A fixed-income desk quantitative analyst at an investment bank aims to predict future short-term interest rates using the Vasicek model. This model is defined by the following equation: $dr = k * (e - r) * dt + g* dw$

In this context:

• $dr$ represents the change in the short-term interest rate,
• $e$ is the expected long-term average of the short-term interest rate,
• $k$ denotes the speed of mean reversion,
• $r$ is the current short-term interest rate,
• $\sigma$ is the annual volatility of the short-term interest rate, quantified in basis points,
• $dt$ signifies the time period in years, and
• $dw$ is a random variable that follows a normal distribution with zero mean and a standard deviation equal to the square root of $dt$.

The following data has been gathered for the analysis:

• Current short-term interest rate ($r$): 3.35%
• Long-term expected short-term interest rate ($e$): 4.55%
• Mean reversion rate ($k$): 0.06
• Annual volatility in basis points ($\sigma$): 120 bps

Using these inputs, the analyst constructs an interest rate tree and projects the anticipated short-term interest rate for the 8th year. Additionally, the analyst calculates the time required for the short-term interest rate to revert halfway to its long-term average. Based on this analysis, what would be an accurate statement for the analyst to make?