BiggerPockets (www.biggerpockets.com), the world’s largest online hub for real estate investors, today released its 2016 BiggerPockets Real Estate Investment Market Index (downloadable spreadsheet available here). This Index analyzed the 50 largest U.S. MSAs (Metropolitan Statistical Areas) to determine those that were most likely to produce outsized returns for residential real estate investors between 2015 and 2016.
BiggerPockets also breaks down those markets of the top 50 MSAs that were most likely to produce the worst returns for real estate investors.
The 10 Best Markets for Real Estate Investors
Dallas, TX tops the list of real estate markets over the period studied for the second year running with an even better year than last, exhibiting strong price appreciation, while remaining a market in which investors saw strong rents relative to property values. Dallas, TX investors stood to earn 20.7% unleveraged returns over the past year compared to 19.5% the year prior.
Falling closely behind Dallas, Portland, OR takes the number two spot, driven largely by almost a national best 14.6% year over year appreciation in home values over the period. Denver, the runner-up last year, falls to third place with a 13.8% appreciation driving most of the returns for investors.
Rounding out the top 10 are two Florida markets, two more Texas markets, Nashville, Atlanta, and Seattle, WA.
Top 10 Cities Offering the Most Opportunity for Real Estate Investors, 2016
- Dallas, TX
- Portland, OR
- Denver, CO
- Miami, FL
- Tampa, FL
- Seattle, WA
- Nashville, TN
- Atlanta, GA
- Houston, TX
- Austin, TX
The 10 Worst Markets for Real Estate Investors
The worst markets in the country, for the most part, had relatively low rents per dollar in home value and suffered negative or low appreciation over the time period. The Northeast and Midwest contained the bulk of the cities likely to produce the worst returns for real estate investors, but two California markets made the list in spite of relatively average appreciation due to exceptionally low rent-to-value ratios.
Indianapolis, IN was the market in the study that offered the least opportunity for residential real estate investors overall. In a year when most markets saw strong appreciation gains, residential real estate prices actually fell about 2.57% year over year in the Indianapolis MSA. The poor returns offered by the Indianapolis market were followed by Washington, D.C.
The New York City MSA also found its way into the list of the top 10 worst markets for residential real estate investors, with relatively weak appreciation accompanied by low rents per dollar invested.
The chart below shows the 10 worst markets for real estate investors:
The Top 10 Markets for Residential Property Appreciation
Appreciation gains drove much of the return for residential real estate investors, and if we isolate the 10 markets with the strongest appreciation gains, we see a lot of familiar names with overlap to the top 10 overall markets.
The Portland, OR metro region tops the list with a whopping 14.59% year over year increase in sales prices for residential real estate. Following Portland are the Denver, Dallas, and San Jose, CA markets. Seattle, Nashville, San Francisco, Tampa, and Austin, TX were also included in the top 10.
The chart below shows the 10 best markets for appreciation for real estate investors:
The Top 10 Markets for Strong Rent-to-Value Ratios
Many investors prefer cash flow potential of residential real estate over appreciation potential. While appreciation is
notoriously difficult to predict and highly speculative, it is perhaps more likely that the large metro regions in this study will continue to see similar levels of gross rent relative to the value of their property over the next few years. At the very least, HUD releases 2017 Fair Market Rents well in advance, and with a price floor set by the government, investors can rest a little bit easier with their assumptions about cash flow.
This study suggests that the best places to look for cash flow given the returns over the past 18 months are in Southern and Midwestern markets. Memphis, TN offered residential investors the largest amount of gross rent in relation to property value of the markets studied for the second year in a row. It is trailed by Detroit, MI, and Tampa FL.
The chart below shows the 10 best markets that offered strong rent-to-value ratios for residential real estate investors:
Purpose: This index seeks to determine which of the 50 most populous U.S. metro markets were most likely to have provided strong returns for residential real estate investors between early 2015 and early 2016. This index measures both appreciation and gross rents as a percentage of average purchase prices.
