Encounters with the real estate industry

I was intrigued, not only because the client said virtually nothing about themselves, but also because of the notwithstanding presumptuousness in thinking I want to be brought on to their team.

I went to the meeting. There, I was introduced to two members of the client’s company Trajan.ai. The members were Gureet Pannu aka Rick and Manjit Pannu. They talked at length about the company, and about themselves. But very little of what they said furthered my understanding of the company’s purpose. Rick’s seemingly boastful claims and unrelenting talkativeness made me wonder if I was looking at a vanity project.

I was ready to quit. But then I thought maybe it’s too soon, maybe I’m judging a book by its cover. I decided to continue with our exchange for a few more days. In our next meetings, I asked pointed questions about the company so that I could make up my mind. What I learned gave me some relief in that I wasn’t too quick in my decision.

Before I can explain what I learned and why I was skeptical at first, I’m going to have to talk a little about myself. I’m a 33-year-old man, born and raised in India. I went to India’s best institutes for my studies – B. Tech. in Aerospace Engineering from the Indian Institute of Technology, Kharagpur, MBA in Finance from the Indian Institute of Management, Ahmedabad. I spent two years at Credit Suisse as a market risk analyst for their equity derivatives business, and one year at PwC in their financial risk and regulations advisory. Before and after each stint, I’ve taken long breaks trading derivatives on my own account so that I can study the markets firsthand.

Although I’ve barely exhausted my study of the markets, the overwhelming impression I have formed is that markets are efficient. With high-frequency algorithmic trading, any opportunities for arbitrage are identified and saturated within fractions of a second. So, when I see the calculation of a 70% return in Rick’s spreadsheet, my disbelief, or as a matter of fact anyone’s, should be no surprise. Although, to me, the 70% return is still far-fetched, I can now see a clear path to supernormal returns.

The predominant focus in my study of the markets had been the global markets – the markets of stocks, bonds, and commodities. These are the markets of securities which can be traded from anywhere in the world, making them per force competitive. However, there still are markets, as I learned through my interactions at Trajan.ai, that have successfully resisted the force of globalization and digital technologies. One of them is the real estate markets.

I had never personally considered the real estate markets for trading or investment before. The simple reason was that I didn’t know enough about them. Even if I did it wouldn’t have been a simple buy or sell decision as with stocks or bonds. No, the real estate markets are unique. They come with many idiosyncratic risks. They are inherently localized, and governed by a complex hierarchy of regulators, from community planners to state legislators, to international standard-setting agencies like The Basel Committee which indirectly regulate the financing of a real estate project. Moreover, real estate assets are heterogenous, not only in their finished forms, but also in their development processes. This naturally causes friction in the market, making it less competitive. It is probably for these challenges that the real estate development market is left untouched by most of Wall Street. But, for the same reasons, now, there are opportunities.

Before moving forward, I’m going to take a pause to explain what I learned in my meetings with Rick, and why I decided to stay. Throughout my stay at Trajan.ai so far, I have learned things about the real estate market that are so out of place in the context of the global markets that it almost defies belief. I’m going to recount a few of them to help illustrate the opportunities that I saw therein.

Rick is an experienced real estate developer. He had had developed properties before when I met him. He told me how he does it. He lays out the schedule of construction down to the placement of nails and screws before beginning construction. I was surprised, however, only when he told me that nobody else does it this way. Another similar event was when Rick and the team were walking me through their database. They had been collecting the data posted by the Los Angeles Department of Building and Safety on their website. I asked them, “if this data is publicly available, what value do you expect to add?” Again, the answer was a surprise – “Nobody else is using them”. Indeed, I have yet to come across an organization that uses this data at any scale. I couldn’t believe that there was so much data that could be harnessed to streamline virtually all processes in all aspects of real estate development, yet no one was using it. I was sold. Yet, more surprises were to follow.

