Assignment Task
Learning Outcomes
This coursework assignment assesses the following learning outcomes (LO) of the module:
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Get Help Now!- Assess the properties and limitations of econometric methods as applied to the analysis of financial data.
- Formulate and test econometric models to examine different forms of financial data.
- Evaluate the results of econometric analysis.
Software:
Eviews is the required software to carry out this coursework assignment.
Data:
You have been provided data about one stock downloaded from Yahoo Finance. The data file containing your data is available on the Module Moodle page.
Your Price series is p_adjclose_
The return series is ???? Continuously Compounded Ret
In answering the questions below, you may wish to consult the help option in Eviews.
- For your series, in Eviews use the Genr option to calculate (i) the log of the price series, e.g. e=log (p_adjclose_????), and (ii) the daily log returns (e.g. r=???? Continuously Compounded Ret).
- Examine the descriptive statistics for both e and r. What do you conclude about the distributions of e and r? Is e normally distributed? Is r normally distributed? Explain why/why not?
- Obtain the correlograms, and examine the autocorrelations and partial autocorrelations for both e and r. What do you conclude about the behaviour of e and r? Are they stationary/non-stationary?
- Are your conclusions about stationary/non-stationary of e and r confirmed by appropriate unit root tests?
- Estimate and select an appropriate ARMA (p,q) model for e. In selecting your preferred model, use the information provided by:
- The estimated coefficients (and their t-statistics or p values)
- Serial correlation in the residuals
- Information criteria.
Produce a summary table similar to this.
- Carry out forecasts (Ex-post Out of sample) of the e series for the last 60 observations (fixed forecasting horizon) using your chosen model from the part 2(ii) and repeat the exercise for competing models (i.e. AR(1), AR(2) …. ) and choose the best model using the following criterions.
- AIC SBC LM(12) RMSE MAE MAPE THEIL
- Carry out forecasts (Ex-post Out of sample) of the e series for the 60 observations (t+20, t+40 and t+60) using the chosen model from part 2(iii) [pay attention to the forecast summary statistics] and comment on your results.
| Out of Sample Horizon | 20 observations | 40 observations | 60 observations |
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