Why does using just price data often outperform traditional market fundamentals in predicting real estate trends?

In this episode, financial engineer and real estate investor Stefan Tsvetkov explains why relying on price trends can be more accurate than using population, income, or job growth to forecast appreciation. Drawing from years of data modeling and firsthand investment experience, Stefan breaks down the mechanics of momentum in real estate markets and introduces tools for predicting downside risk. He also shares lessons from the 2008 crash to highlight the risks of ignoring valuation. This is a numbers-based look at smarter, leaner ways to evaluate and choose real estate markets.

[00:01 - 06:00] The Case for Price Over Fundamentals

• How price data leads to fewer forecasting errors.
• Why adding more variables increases uncertainty.
• The importance of simplifying your analysis.

[06:01 - 12:43] Momentum in Real Estate

• How last year’s prices help predict this year’s.
• Why many markets show strong trend patterns.
• The significance of autocorrelation in market forecasting.

[12:44 - 18:51] Forecasting with Models

• How tools like ETS help spot short-term trends.
• Why 2021 broke from historical patterns.
• The need to update models as trends shift.

[18:52 - 24:37] Population Growth vs. Price Performance

• Why population explains only part of the trend.
• How combining metrics offers a fuller view.
• The importance of watching overvalued markets.

[24:38 - 27:44] Measuring Downside Risk

• How past crashes linked to overvaluation.
• Why fundamental misalignment increases risk.
• The importance of tracking valuation gaps.

Connect with Stefan:

https://www.linkedin.com/in/stefantsvetkov

Key Quotes:

"You commit a five times bigger error trying to model future appreciation with fundamentals than if you just look at prices alone." - Stefan Tsvetkov

"Real estate is a fundamental asset. When prices deviate far from fundamentals, downside risk increases significantly." - Stefan Tsvetkov

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