How to Predict Housing Prices
If predicting housing prices was so easy, wouldn't we all be doing it? We're certainly not the first to try, but we're certainly one of the first to bring these insights down to users, and at the zip code level.
In this post, we explain the methodology behind the key real estate metrics that influence our market forecast score. We dive into the constituent components— Looking at how market supply, our overvalued market index, population growth, price cuts, listing supply, and other indicators— all combine to influence our Market Forecast Score.
But first, lets talk about why we trust these metrics ourselves.
A Love of Data
Our founding team is made up of trained statisticians with a track record at top global tech and finance companies. But more importantly, they're united by the same love of real estate data, and what to do with it. Prop:Metrics was born out of a to get basic data access about the housing market and build models around that data to make better investments. Those same models, and the ones that our platform delivers today, have been used by members of our team to build a profitable real estate portfolio nationwide.
Quality Data Feeds
Our platform is underpinned by reputable, frequently updated market feeds and rigorously validated to ensure accuracy and reliability. We source data from some of the most trusted names in real estate, such as:
Federal Agencies: US Census Bureau, Department of Housing and Urban Development [HUD], National Mortgage Database
Leaders in Property Tech: Zillow, Realtor.com, MLS
Proprietary Sources: We pay thousands of dollars a year for access to some of the same industry data providers that power major players in the corporate real estate investment space
This high-quality foundation underpins our analytical models, providing you with robust, trustworthy insights for making informed real estate decisions.
Backtesting, or in other words, making sure our predictions are accurate
How good is a forecast if it doesn't actually do a good job at forecasting the future?
While we're not fortune tellers, and legally— this is not financial advice — We have to have a methodology to evaluate our own forecasting models.
Backtesting is simply testing our prediction methods using old data to see if they would have correctly forecasted past market movements. By doing this, we learn what works best and how to improve our future predictions.
We evaluate our forecasts based on well they were able to predict the price movement of homes in the 1, 3, and 5 year time horizon
The Building Blocks of Our Model
Our Prop:Metrics Forecasting model is grounded in a set of five rigorously defined scores. Each score captures a specific aspect of market dynamics. These sub-metrics are then aggregated, using a weighted sum approach, to produce our overall Home Price Forecast.
Market Supply Score
Our Market Supply Score evaluates the pace at which homes are selling by analyzing how many days properties stay listed on the market compared to historical averages, and the trajectory they've been on over the last 3 months.
Methodology:
Current Days on Market: We analyze current listing duration data, both at the most recent date, as well as incorporating a 3 month moving trajectory.
Normalization: The current data is normalized against historical averages specific to each market to determine deviations from typical market behavior.
Scoring: The resulting metric is converted into a score that reflects market supply conditions.
Overvalued Index
The Overvalued Index identifies potential market imbalances by comparing current home prices with historical household income levels.
Methodology:
Price-to-Income Ratio: Calculate the current ratio of home prices to household incomes.
Benchmarking: Compare the current ratio against historical benchmarks to flag significant deviations.
Scoring: A higher score indicates that current prices may be inflated relative to long-term affordability trends.
Population Growth
Description: Population Growth measures the expansion rate of a market compared to others across the United States—a key indicator of future housing demand.
Methodology:
Growth Calculation: We use census data to compute the percentage population increases over a range of time horizons and demographics. We look at both how many people are moving to an area, as well as who is moving to an area. Growing families, college educated individuals, and those with jobs in tech are great predictors of future home price appreciation!
Comparative Analysis: Benchmark the local growth percentage both within a given market and across markets nationwide.
It may seem simple, but population growth is one of the strongest predictors of price appreciation! We take things a step further by also looking at not only growth, but who is driving that growth.
Price Cut Ratio
Our Price Cuts Ratio reflects the frequency with which listing prices are reduced and can signal shifting seller sentiment or market pressure.
Methodology:
Price Reduction Count: Count the number of active listings that have experienced price cuts over a given time period, observe trends in the last trailing 3 and 6 months to observe price reduction pressure.
Percentage Calculation: Express this count as a percentage of total active listings and compare these percentages both within a given market and across markets nationwide.
Listing Counts
Listing Counts measure market saturation by comparing the number of active listings to the overall available housing supply.
Methodology:
Active Listings: Capture the current count of active listings in a market, both coming from existing supply and new construction.
Supply Ratio: Calculate the proportion of these listings relative to the total housing supply, taking into account both new construction and historical inventory trends.
Normalization: The ratio is then benchmarked against national averages, creating a score that indicates market saturation.
Listing counts can be a handy tool for investors, but at Prop:Metrics we take things a step further to understand if this is coming from market growth or sellers eager to get out.
In Conclusion
By breaking down our methodology and sharing the details behind each metric, we aim to provide transparency into how our Home Price Forecast is derived. The integration of robust sub-metrics and continuous refinement through backtesting underscores our commitment to accuracy and analytical rigor. We encourage you to explore our data visualizations and to delve deeper into the numbers that drive these insights.
For those looking to navigate today’s complex real estate market, understanding these metrics is a crucial first step towards making data-informed decisions. Prop:Metrics is here to help.