We follow a 5 step process, below you can learn more about our "Forecasting Process".
Step 1: Aggregate Data
Accurate forecasts and insights begin with great data. HouseCanary continues to build an advanced real estate data platform to predict future real estate prices, including 1,000+ data series for each real estate market and 50+ years of monthly history. Our real estate data is combined with macro-economic data, capital markets data, mortgage data, search & social data, and house/parcel data to form the most comprehensive and multi-faceted data set.
Step 2: Transform Data
We transform data to develop "smart" proprietary variables that help to explain market behaviors over time and eliminate spurious relationships. Our "smart" proprietary variables explain how the market behaves and where we are in the housing cycle.
Step 3: Identify Leading Variables
For each metro area and market, we identify which variables are driving future change. We use machine learning to define how far each variable leads what we are predicting and the relationship. This enables us to leverage data that is known as of today, that has leading relationships to create time-tested predictive models.
Step 4: Model Selection & Forecast Development
We turn data into predictive models you can trust. Using our leading indicators, we build customized models for each metro area and zip code that best explain price change 36 months into the future. Using advanced statistical methods, machine learning, and mass computing power, we scan the space of up to 4 billion potential models for each area, and average the best ~1,000 models to arrive at the most accurate forecast.
Step 5: Back Testing
Every month we back-test our models for each metro area and zip code to see how our predictions match up with what actually happened. Across all markets, our models explain more than 95% of the past variability in price changes (R2>0.95). Furthermore our models yield highly accurate out-of-sample forecasts in the near-term and long-term, and they continue to improve through our ongoing research and development.