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To address climate change, leading real estate funds and companies around the world are setting decarbonization and net-zero targets. These targets can differ widely and consist of many elements, and some may be more credible than others. In this report — which builds on our net-zero report for companies, “Breaking Down Corporate Net-Zero Climate Targets” — we outline an approach for evaluating real estate funds’ and companies’ decarbonization and net-zero targets. It aims to help the industry set net-zero commitments, as well as support asset owners in evaluating decarbonization targets of companies and funds they invest in. It argues that best practices for decarbonization and achieving net-zero are:

  • Comprehensive: Include all significant sources of emissions, even those that may be hard to quantify, including Scope 3 emissions from tenant-controlled energy use and development activities.
  • Ambitious: Pursue absolute reductions in the short and long term, in line with accepted, science-based pathways.
  • Feasible: Demonstrate progress toward goals, supported by a robust business strategy

This report was originally published in https://www.msci.com/www/research-paper/breaking-down-real-estate-net/03021835623

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Cushman & Wakefield’s 2022 Signal Report shows that recovery in all regions and sectors of the global real estate market will hit a new record in 2022. In this global report, our Global Head of Capital Markets Insights and Head of Investment Strategy for EMEA Capital Markets provide a quarter-by-quarter guide to investments in Commercial Real Estate (CRE) in 2022. 

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What can Artificial Intelligence (AI) offer the built environment in our age of climate emergency? At the heart of Deep Reinforcement Learning is an agent and an environment. Just as we are starting to learn that our actions within our environment have consequences on an immense, planetary scale, innovative AI is learning too – and faster than us.

By using Deep Reinforcement Learning to optimise the energy efficiency of HVAC systems in the built environment, we can minimise the negative impact of our own actions without sacrificing occupant comfort. As businesses all over the world attempt to transition to Net Zero, this technology has a pivotal role to play.

But why is Deep Reinforcement Learning the best way to optimise HVAC performance?

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Real Estate Investment Trusts (REITs) and Infrastructure Investment Trusts (InvITs) are conceptually like mutual funds in that funds are raised (backed by a sponsor) from institutional and retail investors which is then invested in infrastructure or real estate projects. The income earned from such projects is periodically distributed (at least 90% of net distributable cash flows (NDCF)) to unitholders. However, unlike mutual funds, they also have characteristics of a business enterprise considering they also raise debt and through a Trustee and an Investment Manager, are actively involved in projects to maximize returns to unitholders.

The rising emergence and popularity of REITs/InvITs in India is a welcome development for capital thirsty sectors, e.g., infrastructure (roads and highways, ports, railways, etc.), power, real estate, etc. With a view to increasing private participation supported by favorable government policies (e.g., enabling investment by foreign portfolio investors) and long- term investment outlook, many marquee investors including sovereign and pension funds are continuing to raise their stakes in such assets. Investors benefit from generating regular cash distributions, stable yield and an opportunity for sponsor(s) to expand their asset base.

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Take-up in the region’s warehouse markets remained robust in the second half of 2021, lifted by resurgent trade flows from the recovery in global demand. As a result, rents for logistics warehouses across Asia-Pacific rose by a marginal 0.5% year-on-year in the same period. Despite close to 9 million sqm of new supply expected to be delivered in the region in 2022, vacancies are likely to remain tight on strong demand and active pre-commitments.

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