First post from Tokyo

Renovation needs may decide whether a warehouse works for me more than any apparent price reduction. I’m a Tokyo homeowner exploring warehouses and trying to understand acquisition costs, completed deals and ongoing management rather than relying on advertised figures alone.

I may be assuming that broad market comparisons will transfer neatly to Japan, but an older building with difficult access could quickly disprove that. Which section of the local board is best for questions about renovation and property management, and what information should I gather before attempting an investment model?
 
Starting with broad price data could send you towards the wrong warehouse if the intended use and holding period are still undefined. Two buildings might show a similar difference between list and sale price, yet one may need major renovation while the other has higher management costs.

I would first decide whether this is a possible purchase or simply a modelling exercise. Then use the Tokyo or Japan board to investigate completed prices, acquisition costs and management separately, bringing them together only after the property type and assumptions are clear.
 
The headline price gap is a weak comparison on its own. My specific concern is that it can conceal differences in building age, condition, access and renovation scope.

For example, a warehouse sold well below its advertised price may still be the worse deal once necessary works and management costs are included. Define the intended warehouse use and holding period first, then compare completed evidence for genuinely similar properties. That will also make questions on the local board much more precise.
 
For a practical start, build one simple comparison sheet using the same assumptions for every candidate: asking price, completed price where available, transaction costs, financing terms, renovation allowance and management costs. Keep uncertain figures visibly separate rather than forcing a precise return estimate. Then use the local board for targeted questions—especially mortgage comparisons and legal checklists, since those are jurisdiction-specific—rather than asking for one dataset to cover everything.
 
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