About us

Quantitative finance, applied to real estate.

We are a team of data scientists with a background in quantitative finance. We strongly believe that a better use of data can make the residential real estate market more efficient — so we build the models and KPIs to prove it, and put them in your hands.

Models built like a trading desk

We create models and KPIs inspired by the world of quantitative finance to assess the market — views, pricing, risk and profitability, measured, not guessed.

Democratized access

We democratize access to those results and surface brand-new insights that standard listings never show — so anyone can act on institutional-grade analytics.

Invest rationally

Real estate is often the largest investment of your life. Our job is to give you the toolkit to answer the hard questions with confidence, not intuition.

Transparency, by design

We are committed to bringing much-needed transparency to the market — the kind that makes you feel like you understand exactly what you are getting.

How we think about insight

Insight = Data Quality × ( Modeling + Analytics ) Complexity
Johan Drylewicz

Johan Drylewicz

Founder

“I decided to create Haystock when I realized that most people around me — myself included — felt uneasy after buying or renting a new apartment: did we pay a fair price? Should we have waited? Not having the right toolkit to answer that is not acceptable. With Haystock we are committed to bringing the transparency and tools that let you understand exactly what you are getting.”

Johan worked for over 15 years on Wall Street as a quantitative trader before creating Haystock. He started his trading career at Goldman Sachs in London (2007) and moved to NYC to join JPMorgan as an exotics trader (2010), where he went on to manage their quantitative and execution-strategies trading and research teams.

He became a portfolio manager at the hedge fund Laurion (2017), where he spent six years designing investment strategies and exploring how to extract the most value out of datasets. He is a graduate of École Polytechnique (applied mathematics and physics) and NYU Courant (MSc, quantitative finance).

With Haystock he is exporting the best practices of quantitative finance into real estate, helping every actor make better investment decisions.

See everything before you buy

Explore the data listings don't show — views, sun, construction risk, comps and market signals.

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