Research
My research interests lie at the intersection of real estate, finance, and AI/ML technology, focusing on pressing challenges and emerging opportunities in these fields. I focus on the dynamics of price bubbles, particularly their empirical detection across diverse asset classes. Currently, I am developing a neural network framework to enhance the asset price bubble technology introduced in Choi and Jarrow (2024, WP).
Housing affordability is another critical area of my work, where I examine the economic, social, and policy dimensions of making housing accessible to diverse populations. In an ongoing project, Choi, Nowak, Smith, and Tchistyi (2024, WP), I investigate which groups of homebuyers are more susceptible to the winner's curse effects, such as lower housing returns and higher mortgage default probabilities, in the U.S. housing market. In a related strand of research, I analyze potential disparities within the real estate brokerage industry and their influence on housing outcomes. My broader inquiries include mortgage finance, accessible credit, and the interplay between climate risk and real estate markets.
I also delve into the complexities of debt contracts and the valuation of contingent claims. In Choi, Jarrow, Lebret, and Liu (2024, WP), I formalize and price co-tenancy clauses common in retail contracts using an option pricing framework. Building on this foundation, I am extending reduced-form credit risk models to explore applications in climate risk and insurance, investigating how environmental challenges affect financial systems and real asset valuations.
Finally, I am deeply passionate about leveraging artificial intelligence and machine learning in finance and real estate. These advanced tools play a pivotal role in my projects, including price bubble detection, housing market dynamics, banking, and climate risk modeling, enabling me to uncover patterns and enhance decision-making that traditional methods might overlook.
WORKING PAPERS
Abstract: The Indian equity benchmark index, Nifty, hit a record high over twenty times in 2024. Using a new statistical methodology generated by Choi and Jarrow 2024, we investigate the presence of asset price bubbles in the Nifty 100 over two time periods: March 2022 - April 2023 and June 2023 - September 2024. We find no bubble in the first period and the probability of a price bubble more than 91% in the second period.
The Winner's Curse in Housing Markets (with Adam Nowak, Patrick Smith, Alexei Tchistyi)
Abstract: This paper tests for a winner’s curse in housing markets by examining the subsequent performance of bidding war transactions relative to non-bidding war transactions. We develop a model in which homeowners who purchase their house in a bidding war transaction experience lower annualized returns and a higher likelihood of mortgage default. Consistent with the model predictions, we find homebuyers who purchase their house in a bidding war experience 8.8pp lower total unlevered return compared to those not engaged in a bidding war and are 2.1pp more likely to default. These winner’s curse effects are even more pronounced among socioeconomically vulnerable homebuyers.
Abstract: Evidence of excess volatilities at high asset prices is associated with bubbles. We propose a new asset price bubble testing methodology based on volatility estimates. Examining the current U.S. equity bull market, we find that the S&P 500, Dow Jones, and Nasdaq do not exhibit bubbles. We investigate Lyft’s earnings error news and estimate that the bubble’s lifetime is approximately 3 months. Our methodology and results are robust to various adjustments for outliers.
Pricing the Upside Potential to Downside Risk (with Robert A. Jarrow, Daniel Lebret, Crocker H. Liu)
Semifinalist for Best Paper Award, Financial Intermediation & Institutions, FMA 2023
Best Practitioner Research Award (Non-residential), American Real Estate Society 2023, sponsored by BOMA International
Abstract: Shopping centers represent a rare example wherein prices reflect the internalization of externalities. The relatively lower rent anchors pay which other tenants subsidize proxies for externalities anchors create. A related proxy we theoretically model and empirically analyze are co-tenancy lease provisions triggered when an anchor leaves. This real option provides temporary rent relief and early lease termination. We show this option price increases (decreases) with base rent (rent abatement, lease term, bond price, and default time). Using 236 centers, we find co-tenancy increases a center’s expected sales price and the odds of selling it for more than its offering price.
Abstract: Firms acquiring durable assets face a lease-or-purchase decision. The collateral channel narrative argues that durability can facilitate (hinder) purchases by enhancing pledgeability (requiring large down payment). Prior research hasn't recognized that some durable assets (e.g. property) can appreciate at a rate that exceeds operational income growth. It also doesn't endogenize a firm's decision to lease assets. We explicitly factor these into a firm's optimal financing and investment decision. A financially constrained firm purchases durable assets expecting to benefit from a profitable resale. If leasing is feasible, it reverts to renting if its down payment becomes burdensome.
Work-in-Progress
Curbing Short Sale and Price Bubbles during COVID-19 (with Robert A. Jarrow)
Selling Houses as Minority Broker: Quantifying Diversity Discount
Selling Houses as Minority Broker: Quantifying Diversity Discount
Innovative Thinking Award - "Thinking Out of the Box", American Real Estate Society 2024, sponsored by Greenfield Advisors