Roman Kirzhner believes one of the most important skills in real estate is knowing when not to buy.
In this monthly update, Roman shares what his team is seeing in Texas multifamily and why they are putting more attention on smaller markets instead of major cities like Dallas, Houston, and Austin.
One market on his radar is Texarkana, where his team already owns a 22-unit property and is now working on a 60-unit property about 10 minutes away.
Roman walks through what makes the deal interesting. The property is currently 77% occupied, rents are about 17% below market, and the planned improvements are focused on light renovations, curb appeal, and getting amenities like the gym and laundry working well.
He also explains one of the strongest financial pieces of the deal: an assumable loan at 5.5% with another six years of interest-only payments.
Then Roman takes us behind the scenes of due diligence. He explains why the due diligence clock should not start until the seller has provided the required documents, why his team walks every unit, and why paperwork alone does not always tell the full story.
On the Texarkana property, the insurance loss run showed zero claims. The physical inspection told a different story. One unit had burned, and that discovery brought Roman and his team back to the negotiating table, where they negotiated about $25,000 to cover the issue.
Roman also shares why he is studying artificial intelligence, how his team uses AI during due diligence, and a simple habit he recommends when using AI: after getting an answer, ask the tool to critique its own response.
In this episode, you’ll hear about:
- Why Roman is concentrating more of his attention on Texas
• What he looks for in smaller Texas markets
• Why 20 to 75 unit properties fit his buy box
• The plan for a 60-unit Texarkana apartment property
• How below-market rents and vacancy create a value opportunity
• Why the assumable 5.5% loan matters to the deal
• What Roman checks during physical and financial due diligence
• How an inspection uncovered a burned unit that was not shown on the loss run
• How Roman is using AI to help analyze real estate information
• Why he recommends asking AI to critique itself
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