This Houston company has the key to a more exact searching process when it comes to finding a new home to buy. Courtesy photo

For most consumers, the home buying process includes a very specific online search. People specify their neighborhood requirements, the number of bedrooms or bathrooms, backyard size, and more — yet still, the search results in a staggering amount of homes. It's way more than anyone can reasonably look at.

That's where Martin Kay and Entera Technology, the company he founded and is CEO of, come in. Kay, a 20-year veteran of the tech sector, who's bought multiple homes as rental properties, realized the way to solve the problem of that kind of search engine overload was through machine learning. He now works with some of the largest home-buying companies in the world, helping them find properties that match the specifications they have to attract the clients they want.

"All residential real estate is a consumer product," he says. "Ultimately, the people who are going to live in that home care most about, is it a nice home with a big backyard neat good schools, is it safe? The [home buying] companies are trying to figure out what do the end consumers really care about so we can give them exactly what they need?"

To do so, Entera collects data — lots and lots of it. Kay and his team have taught their software programs what a chef's kitchen is, for example. They did so by compiling tens of thousands of photos of kitchens and telling the software, "This is a kitchen." Then, they taught it to recognize what makes a chef's kitchen — a larger size, more than one sink, high-end appliances. They used the same techniques in identifying things like millennial-friendly neighborhoods or neighborhoods that were up-and-coming on the real estate scene. They draw from listings available with the Houston Association of Realtors and beyond, a vast array of tens of thousands of homes.

Officially launched in 2017, Entera blends its data collection and analysis with on-the-ground service. After Entera's proprietary software collects what it thinks home-buying companies want, members of Entera's service team go out to look at the homes.

"We're a little bit like Netflix," he says. "They go out and get content from everyone, and they begin to watch your behavior. So, Netflix has 2,000 profiles and you probably fit five or six of those. We have almost 100 profiles and what we do is say, we're going to understand what you want, watch your behavior and instead of giving you 40,000 properties on a big map, we actually match you based on your preferences, to the five or six houses that are best for you."

While Entera has been working with larger home-buying companies — like firms that buy tens of thousands of homes every year — Kay says they have begun working with smaller entities, and he figures within the next few years, Entera will be using the same data collection and machine learning to work with individual home buyers.

Based in Houston, Entera has operations in New York and San Francisco as well. The company has 17 full-time employees, along with approximately 100 contractors in its markets. And while Kay understand a human touch is needed in business, he loves that he can use a data model to present unbiased opinions to his clients.

"[Real estate] actually affects people's lives meaningfully," Kay says. "Real estate data — where you live, what your neighborhood is, how you make that choice — …this data matters to people in a way they can tangibly touch and understand and feel. We can help people make what are big, complex choices that are often highly ambiguous. I love it because it matters. You can measure how it matters immediately."

Data-driven tech

Courtesy of Entera

Entera focuses on collecting data and analysis and pairs it with on-the-ground service. After Entera's proprietary software collects what it thinks home-buying companies want, members of Entera's service team go out to look at the homes.

A growing digital home sales platform has moved into town. Courtesy photo

Digital home buying and selling tool expands to Houston market

Real estate tech

A Phoenix-based real estate company has expanded to the Houston market and opened a new office in town.

First launched in 2015, Offerpad is a tech-enabled home buying and selling solution. As of October, Offerpad had expanded to 534 cities with access to an estimated 6.7 million home-owning households.

The company is what's known as an iBuyer — a type of investor that uses automated valuation models, or AVMs, and other technology to quickly turn around offers on homes to sellers and then resell them to home buyers. The process tends to be quicker and higher tech than the normal home selling and buying process.

Offerpad previously had expanded into Dallas before launching in Houston on January 15. It's the first expansion in 2019 — a year that's poised to be full of growth for the company, the press release says.

"The company has a very concentrated vision to bring our real estate solutions to millions more people this year," Trent Capps, Offerpad's regional market director focused on Texas, says in the release. "Our start in Texas, with Dallas-Fort Worth, has far and away exceeded our expectations and we anticipate the same for our other Texas markets. In Houston, we began receiving home offer requests weeks ago, so we foresee huge success there, as well as in San Antonio later in the quarter."

The new local office is located in The Woodlands and serves 86 cities within the Houston area including Bellaire, Pearland, Sugar Land, Seabrook, and Friendswood. San Antonio is the next Texas market Offerpad is headed for.

