AI-supported, fully automated, and refreshed on every run: public data flows in, the models update, and the reports are written by code. No analyst hand-picks a number, talks their book, or hands you a view — which is exactly why this is information and forecasts, not advice.
In plain terms
MPLC Research is a fully automated model, not a team of analysts. Public data flows in from official sources; the model processes it the same way every time; and the reports — every figure, chart and sentence of commentary — are generated by code. No human chooses a number to fit a view, writes a personal opinion, or is influenced by who's paying.
That's deliberate. An automated, AI-supported process is consistent (the same inputs always give the same answer), reproducible (anyone can audit how a figure was reached), always up to date (it refreshes from source on every run), and free of the bias that creeps into a human market call. It is also why everything here is information and forecasts only — not financial advice, and not a recommendation to buy, sell or hold anything.
AI-supported · automated · always up to dateThe method
No black box. The method is published, the forecasts are tested against history, and every figure carries its source.
The RBA cash rate and the bond market set the market yield each sector should price at — the macro anchor.
The building-approvals pipeline and a leasing-sentiment signal show what supply and demand are actually doing on the ground.
The two meet in a tested error-correction model, run thousands of times (a Monte Carlo) to produce a return range and an honest downside.
The data
The edge isn't a louder opinion — it's more ground truth, every point sourced and checked automatically on each run.
Every series traces to a named public source — the exact RBA table, ABS dataflow or Census table — with how it's accessed, how it's derived, how often it updates, and why it moves commercial property. The model resolves from the national economy down through 6 states, 96 city sub-markets and 344 sub-market groups to 1,113 individual precincts. Freshness and plausibility are checked automatically on every run; anything that looks off is flagged, in the open.
Tested against history
The model is back-tested the honest way — walk-forward and out-of-sample, only ever using data it would have had at the time.
A signal is only added to the model if it improves accuracy on this out-of-sample test — never because it sounds clever. The same discipline applies to the honest limits: the model is strong on yields and value, weaker on precise rents, and it is built to recognise regime shifts and shocks rather than to nail a single point forecast.
To be clear