Research

The Role of Financial Traders for Price Responses to Shocks in the Commodity Futures Markets

(Job Market Paper: Available at SSRN [Link])

Abstract 

This paper shows that trading between financial and commercial traders in agricultural commodity futures markets dampens price changes during the Russia-Ukraine war but amplifies them during the Global Financial Crisis. However, their mitigating effect lasts only until financial traders' market share reaches a certain threshold. To the best of my knowledge, this paper is the first to link the price-stabilizing or destabilizing role of financial traders to both the nature of the disruption and their market share, measured in terms of open interest. As financial traders increasingly dominate the market, their trading shifts from being an offsetting force to an amplifying driver of price fluctuations originating in the spot market. To obtain these results, I construct a structural framework consisting of simultaneous linear equations based on hedging pressure theory. This unique approach helps ensure the estimated results are free from simultaneity bias, which is often not specifically addressed in much of the literature that relies on reduced-form estimations.

Financialization of Commodity Markets with Heterogeneous Agents and Supply-Side Information Frictions

With Sirui Zhou

(Available at SSRN [Link])

Abstract 

We develop a general equilibrium model to examine how financialization influences the key variables in the commodity futures market. Our model features producers and heterogeneous financial traders, with focuses on supply-side information asymmetries and within-trader risk aversion heterogeneity. Producers observe supply-side fundamental perfectly, while heterogeneous financial traders receive noisy private signals of it. Our findings are threefold. First, expanding total financial trader participation lowers futures price's loading on supply-side fundamental but raises price informativeness by displacing noise trading, producing non-monotonic volatility, compressing futures risk premium, shifting commodity-equity comovement upward, boosting producers' operating profits while depressing their welfare. Second, increasing the financial hedger share reduces both supply-side loading and price informativeness, lowers volatility, raises the futures risk premium, and likewise moves comovement upward, while reducing producers' operating profits but improving their welfare. Third, financial traders' risk aversion heterogeneity, producer-trader and hedger-speculator information asymmetries can amplify or reverse these patterns by shifting the relative weights of speculative and hedging motives. These findings provide theoretical insights into the interplay among financialization, trader heterogeneity, and market stability in the commodity market.

Shortage, Liquidity, and the Effectiveness of Monetary Policy: Evidence from the U.S. Commodity Futures Markets

With Giacomo Cattelan

(Available at SSRN [Link])

Abstract 

We find that monetary policy shocks have no significant effect on commodity futures prices when markets are in backwardation, that is, when futures prices lie below spot prices. Because backwardation signals supply constraints, reflecting a positive convenience yield that arises under tight supply or low inventories, this finding reveals a new channel for understanding the effects of monetary policy under supply shortages. Our model to investigate this mechanism relies on the inventory arbitrage of commercial traders and the rational inattention of financial traders, which together replicate the higher price response to the aggregate demand shock under ample inventories than under tight inventories. To reinforce our empirical findings, we conduct two complementary analyses. The first tests the assumption that the basis is informative about storage conditions by constructing an Inventory Constraint Index, which closely tracks observed inventory data from the World Agricultural Supply and Demand Estimates and the U.S. Energy Information Administration. The second examines the liquidity channel, an alternative mechanism through which monetary policy may affect commodity futures markets. Both analyses support our interpretation: while illiquidity is priced through changes in interest rates, inventory tightness, as indicated by the basis, remains the primary transmission channel.

Work in Progress

Liquidity, Credit Spreads, and Monetary Policy Shocks: Evidence from the U.S. Corporate Bond Market

With Giacomo Cattelan

(Most recent draft: March 2025. [Link])

Abstract 

This paper examines the interplay between corporate bond liquidity and monetary policy in determining credit spreads dynamics. Using intraday transaction-level data from the Trade Reporting and Compliance Engine (TRACE), we construct comprehensive liquidity measures—including bid-ask spreads and turnover ratios—to assess their contribution to credit spreads. Using high-frequency identified shocks for Gurkaynak et al. (2005) and Nakamura and Steinsson (2018), we document that the credit spread for less liquid bonds increases by more as a consequence of a monetary tightening. Hence, we proceed to identifying the liquidity channel of monetary policy on corporate bond spread by adopting a two-step procedure: first, we compute the responses of liquidity measures to the shocks, and then use the fitted values in a second local projection regression to compute the responses of credit spreads. Lastly, we show that the loading of the liquidity risk factor varies over time and strongly anti-correlates with the slope of the yield curve, suggesting a higher-order nonlinear effect of the liquidity channel.

The Impact of Commodity Terms of Trade Growth and Volatility on Emerging Markets and Low-Income Countries 

With Ryan Wu

Abstract 

This paper examines the impact of the level and volatility of the commodity terms of trade on medium-term growth outcomes in emerging markets and low-income countries. We use quantile regression to capture the heterogeneous effects of the first and second moments of commodity terms of trade, taking into account the ongoing economic situation and the potential risk of an extreme economic downturn. Our findings indicate that, in cases where a country is already facing economic challenges, the negative growth effects of commodity terms of trade volatility can be substantially severe, outweighing the positive impact of an increase in the level of commodity terms of trade. 

Predicting the past: Imputation of missing financial data

(Third Year Paper: Draft available upon request)

Abstract

Empirical research in asset pricing extensively relies on firm characteristics. However, available data is typically nowhere near a balanced panel. As the data accessibility and the popularity of machine learning applications are growing, the unbalance problem becomes more biting. This study focuses on recovering missing observations related to firm characteristics by leveraging information from other observed characteristics via a graph neural network model. Resulting balanced data achieves a lower mean squared error compared to previous studies. In addition, characteristic-based factors constructed with the balanced dataset exhibit lower returns compared to those from the original unbalanced data. My results highlight a potential concern in applying machine learning with high deimentional datasets in asset pricing, suggesting that using ad-hoc solutions like removing observations with missing values or employing mean or median imputation might suffer from unintended selection biases. 

Other Papers

Drivers of Post-pandemic Currency Movement: Recurring impacts of sovereign risks and oil prices