"Dallas, Houston, and San Antonio are all cities we've had intentions of offering our service in," Founder and CEO Brian Bair says in the release. "I'm confident that Texans are going to value the solutions we've developed to the once complicated and stressful process of selling a home."

Graphic courtesy of Offerpad

Ad Placement 300x100
Ad Placement 300x600

CultureMap Emails are Awesome

Power grid tech co. with Houston HQ raises $25M series B

money moves

A Norway-based provider of technology for power grids whose U.S. headquarters is in Houston has raised a $25 million series B round of funding.

The venture capital arm of Polish energy giant Orlen, Norwegian cleantech fund NRP Zero, and the Norway-based Steinsvik Family Office co-led Heimdall Energy's round. Existing investors, including Investinor, Ebony, Hafslund, Lyse, and Sarsia Seed, chipped in $8.5 million of the $25 million round.

“This funding gives us fuel to grow internationally, as we continue to build our organization with the best people and industry experts in the world,” Jørgen Festervoll, CEO of Heimdall, says in a news release.

Founded in 2016, Heimdall supplies software and sensors for monitoring overhead power lines. The company says its technology can generate up to 40 percent in additional transmission capacity from existing power lines.

Heimdall entered the U.S. market in 2023 with the opening of its Houston office after operating for several years in the European market.

“Heimdall Power has built itself a unique position as an enabler for the ongoing energy transition, with fast-increasing electricity demand and queues of renewables waiting to get connected,” says Marek Garniewski, president of Orlen’s VC fund.

Heimdall says it will put the fresh funding toward scaling up production and installation of its “magic ball” sphere-shaped sensors. In the U.S., these sensors help operators of power grids maximize the capacity of the aging power infrastructure.

“In the United States alone, there are over 500,000 miles of power lines — most of which have a far higher transmission capacity than grid operators have historically been able to realize. To increase capacity, many have launched large-scale and expensive infrastructure projects,” Heimdall says.

Now, the U.S. government has stepped in to ensure that utilities are gaining more capacity from the existing infrastructure, aiming to upgrade 100,000 miles of transmission lines over the next five years.

Heimdall's technology enables grid operators and utilities to boost transmission capacity without undertaking lengthy, costly infrastructure projects. Earlier this year, the company kicked off the largest grid optimization project in the U.S. with Minnesota-based Great River Energy.

Houston energy data SaaS co. partners with trading platform

team work

In an effort to consolidate and improve energy data and forecasting, a Houston software company has expanded to a new platform.

Amperon announced that it has expanded its AI-powered energy forecaststoSnowflake Marketplace, an AI data cloud company. With the collaboration, joint customers can seamlessly integrate accurate energy forecasts into power market trading. The technology that Amperon provides its customers — a comprehensive, AI-backed data analytics platform — is key to the energy industry and the transition of the sector.

“As Amperon continues to modernize energy data and AI infrastructure, we’re excited to partner with Snowflake to bring the most accurate energy forecasts into a single data experience that spans multiple clouds and geographies," Alex Robart, chief revenue officer at Amperon, says in a news release. "By doing so, we’re bringing energy forecasts to where they will be accessible to more energy companies looking to increase performance and reliability."

Together, the combined technology can move the needle on enhanced accuracy in forecasting that strengthens grid reliability, manages monetary risk, and advances decarbonization.

“This partnership signifies Amperon’s commitment to deliver world-class data-driven energy management solutions," Titiaan Palazzi, head of power and Utilities at Snowflake, adds. "Together, we are helping organizations to easily and securely access the necessary insights to manage risk and maximize profitability in the energy transition."

With Amperon's integrated short-term demand and renewables forecasts, Snowflake users can optimize power markets trading activity and manage load risk.

"Amperon on Snowflake enables us to easily integrate our different data streams into a single unified view," Jack Wang, senior power trader and head of US Power Analysis at Axpo, says. "We value having complete access and control over our analytics and visualization tools. Snowflake allows us to quickly track and analyze the evolution of every forecast Amperon generates, which ultimately leads to better insights into our trading strategy."

Amperon, which recently expanded operations to Europe, closed a $20 million series B round last fall led by Energize Capital and tripled its team in the past year and a half.

