Quantifying Mortgage Risk — Best Practices in the Wake of SVB
Much has been made of the Silicon Valley Bank saga, from the need for basic risk management (was there any, other than a trivial nod?) to the possibility of re-extending the Dodd-Frank rules to cover all banks. Rather than adding our voice to that noise, this post makes a pitch for best practices in MBS and whole loan risk, regardless of whether existing regulation covers your institution.
“Best practices” in mortgage risk is a broad term meaning different things to different people. For our purposes, it refers to using sophisticated risk management tools to quantify both first- and second-order risk of various factors. It also refers to using scenario analysis to capture projected P/L under combinations of risks, for example twists in the interest rate curve combined with spread changes and changes in implied volatility.
Before these risks can be offset using rate and option hedges, our first step is quantifying what the risks are.
In the simplest case, good risk management analysis should quantify projected P/L of a rate-sensitive mortgage or MBS position for shifts in the rate curve — not just local rate shifts of 25 to 50bp, but much larger shifts in rates. It’s helpful to remember that MBS and their underlying mortgages have embedded calls, which lead to significant changes in both projected durations and projected convexity as rates move. Running scenarios with large rate shifts can help highlight the sizable second-order risks in MBS, which are typically negative but turn positive under large enough shifts. In turn, this extended analysis highlights a non-trivial third-order rate effect in MBS.
In the following chart, we show P/L on a position of TBA passthroughs, securities similar to SVB’s held-to-maturity portfolio. We project price movements under parallel rate shifts as of January 3, 2022, which roughly corresponds to the start of the tightening cycle. For this analysis, we use RiskSpan’s prepayment and interest-rate models, which are available in the Edge interface or via overnight batch.1
In this analysis, the model projected prices of FNCL 2.0 to 3.0 within 2.5% of actual observed prices on March 8, 2023, shown by the diamonds on the chart, the Wednesday before the SVB crisis began to unfold. While not exact, this analysis illustrates the power of a straightforward rate curve to help a bank’s risk management team project actual, realized prices over very large rate moves.
In the next chart, we show a P/L chart that is duration-neutral at outset. This chart shows the losses from negative convexity,2 driven by the homeowner’s option to refinance moving from at-the-money to significantly out-of-the-money. As rates continue to rise (moving right on the chart), underperformance from convexity continues to increase, but only to a point. This is where the homeowner’s call option is offset by the natural, positive convexity of discounting. Beyond that point, MBS become mildly positively convex as the call options become less relevant.
What does this change in convexity look like? In the final chart, we show convexity at various rate shifts for a par-priced passthrough.3 This highlights convexity changes over large moves (and a non-trivial third derivative with respect to changes in rates) and underscores the importance of a quantitative approach to risk management for MBS.
From these straightforward scenarios, banks and other institutions can overlay combinations of other risk shocks, for example curve flatteners and steepeners, OAS changes, and changes in implied volatility. These mixed scenarios can quantify risk from cross-partial derivatives and inform potential hedges under multiple changes in inputs. All these simple and more complex user-defined scenarios are available in RiskSpan’s Edge platform, giving small and mid-sized banks the ability to quantify risk on high-quality MBS, which is the first fundamental in a rigorous risk management framework. Recent events have highlighted the tradeoff between cost savings generated by taking a light approach to rate risk management and the existential risk of insolvency. Yes, small and mid-sized banks can save costs while remaining within the current regulatory framework. But, as SVB has taught us, to do so can be tantamount to unwittingly betting the entire enterprise. Laying out a few basis points to ensure you’ve quantified the interest rate risk properly has never looked like a more worthwhile investment.