Using Hesti Market Data to spot the next growth neighbourhood

Hesti Market Data dashboard with charts
Key takeaways
  • Filter by year or quarter, city and neighbourhood. Hesti Market Data shows average, median and deal volume for each slice you pick.

  • Momentum = rising price + rising volume. When both climb for several quarters, the area is likely enjoying strong demand and future upside.

  • Compare series types (new builds, Soviet‑era blocks, pre‑war stock) and room counts to zero‑in on outperforming segments.

  • Market data guides investors on entry timing, rental yield checks and avoiding overpaying.

What is Hesti Market Data?

Hesti Market Data aggregates average and median €/m² plus deal count and volume across Latvia. Filters let you drill down by city, neighbourhood, building series, room count and period (year or quarter). For sales you also get transaction volume — your proxy for market activity.

Why momentum matters

Analysts watch momentum — the direction of both price and volume — to catch neighbourhoods on the rise. When average price and volume rise for two or more quarters, demand is accelerating and future gains are more probable. Price up but volume down might signal a topping market.

Using the filters
  • City / neighbourhood. Try Riga → Centre vs Teika.
  • Series type. New builds often outpace Soviet blocks in capital gains.
  • Room count. Studios can surge near universities.
  • Period. Flip between year and quarter; momentum usually shows up over 2–3 quarters.
Turning data into decisions
  1. Entry timing. Rising price & volume = early‑stage upswing.
  2. Diversification. Mix series types: new builds for lower upkeep risk, renovated pre‑war flats for higher appreciation.
  3. Yield check. Combine sale and rental averages to compute gross yield.
  4. Exit clues. Flattening momentum hints it may be time to harvest gains.
Takeaway

Hesti Market Data makes momentum analysis simple: select an area, see if both prices and volume climb, compare segments — and act on the insight to find tomorrow’s hotspots before the crowds.

Article author
Mārtiņš KozlovskisMārtiņš Kozlovskis