The delta-gamma method improves upon the delta-normal method by incorporating the gamma of the options, which accounts for the curvature in the price relationship of the option to the underlying asset. This method better captures the non-linear aspects of option pricing, especially for extreme price movements. Gamma measures the rate of change of delta with respect to the price of the underlying asset, thus allowing for a more accurate reflection of the option's risk profile. By including gamma, the delta-gamma method can more accurately represent the risks associated with both small and large movements in the underlying asset's price, making it particularly effective for capturing the full spectrum of option price risk.

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.

Earnings-at-risk stress testing evaluates the bank's earnings sensitivity. This method assesses how changes in economic conditions or other risk factors might impact the bank's earnings, providing insights into the potential volatility in profitability.

A decrease in inflation rates typically leads to an increase in the price of fixed income instruments like bonds.
Lower inflation increases the real value of the fixed payments received from bonds, making them more attractive to investors and driving up their prices.