Publications

6. "Oil Volatility Risk" with Lin Gao, Steffen Hitzemann and Ivan Shaliastovich, Journal of Financial Economics, Vol.144, Issue.2, pp.456-49, 2022, [PDF] [Online Appendix]

Abstract: The option-implied oil price volatility is a strong negative predictor of economic growth beyond traditional financial and macroeconomic uncertainty measures. A rise in oil volatility also predicts an increase in oil inventories and a reduction in oil consumption, in line with a propagation channel through the oil sector. We explain these findings within a macro-finance model featuring stochastic uncertainties and precautionary oil inventories: firms increase oil inventories when oil volatility rises, which curbs oil use for production and depresses economic activity. In the model and the data, aggregate equity prices fall at times of high oil volatility, with differential exposures across economic sectors.

Presentations: EABCN Asset Prices and the Macro Economy Conference, 2018; American Finance Association Meetings, Chicago, 2017; Cancun Derivatives Workshop, 2017 ; Citrus Finance Conference, UC Riverside, 2017; Midwest Finance Association, 2017; Commodity and Energy Markets Annual Meeting, 2017; BI CAPR Investment and Production-Based Asset Pricing Workshop, 2017; Western Finance Association Meetings, Utah, 2016; Bank of Canada, 2016; Chicago Fed, 2016; University of Houston, 2016; Financial Econometrics Seminar, Duke University, 2016; European Finance Association 2016, Econometric Society North American Summer Meeting, 2016; World Finance Conference, 2016.

5. "The cross-section of monetary policy announcement premium" with Hengjie Ai, Leyla Jianyu Han and Xuhui Pan, Journal of Financial Economics, Vol.143, Issue.1, pp.247-276, 2022, [PDF]

Abstract: Using the expected option-implied variance reduction to measure the sensitivity of stock returns to monetary policy announcement surprises, this paper shows that monetary policy announcements require significant risk compensation in the cross section of equity returns. We present evidence that our sensitivity measure captures the exposure of stock returns with respect to growth rate expectations. We develop a parsimonious equilibrium model in which FOMC announcements reveal the Federal Reserve's private information about its interest rate target, which affects the private sector's expectation about the long-run growth rate of the economy. Our model accounts for the dynamics of implied variances and the cross section of the monetary policy announcement premium realized around FOMC announcement days.

Presentations: Canadian Derivatives Institute Annual Conference, 2020; European Finance Association, 2020; Midwest Finance Association Meetings, 2020; Western Finance Association Meetings, 2019; University of Houston, University of Hong Kong, Tsinghua University (PBC), and Tulane University.

4. "The Term Structures of Expected Loss and Gain Uncertainty" with Bruno Feunou, Ricardo Lopez Aliouchkin and Roméo Tédongap, The Journal of Financial Econometrics, Vol. 18, Issue 3, pp.437-501, 2020 [PDF] [Online-Appendix]

Abstract: We document that the term structures of risk-neutral expected loss and gain uncertainty on S&P 500 returns are upward-sloping on average. These shapes mainly reflect the higher premium required by investors to hedge downside risk and the belief that potential gains will increase in the long run. The term structures exhibit substantial time-series variation with large negative slopes during crisis periods. Through the lens of Andersen et al. (2015)’s framework, we evaluate the ability of existing reduced-form option pricing models to replicate these term structures. We stress that three ingredients are particularly important: (1) the inclusion of jumps; (2) disentangling the price of negative jump risk from its positive analog in the stochastic discount factor specification; and (3) specifying three latent factors.

3. "Tail Risk Premia and Return Predictability" with Tim Bollerslev and Viktor Todorov, Journal of Financial Economics, Vol.118, pp.113-134, 2015. [PDF] [Data]

Keywords: Variance risk premium; time-varying jump tails; market sentiment and fears; return predictability.

Abstract. The variance risk premium, defined as the difference between actual and risk-neutralized expectations of the forward aggregate market variation, helps predict future market returns. Relying on new essentially model-free estimation procedure, we show that much of this predictability may be attributed to time variation in the shape of the tails and compensation demanded by investors for bearing jump tail risk. Our results are consistent with the idea that the temporal variation in the separate diffusive and jump risk components of the variance risk premium may be associated with notions of time varying economic uncertainty and changes in risk aversion, or market fears, respectively.

Presentations: Midwest Finance Association meetings, Chicago, 2015; SCOR/IDEI conference on Extreme Events and Uncertainty in Insurance and Finance in Paris, France, 2014; Workshop on Financial Econometrics in Natal, Brazil, 2013; SETA Meetings in Seoul, South Korea, 2013; University of California Berkeley; NYU Stern.

2. “Stock Return and Cash Flow Predictability: The Role of Volatility Risk" with Tim Bollerslev and Hao Zhou, Journal of Econometrics, Vol.187, No.2, pp.458-471, 2014. [PDF]

Keywords: Return and dividend growth predictability; variance risk premium; equilibrium pricing; stochastic volatility and uncertainty; “structural” factor GARCH.

Abstract: We examine the joint predictability of return and cash flow within a present value framework, by imposing the implications from a long-run risk model that allow for both time-varying volatility and volatility uncertainty. We provide new evidence that the expected return variation and the variance risk premium positively forecast both short-horizon returns and dividend growth rates. We also confirm that dividend yield positively forecasts long-horizon returns, but that it does not help in forecasting dividend growth rates. Our equilibrium-based “structural” factor GARCH model permits much more accurate inference than univariate regression procedures traditionally employed in the literature. The model also allows for the direct estimation of the underlying economic mechanisms, including a new volatility leverage effect, the persistence of the latent long-run growth component and the two latent volatility factors, as well as the contemporaneous impacts of the underlying “structural” shocks.

Presentations: North America Winter Meeting of the Econometric Society (part of ASSA Annual Meeting), 2014; China International Conference in Finance, 2013; Duke Financial Econometrics Lunch Group.

1. “Stock Return Predictability and Variance Risk Premia: Statistical Inference and International Evidence" with Tim Bollerslev, James Marrone, and Hao Zhou, Journal of Financial and Quantitative Analysis, Vol.49, No.3, pp.633-661, 2014. [PDF]

Keywords: Variance risk premium; return predictability; over-lapping return regressions; international stock market returns; global variance risk.

Abstract: Recent empirical evidence suggests that the variance risk premium, or the difference between options implied and actual realized return variation, predicts aggregate stock market returns, with the predictability especially strong at intermediate quarterly horizons. We demonstrate that statistical finite sample biases can not “explain” this apparent predictability and that the inclusion of more recent data spanning the financial crises only strengthens the results. Further corroborating the existing empirical evidence pertaining to the U.S., we show that country specific regressions for France, Germany, Japan, Switzerland and the U.K. result in quite similar, albeit not as significant, return predictability patterns. Defining a “global” variance risk premium, we uncover even stronger predictability and almost identical cross-country patterns through the use of panel regressions that effectively restrict the compensation for world-wide variance risk to be the same across countries. These new empirical findings are broadly consistent with the implications from a stylized two-country general equilibrium model explicitly incorporating the effects of world-wide time-varying economic uncertainty.

Presentations: European Summer Symposium in Financial Markets (Asset Pricing) in Gerzensee, 2011; New York University Stern Volatility Institute Conference, 2011; Hedge Fund Conference at Imperial College London, 2011; Inquire Europe Autumn Seminar in Luxembourg, 2011; NBER-NSF Time Series Conference at Michigan State University, 2011; China International Conference in Finance, 2011 (Best Paper Award); Notre Dame University, University of Zurich, and Duke Financial Econometrics Lunch Group, 2011.