The task you are given is to estimate the

EFB344 Assignment Part A Due: Wednesday the 10th of October, 2018 at 11:59pm Weight: 30% of the overall unit Note: This is an individual assignment. Overview The task you are given is to estimate the market risk for a holding of 10,000 Macquarie Bank shares (MQG.ax) and 5,000 Westpac shares (WBC.ax), held on August 1 , 2018 (you are working out the risk position assuming that you own these shares before the open of trading that day). You will do this by estimating the Value-at-Risk for the stock portfolio. This will require you to choose the best VaR model by backtesting several methods to determine the most reliable for the task at hand. Description You will be asked to calculate the following; 10 day VaR for the portfolio of shares at a confidence level of 99%. Note: This risk estimate applies to the next 10 trading days from August 1, 2018 until August 14, 2018 (i.e. it should be a forecast of risk). Based on what you have learnt from EFB344, you are considering several options for how to compute this risk measure, a) the normal distribution using the EWMA, or b) historical simulation based on a rolling window. Both methods require choosing parameters to assign weight to past data, for the EWMA and the window length for the historical simulation. You will consider several possibilities for each as per the following; EWMA 1 for both volatilities and the covariance. EWMA 2 for both volatilities and the covariance. EWMA 3 for the volatilities and for the covariance. Historical Simulation 1 Rolling window with 252 trading days. Historical Simulation 2 Rolling window with 500 trading days. This leaves you with 5 possible models that could be used to provide the VaR measure asked for above. You must choose the most appropriate model and report the associated VaR. To inform your decision of which to use, you are going to consider the recent historical performance of the five models in calculating 1 day VaR at the confidence level of 99%. You will do so by first examining the frequency of instances when the VaR was exceeded by the observed return over the prior five years. You will then evaluate the appropriateness of these frequencies over time relative to the Basel traffic light levels discussed in lectures (over the same five years). Based on this performance, select the best model and report the required VaR(10, 99%) for August 1, 2018. Presenting your results You are to conduct your analysis in a copy of the Excel file Assignment_Part_A Data and Results.xlsx provided on Blackboard. This file contains the three tabs with the raw data for your analysis as well as a front page for you to summarize your results. All working is to be contained in the subsequent tabs. The front tab asks you to provide the following Your name and Student number The exceedance probabilities for the five models above. A graph summarizing the Basel Traffic Light results (such as the one shown in lecture 3). Which of the 5 models above is your preferred model based on the backtesting results. The final VaR(10,99%) for the portfolio based on your preferred model. An evaluation of the relative performance of the various models and a clear justification of which model is superior based on your backtesting. This is essentially a discussion of how you should interpret the backtesting results in order to select the most appropriate model. This should be no more than 500 words. Your excel file should be formatted in a reasonably clear way, so that someone who was given the same job after you would be able to understand your working and replicate what you have done. Details of Submission Submit the Excel file through the assignment portal that is available on the EFB344 Risk Management and Derivatives Blackboard site. Please include your name and student number in the file name of your document. Note that the portal will close after the due date and that any assignments that have been granted official extensions must be emailed to Steve Thiele (sr.thiele@qut.edu.au). Also note QUTs late assignment policy: Late Assignment + No Extension = 0% Additional Notes and Instructions I have sourced the raw data for you from Yahoo finance, going all the way back to the start of the year 2000. You will need to make it suitable for analysis. Your excel spreadsheet must contain the formulas that you have used for all calculations (i.e. dont paste the values for the calculations). There is an Excel file available on blackboard (called Excel guide.xlsx) that includes instructions for how to do several useful things in excel. It also includes some informative examples which might be of interest. Please look at this file. A few hints that will help stop people going down the wrong path; In theory, you should use arithmetic returns as you are constructing a portfolio, but I dont mind if you use log returns (the results will be very similar). You can assume that the mean returns are zero. Alternatively, you can estimate them from the data. However, you should not use a time-varying estimate of the mean. The reason is that we dont think the true value changes over time in the same way the volatility does, so any variation is likely to be random noise. The portfolio weights should stay fixed throughout your backtesting at the values they are as of August 1, 2018. It is vital that you match the dates for the two stock returns used in your analysis. It is not enough to match them on the first day and hope it works out. You can only use days were you have a return for each stock. You measured covariance will be vastly understated if you allow the two sets of returns to fall out of sync. If you have any questions about any of this, please ask them!!!! Criteria and Standards Sheet for Assignment Part A (30 marks) Marking Criteria High Distinction Distinction Credit Pass Fail Mark KS (1.1): Demonstrate and apply integrated discipline (including technical) knowledge Subject Knowledge Demonstrates comprehensive understanding of relevant finance and risk management concepts and techniques. Demonstrates a developed understanding of relevant finance and risk management concepts and techniques. Demonstrates a developed understanding of relevant finance and risk management concepts and techniques but with a few errors. Demonstrates an adequate understanding of relevant finance and risk management concepts and techniques. Insufficient or inaccurate understanding of relevant finance and risk management concepts and techniques. /18 KS (1.2): Apply technical and technological skills appropriate and effective for real world business contexts Excel Use and Formatting Document prepared and formatted according to standards required by the subject. Document generally prepared and formatted according to standards required by the subject, but with a small number of minor errors Document generally prepared and formatted according to standards required by the subject, but contains some errors Frequent errors, but displays an ability to prepare and format the document according to standards required by the subject. Fails to format the document to an appropriate standard required by the subject / 5 HO (2.2): Exercise independent judgement and initiative in adapting and applying knowledge and skills for effective problem solving Critical Analysis Provides a clear and well-reasoned justification for the choice of superior risk management model that fully considers the empirical findings. Provides a strong justification for the choice of superior risk management model that is supported by the empirical findings. Provides a solid justification for the choice of superior risk management model which is generally consistent with the empirical findings. Provides only weak justification for the choice of superior risk management model which barely takes account of the empirical findings. Fails to provide a justification for the choice of superior risk management model and/or the arguments are at odds with the empirical findings. /7 Overall Grade: HD, D, C, P, F Overall Mark: ________ Comments: An overall mark is awarded to the group, but can be adjusted for individuals at the discretion of the unit coordinator.

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