Common Idiosyncratic Volatility and Carry Trade Returns
Job Market Paper
Abstract: I provide new evidence that incomplete consumption risk sharing across countries is an important determinant of carry trade returns. I show that there is a strong co-movement in idiosyncratic volatilities over time, and that shocks to the common idiosyncratic volatility (CIV) factor, defined as the equally weighted average of the idiosyncratic volatilities in the cross-section, are priced. I find that high-interest rate currencies deliver low returns when the CIV increases, which are bad times for investors. Low-interest rate currencies provide a hedge by yielding positive returns. CIV shocks remain an empirically powerful risk factor in explaining the cross-section of carry trade returns after controlling for global foreign exchange (FX) volatility risk. Furthermore, CIV risk is correlated with cross-country income risk faced by households. My findings are consistent with a heterogeneous-agent model with persistent, uninsurable idiosyncratic shocks in consumption growth. The calibrated model quantitatively accounts for the cross-sectional differences in average returns across CIV-beta sorted portfolios for plausible market prices of CIV risk.
Fed-Implied Market News
Joint with Charles W. Calomiris, Joanna M. Harris, and Harry Mamaysky (November 2020)
Abstract: We propose a novel text processing technique to extract views of market conditions that are implicit in the Fed's policy statements and minutes. The method is easy to apply and addresses several problems inherent in the use of changes in interest rates as a proxy for central bank policy. First, we project market variables into the text of FOMC statements and minutes (separately) using support vector regressions (SVRs) to predict the levels of 10-year yields, 3-month yields, 2s10s, DXY index, VIX, HY, and IG spreads. We then define measures of monetary policy ("Fed diff" variables) as the Fed-implied deviation away from the market variable: the out-of-sample value of the market variable implied by the SVR minus the corresponding value of the market variable the day before the statement (minutes) release. We show that different markets respond differently to monetary policy news in the short-run, in a way that has independent and complementary implications for market movements in the long-run. Fed news also has important long-run implications for macroeconomic outcomes. Our Fed measures outperform Bernanke-Kuttner and changes in 2-year yields for forecasting macro and financial outcomes in the future. Finally, we show that there are Fed-risky and Fed-hedging industries, and these earn risk premia on Fed statement days.
FX Intervention and Carry Trade Returns
Joint with Amanda Dos Santos (November 2020)
Abstract: Most of carry trade explanations in the academic work are risk-based stories. However, there is a large and diverse set of players in FX markets, some of which are not necessarily motivated by getting exposure to risk factors or by profiting through FX trading, such as central banks. This paper studies the relationship between carry returns and government policy. Because the losses tend to occur during bad times, central banks often respond with stabilizing actions. If FX interventions by central banks truncate carry trade losses, this has major implications for the distribution of income and wealth. By using four matched administrative registers for Brazil - credit, employment, banks' foreign claims, and hedge fund's holdings - this paper tries to address the following questions: (i) Do central banks' FX interventions truncate carry losses, concentrating those losses in the least sophisticated areas of the markets; (ii) How does FX intervention during periods of market turmoil affect the distribution of income and wealth; and finally, (iii) Do FX interventions increase moral hazard and create an incentive for domestic banks to take up riskier (foreign) funding than they otherwise would?
Multiscale Stochastic Volatility and Option Pricing
Joint with Caio Almeida and Yuri Saporito (May 2018)
Abstract: The stochastic volatility model proposed by Fouque, Papanicolaou, and Sircar (2000) explores a fast and a slow time-scale fluctuation of the volatility process to end up with a parsimonious way of capturing the volatility smile implied by close to the money options. In this paper, we test three different models of these authors using options on the S&P 500. First, we use model independent statistical tools to demonstrate the presence of a short time-scale, on the order of days, and a long time-scale, on the order of months, in the S&P 500 volatility. Our analysis of market data shows that both time-scales are statistically significant. We also provide a calibration method using observed option prices as represented by the so-called term structure of implied volatility. The resulting approximation is still independent of the particular details of the volatility model and gives more flexibility in the parameterization of the implied volatility surface. In addition, to test the model's ability to price options, we simulate options prices using four different specifications for the data generating process. As an illustration, we price an exotic option.