Risk Management and Derivatives Final
Q1. You work for a UK building society (ie. mortgage bank) which is considering to launch a 10 year fixed mortgage based on the potential demand for such a product and similar products which are available from some of your competitors. but in the future it is expected that rates are going to rise (possible due to inflationary pressure). The Board of Directors knows that you have just completed a module in Derivatives and Risk Management and they want you to present to them the case of offering such a product with the potential risks to your institution highlighted and how you could deal with them. How would you launch a 10 year fixed rate mortgage product? [35 marks]
Q2. Use the BOPM to price a call and put option. Use Excel to build a 10 nodes tree. The time to expiry should be 1 year and interest rates are 1% per annum. You need to choose your own stock price, strike price and volatility. (Important : You need to choose different parameters than given in the Excel spreadsheet provided for the module). Price a European Call, European Put, American Call and American Put option. Compare your results against the Black-Scholes model and make suggestions how you could improve on the calculations undertaken in the BOPM. [30 marks]
Q3.You are a UK based asset management company and you hold the following international portfolio. On the 20th of December 2018 you set up the following international portfolio. You investment is just less than £10,000. Use data provided in ‘cw Data 2020.xlsx’.
Country Â
Company
Number of Shares
USÂ Â
Bank of America Â
85
Germany Â
BMW
30
Germany Â
Lufthansa
130
US
Amazon
3
UK
Tesco
273
(a.) Calculate the 10 day VaR of your portfolio at the 95% confidence level based on the variance-covariance method on the 10th June 2019, 24th June 2019, and 8th July 2019.
(b.) Repeat the calculations above, but use the exponential moving average for your volatility forecast in the calculation of the VaR using the variance-covariance method.
(c.) Repeat the calculations of the VaR of your portfolio using historic simulation.
(d.) Calculate the actual change in the value of your portfolio over the following 10 days. Compare your calculations with your VaR calculations performed in (a.) to (c.) and critically asses them. Comment critical on the practical implications. Explain what we understand by backtesting, how you would do it and what is the significance of it.
(Make any reasonable assumptions you need for the calculations.) [35 marks]
Hint : You have to draw standard normally distributed random variables. In Excel that can be done with the following command : NORMSINV(RAND())
Normal Distribution
Cumulative Normal Distribution : N(0,1)
z 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09
0 0.5 0.504 0.508 0.512 0.516 0.5199 0.5239 0.5279 0.5319 0.5359
0.1 0.5398 0.5438 0.5478 0.5517 0.5557 0.5596 0.5636 0.5675 0.5714 0.5753
0.2 0.5793 0.5832 0.5871 0.591 0.5948 0.5987 0.6026 0.6064 0.6103 0.6141
0.3 0.6179 0.6217 0.6255 0.6293 0.6331 0.6368 0.6406 0.6443 0.648 0.6517
0.4 0.6554 0.6591 0.6628 0.6664 0.67 0.6736 0.6772 0.6808 0.6844 0.6879
0.5 0.6915 0.695 0.6985 0.7019 0.7054 0.7088 0.7123 0.7157 0.719 0.7224
0.6 0.7257 0.7291 0.7324 0.7357 0.7389 0.7422 0.7454 0.7486 0.7517 0.7549
0.7 0.758 0.7611 0.7642 0.7673 0.7704 0.7734 0.7764 0.7794 0.7823 0.7852
0.8 0.7881 0.791 0.7939 0.7967 0.7995 0.8023 0.8051 0.8078 0.8106 0.8133
0.9 0.8159 0.8186 0.8212 0.8238 0.8264 0.8289 0.8315 0.834 0.8365 0.8389
1 0.8413 0.8438 0.8461 0.8485 0.8508 0.8531 0.8554 0.8577 0.8599 0.8621
1.1 0.8643 0.8665 0.8686 0.8708 0.8729 0.8749 0.877 0.879 0.881 0.883
