The Algorithm
The Postcode Pricing Model generates an estimated price by using the changes in average sales price from when the house was purchased.
The average price is obtained by taking a geometric mean of the completed sales within the TF1 postcode.
Three estimates are calculated, each using a different timeframe of one month, three months and six months.
The longer timeframes give a less volatile result, but are less relevant to the current market.
The Calculations
Purchase Date March 2017
Purchase Price £172,000
One Month
Average Price between March 2017 and April 2017 £130,071 (22 sales)
Average Price between October 2024 and November 2024 £196,939 (14 sales)
% difference 51.409 %
£ difference ( 51.409 % of £172,000 ) £88,423
Estimated Price £260,423
Three Months
Average Price between January 2017 and April 2017 £155,699 (89 sales)
Average Price between August 2024 and November 2024 £205,779 (90 sales)
% difference 32.165 %
£ difference ( 32.165 % of £172,000 ) £55,323
Estimated Price £227,323
Six Months
Average Price between October 2016 and April 2017 £156,669 (283 sales)
Average Price between May 2024 and November 2024 £213,788 (190 sales)
% difference 36.458 %
£ difference ( 36.458 % of £172,000 ) £62,708
Estimated Price £234,708
The Pros and Cons

Based on actual sales data

The model is based upon actual completed sales figures.
Other models, for example the Halifax House Price Index are based on approved mortgage applications rather than completed sales.
Although mortgage approvals give a more timely index, not every approval leads to a completed sale.
Additionally within some districts many properties are purchased mortgage free by foreign nationals, this skews the Halifax and Nationwide House Price Indexes.

Model lags current market

The model's estimates lag behind the current market because it is based upon completed sales.
A typical house transaction takes around 8 weeks to complete, this creates a lag from the date the price is agreed to the date the transaction is recorded.
Therefore, on a rising market this model will underestimate the house price and on a falling market this model will overestimate the price.

Model doesn't adjust for home improvements

This is an algorithmic model which is based purely on changes to average house prices.
The model doesn't factor in any improvements made to the specific property.
This aspect of the model is not as bigger weakness as expected.
On average most homes get brought, get some level of home improvement, and then get sold in a seven year period.
Therefor the sample which we draw the averages from also contains houses which have had home improvements.
We always recommend that you use a professional valuer, or estate agent to get an accurate valuation.

Uses postcode boundaries

A house's postcode is an important factor to its price.
Prices in one postcode can appreciate, while houses in the next postcode stagnate.
Other information on this house

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