Free GARP FRM-Part-1 Exam Questions

Suppose a bond with a par value of 1000 has coupon payments of 10% per annum and a yield to maturity of5%. If the bond has 4 years to maturity, what is the price of the bond?

A risk manager at an investment bank is examining the forward and futures contracts the bank’s clients use as hedging instruments. The manager compares the way the two types of contracts are priced, how profits and losses are calculated, and how decisions to offset or deliver against the contracts are made. Which of the following statements is correct?

A risk analyst uses the bootstrap method to assess the market risk of a global equity portfolio that experienced significant volatility in the recent past. The analyst applies independent and identically distributed (IID) bootstrapping to the extracted standardized residuals of the fitted model, and these bootstrapped standardized residuals are then used to generate time paths of future asset returns. In the final step, the simulated data is used to estimate the VaR of the global equity portfolio over a 1-month horizon. Which of the following will the analyst find to be correct when applying the IID bootstrap method?

A trader on the interest rate desk of a large bank entered into a customized 2-year interest rate swap contract on July 31, 2020, on a notional amount of USD 7.5 million. According to the terms of the swap, the bank received an annual fixed rate of 2.3% and paid an annual rate of SOFR as of the first day of the month of payment plus 1.95%. Payments were made every 6 months. The table below displays the relevant SOFR rates over the 2-year period:Date AND 6-month SOFR1-Jul-20: 0.11%1-Jan-21: 0.10%1-Jul-21: 0.05%1-Jan-22: 0.05%1-Jul-22: 1.52%Assuming no default, which of the following was the best estimate to the net amount that the bank paid or received on July 31, 2022?

Which of the following statements is true regarding the mixture of distributions for risk modeling?I. Distributions should never be combined.II. It may be helpful to create a new distribution if the underlying data you are working with does not currently fit a pre-determined distribution.