In Part 1 of a 2-part series, Max Bowie looks at the data needs for investors looking to trade real estate investments. To read Part 2, which looks at how blockchain could boost this market, click here. 

It’s easy to assume that the financial markets have already exhausted all major asset classes, and the markets with the most valuable assets already trade daily on exchanges around the world. And it’s true that foreign exchange trading has a turnover of around $5 trillion per day, while over-the-counter derivatives have a gross market value of about $10 trillion, though their notional outstanding is much higher.

But there’s a market with an even higher value that has yet to be fully exploited: property. Nareit, the industry body representing real estate investment trusts (REITs), estimates the value of commercial real estate in the US in 2018 was as high as $17 trillion.

Until now, this market has been the exclusive domain of real estate moguls and large property firms, or banks spending millions on buildings that they might own for decades, collecting rent and waiting for the value to double. The participation of retail and institutional investors alike has largely been limited to exposure through buying shares in REITs and property companies.

“Obviously, it’s easier to get data on a company that issues debt, than on a building itself,” says Elisabeth Kashner, director of exchange-traded fund (ETF) research at FactSet. “Real estate ETFs don’t fully represent the US real estate market because most of the market is privately held. … And most indexes—and the ETFs that track them—have a liquidity screen, so most penny stocks get screened out … and the underlying securities need to be accessible on public markets.” She adds that the similarity between securitized real estate assets and microcap stocks presents “real hurdles” to the inclusion of real estate in investment funds.

The real estate market dwarfs equities, for example, but has been very illiquid as an asset class because of the lack of transparency around pricing.

Phillip Silitschanu, Token IQ

Now, though, with the evolution of technology and data, some market participants are setting their sights on disrupting this exclusivity and opening up this market to new audiences and trading practices.

“The real estate market dwarfs equities, for example, but has been very illiquid as an asset class because of the lack of transparency around pricing,” says Phillip Silitschanu, director of strategic relationships at securities token issuance platform Token IQ, and former industry research analyst. “In the next few years, I don’t really see real estate being traded with the liquidity of equities or debt—I don’t think people will be day-trading real estate. But I do see people adding it to a portfolio or long-term investment plan where they can commit those assets for the extent of the development … and it takes on a stabilizing role within a portfolio of investments.”

The appetite for exposure to real estate among asset managers, alternative investment firms, and family offices is so great that traders are looking to gain participation through any and all avenues, including REITs, publicly traded companies operating in property markets, developers, and any related company in the supply chain, such as developers and supply stores such as Home Depot, says Erez Katz, CEO of big data analytics platform vendor Lucena Research.

While these types of investors may be driving change, traditional investors in the space are also contributing to increased transparency and data availability, driving service providers to offer more information around their investments.

Targeting Transparency

“We are seeing more money flowing into real estate … and we are getting into being a full-service real estate client data provider for our clients,” says Melanie Cohen, global head of private equity real estate at fund administrator Apex Group. Apex’s clients include multi-billion dollar funds with multiple real estate assets, ranging from shopping malls to railways, with up to 100 institutional investors such as pension funds, as well as closed-end funds with a horizon of between 10 and 15 years.

“It may be a 10- to 15-year investment, but they’re not going to wait 10 to 15 years to see how their investment is doing—and quarterly reports are not frequent enough anymore. Investors want to know more, and as a service provider, you have to be ready, willing and able to answer them,” Cohen says.

To do this, Apex has created a portal that fund clients can use to share more frequent and granular information about performance and a fund’s assets (for example, statistics relating to a building owned by a fund) with their investors, and is looking at implementing a system in-house—similar to that operated by real estate management software and data provider Yardi—to give its clients access to data inputs to perform their own valuations.

Real estate, I think, is a sector that is ready for disruption.

Annerie Vreugdenhil, ING

Others see even greater opportunities on the horizon. 

