Real Estate

There are multi-dimensional features for analyzing the valuation and financial feasibility of residential real estate investment. The first and most important feature to consider is location. Defining the location is more than just identifying desirable zip code / schools or commuting circle, but more importantly, involves defining the market most likely to increase/reserve value or generate income. DATAMIMO uses tremendous amount of historical and real-time market data in its analytical radar scanning to research supply / demand and competition in different areas that are often overlooked by even the most experienced investors and agents. 

For residential real estate, another important sets of features is physical and environmental feature, including proximity to freeway, nearby traffic patterns, topography, water quality, and zoning, etc.. Often neglected by inexperienced investors, these factors can be an integral part of the future desirability for residential real estate.  DATAMIMO appreciates these features and implements them into our analysis to better understand the community dynamics of the areas interested. DATAMIMO also focuses on the neighborhood features including accessibility to school and public service resources, trending in composition of the communities etc.. Instead of qualitative description or impressions for these features, we implemented these features into the feature matrix with calibrated weights, in a quantitative way.

The last sets of features DATAMIMO digests are economic characteristics and trends in the area as well as at national level. These features help draw the big picture of market: business development opportunities, overall economic health (GDP, employment rates, interest rates, inflation and tax changes) and population trend as a representation of future demand and regional growth patterns.

With the different sources and enormous amount of data, DATAMIMO provides a comprehensive picture of the residential real estate market and provides the outlook for a real estate investment. Our valuation is more accurate by combining value approach, cost approach and time-series models, and our cost-function is asymmetric and can be adjusted according to your personal needs (whether you are buyer or seller). We use contextual multi-armed bandit and reinforcement learning to help you optimize selling strategy like time to market and asking price, or buying strategy like time to offer and several versions of offering contracts.