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Hilton Atlanta, Grand Ballroom D
American Finance Association
Topics in Return Dynamics
Saturday, Jan. 5, 2019 10:15 AM - 12:15 PM
- Chair: Svetlana Bryzgalova, Stanford University
Leverage-Induced Fire Sales and Stock Market Crashes
AbstractThis paper provides direct evidence of leverage-induced fire sales contributing to a major stock market crash. Our analysis uses proprietary account-level trading data for brokerage- and shadow-financed margin accounts during the Chinese stock market crash in the summer of 2015. We find that margin investors heavily sell their holdings when their account-level leverage edges toward their maximum leverage limits, controlling for stock-date and account fixed effects. Stocks that are disproportionately held by investors facing financial constraints experience high selling pressure and abnormal price declines that subsequently reverse over the next 40 trading days. Unregulated shadow-financed margin accounts, faciliated by Fintech lending platforms, contributed more to the market crash even though these shadow accounts had higher leverage limits and held a smaller fraction of market assets relative to regulated brokerage accounts.
Valuing Private Equity Investments Strip by Strip
AbstractWe propose a new valuation method for private equity investments. The first step is to construct a cash-flow replicating portfolio for the private investment, using cashflows on listed equity and fixed income instruments. The second step is to value the replicating portfolio using a flexible asset pricing model that accurately prices the systematic risk in equity and fixed income strips. The method delivers time series for the expected return on PE funds as well as a measure of the realized risk-adjusted profit of a PE investment. We apply the method to real estate, infrastructure, energy, and corporate private equity funds, and compare the results to standard valuation approaches.
The Time Variation in Risk Appetite and Uncertainty
AbstractWe develop new measures of time-varying risk aversion and economic uncertainty that can be calculated from observable financial information at high frequencies. To do so, we formulate a dynamic no-arbitrage asset pricing model for the two main risky asset classes, equities and corporate bonds. The joint dynamics among asset-specific cash flows, macroeconomic fundamentals and risk aversion feature time-varying heteroskedasticity and non-Gaussianity. We use returns but also realized volatility and option prices to help distinguish time variation in economic uncertainty (the amount of risk) from time variation in risk aversion (the price of risk). We find that variance risk premiums on equity are very informative about risk aversion, whereas credit spreads and corporate bond volatility are highly correlated with economic uncertainty. Our model-implied risk premiums outperform standard instrument sets for predicting excess returns on equity and corporate bonds. A financial proxy to our economic uncertainty predicts output growth negatively and significantly, even in the presence of the VIX.
University of Pennsylvania
Harvard Business School
University of Southern California
- G1 - General Financial Markets