Duc V. Le

About

I am a PhD candidate in the Department of Economics at Georgetown University. My research is in financial economics, with interests in financial stability, asset pricing, and applied econometrics.

Research

Publications

“Globalization, economic growth, and innovation: A two-country two-period model.” Cuong Le Van, Duc V. Le, and Thanh Tam Nguyen-Huu.
International Economics 187 (2026), 100725. DOI · arXiv · PDF
Abstract
This paper examines how a developing country can benefit from trade liberalization. We develop a two-period model, comprising an autarky phase and a globalization phase, and a two-country framework, featuring a developing country and a developed country (representing the rest of the world). Our findings indicate that globalization may disadvantage a developing country when its total factor productivity (TFP) is significantly lower than that of the developed country. However, we demonstrate that the developing country can still achieve gains from trade openness by allocating part of its capital to innovation during the autarky period, thereby enhancing its TFP.
BibTeX
```
@article{levan2026globalization,
  title   = {Globalization, economic growth, and innovation: A two-country two-period model},
  author  = {Le Van, Cuong and Le, Duc V. and Nguyen-Huu, Thanh Tam},
  journal = {International Economics},
  volume  = {187},
  pages   = {100725},
  year    = {2026},
  doi     = {10.1016/j.inteco.2026.100725}
}
```

Working papers

“Does Dealer Gamma Move Volatility? Causal Evidence from the Option-Expiration Roll-off.” Working paper, 2026. Code · Docs
Abstract
Option dealers hedge the gamma of their inventory by trading the underlying asset: when short gamma they trade with price moves, amplifying volatility, and when long gamma they trade against them, dampening it. Because dealer positioning and volatility are jointly determined, the causal effect of this channel has not been established. I instrument dealer gamma with the dollar gamma scheduled to expire at the next monthly option expiration, a calendar-determined shock to the stock of dealer gamma. In the S&P 500 and its constituents over 2016–2024, instrumented dealer gamma lowers future realized volatility by about two annualized points per standard deviation — an effect the VIX subsumes in predictive regressions but cannot explain away. Call and put gamma carry opposite-signed effects, validating the dealer-positioning convention. Aggregate short-gamma states are rare but coincide with roughly doubled index volatility.
BibTeX
```
@unpublished{le2026dealergamma,
  title  = {Does Dealer Gamma Move Volatility? Causal Evidence from the Option-Expiration Roll-off},
  author = {Le, Duc V.},
  year   = {2026},
  note   = {Working paper}
}
```
“Do Short-Dated Call Options Predict Stock-Price Crashes?” (with Dan Cao). Working paper, 2026.
Abstract
We show that short-dated retail call-option activity predicts subsequent stock-price crashes, whereas long-dated call activity predicts the opposite. In a panel of 3,447 U.S. firms from 1996 to 2021, stocks in the top quintile of short-dated retail call share have a 24-month-forward crash probability 25.5 percentage points higher than those in the bottom quintile; for long-dated calls the spread reverses to −4.7 points, so a high long-dated share is associated with lower crash risk. To rationalize this maturity asymmetry, we develop a heterogeneous-belief model with demand-pressure dealers. A wealth-share amplification channel generates the pattern: as optimistic retail investors accumulate wealth, their demand bids up the underlying through the dealer’s hedging costs, leaving prices elevated and prone to mean-reverting crashes. The model reproduces the empirical magnitude, implying a +28.6-point quintile spread against +25.5 in the data. Mediation tests attribute roughly 30% of the predictive power to this retail-ownership channel, with the remainder reflecting a separate institutional informed-trading channel concentrated in large-cap stocks.
BibTeX
```
@unpublished{caole2026shortdated,
  title  = {Do Short-Dated Call Options Predict Stock-Price Crashes?},
  author = {Cao, Dan and Le, Duc V.},
  year   = {2026},
  note   = {Working paper}
}
```
“Shorting Fees, Intermediation Cost, and the Fragility of Multiple Equilibria in a Heterogeneous-Belief Asset-Pricing Model.” (with Dan Cao). Working paper, 2026.
Abstract
We study a Lucas-tree economy with heterogeneous beliefs in which a pessimistic agent short-sells the asset to an optimistic agent, subject to a share-lending cap and a per-share borrowing fee. We establish three results. First, the frictionless model has no recursive equilibrium — the pessimist’s frustrated short breaks existence at every tested level of risk aversion. Second, even a small intermediation cost restores existence and generates an equilibrium borrowing fee orders of magnitude larger than the underlying cost, amplified by the binding lending cap. Third, the multiple equilibria emphasized in the heterogeneous-belief literature are fragile: they collapse at higher fee levels and disappear entirely once the fee responds to lending volume, as it does empirically. Under any economically realistic fee schedule the model has a unique recursive equilibrium; the much-discussed multiplicity is a knife-edge artifact of fee-volume insensitivity, not a generic feature of the model.
BibTeX
```
@unpublished{caole2026shortingfee,
  title  = {Shorting Fees, Intermediation Cost, and the Fragility of Multiple Equilibria in a Heterogeneous-Belief Asset-Pricing Model},
  author = {Cao, Dan and Le, Duc V.},
  year   = {2026},
  note   = {Working paper}
}
```

Code & Resources

Dealer-gamma replication code (Python). A pipeline for the dealer-gamma study: WRDS/OptionMetrics data pulls, instrumental-variables (2SLS) estimation, panel fixed effects, and HAC inference. GitHub · Docs
“Stata for Empirical Economics: A Reproducible Methods Portfolio.” A two-book set with twelve documented .do scripts (difference-in-differences, instrumental variables, regression discontinuity, synthetic control, and dynamic-panel GMM). GitHub · DOI
- A Stata Reference for Empirical Economics: Methods, Code, and Verified Results · DOI · PDF
- Stata Line-by-Line: An Empirical Economics Guide · DOI · PDF

Contact

Email: dvl11@georgetown.edu
Office: ICC 580, 3700 O St NW, Washington, DC 20057, USA