The Top 10 Cities Index September 2019

Do you want to know where the UK residential market is going?

Our latest report for September analyses the UK residential property market using several AI based methods and new benchmarks to forecast future trends.

Our proprietary indices allow you to quickly assess what is going on in the top 10 urban residential property markets across the UK.

For the first time in a while we are seeing signs that the Brexit headwind is starting to abate as the index rose for the first time in six months.

To find out more, click the image below to see a video introducing our September 10 Cities report.

Click the image to watch the video

At Houseprice.AI we are committed to giving our clients advanced, accurate and granular data analytics and solutions.  If you would like a copy of the full version of this report, our Regional Overview reports, or to find out more about what we can do to help your business, please contact us at:

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Unwrapping 2019

Having just exited 2018, and as we step blinking into 2019, the team at Houseprice.AI thought that we should take a look at the year ahead. So to start with, we want to talk about property predictions and their accuracy.

As the Chinese proverb goes, the appropriately named year of the Pig promises to be an interesting time and clearly not just for the property market. All, largely due, to the ever surprising package we call Brexit.
So even though all the presents of 2018 are now unwrapped, one is sitting there and as we give the box a squeeze, we still have no clue what this one marked 'Brexit' will actually look like because the tag still reads 'Only open on March 29th'.

To help us we have reviewed a number of possible outcomes and scenarios and we have combined a number of resources and estimates from the following sources: Bank of England (BOE), Office for Budget Responsibility (OBR), Institute for Fiscal Studies (IFS), Centre for European Reform (CER) , Centre for Economic Policy Research (CEPR) all of which offer current best estimates for the UK’s economy and either explicitly or implicitly, associated potential impacts on the UK's residential property market.

Now many readers will say, 'ahah here's yet another crystal ball, mystic Meg exercise'. However, prediction is actually our business, and we are pretty good at it when it comes to property. By using objective data, paired with Machine Learning (ML), all expressed within a probabilistic framework, we are able to estimate property values to average errors of 2-3%. Our approach is scientific, by this we mean it is expressed as how probably wrong we are, not how absolutely right we are.

However there are three points that need to be stressed.

Firstly, it must be stated that the following are scenarios not forecasts. The scenarios illustrate what could happen, not even necessarily what is most likely to happen under a set of key assumptions. It is therefore a spectrum of outcomes that we worked with.

Secondly, whilst Brexit is clearly the major domestic factor for the UK, the global macro-economic environment is clearly another major concern. We could obviously mention the current fall in global stock markets, the prospect of further trade tensions between the US and China, the start of Quantitative Tightening (QT) and the flattening and inversion of the yield curve. All of the above point to much increased economic downside risks in addition to Brexit. For example, the chart below is reason for concern, since flattening of the yield curve, historically, is more often than not, a pretty good predictor of housing property declines.

Thirdly, whilst real estate is one of the largest asset classes, it is also the most heterogeneous. By comparison, traded stocks, bonds and commodities whilst also very diverse are far more standardised, so a further caveat we must make is that individual properties values can vary very greatly within a single location. Using our ML based algorithms we have high confidence for the predictive accuracy of our appraisal predictions at both a micro and property specific level. The image below links to an interactive map and this example in Stevenage - postcode outer SG4 - shows that HP.AI's average prediction error was 1.10% for 93 Terrace properties that sold and that we predicted over the previous 12 trailing months.

It should be mentioned that this is just one sample postcode area randomly taken from over 2,100 postcode areas that we estimate precise individual property values for, every month, based on our estimates vs actual Land Registry transactions. In fact, if you click on the map image you can see the sample for 12 months up to November 2018 has over 530,000 property valuations. Incidentally why only 530,000? Well we have to calibrate our ML models on the others, so some 700,000 in the last 12 months along with another 15 million from previous years.

Click the image to go to the reactive map

So whilst we are probably wrong, but we are also probably more likely to be less wrong than someone who is authoritatively pointing a finger in the air and citing subjective and anecdotal evidence. The interactive map below shows how accurate our valuations are in every postcode in England & Wales.

Click the image to go to the reactive map
We hope you have a good week!

Eldred Buck is CEO and Co-Founder of Houseprice.AI Ltd. He has over 25 years experience in capital markets and banking, specialising in quantitative models and derivatives trading across all major asset classes. Previously he founded Eiger Trading Advisors, a leading fintech company.
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