than 600 words) describe key characteristics

of the time series. This will serve as a ”data” section of your report.

7. For all four models in Question 4, using a rolling window approach:

(a) obtain one-step ahead forecast errors, and calculate the out-ofsample

root mean square forecast error (RMSFE) measures;

(b) test the hypotheses of (i) error unbiasedness; (ii) error efficiency;

and (iii) no autocorrelation.

(c) test the hypotheses of equal forecast accuracy of all models relative

to the random walk model.

8. Present a table with these results. Briefly (no more than 1000 words)

describe key findings of your analysis. This will serve as a ”results”

section of your report.