If you are contemplating an investment in a mortgage pool fund, one of your first steps should be reading the offering memorandum and learning about the fund’s underwriting criteria. The lending parameters that structure the portfolio are major determinants of the fund’s risk/return profile. Understanding the fund’s lending concepts will also make you a more knowledgeable investor.
A concept fundamental to real estate lending is LTV or loan-to-value. The loan-to-value ratio measures the loan amount as a percentage of the collateral property’s value. Prudent lenders can manage risk by keeping loan-to-value ratios in the portfolio at moderate levels. The concept behind LTV is fairly simple. A smaller loan-to-value ratio provides a greater cushion to protect investors if a loan defaults and a property must be sold to recover the principal.
For example, Lender A’s maximum loan-to-value ratio is 65%, meaning that loans are made at 65% or less of the property’s value. On a $200,000 property, the maximum loan that Lender A will make is 0.65 x $200,000, or $130,000. Lender B has more lenient underwriting terms and accepts loan-to-value ratios as high as 85%. On the same $200,000 property, Lender B would be willing to lend $170,000. If the real estate market weakens and the value of the $200,000 property declines, Lender A has a $70,000 cushion to cover market fluctuations. In addition, Lender A is more likely to recover the entire principal and interest if the property is sold. Lender B’s cushion is much smaller at $30,000. A 15% decline in the value of the property would wipe out his cushion and Lender B may not be able to recover the principal through a property sale. Expenses for foreclosure and remarketing the property may consume all of the cushion.
The importance of loan-to-value ratios became readily apparent during the 2008 real estate meltdown. Prior to the recession, demand for housing was high, bidding wars were common and every lender seemed convinced that real estate could only appreciate in value. Commercial banks were making loans at loan-to-value ratios as high as 125%. When the real estate market collapsed and housing prices plummeted, many lenders and borrowers were left holding mortgage debt that far exceeded the value of the properties.
Although loan-to-value is an extremely useful tool, this ratio isn’t perfect. One of its major weaknesses is the assumption that the lender has appropriately valued the property. An inexperienced lender or one provided with inaccurate data could overstate the value of the property and understate the loan-to-value ratio, resulting in elevated risk.
When evaluating a mortgage pool fund, investors should look at the average loan-to-value ratio across the portfolio rather than at individual loans. Most mortgage pool funds consider a loan-to-value ratio below 75% an optimal trade-off between risk and reward. The Socotra Fund is more conservative than most funds and sets its average loan-to-value ratio below 65%, providing a greater safety net for fund investors. The table above shows average loan-to-value ratios for the Socotra Fund portfolio during 2015 ranged from 40% on land loans to 49.5% for single-family residential properties. As a result of its emphasis on safety, the Socotra Fund has never suffered a major write-off despite exponential growth in the loan portfolio since 2011.
Another factor that influences a fund’s risk is its ability to appropriately value its properties. Because of this, investors should look for funds that have expertise in their lending markets and a track record of reliable income. The Socotra Fund focuses lending activities in its home market of California and is an expert on that market. In addition, the Socotra Fund has paid dividends to its investors every month without interruption since it began accepting subscribers in 2011.
An investor looking at a regionally focused fund should understand the appeals and risks specific to that regional market. The Socotra Fund concentrates on California real estate because of the area’s robust economic growth, rising home values and diverse economy. In addition, California has a regulatory environment that favors lenders. California foreclosures don’t involve a judicial process and are thus simpler, faster and less costly than foreclosures in other states. While there are some advantages to a national lending focus (for example, access to more markets), a downside of national funds is that underwriting decisions are made with inferior knowledge of local conditions.
Other parameters that impact the risk/return profile of a mortgage pool fund include the number of loans, the average loan size and the diversity of the portfolio. Lenders usually set parameters for average loan size and minimum and maximum lending range. In general, a portfolio with many small loans is less risky than a portfolio with fewer but larger loans. The average loan size in the Socotra Fund portfolio is modest at $237,000 and loan amounts range from approximately $17,000 to $1.2 million. The portfolio has nearly doubled in size from 98 loans in 2011 to 172 loans today. Despite this growth, 98.8% of the fund’s loans were current at year-end 2015, a better percentage than some commercial banks. In addition, keeping loan-to-value ratios low enabled the Socotra Fund to recover 100% of the interest and principal on the one loan in its portfolio that was foreclosed last year.
Regionally focused funds often reduce risk by diversifying their portfolios across multiple cities. A list of the Socotra Fund’s 2015 top 25 holdings showed investments across 20 California markets, including Malibu, Oakland, Stockton, San Francisco, Berkley, Vallejo and Sacramento.
Mortgage pool funds can also control risk by varying their portfolios by property type since each type has a different risk profile. As shown in the pie chart, the Socotra Fund portfolio is a diverse mix of single family residential, multi-family residential, duplex, commercial and land loans. The major property types, single family residential and commercial, represented 64% and 29% of the portfolio, respectively, at year-end 2015. .
