2016-FRR Exam Dumps - Financial Risk and Regulation (FRR) Series

The cost of credit is typically influenced by factors that increase the risk or the expected return required by lenders. Increasing inflation rates (A) raise the cost of credit because lenders demand higher returns to compensate for the loss of purchasing power. A higher risk premium on a fixed income instrument (C) directly increases the cost of credit as lenders require more return for taking on additional risk. Similarly, a higher return on alternative investments (D) increases the cost of credit because lenders will demand higher returns to justify lending over these alternatives. However, an increase in the consumption of goods and services (B) does not typically increase the cost of credit. Instead, it often signals a healthy economy, which can lower the perceived risk and cost of borrowing.

Moral hazard occurs when one party in a contractual relationship can take risks because the consequences of those risks will be borne by another party. In this scenario, the credit associate is concerned that the obligor might use the loan proceeds for purposes not sanctioned by the lender, thereby increasing the risk of default. This situation is a classic example of moral hazard, where the obligor's behavior after receiving the loan could change in a way that increases the lender's risk without the lender having control over those actions.

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.

References:The inherent uncertainty in predicting future volatility is discussed in the context of option pricing in the "How Finance Works" document​​.

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.

Key Drivers of Loss Given Default: According to Moody's study, the most important drivers of loss given default (LGD) historically have been debt type and seniority, and the macroeconomic environment. These factors directly impact the severity of losses in the event of default by determining the priority of debt repayments and the overall economic conditions affecting the obligor's ability to recover.

Exclusions: The asset type of the obligor and recourse are not considered primary drivers of LGD in Moody's historical analysis. While they can influence the recovery process, they do not hold the same level of importance as the debt structure and economic conditions.

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.

References:

How Finance Works: "Expected Loss = Probability of Default x Loss Given Default x Exposure at Default"

When a country reduces its budget deficits and lowers its dependence on debt, it generally strengthens its fiscal position. This can lead to increased investor confidence and higher demand for the country’s currency. In Japan's case, if it reduces its budget deficits and its dependence on debt, the Japanese yen (JPY) would likely appreciate in value against other currencies. This appreciation occurs because a stronger fiscal position reduces the risk of inflation and debt defaults, making the currency more attractive to investors.

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

Verified information from the document ​