---
title: "Suburb Trajectory"
method: GET
path: "/api/v1/cd-planner/suburb-trajectory"
tags: ["cd-planner"]
---

# Suburb Trajectory

`GET /api/v1/cd-planner/suburb-trajectory`

## Request

- Base URL: `https://api.casaintelligence.com.au` (the document declares no server; this is the origin it was published from)
- URL: `https://api.casaintelligence.com.au/api/v1/cd-planner/suburb-trajectory`
- Auth: API key in header `X-API-Key`

Multi-quarter price trajectory for a suburb (optionally per type),
expressed as an annualised compound growth rate from a log-linear
regression on quarterly medians. Replaces the prior single-year YoY
delta which was noisy in low-volume suburbs.

Math
────
1. Bucket sales into quarterly medians over the last 24 months.
2. Need ≥3 quarters with ≥10 sales each to compute a suburb estimate.
3. Linear regression: log(median_t) = a + b·t (t in years from earliest
   quarter). annualised_growth = exp(b) - 1.
4. R² = 1 - SS_res/SS_tot for confidence.
5. If suburb fails the threshold, fall back to the LGA's trajectory
   and report fallback_used=True so the caller can surface the
   degradation honestly.

Why this matters
────────────────
SEQ markets in 2025-26 are running +15-25% YoY. The pricing engine
used to time-adjust comparables using a single 12mo-vs-prior-12mo
delta — fine for high-volume suburbs, noisy in small ones (a 30-sale
suburb's median can swing ±10% from one outlier). Quarterly regression
gives 4-5 data points and a confidence measure.

## Query parameters

- `suburb` string, required
- `property_type` string, nullable: Optional filter: 'house', 'unit', 'land', 'townhouse'

## Response `200`

Successful Response

- unknown

## Other responses

- `422`: Validation Error

---

[API](https://skmtc.dev/casaintelligence/apis/casa-intelligence-engine.md) · [All operations](https://skmtc.dev/casaintelligence/apis/casa-intelligence-engine/llms.txt) · [OpenAPI document](https://skmtc.dev/casaintelligence/apis/casa-intelligence-engine/revisions/71d711039de0?raw)