It’s good that finally the media is including forecasts when discussing the future of Australian’s real estate prices.
However we can improve on the forecasts being used. The CoreLogic Moody’s forecasts that are quoted are regularly highly inaccurate; Vifortech Solutions has proved it can do better.
Comparing the percentage error of annual forecasts in the discussion below, we see:
- In only one case is the Vifortech Solutions forecast wrong by more than 25%; and
- In four out of five cases the CoreLogic Moody’s forecast is wrong by more than 30%.
Contact me if you would like to discuss further.
Now… Let’s dive into some details.
What is the claim?
A recent article (archive) by Shane Wright (no relation!) in the Sydney Morning Herald points to the Moody’s Analytics property price forecasts with mentions of regions and expected movements:
In Sydney, Moody’s is predicting an overall drop of 3.3 per cent in values. Areas such as Ryde (6.6 per cent) and the eastern suburbs (6.7 per cent) are forecast to endure substantially larger drops in value.
Whilst Moody’s (and Moody’s Analytics) are well known brands, there is no discussion of the (in-)accuracy of their previous work. Let’s look and compare against the Vifortech Solutions forecast.
(For context, I should point out that I founded the CoreLogic International Analytics team, so I know something of their business.)
Forecasts: CoreLogic Moody’s vs. Vifortech Solutions
Vifortech Solutions regularly outperforms CoreLogic Moody’s
In the table below I have the performance of both the Vifortech Solutions and CoreLogic Moody’s (CLM) forecasts for the 12 months ending Q1 2017 for the five largest Australian (capital) cities. That is, how accurate were the 12 month forecast?
(Yes, I know this is a while ago, but these are the only comparisons I’m able to publish at the moment.)
The table below lists the percentage error of the forecast 12 month change against the actual (observed) 12 month change. For those playing at home, the percentage error is the difference (i.e. forecast minus actual) divided by the absolute value of the actual.
Percentage Error | ||
Vifortech Solutions | CoreLogic Moody's | |
Adelaide | -24% | -91% |
Brisbane | 40% | -7% |
Melbourne | -25% | -32% |
Perth | -12% | 100% |
Sydney | -18% | -79% |
What do we see?
In four of the five markets the Vifortech Solutions outperforms CLM. We didn’t do so well in Brisbane.
In the closest market, Melbourne, the CLM estimate differs from the observed result by 32% compared to the Vifortech difference of 25%. That is, the CLM estimate is 28% (i.e. \( \frac{32}{25} – 1 \)) more wrong.
Magnitude of errors
More telling is the magnitude of error compared to what actually happened:
- In only one case is the Vifortech Solutions forecast wrong by more than 25%; and
- In four out of five cases the CoreLogic Moody’s forecast is wrong by more than 30%.
Perth, the most volatile of markets reinforces this point; the CLM forecast is incorrect by 100% – estimating zero change whilst the market fell by 4%.
The performance of the CoreLogic Moody’s index
Below are the actual, published, CoreLogic Moody’s results.
CoreLogic Moody's | ||||
Actual | Forecast | Difference | ||
Adelaide | 3.5 | 0.3 | -3.2 | (-91%) |
Brisbane | 4.5 | 4.2 | -0.3 | (-7%) |
Melbourne | 10.6 | 7.2 | -3.4 | (-32%) |
Perth | -4.0 | 0.0 | 4.0 | (100%) |
Sydney | 10.7 | 2.2 | -8.5 | (-79%) |
Here is a plot of the Reserve Bank of Australia House Price Index values. The CoreLogic Moody’s results are against their bespoke index – the results differ from the public data, but not materially enough to change the conclusions herein. The squares represent the equivalent CoreLogic Moody’s forecast for this data, the triangles the Vifortech Solutions forecast.
Final thoughts
It’s good to finally see some articles talking about forecasts based on analytics. It’s a pity the easiest to consume analytic articles aren’t using the best insights in the market.
The other question that we can’t answer with the published results is the uncertainty of the results. How reliable are the forecasts? With four out of five forecasts wrong by more than 30%, I’m guessing not very.
If you’d like to know more, please reach out.