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Asset Pricing: Volatility, Tail Risk

Paper Session

Saturday, Jan. 4, 2020 8:00 AM - 10:00 AM (PDT)

Manchester Grand Hyatt, Seaport DE
Hosted By: American Finance Association
  • Chair: Bryan Kelly, Yale University

Premium for Heightened Uncertainty: Solving the FOMC Puzzle

Grace Xing Hu
,
University of Hong Kong
Jun Pan
,
Massachusetts Institute of Technology
Jiang Wang
,
Massachusetts Institute of Technology
Haoxiang Zhu
,
Massachusetts Institute of Technology

Abstract

Lucca and Moench (2015) document that prior to the announcement from FOMC meetings, the stock market yields substantial returns without major increase in conventional measures of risk. This presents a “puzzle” to the simple risk-return connection in most (static) asset pricing models. We hypothesize that the arrival of macroeconomic news, with FOMC announcements at the top of the list, brings heightened uncertainty to the market, as investors cautiously await and assess the outcome. While this heightened uncertainty may not be accurately captured by conventional risk measures, its dissolution occurs during a short time window, mostly prior to the announcement, bringing a significant price appreciation. This hypothesis leads to two testable implications: First, we should see similar return patterns for other pre-scheduled macroeconomic announcements. Second, to the extent that we can find other proxies for heightened uncertainty, we should also observe abnormal returns accompanying its dissolution. Indeed, we find large pre-announcement returns prior to the releases of Nonfarm Payroll, GDP and ISM index. Using CBOE VIX index as a primitive gauge for market uncertainty, we find disproportionately large returns on days following large spike-ups in VIX. Akin to the FOMC result, such heightened-uncertainty days occur on average only eight times per year, but account for more than 30% of the average annual return on the S&P 500 index. Inspired by the VIX result, we search for direct evidence of heightened uncertainty using VIX as a proxy and find a gradual but significant build-up in VIX over a window of up to six business days prior to the FOMC announcements.

Volatility Uncertainty and the Cross-Section of Option Returns

Jie Cao
,
Chinese University of Hong Kong
Aurelio Vasquez
,
Technological Autonomous University of Mexico (ITAM)
Xiao Xiao
,
Erasmus University Rotterdam
Xintong Zhan
,
Chinese University of Hong Kong

Abstract

This paper studies the relation between the uncertainty of volatility, measured as the volatility of volatility, and future delta-hedged equity option returns. We find that delta-hedged option returns consistently decrease in uncertainty of volatility. Our results hold for different measures of volatility such as implied volatility, EGARCH volatility from daily returns, and realized volatility from high-frequency data. The results are robust to firm characteristics, stock and option liquidity, volatility characteristics, and jump risks, and are not explained by common risk factors. Our findings suggest that option dealers charge a higher premium for single-name options with high uncertainty of volatility, because these stock options are more difficult to hedge.

Higher-Moment Risk

Niels Gormsen
,
University of Chicago
Christian Skov Jensen
,
Bocconi University

Abstract

We estimate and analyze the ex ante higher order moments of stock market returns. We document that even and odd higher-order moments are strongly negatively correlated, creating periods where the return distribution is riskier because it is more left-skewed and fat tailed. Such higher-moment risk is negatively correlated with variance and past returns, meaning that it peaks during calm periods. The variation in higher-moment risk is large and causes the probability of a two-sigma loss on the market portfolio to vary from 3.3% to 11% percent over the sample, peaking in calm periods such as just before the onset of the financial crisis. In addition, we argue that an increase in higher-moment risk works as an uncertainty shock" that deters firms from investing. Consistent with this argument, more higher-moment risk predicts lower future industrial production.
Discussant(s)
Toomas Laarits
,
New York University
Dmitriy Muravyev
,
Boston College
Mathieu Fournier
,
HEC Montreal
JEL Classifications
  • G1 - General Financial Markets