Explore the 7 key factors driving London property prices based on our comprehensive analysis of real estate market data from 1995.
Our analysis of the London real estate market is based on a cross-sectional factor model similar to the MSCI Barra model for equity return decomposition. This approach allows us to identify and quantify the specific factors that drive property prices in London, providing valuable insights for investors, homebuyers, and market analysts.
The advantage of this model is the simplicity of the factors identified, which are easy to understand and make the model very explainable.
By decomposing property returns into these factors, we can better understand London housing market dynamics, identify trends, and make more informed property investment decisions. Each factor represents a specific characteristic or market condition that influences property values across different London neighborhoods.
Below is a summary of all factors in our London property market model. Click on any factor to jump to its detailed analysis and historical performance.
The residual of the regression, representing the overall London housing market movement independent of specific property characteristics.
The impact of a property's total floor area on its price, showing how size directly affects valuation in the London property market.
The price premium or discount associated with newly constructed properties compared to existing housing stock in London real estate.
The non-linear relationship between property size and price, capturing diminishing returns of additional space in London properties.
The non-linear impact of room count on London property values, beyond just the total floor area.
The impact of energy efficiency on London house prices, reflecting environmental concerns and energy costs.
The non-linear impact of a property's age on its value, reflecting different architectural styles and building standards in the London housing market.
The baseline market return represents the residual of the regression, capturing the overall London property market movement independent of specific property characteristics. This factor reflects the general trend of the London real estate market.
When this factor is positive, it indicates that the overall London housing market is appreciating regardless of property-specific features. When negative, it suggests a general market decline affecting properties across London.
The total floor area factor measures the impact of a property's size on its price in the London real estate market. This factor quantifies how much additional value is added per square meter of living space in different London neighborhoods.
Historically, this factor has remained positive, indicating that larger properties consistently command higher prices in the London property market. However, the premium for additional space varies over time and across different market conditions and London boroughs.
For London property investors, understanding this factor helps identify when the market is placing higher or lower premiums on property size, which can inform buying and selling decisions.
The new build factor captures the premium or discount associated with newly constructed properties compared to existing housing stock in the London property market. This factor has shown interesting variations over time as buyer preferences and construction standards have evolved.
Historically, London new builds have often commanded a premium, but this has fluctuated based on market conditions, construction quality trends, and buyer preferences. In some periods, new builds have actually sold at a discount to comparable existing properties in certain London areas.
Understanding this factor is crucial for developers, investors, and homebuyers considering London property investment in newly constructed developments versus established properties.
The Non-linear area factor captures the non-linear relationship between property size and price. This factor recognizes that the value added by additional space is not strictly proportional.
In particular, deviating from the mean floor area has non-linear effects on the price, so going from 50 to 60 square meters may have a different impact than increasing from 150 to 160 square meters. This non-linear relationship is important for accurately valuing properties of different sizes.
The number of rooms factor measures the non-linear impact of room count on property values. This factor captures how the layout and division of space affects pricing beyond just the total floor area.
Interestingly, this factor has generally shown negative values, suggesting that for properties of the same size, those with fewer, larger rooms may command higher prices than those with more, smaller rooms in the London market.
The energy score factor measures the impact of energy efficiency on property values. As environmental concerns and energy costs have become more prominent, this factor has gained importance.
The historical data shows an interesting evolution in how the market values energy efficiency, with a general trend toward higher premiums for energy-efficient properties in recent years.
The constructon period factor captures the non-linear impact of a property's construction period on its value. Different construction periods are associated with different architectural styles, building standards, and materials.
This factor shows how the market values properties from different eras, with some vintage periods commanding premiums while others may face discounts.