Job Market Paper
Dividend Flows and the Foreign Exchange Rate
Abstract: A simple dividend-based currency strategy, which shorts a currency on the date its country's recent aggregate dividend payment by listed companies is large, exhibits a significant Sharpe ratio and alpha not explained by standard factors in the currency market. To understand this anomaly, I identify the significant price impact of predetermined dividend payments on exchange rates around payment dates. I propose a dividend repatriation channel where benchmark investors (ETFs and mutual funds) predictably repatriate a certain proportion of dividends received in local currency. I build a model in which heterogeneous financial intermediaries with limited risk-bearing capacity accommodate benchmark investors' currency demands stemming from dividend repatriation flows. In line with the model's implications, I find that the price impact of dividend flows on FX around the payment date is large when the intermediary capital ratio is low, CIP deviations are large, and FX implied volatilities are high. My findings have implications for currency-market elasticity, capital regulations, and FX regimes.
Investors' Demand System in High-Dimension: A Machine Learning Approach
I develop an estimation procedure for investors' characteristic-based demand system to accommodate a large universe of stock characteristics containing both price-based and exogenous characteristics. I propose an identification strategy based on the inter-temporal structure of latent demand to address the endogeneity of price-based characteristics, in addition to using instrumental variables to address the endogeneity of asset prices. Using the U.S. stock market data, I illustrate how we can use the estimated demand system to analyze each stock characteristic's impact on cross-sectional stock returns, and which investors matter for characteristic pricing.
Portfolio Choice with Substitutes and Complements: A Spatial Autoregressive Approach
I propose a spatial autoregressive demand system for portfolio choice of stocks, where the spatial weighting matrix is constructed as the inverse distance between stocks in the extended characteristics space. This demand system breaks the independence of irrelevant alternatives (IIA) property and allows for a more general pattern of substitution between alternatives. I provide a microfoundation for the specification from cross-predictability perspectives, relaxing the traditional assumption that expected returns only depend on stocks' own characteristics. Empirical analysis using 13F holdings data in the U.S. stock market provides evidence that the spatial autoregressive demand system is a better description of investors' portfolio choice.
Tail Risk in Corporate Bond Markets (with Mihir Gandhi)
We measure aggregate return tail risk and illiquidity tail risk in the corporate bond market from July 2002 to December 2014. Both measures are persistent and highly correlated. Return tail risk captures price crashes, while illiquidity tail risk captures liquidity crunches. In the time series, tail risk predicts aggregate corporate bond returns for up to nine months. In the cross-section, bonds with higher exposure to tail risk command higher expected returns. We find evidence that investors hedge against tail events. We hypothesize that corporate bond tail risk reflects interest rate risk but does not reflect cash flow risk.
Once Bitten, Not Shy: The Effect of Learning from Terrorism on Stock Prices (with Mihir Gandhi, Gursharan Bhue)
We document that the stock price responsiveness to terrorist attacks is decreasing in recent times. We use a continuous-time model in which investors learn about the regime -- high or low frequency of terrorist attacks -- from the occurrence of such incidents. When a terrorist attack occurs, investors' probability assessment of the high-frequency regime increases. The responsiveness of the stock market is small when investors are confident about the regime. Our model rationalizes the muted response of the market to recent terrorist attacks and other key geopolitical events such as the rise of the Islamic State and the European refugee crisis.
Work in Progress
Financial Technology for Financial Intermediation (with Lin William Cong), under preparation, Annual Review of Financial Economics
The Evolution of Credit Spreads in Securitized Commercial Real Estate Loans (with Joseph Pagliari)
The Rise and Fall of FTX (with Lin William Cong), published on International Journal of Law and Legal Studies
The abrupt downfall of Futures Exchange (FTX) has sent shockwaves throughout the cryptocurrency industry. In this case report, we delve into the causes and consequences of the crisis at the FTX exchange, examining the precarious relationship with Alameda that sowed the seeds of danger. The extensive lending of money to Alameda, using FTX’s own token as collateral, gave rise to a death spiral, a destructive interplay between FTX’s assets and liabilities. While the repercussions of the event extended to other crypto related entities, the fallout was predominantly contained within the crypto sector. We conclude with a discussion on the future regulatory landscape and its implications for the industry.