Habidatum’s Location Risk Score (LRS) data feed helps to harness the power of the hard to quantify local market factors surrounding assets and asset valuation. According to Moody’s Analytics, location is responsible for about 80% of the property value. CRE investors and industry analysts can use the LRS to quickly compare assets and put them into context with peers for the purpose of location analysis. Not only is LRS incredibly effective for maintaining an appropriate risk profile for CRE portfolios as the name implies, but it can also be used to evaluate a property’s price and the location’s risk premium.
In order to make LRS functional and instrumental, Habidatum “decouples” the location from the property, measuring commercial potential/risk associated with location separately from the property. This is done by comparing similar listings on the basis of building quality, available space, and listing type. When location risk and price are the variable components, they tend to correlate inversely.
LRS in detail
The data feed is a composite of human mobility data, business volume, and business diversity. With numerous submetrics based on location accessibility to other locations, the LRS is adaptable to the complexities of geographically dispersed, multi-asset class portfolios. With granular location data and accessibility isochrones involved, LRS allows taking both the assets’ localities (closest proximity) and local markets (catchment areas) into account.
New York offices pricing analysis
To assess NY office pricing, the dataset from on-market sales listings of office space in the New York Metropolitan Area was used. We eliminated all properties with less than 1,000sf, and any investment-sales type listings with a tenant credit component. We performed a detailed assessment of each building and sorted the data by the quality of the office. The remaining were three sets of comparable properties.
The accessibility mix used for NYC Office Listings (represented as Local score and accessibility scores in minutes: Walk 10, Auto 10/15/20, Public 10/15/20), encompasses many different modes of transportation and was chosen to reflect the preference of commuters to travel via car and public transport. The score also includes the local area score to account for the need for offices to be in high activity areas with options for food and entertainment.
Full analysis here.
This analysis is part of a series of publications resulting from FIABCI's partnership with Habidatum.
Habidatum is a software and data analytics company, assisting policymakers and businesses in understanding the hyper-dynamic urban environment through advanced analytics of diverse data sources driven by machine learning and interactive visualization.
Habidatum operates as a gateway between the professional communities that require data-driven insights and data carriers.
The company was founded in 2014 by a collaboration between professional urban planners and digital designers. Since 2014, the company has worked in more than 20 cities globally including London, New York, Moscow, Dubai, Singapore, Pune, Denver, and Miami.