“Real estate, I think, is a sector that is ready for disruption,” says Annerie Vreugdenhil, head of innovation in ING’s wholesale banking business. “For starters, there is a lot of data, and a lot of data in registers that are relatively easily accessible. It also has a lot of middlemen who charge quite high fees. These are signs that a market can be disrupted.”

One of the protagonists looking to disrupt the space is the International Property Securities Exchange (IPSX), a London-based and Financial Conduct Authority-regulated exchange for trading securitized property assets in an equities-style format, by securitizing individual commercial buildings with values ranging from tens of millions to hundreds of millions of dollars, and listing them via an IPO.

“The idea of securitizing real estate has been around for decades, but has not been successfully done,” says Anthony Gahan, founder and chairman of IPSX. “It’s deemed an alternative market because there is no real public market, and there is very little data. There is private market data … but you can’t necessarily rely on that. It’s an industry that is still relatively data-poor, even though it is better than it was five years ago.”

Half of the UK market is owned by institutions, and trades infrequently, Gahan says. But half of the market is owner–occupier, where properties sit inefficiently on a company’s balance sheet as an expense, instead of becoming an asset that can be exploited.

However, you can bring a horse to water, but you can’t make it drink: While there is an appetite to gain exposure to real estate’s profits, some investors are still reluctant. The percentage of UK-based institutional investors’ portfolios invested in real estate assets is between 2% and 5%, whereas a balanced portfolio should be between 10% and 20%, Gahan says. “But there’s no liquidity, so they don’t want to hold it as an investment,” he adds. “That’s why, early on, we took the view that we needed to create a fully regulated market—because real estate is renowned for a lack of transparency.”

An IPO process for real estate assets would force owners to disclose more data about their buildings, he adds.

To provide transparent information in a manner that investors are familiar with, IPSX—which is currently signing up trading participants, and envisages expanding to other markets in the US, Europe and Asia in the future—has divided its information offering into market data, indexes, and benchmarks and derived data. It will make the data available through traditional channels, including low-latency data and trading infrastructure provider QuantHouse, which will provide IPSX’s data in the same format as the data it already carries, so clients can easily incorporate it into existing strategies.

“For us, IPSX is another interesting source of data. Our clients want more business opportunities than those being provided by equities, options, and other asset classes,” says Stephane Leroy, co-founder and chief revenue officer of QuantHouse, who believes property will prove to be a huge opportunity for asset managers and hedge funds.

“All those technology-driven clients have a solid appetite for anything new. They want first-mover advantage. So all our clients are curious, and now we have connection to the market …it’s very easy for them to test,” Leroy says. But because real estate is a different beast from other asset classes, it requires additional data for traders to make the best use of it. “A property is a physical location, and you have a lot of attributes that describe that property and location. So we are working on other datasets that can enrich the IPSX feeds—for example, satellite imagery, or geographical coordinates—to provide additional information on the area around a property,” he adds.

The institutional market is still investing the same way they did 10 years ago—through private investment, private equity funds, and REITs.

Jesse Stein, Compound Asset Management

The idea of listing real estate on an exchange isn’t entirely new: In 2012, Jesse Stein started a company called Etre Financial, which aimed to list real estate assets on exchanges. Retail investors loved the idea, but institutions were hesitant to get involved early.

“The institutional market is still investing the same way they did 10 years ago—through private investment, private equity funds, and REITs,” says Stein, who is now chief investment officer at Compound Asset Management, which has created a real estate investment product called the City Fund, which will create city-specific investment vehicles that will behave similarly to REITs, and which the firm plans to list on the New York Stock Exchange.

What’s interesting about Compound’s approach is that the firm will own the properties within the City Funds that it launches. It has seeded its Manhattan fund with four buildings, and is raising capital in the private markets to add more assets to the portfolio before IPOing the fund around year-end or early next year, and launching similar funds for other cities. This fragmented approach reveals the fragmented nature of the “market data” that exists in this space, and how data that’s useful for valuing assets in one city may not be applicable to other cities.

