REIT Geospatial Analytics

This listing offers detailed analytics on REITs at the REIT level, Geographic Level and Property Level. Additionally, the analytics provide counts of the number of grocery stores, highway exists, cofffee shops, restaurants (by type), gas stations and other business types at varying levels of proximity to REIT owned properties.

The data is structured across three tables:

- REIT Level Metrics: Provides Herfindahl-Hirschman Index (HHI) concentration values as a metric for geographic concentration risk for each REIT along with a metrics for REIT portfolio concentration in by Urban, Suburban and Rural

- Geography Level Metrics: REIT property counts and portfolio proportions for different levels of political and urban geography to include: Country, State, County, MSA, Zip code. Breakdowns of portfolio concentration by Urban, Suburban and Rural classification is also provided down at State, County, MSA geographic levels

- Property Level Metrics: Provides locational details of specific REIT owned properties plus counts of the number of grocery stores, highway exits, coffee shops and other tenant desired features at different levels of proximity to REIT owned properties.

This offering is more than a mere investment aid; RDM's analytics provides a nuanced understanding of the inherent risks involved in the allocation of assets in specific geographical locations, enabling users to make well-informed decisions to optimize risk management and asset diversification. Data tables can help answer questions like, Is our investment strategy giving us true diversification? Or is the geographic overlap of different REITs actually over exposing our portfolio to same risks type despite attempts for asset diversification?

The Property level data are counts for hundreds of business types in close proximity to each REIT owned property, which allows subscribers to understand quality of a property's location. For example, data can be use do determine what REITs are located closest to features associated with higher rents, lower crime or logistical nodes like highway exits?

By leveraging this data, users can refine their risk assessment models, enhance their analytical capabilities, and gain a clearer perspective on the geographic concentration risks involved in REITs.

Fields Included:

- QY (QuarterYear)
- REIT
- GEOGRAPHY_LEVEL
- GEOGRAPHY
- ATTRIBUTE
- VALUE
- PROPERTY_ID

搜集汇总

背景与挑战

背景概述

该数据集通过REIT、地理和物业三个层级的指标，提供房地产投资信托基金的地理集中度风险分析和周边商业设施统计。数据支持用户评估资产多样化程度和物业区位质量，优化风险管理和投资决策。