The task you are given is to estimate the market risk for a holding of 10,000 BHP shares (BHP.ax) and 10,000 CBA shares (CBA.ax), held on March 1, 2023 (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 March 1, 2023 until March 14, 2023 (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, b) the normal distribution using a rolling window, or c) historical simulation based on a rolling window. All methods require choosing parameters to assign weight to past data, for the EWMA and the window length for the other two. You will consider the following choices for each

Normal EWMA	lambda = 0.94 for both volatilities and the covariance.
Normal Rolling Window	Rolling window with 252 trading days.
Historical Simulation	Rolling window with 252 trading days.

This leaves you with 3 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 three 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 past five years.

You will then evaluate the appropriateness of these frequencies over time relative to the Basel traffic light levels discussed in lectures. Based on this performance, select the best model and report the required VaR(10, 99%) for March 1, 2023.

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 Canvas. 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 three models above.
  • A graph summarizing the Basel Traffic Light results (such as the one shown in lecture 3).
  • Which of the 3 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 400 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.