Free GARP 2016-FRR Practice Exam with Questions & Answers | Set: 7

As of April 2007, the three most widely traded currencies on the global foreign exchange market in decreasing order of market share were the United States dollar (USD), the European euro (EUR), and the Japanese yen (JPY). This ranking reflects the liquidity and trading volume associated with each currency, with the USD being the most traded, followed by the EUR and then the JPY.

Vega represents the sensitivity of an option's price to changes in the volatility of the underlying asset. If a call option on the GBP has a Vega of 0.02, this means that for every 1% increase in the perceived future volatility, the price of the call option will increase by 0.02. Therefore, if the volatility increases by 1%, the call option's value increases by 0.02.

The same approach as question 29 is applied here but focuses on the straightforward default calculation without collateral consideration:

Loan Amount (EAD):$100,000

Loss Given Default (LGD):50% of EAD????????????=50%×$100,000=$50,000LGD=50%×$100,000=$50,000

Annual Expected Default Rate:2%

Expected Loss:Annual Expected Default Rate × LGDExpected Loss=2%×$50,000=0.02×50,000=$1,000Expected Loss=2%×$50,000=0.02×50,000=$1,000

Hence, the expected loss due to default is $1,000 without considering the collateral. If considering the collateral explicitly, it would be slightly different as the collateral reduces the direct exposure.

Futures contracts have several key characteristics that differentiate them from other types of financial instruments. The features include a fixed notional amount per contract, fixed dates for delivery, and daily margin calls to manage credit risk. Futures are standardized contracts traded on exchanges, not over-the-counter (OTC). OTC trading typically refers to securities or derivatives that are not listed on formal exchanges and are traded directly between parties, which is not a feature of futures contracts.

The value of foreign exchange options is influenced by several factors, including:

Change in the value of the underlying (I):This directly affects the option's intrinsic value.

Change in the perception of future volatility (II):Higher expected volatility increases the option's potential payoff.

Change in interest rates (III):This affects the cost of carrying positions in the underlying asset.

Passage of time (IV):This influences the time value of the option. All these factors collectively impact the pricing dynamics of options throughout the trading day.

The credit spread reflects the additional yield over the risk-free rate that investors demand to compensate for the risk of default. An increase in the probability of default of the issuer (I) would directly increase the credit spread as investors require more return for higher risk. Similarly, an increase in expected loss (IV) would increase the credit spread since the potential loss in the event of default is greater. On the other hand, a decrease in risk premium (II) or a decrease in loss given default (III) would typically lower the credit spread, not increase it.

Chooser options give the holder the flexibility to decide whether the option will be a call or a put at a specific future date. This feature makes chooser options valuable in uncertain marketconditions, as the holder can choose the type of option that will be more beneficial depending on the market scenario at the decision point.

The value of an option is influenced by several factors, including the perceived volatility of the underlying asset, in this case, foreign exchange rates. As the perceived future volatility of foreign exchange rates increases, the value of all options (both calls and puts) also increases. This is because higher volatility increases the likelihood that the option will end up in-the-money, thereby increasing its potential payoff. This relationship is fundamental to option pricing models, such as the Black-Scholes model, which incorporate volatility as a key input.

Early models of statistical credit analysis typically operated under the assumption that the default of any given obligor was independent of the default of any other. This simplification made the models more tractable but less realistic, as it did not account for potential correlations between defaults (e.g., economic downturns affecting multiple obligors simultaneously).

To quantify the aggregate average loss for the credit portfolio and its possible constituent subportfolios, a credit portfolio manager should use the expected loss metric. This measure captures the average anticipated loss due to defaults and is essential for understanding the baseline risk of the portfolio.

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