In March, Amperon announced that it replatformed its AI-powered energy analytics technology onto Microsoft Azure.

Learn more about the company on the Houston Innovators Podcast episode with Sean Kelly, co-founder and CEO of Amperon.

------

This article originally ran on EnergyCapital.

Rice research on bond and stock market differences, earnings variations

houston voices

At the end of every quarter, publicly traded companies announce their profits and losses in an earnings report. These updates provide insight into a company’s performance and, in theory, give investors and shareholders clarity on whether to buy, sell or hold. If earnings are good, the stock price may soar. If they’re down, the price might plunge.

However, the implications for the stock price may not be immediately clear to all investors. In the face of this uncertainty, sellers will ask for high prices, and buyers will offer low ones, creating a significant “bid-ask spread.” When this happens, it becomes more costly to trade, and the stock becomes less liquid.

This is a well-documented effect on equity stock markets. However, according to research by Stefan Huber (Rice Business), Chongho Kim (Seoul National University) and Edward M. Watts (Yale SOM), the corporate bond market responds differently to earnings news. This is because bond markets differ from stock markets in a significant way.

Stocks v. Bonds: What Happens When Earnings Are Announced?

Equities are usually traded on centralized exchanges (e.g., New York Stock Exchange). The exchange automatically queues up buyers and sellers according to the quote they’ve entered. Trades are executed electronically, and the parties involved are typically anonymous. A prospective buyer might purchase Microsoft shares from someone drawing down their 401(k) — or they could be buying from Bill Gates himself.

Corporate bond markets work differently. They are “over-the-counter” (OTC) markets, meaning a buyer or seller needs to find a counterparty to trade with. This involves getting quotes from and negotiating with potential counterparties. This is an inherent friction in bond trading that results in much higher costs of trading in the form of wider bid-ask spreads.

Here’s what Huber and his colleagues learned from the research: Earnings announcements prompt many investors to trade. And on OTC markets, potential buyers and sellers become easier to find and negotiate with.

A Stronger Bargaining Position for Bonds

According to Huber, “When earnings information comes out, a lot of people want to trade. In bond markets, that makes it much easier to find someone to trade with. The more options you have to trade, the stronger your bargaining position becomes, and the lower your trading costs go.”

He compares the process to shopping in a market with a flexible approach to pricing.

“Let's say you're at a farmers market and you want to buy an apple,” Huber says. “If there is only one seller, you buy the apple from that person. They can ask for whatever price they want. But if there are multiple sellers, you can ask around, and there is potential to get a better price. The price you get depends on the number of options you have in trading partners.”

What’s at Stake?

Although bonds receive less attention than equities, the stakes are high. There is about $10 trillion in outstanding corporate debt in the U.S., and more than $34 billion in average daily trading volume.

A detailed record of bond trades is available from the Financial Industry Regulatory Authority (FINRA), which requires that trades be reported via their Trade Reporting and Compliance Engine (TRACE).

The study from Huber and co-authors uses an enhanced version of TRACE to examine trades executed between 2002 and 2020. The team analyzed the thirty-day periods before and after earnings announcements to gather data about volume, bid-ask spreads and other measures of liquidity.

They find that, like on the stock market, there are more investors and broker-dealers trading bonds around earnings announcements. However, unlike on the stock market, transaction costs for bonds decrease by 6 to 7 percent in the form of bid-ask spreads.

What Sets This Research Apart?

“Taking a purely information asymmetry-based view would predict that what happens to stock liquidity would also happen to bonds,” Huber says. “A piece of information drops, and some people are better able to work with it, so others price protect, and bid-ask spreads and the cost of trading go up.”

“But if you consider the search and bargaining frictions in bond markets, you get a more nuanced picture. While information asymmetry increases, like it does on stock markets, the information prompts more investors into bond trading, which makes it easier to find counterparties and get better transaction prices. Consequently, bid-ask spreads go down. This search and bargaining friction does not really exist on equities exchanges. But we cannot ignore it in OTC markets.”

As corporate debt markets continue to grow in importance, it will become crucial for investors and regulators to understand the nuanced factors influencing their liquidity. This study provides a solid foundation for future research.

------

This article originally ran on Rice Business Wisdom. For more, see “Earnings News and Over-the-Counter Markets.” Journal of Accounting Research 62.2 (2024): 701-35.