Diana Olick

Realm CEO on Navigating the CRE Landscape with a Family Office Approach

Travis King, CEO of Realm, ⁢a firm‍ working ⁢with ultra-high-net-worth families, shared insights into the current commercial real estate⁣ (CRE)​ market and Realm’s investment strategy in a recent interview. King emphasized‍ the ⁣unique position family ⁤offices hold in⁣ navigating the complexities ‌of the market, leveraging ‍scale and a long-term investment horizon.

A unique‍ Perspective Through Scale and Diversification

King ‌highlighted the​ advantage Realm possesses ⁣due to its⁤ broad ‍reach. “Continues to⁤ be a very true adage,” he stated, referring to the⁣ importance of‌ diverse perspectives.⁣ “What we ‌find is that we’re unique in that ⁣we move across property type and across geography.” Realm manages collectively north of $12 ⁢billion in investable⁣ assets for ⁢the families it serves, granting access to a notable volume of deal flow across various sectors.

He ⁤stressed ⁣the⁢ importance of understanding both macro‌ and micro-cycles within real estate. “You don’t want ​to swim against​ the tide. You also ‍don’t want to, ⁣you know, try to fight the cycle. But there’s ⁤micro-cycles ‌that happen in different geographies ⁢and ⁤within ⁢different property types, so that’s a key thing to⁢ consider.”

Office as an Chance

When asked⁤ about his⁢ favorite CRE sector, King‌ pointed to office properties. He believes pricing in‍ many areas has begun to bottom‍ out.”If you⁢ look at this point in time, what we think is engaging, you’ll start with office,” he explained. ⁢He described ​a ⁢shift ⁣in investment evaluation, moving beyond‍ simply seeking lower prices to recognizing intrinsic value. “It really gets down to saying, ‘we know ​it’s cheap. It’s ​intrinsically cheap.’ In some cases, we’re buying things at 15% of replacement cost.” He ⁣cited a current ‌investment opportunity in⁢ northern California as an example.

Avoiding Broad Categorizations & Focusing on the Lower Middle Market

King outlined a strategy of avoiding broad sector bets, recognizing cyclicality.‌ “What I try to stay away from are broad categories,right?‍ Say,for example,like,well R&D or ⁢industrial⁤ is going to be‌ over. These things cycle, ‍and there’s going to be‍ different points ⁤in time.”

He acknowledged the current sentiment⁢ surrounding data centers, noting concerns about over-investment. Though, Realm’s focus on the​ “lower ⁤middle market” – deals of $50 million and below – keeps them somewhat distanced from this⁤ sector. “We especially ⁣were, we’re not really‍ in data centers in a large way,⁤ as we focus on that lower⁤ middle market,” King⁤ said. “If ​you look‌ at the big boys that have got tens of billions of dollars in their fund⁤ to be⁢ able to ‍invest,⁤ there’s a lot of dollars required to do the infrastructure in the data center. We really focus on,kind ‌of $50 million deals and below,as we feel like we’ve got an edge there.” He ‍conceded that many⁤ investors are pursuing data centers, but⁣ it’s outside Realm’s current ⁢investment scope, and he agrees with⁢ the assessment that the sector may be late in⁤ its cycle.

impact of Potential Interest Rate Cuts

King anticipates⁤ that decreasing interest rates would broadly benefit the real estate market. “I would​ say reducing interest rates helps real estate⁣ in most every‌ regard,” he stated. ⁤”I ‍think first and foremost, it’s going to help transaction volume. I think​ it just provides a wind to the sails⁣ of transactions, and it raises the value of all real⁢ estate.”

Data-driven Real Estate: BGO’s‍ Shift to Local⁣ Market Focus

BGO, a real estate investment firm, discovered that the success or failure of ⁤its investments was overwhelmingly persistent by the specific local market ‌chosen, reinforcing the industry’s long-held “location, location, location” mantra. This realization prompted a significant shift in strategy, prioritizing a deep understanding of local market fundamentals over broader property pricing trends‍ and national ⁤economic indicators.

While numerous research firms offer ​rankings of local ⁣real estate markets, BGO found their assessments inconsistent.Instead, the firm turned inward, analyzing its own ancient performance to build a predictive model. This model backtests the factors that drove both its best ‌and worst ‌results, incorporating‌ a ⁣wide range of localized data points – including‌ demographic shifts and unique supply trends. Artificial intelligence was⁤ then leveraged to amplify the model’s capabilities, processing a considerably larger volume of data at a faster pace.

“We have ​taken thousands of data inputs, many freely available from government sources, and others purchased from providers like telecom companies. We’ve ⁢identified the key drivers,” explained BGO’s Carrafiell, emphasizing the​ model’s proven accuracy through rigorous backtesting.

This‌ data-driven approach recently informed a prosperous investment in an industrial growth in Las Vegas, undertaken in partnership with Northpoint Development. Despite conventional research suggesting only mediocre performance,​ BGO’s model predicted substantial growth. ⁤The⁤ firm initially projected rents of⁢ $5.88⁢ per square foot, but ultimately secured leases in the $9-per-square-foot range – a ‌result​ Carrafiell attributes not to luck, but to the model’s insights.

The model identified a⁣ shift in logistics, noting that the Inland Empire of ​California was becoming ⁣prohibitively expensive. It then⁤ analyzed transportation routes and determined that Las Vegas offered a compelling alternative, providing ⁤significant cost savings ‍in rent, taxes, and labor. ⁤ “You had an extra two-hour drive, but you‍ saved like 60% on your total cost, and that’s what ‌the model‌ saw,” ⁤Carrafiell stated. The tenants attracted to ⁢the Las Vegas development serve a regional market, not just the city itself.

BGO has replicated this analytical process for ‍investments in Florida and the Rust Belt, consistently achieving strong returns.”We think our performance has ⁢materially⁤ increased as a result of this model,” Carrafiell confirmed.

However, he​ acknowledged the inherent limitations of any predictive‌ model, stating that unforeseen events ‍- such as a major company relocating – ⁣could ​disrupt⁤ even the most ‌accurate forecasts.

BGO employs ⁤a dual-modeling approach:⁣ the investment team focuses on upside potential, while the lending team concentrates on downside risk assessment. Future iterations of the model ​will incorporate asset allocation strategies, aiming to identify optimal portfolio mixes across different commercial real‌ estate sectors.

Carrafiell emphasizes that AI is not a replacement ‌for data science, but rather an “enhancer and ⁣accelerator.” He describes the firm’s dedicated data science team as an integral component of the investment process, working directly alongside the CEO, asset management, and acquisitions teams.