Real estate market change monitoring system
- Post by: Valentas
- 2022-12-15
- Comments off
Market trends valuation center implementing the project Inostart financed by the European Union, during which it realized the prototype of the real estate expert evaluation system. The realized prototype allows to analyse the changes in real estate prices based on the economic, social and financial indicators continuously. The goal of the developed system is to provide a supporting tool for improving investment decisions for both private and public companies. Although the system is currently implemented for the valuation of housing, it can be extended to analyse other types of property, such as movable property or business. The current system covers the main two functionalities:
1. Monitoring of market trends. In order to improve decision-making when deciding on investment projects, it is important to know not only the current market situation, but also possible changes with the analysed project. For this reason, long-term forecasts of economic, social and financial indicators are made, both regionally and nationally.
Based on these forecasts, it is possible to forecast changes in the prices of specific asset types (currently this includes the apartment market).
2. Analysis of specific assets. When valuating a specific property, it is possible to obtain a comparison with historical sales, which allows the value of the valued object to be quickly compared to the market value. The system allows to make long-term forecasts of the value and to extract the correction factor, even when the comparable differ by more than 2 factors.
The system itself is multi-functional and the developed algorithms for real estate can be used to calculate:
– retrospective, current and forecasting average real estate prices, not only in large cities, but also in all Lithuanian municipalities;
– provide a sample of municipalities with similar price levels;
– it is possible to calculate the amounts of price corrections in relation to time, year of construction, location;
Application cases
The market monitoring section provides an opportunity to familiarize yourself with the functionality of the system. It is also possible to provide programming access (application programming interface API), which allows functionality to be integrated into existing systems.
Long-term price forecasts of specific assets
Long-term price forecasts of specific assets can be made using an artificial intelligence algorithm. In the created user interface, or using programming access, you need to provide the object’s address and its technical characteristics (e.g. area, number of rooms, etc.). This functionality allows you to extract price changes in the long term, which can help you make optimal decisions in risk management, investments, etc.
Market comparison
Users who want to compare a specific real estate object with the market situation can automatically receive information on similar transactions. Users using their company’s data can see detailed information, not just a summary. This functionality can also help valuators to choose comparables more objectively. In active markets, the recommendation of comparables is made by taking into account the location and technical characteristics of the real estate. In inactive areas, we take into account the local economic development level.
Correction coefficients
The system allows you to compare two properties and quantify the difference in each variable. In this way, correction factors are extracted that can help valuators or other users understand market trends and the reasons for the price difference. Usually, the extraction of correction factors is possible when the comparators are practically identical. This is because traditional statistical methods are not suitable for extracting correction factors when there is a difference in several variables between the comparables. However, there are approaches to the explainability of artificial intelligence algorithms that allow the extraction of correction factors even when there is a difference of more than 2 factors.
More than 60 economic, social and financial indicators are integrated in the realized model. Explaining the individual influence of each indicator can be difficult to interpret, so we have integrated them into 4 main parts: area, technical characteristics, location and time corrections.
Impact of change in financial indicators
Correction coefficients are intended for the comparison of an individual request, but a global assessment of the model is also possible, which allows identifying the average influence of individual indicators on price changes. This functionality could be used to extract the limits of influence of the relevant variables on the real estate price. For example, the influence of bank interest (euribor), the influence of energy efficiency class, etc. The example shows the influence of the purchased area, which confirms the general perception – the larger the purchased area, the lower the price per square meter.