ACCOUNTING & FINANCE School of ACCOUNTING & FINANCE School of Price Inflation Due to the 2008 SEC Short-Sale Ban Lawrence E. Harris University of Southern California Ethan Namvar University of California – Irvine Blake Phillips University of Waterloo
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ACCOUNTING & FINANCE School of ACCOUNTING & FINANCE School of Price Inflation Due to the 2008 SEC Short-Sale Ban Lawrence E. Harris University of Southern.
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ACCOUNTING & FINANCE
School of ACCOUNTING & FINANCE
School of
Price Inflation Due to the 2008 SEC Short-Sale Ban
Lawrence E. HarrisUniversity of Southern California
Ethan NamvarUniversity of California – Irvine
Blake PhillipsUniversity of Waterloo
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The SEC Ban on Short Selling
• September 19 to October 8, 2008 (14 trading days)
• All financial stocks• Later, some other stocks with significant
financial operations• 987 stocks in total
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The SEC Concerns
“We intend these and similar actions to provide powerful disincentives to those who might otherwise engage in illegal market manipulation through the dissemination of false rumors and thereby over time to diminish the effect of these activities on our markets.”
SEC Release No. 34-58592
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The SEC Concerns
• Price manipulation• Short sellers sap confidence• Clients withdraw business• “Liquidity Death Spirals”
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Potential Unintended Consequence• By preventing short sellers from trading, the
SEC created a bias towards higher prices• Thus, buyers could have purchased at prices
above fundamental values• These buyers would face significant losses
when prices ultimately adjust downward towards their true intrinsic values
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• We estimate the price inflation transferred $597M from buyers to sellers for these stocks
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Anecdotal Evidence: Fanny Mae and Freddy Mac
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Did the Ban Inflate Prices?• One-shot event study• Short period• Lots of other issues– TARP in particular!– Lehman Brothers collapse also occurred just prior
to the ban• The answer may not be knowable, but the
question is very important
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Our Paper• Take our best shot at estimating inflation• Use a factor analytic model to characterize
return determinants for the banned stocks • Estimate the factors from the not-banned
stocks• Estimate “but-for” prices for the banned
stocks
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Problems
• The factor model must work during the crisis• The signal must be sufficiently large relative to
the extreme noise• The noise cannot be specific to the banned
stocks
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The Factor Analytic Approach• Use time-series regressions to identify factor
loadings for known factors • Six return factors– Fama-French and Carhart– Value-weighted banned stock index– TARP-weighted banned stock index
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The Factor Analytic Approach• Use cross-sectional regression to identify
factors returns– Estimate using only not-banned sample.
• Three stock characteristic factors– Inverse price– 10-day rolling volatility– 10-day rolling turnover