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News and blog
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Accounting for tenant default dynamics in logistics real estate
Using alternative data for logistics markets analytics
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Diverging logistics activity accelerates across European markets
Logistics activity across European markets continues to diverge with growing differences also across local submarkets becoming more significant.
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Are your real estate portfolios growing where cities are growing?
The use of alternative data including satellite data can significantly improve outcomes in real estate allocations through identifying locations of accelerating growth both across global markets and within individual markets. To further leverage alternative data, machine learning (ML) techniques can be implemented to process information at near-live time scale or at regular time intervals, e,g, annually, to both identify and monitor emerging and expanding market hotspots.
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Forecasting logistics rents with alternative data, Dallas/Ft. Worth
Using alternative data improves forecasts of logistics rents in a market, provides superior forward looking characteristics compared to traditional data such as employment in the sector and allows significant flexibility in assessing more granular submarket or specific asset geolocations . Alternative data is both more consistent and more timely giving users and investors near real-time nowcasting ability of logistics and distribution activity at any location.
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Logistics, valuing sectors in listed markets using ML
We illustrate how machine learning techniques can enhance valuation methodologies of sectors in listed real estate markets and how investors can both interpret and incorporate changing market conditions when considering sector tilts or underwriting of individual stocks. Sector tilts are an important source of alpha for investors which makes interpreting future prospects for sector performance a critical part of the investment process. We illustrate how ML and econometric models can be utilised for both spot valuations and to form well informed, data driven expectations about future performance.
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Market and city level nowcasting data
Kania is launching unique nowcasting data sets for real estate markets based on monitoring of physical transport vehicle flows. The data sets are a development from Kania’s asset level and geolocation specific monitoring capabilities. Aggregating transport flows across multiple key transport routes such as around freight handling locations and logistics zones within a market provides live nowcasting of both transport and distribution activity critical to logistics real estate but also nowcasting of general economic activity in a market with significant implications for other real estate sectors such as retail and hospitality.
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Active trading patterns in fundamental REIT funds
There is some evidence to suggest that fundamental REIT managers (“FRMs”) are largely trend followers. A large part of messaging from FRMs is comments on most recent performance of various sectors and messaging regarding expectations for secular trends or tailwinds in sectors that are already trending.
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Case Study: Submarket and geolocation intelligence for logistics real estate
Kania Advisors provided unique market intelligence to a US-based private equity investment firm. This information provided unique granular insights to understand, benchmark and compare both logistics market dynamics and specific asset geolocation attributes.