Protecting Value

However, not everyone believes that the exchange-driven model will lend itself to real estate. “I think it’s very unlikely that people will list a building on a stock exchange,” says Jeffrey Adler, vice president of the Matrix suite of data products at Yardi. “Large institutional investors believe they provide value to their clients by offering access to markets that they can’t otherwise reach … so they want to keep this off exchanges,” and are spending millions of dollars to assemble warehouses of proprietary and third-party data to create automatic valuations for every property in their investible universe to deliver competitive advantage, he adds.

According to Adler, just as in the fixed-income markets, valuations are the key data point to real estate being traded in a more liquid manner. “We offer a proprietary data service for institutional investors. But the challenge is that at the end of the day, you have to underwrite a building, and there is no such thing as a continuously updated underwriting for buildings,” he says. “With REITs, the investor is buying part of assets that someone else has underwritten. But to invest directly in a building, you need a daily or intraday update for the value of that building.”

The datasets that contribute to property values can be as diverse as location, the number of units in a building, square footage, occupancy ratio and delinquency (and the same metrics for nearby buildings), local payroll data, mortgage applications, loan and interest rate data, demographic information (such as how people are spending money in different zip codes), Yelp scores of nearby businesses, social media scores of tenants, and hard-to-define metrics such as how a neighborhood and its infrastructure is changing.

“If you think about the factors that coincide in predictive signals, it’s a combination of multiple, independent datasets. So if you think about what really makes the value of real estate go up or down, it’s a compilation of all of these things,” says Lucena’s Katz. In fact, Lucena is building a product that combines many of these predictive datasets specifically to meet demand for predictive valuations of the real estate markets. “This will be specifically for the real estate market, but the information we gather has much larger ramifications because real estate is such an important part of the economy.”

Data will also differ depending on the client and use case. “If you’re a 30-year investor, you may have different data requirements from a retail investor with a three-month timeline,” says Jeff Ramson, founder and CEO of strategic advisory and investor relations firm PCG Advisory, which is providing investor outreach services to institutional investors, family offices, and high-net-worth individuals on behalf of several companies looking to trade real estate as a digital asset.

PCG’s role is helping those companies tell the story of the potential new asset class. “Digital security issuers still need to communicate with investors,” Ramson says, adding that real estate is “probably the most easily digestible type of digital asset to understand …even if [everyone is] not sure yet how it would be traded.”

And before it can be traded beyond niche vehicles, real estate data needs to establish a common bond that ties the information together, in the same way that a Legal Entity Identifier (LEI) or an exchange’s Market Information Code (MIC) unites data about a stock or bond—perhaps, in the case of physical real estate, a new breed of identifiers based on GPS coordinates.

“If you want to trade properties themselves in a more liquid manner, you need more data, and especially a data master so you know what building both sides of a trade are talking about,” says Ely Razin, CEO of commercial real estate finance data provider CrediFi, which provides the reference data and identifiers—covering physical real estate as well as related equities and bonds—to link data to specific buildings, using machine-learning techniques to capture data from 3,000 counties and municipalities relating to property type and the shell companies that own them, to be able to reliably connect owners and buildings, and paint an accurate picture of property ownership.

CrediFi’s identifier includes basic identifying information such as address, how big a building is, and geo code, while its price evaluations take into account discounted cash flow analysis and uses nearby comparable sales.

“For there to be a tradeable universe of unique real estate stocks, you need a database of unique identifiers around them. … The real estate and financial markets have not yet organized themselves around one ID system—and we’ve done the hard work to master that,” Razin says. “From the beginning, we knew we were building the future, and we knew that real estate is a huge asset class that would move in the direction of other asset classes, to become more transparent, liquid, and open … to new classes of investors.”

Part 2 looks at how new technologies—and specifically distributed ledgers—could help to transform this asset class.