Seeing the potential opportunities, I started studying the real estate markets. I learned from Rick that the uncertainty in material prices is one of the big concerns for any developer. When I asked Rick why they don’t use forwards or futures to fix the price beforehand, it seemed as if I was speaking in a foreign language. He didn’t know what I meant, and Rick, as I’ve come to understand, is a leading authority on the subject. When I turned to academics, I was astounded by the dearth of literature on real estate assets. I was puzzled by the industry’s acceptance of concepts like cash-on-cash return and cap rates, both of which disagree with the basic principles of corporate finance.

The list goes on and on. But the point is that I saw opportunity in those gaps. I realized that, in the real estate markets, there remains great value to be added.

My encounter with the real estate industry was almost by accident. I didn’t know the nature of my client’s business before that first meeting. Even when I knew I was skeptical. The real estate market, at least for me, had been full of eccentricities and the accompanying challenges. Some of that is still true. But, besides discovering the untapped potential of the real estate market, I have found at Trajan.ai the team that can help me overcome those challenges – Rick, who knows the real estate industry inside out, Asif, who is the subject matter expert as a civil engineer, Mohsin, who collects and manages the data that we utilize to draw unique insights into the real estate industry, Manjit, who as the team leader and key sponsor keeps everybody in line.

Working together and utilizing every insight we have drawn upon the real estate markets, we have built an app solution for the valuation and risk management of a real estate project. The solution can be applied to any kind of a real estate project – renovation or development, residential or commercial, debt financed or all-equity financed. Risk analysis is done through sensitivity or scenario analysis to answer questions like “If the construction is delayed by one month, how would the returns be impacted?” Having access to the full work history and license details of any contractor, we have developed a capability to select the best contractor for a job, thereby reducing risk at the outset itself. Crime history in the vicinity of a proposed site helps us further narrow down the risks. Using permits and inspections data, we can forecast construction by considering the possible regulatory hurdles.

Uncertainty in cash flow is considered by modelling inflation. Using historical data, a stochastic model for inflation is built, which can be used to project the expected path for inflation or to simulate the possible paths it can follow. The expected return on a project is calculated as the average of returns obtained from every one of 10,000 (say) simulated paths. Different price indices are used for different types of cash flow. Producer price indices are used to predict material prices, employment cost index to predict labor prices, consumer price index to predict rental revenue and operating expenses.

But the most exciting part has to do with regulatory incentives programs. Incentives like the Los Angeles Transit Oriented Communities (TOC) program present a singular opportunity which I have too often seen done wrong. I cannot recall the number of title sheets I have seen that underestimate the maximum building size by using buildable area instead of lot size in the calculation when the latter is allowed. Another thing that is easy to miss is the effects of rounding in calculations such as those for the Los Angeles Density Bonus program. Take, for example, a lot in a zone that permits 6 units. By setting aside 5% of the units to Very Low Income (VLI) households, a developer would qualify for 20% density bonus. Since the numbers are rounded up, the extra units allowed is 2 (20% * 6 = 1.2 rounded up), of which 1 would go to VLI households (since 5% of 6 = 0.3 is also rounded up). So, in effect, 50% of the extra units the developer gets to build goes will be restricted units. Compare this against another lot where 20 units are permitted. The same set of calculations will lead you to conclude that the developer can build 4 units of which only 1 will be restricted. So, this time, only 25% of the extra units will be restricted. The only reason for this difference is that, in the latter case, no rounding up happens.

We have taken great pains to thoroughly understand the various zoning regulations, incentive programs, and key ordinances of various cities. These are translated into a set of rules for our app. So, for an address provided as input, the user will see all the regulatory incentives that the lot qualifies for. Upon the selection of a qualified incentives program, the relevant density calculations (if applicable) will be shown. User inputs will be limited according to the restrictions of the zone or the incentives program. For example, the number of detached Accessory Dwelling Units (ADU) that can be built on an existing multifamily dwelling would be limited to 2.

Understanding regulations allows one to timely execute their projects, and to fully utilize all the available benefits. It is probably the most important factor to consider in reducing the turnaround time of a project. We, at Trajan.ai, aim to achieve the same – to carry out profitable projects one after another in the most streamlined and efficient manner. Given all that I’ve seen, and all that we have worked on or continue to work on, I’m tempted to say, we’re the future of real estate. One may either sit back and observe the phenomenon or participate in it.