1.2 0.8849 0.8869 0.8888 0.8907 0.8925 0.8944 0.8962 0.898 0.8997 0.9015
1.3 0.9032 0.9049 0.9066 0.9082 0.9099 0.9115 0.9131 0.9147 0.9162 0.9177
1.4 0.9192 0.9207 0.9222 0.9236 0.9251 0.9265 0.9279 0.9292 0.9306 0.9319
1.5 0.9332 0.9345 0.9357 0.937 0.9382 0.9394 0.9406 0.9418 0.9429 0.9441
1.6 0.9452 0.9463 0.9474 0.9484 0.9495 0.9505 0.9515 0.9525 0.9535 0.9545
1.7 0.9554 0.9564 0.9573 0.9582 0.9591 0.9599 0.9608 0.9616 0.9625 0.9633
1.8 0.9641 0.9649 0.9656 0.9664 0.9671 0.9678 0.9686 0.9693 0.9699 0.9706
1.9 0.9713 0.9719 0.9726 0.9732 0.9738 0.9744 0.975 0.9756 0.9761 0.9767
2 0.9772 0.9778 0.9783 0.9788 0.9793 0.9798 0.9803 0.9808 0.9812 0.9817
2.1 0.9821 0.9826 0.983 0.9834 0.9838 0.9842 0.9846 0.985 0.9854 0.9857
2.2 0.9861 0.9864 0.9868 0.9871 0.9875 0.9878 0.9881 0.9884 0.9887 0.989
2.3 0.9893 0.9896 0.9898 0.9901 0.9904 0.9906 0.9909 0.9911 0.9913 0.9916
2.4 0.9918 0.992 0.9922 0.9925 0.9927 0.9929 0.9931 0.9932 0.9934 0.9936
2.5 0.9938 0.994 0.9941 0.9943 0.9945 0.9946 0.9948 0.9949 0.9951 0.9952
2.6 0.9953 0.9955 0.9956 0.9957 0.9959 0.996 0.9961 0.9962 0.9963 0.9964
2.7 0.9965 0.9966 0.9967 0.9968 0.9969 0.997 0.9971 0.9972 0.9973 0.9974
2.8 0.9974 0.9975 0.9976 0.9977 0.9977 0.9978 0.9979 0.9979 0.998 0.9981
2.9 0.9981 0.9982 0.9982 0.9983 0.9984 0.9984 0.9985 0.9985 0.9986 0.9986
3 0.9987 0.9987 0.9987 0.9988 0.9988 0.9989 0.9989 0.9989 0.999 0.999
3.1 0.999 0.9991 0.9991 0.9991 0.9992 0.9992 0.9992 0.9992 0.9993 0.9993
3.2 0.9993 0.9993 0.9994 0.9994 0.9994 0.9994 0.9994 0.9995 0.9995 0.9995
3.3 0.9995 0.9995 0.9995 0.9996 0.9996 0.9996 0.9996 0.9996 0.9996 0.9997
3.4 0.9997 0.9997 0.9997 0.9997 0.9997 0.9997 0.9997 0.9997 0.9997 0.9998
BS Option Pricing Model
Calculating the BS option price
Put-call parity concept is used here to calculate the Put premium.
only change the values in the yellow shaded area. Do not change anything else.
S 120
K 125
r 0.02
T XXXXXXXXXX 165 days
d 0
Sigma 0.2
B-S Call Premium XXXXXXXXXX
B-S Put Premium XXXXXXXXXX
Auxillary inputs to calculate B-S premia
d1 d2 N -"dash"
(d1)
XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX
Imp. Vol. Trial and E
o
Calculating the Implied Volatility (using Trial and E
or)
Data Inputs
S 164
K 165
r 0.0521
T 0.0959
d 0
Quoted C Premium 5.75
Trial and E
or calculations
Choose different values for "sigma" and calculate the "theoretical"
call premium using B-S until the latter equals the actual quoted call premium
Trial d1 d2 N -"dash" Call
values for (d1) Premium
Sigma using B-S
0.281 XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX
0.282 XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX
0.283 XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX
0.284 XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX
0.285 XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX
0.286 XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX
0.287 XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX
0.288 XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX
0.289 XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX
Sigma=0.288 gives quoted call premium
Imp. Vol. Sove
Calculating the Implied Volatilities (Using "Solver")
Data Inputs
only change the values in the yellow shaded area. Do not change anything else.
S 164
K 165
r 0.0521
T 0.0959
d 0
Actual Call Premum 5.75
B-S Call Premium XXXXXXXXXX
Cell to be minimised by SOLVER( Actual premium - B-S Premium)^2 = XXXXXXXXXX
Start value (and final value) for Sigma for use in SOLVER = 0.2
Auxillary inputs to calculate B-S premia
d1 d2 N -"dash"
(d1)
XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX
Daily ExR Returns
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