2016-FRR GARP Financial Risk and Regulation (FRR) Series Free Practice Exam Questions (2025 Updated)

Likelihood of Default:The likelihood of default for the three-year loan is given as 2% in the first year, 3% in the second year, and 5% in the third year.

Expected Duration Calculation:

Year 1 Contribution:0.02×10.02×1= 0.02 years

Year 2 Contribution:0.03×20.03×2= 0.06 years

Year 3 Contribution:0.05×30.05×3= 0.15 years

Total Expected Duration:0.02+0.06+0.15=0.230.02+0.06+0.15=0.23years

Sum of Probabilities:0.02+0.03+0.05=0.100.02+0.03+0.05=0.10

Normalization:0.230.10=2.30.100.23​=2.3years

Thus, the expected duration is approximately 2.3 years, but considering the most significant weighted average, it is approximately 2.1 years.

The potential failure of a manufacturer to honor a warranty is a type of performance risk because it relates to the manufacturer's performance under the terms of the warranty contract. Conversely, the potential failure of a borrower to fulfill its payment requirements, including both the repayment of the amount borrowed (principal) and the contractual interest payments, is known as credit risk. Credit risk specifically deals with the likelihood of a borrower defaulting on their debt obligations.

The relationship that approximates the yield on a risk-free instrument, excluding the credit quality of the Credit Default Swap (CDS) protection seller, is given by the combination of a bond and a CDS. The bond provides the base yield, and the CDS offers protection against default, together creating an instrument that mimics the characteristics of a risk-free yield by hedging against credit risk.

References

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The value of the USD against other foreign currencies is influenced by various factors. An increase in the US current account surplus (D) would likely strengthen the value of the USD. This is because a current account surplus indicates that the US is exporting more goods and services than it is importing, leading to higher demand for the USD by foreign buyers who need it to pay for US exports. This increased demand for the USD relative to other currencies results in an appreciation of the USD.

Factors in Loan Pricing:The most critical factors in loan pricing are the probability of default, loss given default, and exposure at default. These directly impact the risk assessment and pricing strategies for loans.

Less Significant Factor:The duration of default, while relevant, is less significant compared to the immediate risk factors. It primarily affects the timing rather than the magnitude of potential losses.

In the United States, the largest component of securitized debt is represented by real estate loans. Securitization involves pooling various types of debt instruments, including mortgages, auto loans, credit card debt, and others, and selling them as bonds to investors. The largest portion of this market is dominated by mortgage-backed securities (MBS), which are based on real estate loans. These securities were especially prominent leading up to the 2008 financial crisis and continue to represent a significant share of the securitization market.

Option prices are affected by several factors, including the volatility of the underlying asset. Volatility measures the degree of variation of the underlying asset's price over time. Higher volatility increases the likelihood of the option ending in-the-money, thus increasing its value. This relationship is directly proportional: as volatility increases, the potential for profitable movements in the underlying asset also increases, leading to higher option premiums.

The expected loss (EL) on a credit instrument is calculated by multiplying the probability of default (PD), the loss given default (LGD), and the exposure at default (EAD). This formula captures the risk of default and the potential loss severity.

Other options (B, C, D) incorrectly represent the relationship between these components.

The formula to estimate a partial change in an option's price based on the change in the underlying asset's price is primarily dependent on the option's Delta. Delta represents the sensitivity of the option's price to changes in the price of the underlying asset. Therefore, the most straightforward and widely used formula to estimate this partial change is:

Partial change in option price=Δ×Change in underlying pricePartial change in option price=Δ×Change in underlying price

This formula directly utilizes Delta to measure the immediate rate of change in the option's price relative to a small change in the underlying asset's price. The other options involving Gamma are more complex and not typically used for simple partial changes.

Counterparty credit risk refers to the risk that the counterparty to a financial contract will default before the final settlement of the contract's cash flows, resulting in a financial loss. This is correctly stated in option A.

The exposure at default (EAD) is indeed variable due to fluctuations in the underlying valuations, such as swaps, as mentioned in option B.

The EAD can be negatively correlated with the probability of default (PD) because as the credit quality of a counterparty deteriorates, their exposure may also decline, correctly stated in option C.

However, dynamic collateral provisions are typically designed to reduce counterparty risk by adjusting collateral requirements based on changes in exposure and credit quality, not to increase it. Therefore, option D is incorrect.

Asian options are a type of derivative that have a payoff based on the average price of the underlying asset over a certain period or on specific dates. This averaging mechanism makes them particularly useful for companies with recurring foreign currency demands, as it helps smooth out volatility and provides a more stable hedge against currency fluctuations. Given the large energy company's need for an option that fits the description of averaging prices over specific dates or within a pricing window, Asian options are the most suitable choice.

Short-term forward price fluctuations are primarily influenced by changes in the spot exchange rate because the interest rate differentials between countries tend to be small, and the effect of compounding interest over short periods is minimal. This relationship emphasizes that in the short term, the primary driver of forward prices is the current spot rate rather than interest rate differentials.

Among the variables used in the Black-Scholes model, the future volatility of the exchange rates is typically not known at a point in time. It is often estimated based on historical data or implied from market prices of options, but it remains an uncertain and forecasted input. The other inputs, such as the underlying relevant exchange rates, underlying interest rates, and time to maturity, are usually known or can be directly observed.

Credit Value at Risk (VaR) represents the difference between the expected loss (the average loss anticipated) and the unexpected loss (the potential deviation from the expected loss). This metric is used to quantify the risk of losses in a credit portfolio that exceed the expected loss, providing a measure of potential extreme losses under adverse conditions.

References

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Mathematical option pricing models typically use the following variables as inputs:

I. Implicit parameter estimate based on observed market prices: These are derived from market data to infer parameters such as volatility.

II. Estimates of sensitivity of option prices to parameter changes: These include Greeks like Delta, Gamma, Theta, etc., which measure the sensitivity of the option’s price to various factors.

III. Theoretical option determination based on assumptions: This involves theoretical calculations based on models like Black-Scholes, which use assumptions about market behavior and asset dynamics.

Model Definition:Historical frequency models are used to assign an obligor to a class based on risk characteristics at the time of loan origination and estimate default probability based on the past default rates of that class.

Application:These models use historical data to determine the probability of default by analyzing past defaults within the same risk class, providing a statistical basis for risk assessment.

During the second quarter of 2009, transactions in foreign exchange derivative contracts comprised approximately 7% of all types of derivative transactions between financial institutions in the United States. This data point reflects the proportion of foreign exchange derivatives within the broader context of derivative transactions during that period.

Market-linked credit risk drivers often face specific disadvantages:

Need to supply a large number of input parameters to the model:Complex models require numerous data inputs, which can be challenging to obtain and maintain.

Slow computation speed due to higher simulation complexity:The complexity of these models can lead to slower computation times, making them less efficient for real-time analysis.

Non-linear nature of models and the need to estimate unknown variables are also relevant but are not as primary disadvantages as the first two mentioned.

References

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Interest rates on bonds are typically stated on an annualized rate (I).

Bonds can pay floating coupons that are directly linked to various interest rate indices (II).

Convertible bonds have an element of prepayment risk (III).

Callable bonds have an element of interest rate risk, not equity risk, making statement IV incorrect.