… and why ownership capital structures matter

Much is written about data in today’s world. Those that have it, and more importantly those that control it, are seen as the new masters of the universe. Some people say it is overcooked, but others clearly see value. Not all industries have managed to properly capitalise on the potential that lies behind gathering ‘good data’. It may come as a surprise to some that the ownership of European commercial real estate is an area where the data business is incomplete.

Many will ask if there is value in knowing who owns a building? In the investment world, knowledge of who owns an asset has become hugely important. Let’s step back and look at the equity markets, where ownership data is more sophisticated and has become a vital component of the investment market. 

Being able to decipher precisely who holds the common stock in a company tells a story. It also answers a lot of questions, such as who is buying, or selling? Are the directors buying? Or are they selling? Is the business family-owned, with a controlling stake? Do the life funds hold it, or are they getting out of it? Are hedge funds buying… or perhaps shorting it? Is Buffett selling, or buying? The simple logic is that having all this information to hand is invaluable for those looking to make investment decisions. 

At its most basic level, of course, data can also facilitate the investment process.  Knowing the shareholder register of a company can greatly enhance liquidity – particularly when it comes to buying and selling smaller, less liquid, real estate stocks.

It is this issue of liquidity that frequently confronts direct real estate investors – especially when compared with other asset classes. And as real estate funds are becoming larger and more sophisticated, so their need for ‘good’ ownership data has grown. For many investment managers, raising ever larger pools of capital, being able to deploy this money is an important consideration. Knowing who owns what, and importantly the capital structure of the ownership vehicle, can deliver a vital edge – especially in the growing M&A market. If your investment thesis has targeted specific sectors in identified locations, then it is invaluable to know if those assets are held by investment vehicles that are likely to sell or not.

The global pandemic has highlighted this need. We have heard from a number of contacts that, during the height of the covid crisis, opportunist funds have been desperate to get hold of good ownership data – hoping to pinpoint possible sellers, such as funds coming towards the end of their life cycle, or owners potentially over-leveraged. Everybody is looking to add Alpha – and good data can deliver a solution.

The availability of good ownership data will not be welcomed in all quarters. Some say that brokers might feel the chill winds approaching – but, frankly, that has been on the cards for a long time. However, one other group that would benefit from a detailed ownership database is the lenders. It will give them far better visibility on what exactly it is that they are funding, and no doubt highlight potential threats lurking in isolated markets.

There are, however, issues associated with the collection of this data. At the heart of the conundrum is the disconnect that exists between the property and finance industries. Let us explain: the property business has long focused on the asset, and any transaction that may change the ownership of that asset. A simple example might involve a transaction where LaSalle sells an office building to German asset manager Deka for £50m, yielding 4.25%, with X number of tenants. Property people are good at recording this – and indeed that data is useful as it delivers current market pricing information and records the name of the new owner’s asset manager as a potential future seller of the asset.

However, there may very well be further information associated with that particular transaction, involving the finance side of the industry, which is not recorded. Deka might manage the asset, but does it actually own it? Almost certainly the ownership will rest in a client fund, and then the question will become: which fund? Is it an open-ended infinite fund, or a closed end spezial-AIF, with a finite life span?

This information not only provides intelligence about expected returns and capital requirements, but also gives an indication of the expected holding period and a future sale date. Furthermore, from knowing the vehicle owner’s capital structure it is possible to decipher if the mandate permits leverage or not – a situation that, as we know from experience, can be a trigger for an asset sale. This additional information, if presented in a coherent fashion, is seen by many investors in the industry as a stepping-stone to enhancing performance.

Property industry data also tends to focus on assets that can be sold individually or as a portfolio. Conversely, the finance industry focuses on asset-owning platforms, which require equity and debt funding in public and private financial markets and can be bought and sold as a platform. They talk the language of leverage, M&A target selection and ownership’s balance sheet strategies – considered an isolated world by many in the property industry. The frustrating thing is that the data is often there but remains confined within the financial world.

Combining these two separate worlds of finance and property data is therefore a complex and difficult strategic mission for all data providers; but once in place, we strongly believe it provides the ingredients to build the perfect intelligence platform.

There are clear signs that companies seeking to offer a strong data solution are becoming increasingly valuable – as illustrated by comparing the market capitalisations (as at 6 January 2021) of CBRE ($21bn), JLL ($7bn) and Costar ($36bn). But a word of warning about this low-volume, high-value data market. Those offering the service to the small but sophisticated universe of commercial property investors will need to produce very high-quality detailed data that is often a step beyond the ‘geeky’ world of data miners. The team that can build a platform that connects the data will clean up.

Read the second article in this series here.