Hello, dear friend, you can consult us at any time if you have any questions, add WeChat: THEend8_
MN50374 Quiz 2
Deadline: Friday, 9th December 2022, 12:00 GMT Page I of I
On 28 November 2022, at 10:39 GMT the following bid and ask prices are quoted for GB bills
and bonds with maturities from 1 month to 5 years:
Name Coupon Maturity Date Next Coupon Last Coupon Currency Bid Ask
GB 1M T-BILL 0 19-Dec-22
GBP 99.849 99.855
GB 3M T-BILL 0 20-Feb-23
GBP 99.29 99.313
GB 6M T-BILL 0 22-May-23
GBP 98.206 98.252
GB 1Y GILT 0.75 22-Jul-23 22-Jan-23 23-Jan-23 GBP 98.434 98.503
GB 2Y GILT 1 22-Apr-24 22-Apr-23 22-Oct-23 GBP 96.904 96.964
GB 3Y GILT 0.625 07-Jun-25 07-Dec-23 07-Dec-24 GBP 93.779 93.86
GB 4Y GILT 0.375 22-Oct-26 22-Apr-23 22-Apr-26 GBP 89.489 89.537
GB 5Y GILT 1.25 22-Jul-27 22-Jan-23 22-Jan-27 GBP 91.337 91.381
All instruments are standard plain vanilla fixed coupon paying and the day count convention
is Actual/365. The settlement date for all cases is 1 working day after trade. At maturity 100%
par value + coupon will be redeemed. For instance, in case of 1-year Gilt, on 24th July 2023, a
total amount of £100.3750 is redeemable.
You can access the table above through the accompanying csv file titled “GB Curve
Quotes.csv”
Required:
Using Python as your calculator and the knowledge from Lecture 6:
1) Calculate bond yields for Ask Price of 8 listed gilts using continuous compounding
rates to at least 4 digits precision. §
[8x10 points]
2) Plot a yield curve for gilts with maturity date from 1 month to 5 years
[20 points]
§ The calculated yields shall correspond clearly to the underlying bonds. A suggestion is for
you to add a column (“Yield”) in the data-frame you import from the csv file containing your
calculated figures.
Additional points:
• Alternative practical assumptions can be made if necessary.
• Your codes need to run.
• To facilitate processing dates in Python, you can use the datetime library.
• To calculate natural logarithm, you can use numpy. log() function.
• You can convert date strings to datetime items using pandas. to_datetime()
function.