Financial Risk and Regulation 2016-FRR GARP Study Notes

Non-statistical risk measures typically used to quantify market risk include:

Option Sensitivities:

Measures such as delta, gamma, vega, and theta which indicate how option prices are affected by various factors.

Convexity:

This measures the sensitivity of the duration of a bond to changes in interest rates, an important factor in bond risk management.

Basis Point Values (BPV):

This measures the change in the value of a financial instrument or portfolio for a one basis point change in yield, used to assess interest rate risk.

Net Closed Positions:

This is not typically used to quantify market risk. It simply represents the net value of positions that have been offset or closed out and does not provide a measure of risk exposure.

Thus, net closed positions are not typically used to quantify market risk.

References

Source: How Finance Works​

In the context of options trading, delta hedging involves managing the delta (rate of change of the option's price with respect to changes in the underlying asset's price) to be neutral.

Options premium: Represents the cost paid to eliminate execution risk associated with sudden market moves (gapping markets).

Execution risk: The risk of being unable to adjust positions quickly enough in response to market changes.

By purchasing options, the trader removes the risk of needing to adjust a delta-neutral position during large market movements. The premium paid is the cost of this protection.

References

Source: How Finance Works​

The TED spread is calculated as the difference between the interest rates on interbank loans and short-term U.S. government debt (T-bills). Specifically, the TED spread = LIBOR - Treasury bill rate. In this case, the 3-month LIBOR rate is 2.5% and the yield on the 3-month U.S. Treasury bill is 0.5%. Thus, the TED spread is 2.5% - 0.5% = 2.0%.

Back testing VaR models involves comparing the predicted losses (VaR estimates) with the actual daily profits and losses to assess the accuracy and reliability of the VaR model. This process helps in validating whether the model is effective in predicting risk and in identifying any discrepancies between predicted and actual outcomes. Therefore, the correct statement about back testing the VaR models is option B.