Analysis: Investor returns in real estate are largely driven by two key factors — appreciation and cash flow. Appreciation is fairly straightforward in most calculations. In this study, it is simply the percentage price increase in residential real estate over the time period studied. Cash flow, conversely, is a function of both gross rents collected and expenses. Because a large number of factors influence rental property expenses and many of these factors are difficult to accurately quantify (landlord friendly/unfriendly laws, for example), we ignore expenses for the purposes of this study and focus solely on gross rents as a percentage of purchase price.
Calculations: Gross rents are calculated as a function of average Fair Market rents, as provided by HUD, as well as median property values in early 2014, as provided by Zillow’s Home Value Index. Where possible, actual sales data from Zillow was used for median home price calculations. In the case of several markets, sales data was not available, and Zillow’s Home Value Index was used instead.
For example, a property purchased for $100,000 in early 2015 might receive $1,000 in rent in 2015 and $1,100 in 2016, averaging $1,050 per month, or $12,600 annualized. Gross rents in this instance average to 12.6% of the initial value.
Appreciation is calculated as the change in price from the beginning of the period studied to the end of the period studied. For example, if the average purchase price in an area studied was $100,000 in early 2015 and increased to $105,000 in early 2016, then appreciation would be 5%.
Method: A multi-step process was used to aggregate data that allowed for a reasonable estimate of appreciation and gross rents collected as a function of beginning property values in the top 50 metro areas.
Aggregate property data ultimately derives from Zillow’s Home Value Index. Here, we look at the median sales price, and an original copy of the dataset is available upon request or at www.zillow.com/research/data for those looking to dig deeper.
This data is a reflection of Zillow’s data for actual sales prices in the respective regions studied. To combat the limitations of Zillow’s data, which may not be robust enough in smaller cities, the study is limited to only the top 50 U.S. metropolitan markets as measured by population. Higher population regions of the country are more likely to experience a higher volume of transactions, giving Zillow more data points to work with, therefore increasing the likelihood of an accurate reflection of sales prices. Furthermore, by taking an average of sales prices across six months, we increase our sample size and lessen the risk of specific months significantly skewing our results.
The average property value across the first six months of 2015 is considered the “initial” property value or “purchase price,” and the average value across the first six months of 2016 is considered the “final” property value or “sale price.” The difference between the the two prices is then used to calculate appreciation.
Rent data is pulled directly from HUD (https://www.huduser.org/portal/datasets/fmr.html). HUD Fair Market rents vary by county and were not readily available by metro. In order for the study to compare Fair Market rents to the property values taken from Zillow, county data needed to be converted to reasonable estimates for each metro area. This study converts the data using a weighted average of Fair Market rents across each of the counties comprising a given metro area.
In calculating a weighted average, many metrics could have been used, including population, land area, total housing units, etc. In this study, Fair Market rents are weighted by population. This “weighted average” of Fair Market rents is then applied to the entire metro area.
Note that Fair Market rents also vary by number of bedrooms. This study averages Fair Market rents of units from 0–4 beds for each county and uses that as the “Fair Market rent” for that county.
This process is repeated using Fair Market rents for both 2015 and 2016.
This Fair Market rent for the each metro area is then used to calculate gross rents as a percentage of the beginning purchase price. Again, as mentioned previously, a $100,000 property receiving $1,000 in rent in 2015 and $1,100 in 2016 would average $1,050 per month, or $12,600 per year. Gross rents per dollar invested would come to about 12.6%.
The final step in this process adds together appreciation as a percentage of initial property values and average gross annual rents as a percentage of initial property values. This calculation reveals in percentage terms the markets where real estate investors looking to buy residential real estate properties were most likely to receive a favorable combination of both gross rents and total appreciation per dollar invested over the period from early 2015 to mid-2016.
It will be obvious to any investor looking at this data that expenses are not included in this study. Expenses vary widely across the 50 metros studied and are impacted by factors such as taxes, insurance, weather/climate, cost of living, landlord friendly/unfriendly laws, contractor costs, and other similar variables. Furthermore, even if accurate data on each of the many expenses listed were readily available to the public, expenses can also vary from investor to investor based on non-market forces like diligence in property management, variations in tenant screening processes, experience with contractors and handyman work, and other experience-related advantages. Because of the complexity in creating any kind of index measuring expenses in the top 50 metro areas, expenses were excluded from this study entirely.
Investors: What do you think of the information in this study? Which data points surprise you (and which don’t)?
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