Martin Luther King, Jr. was a great leader and inspirational speaker. His wisdom can serve as a guide for as long as we remember him.

Andrew Davidson & Co would like to acknowledge a fraction of what he gave us with two relevant quotes that seem fitting in 2021.

In the spring of 2019, National Association of Realtors® (NAR), together with financial-market experts Susan Wachter (Wharton) and Richard Cooperstein (Andrew Davidson & Co., Inc.)  proposed completing the transition of Fannie Mae and Freddie Mac (Enterprises) into market utilities in a publication entitled “A Vision for Enduring Housing Finance Reform.” This work builds on Richard Cooperstein and Andrew Davidson’s 2017 paper, “ Is There a Competitive Equilibrium for the GSEs?”

In NAR’s latest white paper, “GSEs: Their Viability as Public Utilities,” Wachter and Cooperstein expand on several points in their earlier discussion.  On January 14, 2021 at 1:30 PM ET, NAR is hosting a webinar open to all interested parties to further explore and discuss these insights.

Why a Utility?

Fannie and Freddie were established by Congress as private companies with a public mission; namely, to support secondary market liquidity and mortgage access at all times, across the entire country, with a special obligation to support underserved markets. The mortgage origination and capital investment markets are highly competitive and efficient, but the guarantor and securitization markets are not. These markets function better with externally imposed standards for quality, consistency, capital adequacy and fairness.  Further, scale is required to achieve these goals.  These are the characteristics of public utilities.

The common governance structure for utilities is private companies with service obligations and strong regulators that ensure adherence to the mission and to regulate returns.  The cost of capital is by far the largest component of the GSE risk fee, so reducing the unsubsidized cost of debt and equity is the most effective way to reduce consumer cost and advance homeownership.  Financial theory and 100 years of empirical evidence show that government-granted franchises that operate in limited markets have lower return volatility and thus lower required returns on equity and debt.  Indeed, the beta for utility stocks is half that of the S&P 500. 

Three requirements for success are: (1) The GSEs curate stable debt markets for interest rate and credit risk and to intermediate most of their risk into these competitive capital markets.  (2) A federal backstop on pass-through debt (MBS) and corporate financing for approved activities such as Cash Window operations and non-performing loan buyouts, but not for equity holders or credit risk securities. And (3) A governance structure that balances the tension between regulation, mission and capital markets discipline with a regulator, board, shareholders and management. At this stage, the regulator and operating model are largely in place, it remains to establish a Board that represents shareholders and other constituents, and shareholders. 

Separating signal from noise is at the heart of what we do at AD&Co. One of the key tools we utilize for that purpose is a sophisticated set of model performance trigger reports. These monthly reports not only alert us to model drift but also point to possible causes for the drift.

In the mortgage market, changes in behavior on the part of both borrowers and lenders may create gaps between model projections and actual performance. Early analysis of these gaps provides rich information to our modelers based on which they can either identify temporary drifts in model performance or, more importantly, highlight fundamental changes in behavior that need to be captured in our models.

Every product type is monitored along the following four dimensions, with residuals defined as the monthly difference between projected and actual results:

Moving average: Are residuals deteriorating over time?

Trend: Are residuals consistently becoming more positive or negative?

Bias: Is the model persistently overpredicting or underpredicting actuals?

Magnitude: Are model misses large enough to matter?

Multiple types of triggers are useful for determining the seriousness of a breach as well as the type of adjustments that might be warranted in response. For example, a moving average warning might indicate a developing change in borrower behavior that may require either additional explanatory variables or more complex functions of existing variables to tighten the residuals. Alternatively, updated data may provide key information for refitting the model. A small but persistent bias, on the other hand, may be easily corrected with a simple tuning parameter adjustment.

These triggers also help us monitor performance at the factor level. Rather than simply observing, for example, how GNMA 15-year MBS are performing, we have triggers at different levels of credit score, LTV, note rate, and many other factors. This deep analysis, presented as an easy-to-use dashboard, quickly identifies possible causes of model drift.

In January, we will present a detailed review of our trigger methodology, and show how we use the reports to help set our modeling priorities in order to explain performance and, when necessary, modify our models to accommodate new behavioral patterns. For now, we will leave you with the following example of a segment of a trigger report for FHLMC MBS using LDM 2.2 with COVID tunings applied.

Happy Holidays!

Tom Parrent, Model Risk Management

tparrent@ad-co.com

October 2020 FHLMC Trigger Report
 

We proudly launched our new website on November 13th. As you familiarize yourself with the new look of ad-co.com, you will come to know the many new offerings we provide. Along with the new website, we have organized our products as a menu of models and applications for a wide range of investor appetites. Let us review the menu of our product offerings.

Dynamic Models

LoanDynamics (LDM) is the credit modeling solution you need. Our behavioral model helps you manage interest rate and credit risks in single family, multifamily, and auto loans by forecasting prepayments, delinquencies, defaults, and loss probabilities.

RiskValDynamics (RVD) is our flexible valuation engine formerly known as OAS Subroutines. It combines LDM, our suite of MacroDynamics models, and our original, highly-efficient cash-flow engines.  

MacroDynamics (MDM) is our suite of macroeconomic models including InterestRateDynamics, HomePriceDynamics, and UnemploymentDynamics.

Applications 

Kinetics is our new modular platform, designed to deliver the full suite of our models and analytics with the option to license only the tools you need. LoanKinetics , our multi-functional whole loan application, joins the Kinetics platform, along with MSRKinetics (MSRK), our new web-based offering focused on assessing MSR risk, and PoolKinetics, a module for pay-up valuation of agency pools.

RiskProfiler (RP) is our complete valuation and risk assessment solution that covers all asset classes modeled by AD&Co: MBS and ARM pools, loans and their derivatives (IO, PO, MI, MSR), structured securities (CMOs), and hedge instruments. All inputs and outputs are stored in a SQL database.

We hope the new interface helps you learn more about all that Andrew Davidson & Co., Inc. can offer during these unprecedented times.

Happy Holidays and Stay Safe – Ashlea Bonds, Marketing

ashlea@ad-co.com
212-274-9075

Andrew Davidson & Co., Inc. (AD&Co), is proud to support Fite Analytics’ innovative cloud-native Mortgage-Backed Securities Analytics Service. The Fite Analytics solution incorporates AD&Co’s LoanDynamics models that provide forecasts of voluntary prepayments, defaults and losses that drive risk analytics across the mortgage-backed securities market with comprehensive coverage. To read the full press release click here.