Tag Archives: base case scenario

Fannie & Freddie G-Fee Equilibrium

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The Federal Housing Finance Agency’s Division of Housing Mission & Goals has issued its report on Fannie Mae and Freddie Mac Single-Family Guarantee Fees in 2015. Guarantee fees (also known as g-fees) are another one of those incredibly technical subjects that actually have a major impact on the housing market. The g-fee is baked into the cost of the mortgage, so the higher the g-fee, the higher the mortgage’s Annual Percentage Rate. Consumer groups and housing trade associations have called upon the FHFA to lower the g-fee to make mortgage credit even cheaper that it is now. This report gives reason to think that the FHFA won’t do that.

The report provides some background on guarantee fees, for the uninitiated:

Guarantee fees are intended to cover the credit risk and other costs that Fannie Mae and Freddie Mac incur when they acquire single-family loans from lenders. Loans are acquired through two methods. A lender may exchange a group of loans for a Fannie Mae or Freddie Mac guaranteed mortgage-backed security (MBS), which may then be sold by the lender into the secondary market to recoup funds to make more loans to borrowers. Alternatively, a lender may deliver loans to an Enterprise in return for a cash payment. Larger lenders tend to exchange loans for MBS, while smaller lenders tend to sell loans for cash and these loans are later bundled by the Enterprises into MBS.

While the private holders of MBS assume market risk (the risk that the price of the security may fall due to changes in interest rates), the Enterprises assume the credit risk on the loans. The Enterprises charge a guarantee fee in exchange for providing this guarantee, which covers administrative costs, projected credit losses from borrower defaults over the life of the loans, and the cost of holding capital to protect against projected credit losses that could occur during stressful macroeconomic conditions. Investors are willing to pay a higher price for Enterprise MBS due to their guarantee of principal and interest. The higher value of the MBS leads to lower interest rates for borrowers.

There are two types of guarantee fees: ongoing and upfront. Ongoing fees are collected each month over the life of a loan. Upfront fees are one-time payments made by lenders upon loan delivery to an Enterprise. Fannie Mae refers to upfront fees as “loan level pricing adjustments,” while Freddie Mac refers to them as “delivery fees.” Both ongoing and upfront fees compensate the Enterprises for the costs of providing the guarantee. Ongoing fees are based primarily on the product type, such as a 30-year fixed rate or a 15-year fixed rate loan. Upfront fees are used to price for specific risk attributes such as the loan-to-value ratio (LTV) and credit score.

Ongoing fees are set by the Enterprises with lenders that exchange loans for MBS, while those fees are embedded in the price offered to lenders that sell loans for cash. In contrast to ongoing fees, the upfront fees are publicly posted on each Enterprise’s website. Upfront fees are paid by the lender at the time of loan delivery to an Enterprise, and those charges are typically rolled into a borrower’s interest rate in the same manner as ongoing fees.

Under the existing protocols of the Enterprises’ conservatorships, FHFA requires that each Enterprise seek FHFA approval for any proposed change in upfront fees. The upfront fees assessed by the two Enterprises generally are in alignment. (2-3)

The report finds that “The average single-family guarantee fee increased by two basis points in 2015 to 59 basis points. This stability is consistent with FHFA’s April 2015 determination that the fees adequately reflected the credit risk of new acquisitions after years of sharp fee increases. During the five year period from 2011 to 2015, fees had more than doubled from 26 basis points to 59 basis points.” (1)

At bottom, your position on the right g-fee level reflects your views about the appropriate role of the government in the housing finance market. If you favor lowering the g-fee, you want to further subsidize homeownership  through cheaper mortgage credit, but you risk a taxpayer bailout.

If you favor raising it, you want to to reduce the government’s footprint in the housing finance market, but you risk rationing credit to those who could use it responsibly.

From this report, it looks like today’s FHFA thinks that it has the balance between those two views in some kind of equilibrium.

Economic Factors That Affect Housing Prices

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S&P has posted a paper on Economic Factors That Affect Housing Prices. This is, of course, an important topic, albeit one that is an art as well as a science. While S&P undertook this analysis more for mortgage-backed securities investors than for anyone else, it certainly is of use to the rest of us. The paper opens,

The U.S. domestic housing market has experienced a 23% price increase since the beginning of the housing recovery in 2011. Many local housing markets are now close to or above their peak levels of 2006, which leads us to investigate whether the pace of home price appreciation (HPA) can continue at its current pace. In this paper, we (1) examine the economic factors that influence HPA and (2) forecast HPA for numerous geographic regions assuming various economic conditions over the next five years. While the aggregate national pattern in housing prices is an important reference, we need to examine housing prices at a more granular geographic level in order to understand regional housing market dynamics and learn how these are affected by local macroeconomic factors. This paper demonstrates that several economic variables are needed to predict average home price movements for each of 48 different U.S. metropolitan statistical areas (MSAs).

*     *      *

Factors that influence HPA can be difficult to predict. Therefore, residential mortgage backed securities (RMBS) investors frequently use a range of HPA projections to estimate their potential bond returns. With that in mind, for each MSA, we considered five separate hypothetical economic scenarios, ranging from an “Upside” forecast to an extreme “Stress 3” case. Interestingly, our Stress 3 case forecasts a 28% decline in HPI at the national level over the next five years, which corresponds roughly to the decline experienced in the last recession. Our “base case” scenario leads to forecasts at the national level of a 26% increase in HPI over five years. This represents what we believe to be the most likely economic forecast. (1-2)

S&P’s key findings include:

  • Movement in HPA is primarily influenced by up to five variables, depending on the MSA: housing affordability, changes in shadow inventory, the unemployment rate, the TED spread [a measure of distress in the credit markets], and population growth.
  • HPA in many MSAs has momentum, meaning that it depends on its level in the previous quarter of observation.
  • The mortgage rate generally appears to have little predictive power in connection with home prices.
  • Chicago, Houston, Boston, and San Francisco are projected to appreciate at a greater pace (45%, 40%, 27%, and 36%, respectively) than the 26% forecast for the nation as a whole over the next five years, and New York at a slower pace (21%). Columbus led all MSAs with a projected five-year HPA of 50%.
  • Under our most pessimistic (Stress 3) scenario, Chicago is forecast to experience a greater decline in HPI (34%) over the next five years than the nation as a whole (29%), while New York, Boston, Houston, and San Francisco are projected to experience declines that are less severe than that of the nation (19%, 3%, 17%, and 16%, respectively). Markets that have been vulnerable in the past (Las Vegas, Phoenix, and Riverside) are projected to experience the greatest five-year declines under our Stress 3 scenario (66%, 68%, and 68%). The markets that show the greatest movements are the most sensitive to the five factors and frequently show the greatest upside and downside. (2-3, emphasis in the original)

I found the first and third bullet points to be the most interesting, as many pundits weigh in on the factors that affect housing prices. It will be interesting to see if further research confirms S&P’s findings.