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NBS8185 MATLAB for Finance, final report, 2022-2023

金融报告代写 Using the natural logarithm of the GBPUSD spot and forward exchange rates from data set 3, test the forward rate unbiasedness (FRU) hypothesis.

Deadline

Friday 19th May, 10.00 a.m.

Instructions 金融报告代写

Word limit: 2,000 words, not including references section and appendix.

Download three data sets:

Data set 1.

Using Bloomberg or Yahoo Finance, download daily stock price data for any four U.S. 金融报告代写

companies for the period 31/12/97-31/12/08.

Data set 2.

Using Bloomberg or Yahoo Finance, download monthly stock price data for any four

U.S. companies for the period 2010:12-2020:12.

Data set 3.

Using the Bank of England’s statistics database, download monthly data on the end-of-month GBPUSD spot exchange rate (1998:01-2020:12) and the GBPUSD one-month forward exchange rate (1998:01-2020:12).

When you have downloaded your data, answer the following questions using MATLAB for all computations. Submit a PDF document that contains your answers to the questions. In your answers you should include basic information on the data used and brief comments for each answer, along with tables of numerical results and graphs where relevant. You should also include a references section. In an appendix to this PDF document please include the MATLAB code that you used to compute your results. The references section and appendix are not included in the word count.

Questions 金融报告代写

Q1. Pick one of the stocks from data set 1 and compute the natural logarithm of the price series for this stock. Use the Box-Jenkins methodology to estimate an appropriate time series model for the log-price series and investigate the forecasting ability of the model.

30%

Q2.

(a) Using appropriate hypothesis tests, analyse whether the natural logarithm of GBPUSD spot exchange rate from data set 3 is consistent with the random walk model.

10%

(b) Using the natural logarithm of the GBPUSD spot and forward exchange rates from data set 3, test the forward rate unbiasedness (FRU) hypothesis. 金融报告代写

10%

Q3. Using data set 2 and assuming a one-year investment horizon, no borrowing, and no short sales, investigate the optimal portfolio weights for a portfolio of the four stocks and a single risk-free asset (use any sensible values for the coefficient of risk aversion and risk-free rate).

20%

Q4. Using data set 1:

(a) Use the RiskMetrics or Historical Simulation approach to compute the one-day ahead return-VaR for one of the stocks over the period 02/01/08-31/12/08 and conduct backtesting.

15%

(b) Use the RiskMetrics or Historical Simulation approach to compute the one-day ahead return-VaR for an equally weighted portfolio of the four stocks over the period 02/01/08-31/12/08 and conduct backtesting.

15%

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