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Financial & Risk #2

Open MkFint opened 1 year ago

MkFint commented 1 year ago

If someone succeed to proceed this with R or Python code it will be very helpful.

Download historical data for 3 ETFs of your choice. You use weekly quotes, over the longest common period.

You will also build a portfolio (P) made up equally of these 3 ETFs.

Warning: choose ETFs that have been listed for at least 10 years and that are not too correlated with each other.

### Exercise 1

a- Present in a few lines the characteristics of the ETFs selected and of the portfolio P. Specify the calculation made to constitute the portfolio P. b- Represent graphically the evolution of the value of your ETFs and of the portfolio P, by normalizing the initial value to 100 euros (or $ in the case of listing on the US market).

### Exercise 2

The following calculations will apply to weekly geometric returns (not annualized). a- Calculate the descriptive statistics of the yields. b- Apply the Jarque-Bera normality test. c- Represent the autocorrelation function of returns. d- Calculate the matrix of correlations of the returns of the 3 ETFs and of the portfolio P. e- Calculate the approximate expectation-utility to order 4 of a logarithmic utility function for the 3 ETFs and the portfolio P.

### Exercise 3

a- Calculate the VaR at 90% for a horizon of 5 business days (1 week) using 3 methods: historical, Normal and Corrected (Cornish-Fisher) assuming an exposure of 20,000 euros. Calculate the Normal VaR at 90% for a horizon of 15 business days (3 weeks). b- Calculate the 90% CVaR (or Expected Shortfall) for a horizon of 5 business days (1 week) using 3 methods: historical, Normal and Corrected (Cornish-Fisher) assuming an exposure of 20,000 euros.