Rating attributes toolkit for the residential property market

The growing significance of the real estate market prompts investors to search for factors and variables which support cohesive analyses of real estate markets, market comparisons based on diverse criteria and determination of market potential. The specificity of the real estate market is determined by the unique attributes of property. The authors assumed that developing real estate market ratings identifies the types of information and factors which affect decision-making on real estate markets. The main objective of real estate market ratings is to create a universal and standardized classification system for evaluating the real estate market. One from the most important problem in this area is collection of appropriate features of real estate market and development dataset. The main problem involves the selection and application of appropriate features, which would be relevant to the specificity of information related to the real estate market and create a kind of coherent system aiding the decision-making process. The main aim of this study is to elaboration set of variables (knowledge platform) that were used to elaborate the real estate market ratings. The results lead to obtain the necessary set of features that constitute essential information which describes the situation on the local real estate market

HELIOS Approach: Utilizing AI and LLM for Enhanced Homogeneity Identification in Real Estate Market Analysis

The concept of homogeneity in the real estate market is a well-known analysis aspect, yet it remains a significant challenge in practical implementation. This study aims to fill this research gap by introducing the HELIOS concept (Homogeneity Estate Linguistic Intelligence Omniscient Support), presenting a new approach to real estate market analyses. In a world increasingly mindful of environmental, social, and economic concerns, HELIOS is a novel concept grounded in linguistic intelligence and machine learning to reshape how we perceive and analyze real estate data. By exploring the synergies between human expertise and technological capabilities, HELIOS aims not only to enhance the efficiency of real estate analyses but also to contribute to the broader goal of sustainable and responsible data practices in the dynamic landscape of property markets. Additionally, the article formulates a set of assumptions and suggestions to improve the effectiveness and efficiency of homogeneity analysis in mass valuation, emphasizing the synergy between human knowledge and the potential of machine technology

Residuals analysis for constructing 'more real' property value

The price of a real estate is based on its value. The real estate market, where the real estate price is established, is dynamic and undergoes continuous change. Considering the fact that nothing is fully deterministic or fully stochastic in nature, the author has put forward a compromise based on the conducted analyses in order to better diagnose the \u93live spatial structures\u94. The considerations presented in this paper provide grounds for the claim that integration of geo-deterministic inference (represented by the geostatistical model) and geo-stochastic inference (represented by maps of residuals), linked to space valuation, makes it possible to dynamically diagnose and characterise spatial phenomena and to make rational forecasts (and, consequently, planning) of changing in space and, therein, on the real estate market

Geoscience Methods in Real Estate Market Analyses Subjectivity Decrease

Real estate management, including real estate market analysis, is part of a so-called geosystem. In recent years, the popularity of creating various types of systems and automatic solutions in real estate management, including those related to property classification and valuation, has been growing in the world, mainly to reduce the impact of human subjectivity, to increase the scope of analyses and reduce research time. A very important fact that should be underlined is that properties are strongly related to geolocation (space) and strongly determine it. Authors proposed in the paper solutions that highlight implementation of geoscience and “geo-approach” combined with fuzzy logic methods that allow to decrease subjectivity in property analyses and diminish uncertainty in decision making process. The proposed methodology involves three main problematic components of decision support system in property investment analyses development with the use of geo-technologies such as: determination of the database model; elaboration geo-property-zones with geoprocessing activities; identification of homogeneous group of properties transactions. The influence of spatial decision factor determined in the study lead to objective and precise calculation of value differentiation from 22 to 43% depending on the property’s remoteness to the sea