Leverage-Induced Fire Sales and Stock Market Crashes Zhiguo

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Leverage-Induced Fire Sales and Stock Market Crashes Zhiguo He University of Chicago and NBER with Jiangze Bian, Kelly Shue, and Hao Zhou 2018 October, Wharton Liquidity Conference 1

INTRODUCTION Excessive leverage and fire sales are believed to have been major contributors to many past financial crises 1929 US stock market crash 2007/08 financial and housing crises 2015 Chinese stock market crash Limited empirical evidence on fire sales in financial markets, and not in context of leverage E.g., Coval and Stafford (2007) and Edmans, Goldstein and Jiang (2012): fire sale of equities due to fund outflows Ellul, Jotikasthira, and Lundblad (2011): fire sale of downgraded corporate bonds due to regulatory constraints This paper: Direct evidence of leverage-induced fire sales Account-level trading data for margin accounts in Chinese stock market in 2015 Examine role of shadow-financed margin trading and regulation 2

2015 CHINESE STOCK MARKET BACKGROUND Stock market boomed in early 2015 and then crashed in summer of 2015 Two types of margin accounts were popular starting in mid-2014 1. 2. Brokerage-fi nanced margin system Similar to US margin trading (initial margin, maintenance margin, etc.) Tightly regulated, with minimum initial margin and maintenance margin Shadow-fi nanced margin system “Mother account” operated by some online platforms Looks like a normal unlevered brokerage account with huge trading volume Linked through FinTech software to many levered “child accounts” (retail traders) Unregulated grey area: higher leverage, lower maintenance margin, and larger cross-sectional variation 3

DIAGRAM OF MARGIN TRADING SYSTEM Chinese shadow margin system is connected to Chinese shadow banking (say, Trust, Wealth Management Products, etc) June 12 2015: CSRC (China Securities Regulation Commission) released draft rules for a future ban on new shadow-financed margin accounts 4

DIAGRAM OF SHADOW MARGIN TRADING Mother-Child system, against the regulation that each individual ID can only have one trading account. 5

DATA Detailed account-level trading during the crisis (May-July 2015) Brokerage-financed margin accounts (Brokerage) from a leading brokerage firm, cleaned sample represents 5% of market share of brokerage margin service Shadow-financed margin accounts (Shadow) from a leading web-based peer-topeer lending platform Hard to estimate its market share: Best estimate for cleaned sample: 5% Each individual account in both categories Daily stock holdings and trading Daily assets and debt, leverage assets/(assets-debt) Account maximum allowable leverage (Pingcang Line, 平仓线 ) Stock market data: returns, volume, etc. 6

LEVERAGE AND THE MARKET INDEX (1) Large dispersion of account leverage over the sample index, right scale leverage, left scale 7

LEVERAGE AND THE MARKET INDEX (2) Leverage Assets/Equity. Asset-weighted and equity-weighted are quite different! index, right scale leverage, left scale 8

PREVIEW OF RESULTS Accounts with higher risk of margin calls are more likely to sell assets Compare net selling of the same stock on the same day, across accounts with different “distance-to-margin-call” A construction similar to Merton’s distance-to-default These fire sales affect stock prices Stocks disproportionately held by fire-sale accounts (accounts with low distance-to-margin-call) high selling pressure .experience significant short run price declines that eventually reverse Potential concern: these stocks would have fallen in value for other reasons Less likely to explain the long run reversal Event studies around regulatory tightening announcements aid in identification 9

DISTANCE TO MARGIN CALL (1) Develop a measure of the “risk” of at account-date level Risk of losing the control of the account (and creditors dump the stocks in a suboptimal way) : Maximum leverage before the lender takes over, “Pingcang Line” Same for brokerage accounts, varies across accounts for shadow Fixed over the life of any account In general, account risk is determined by leverage, account asset volatility, and the Pingcang Line Leverage amplifies the asset volatility of the account Shift of control to the lender once leverage hits Pingcang Line 10

DISTANCE TO MARGIN CALL (2) For each account-date, calculate the drop in asset values that would push A the account A A Zto its Pingcang Line: jt jt jt A jt jt E jt Ajt Z jt lev j : asset volatility of account j at date t captures the “Distance to Margin Call”, or DMC, at the account-date level, in units of asset sigmas Similar to Merton’s “distance to default” : account-dates with that have been taken over by lenders 11


ACCOUNT-LEVEL EVIDENCE Dummies I kj,t for sorted bins based on , indexed by Account-stock-date level regression: i ,jt k k I kj,t i ,t j i ,jt Account j's net selling of stock i at date t Account j's holding of stock i at the beginning of date t j i ,t Stock-date fixed effect and account fixed effect Identification: account ’s time-varying distance-to-margin-call Omitted category: unlevered accounts Prediction: leverage-induced selling implies that increases with 13

ACCOUNT-LEVEL EVIDENCE Benchmark: classify accounts with as “fire sale accounts” Robust to using ’s as weights to estimate fire sale exposure 14


LEVERAGE OR LEVERAGE CONSTRAINT? In general, rebalancing in a leveraged account will generate sales that are observationally equivalent to “fire sales” Kyle-Xiong (2001), He-Krishnamurthy (2013), etc: w/o margin constraint Garleanu-Pederson (2011) etc: with margin constraint Identified selling intensity due to leverage is the combination of above force Results are robust to the conservative classification of Z 0 as “fire-sale accounts” We make some headway in “ruling in” the role of leverage constraint Shadow account sample with heterogeneous Pingcang Lines allows us to identify the role of leverage constraints controlling for the leverage Endogenous choice of Pingcang Lines due to heterogeneous risk aversion? We instrument the account Pingcang Line (see next slide) 16

LEVERAGE OR LEVERAGE CONSTRAINT? Leverage-to-Pingcang (capturing leverage constraint), and construct bins for LP and leverage A more reduced-form empirical specification: 10 5 5 L Lj L*LP i ,jt k 1 kLP I kLPj IkLj,t 1 LPk j,t 0.4 i ,t j i ,jt ,t k 1 k I k ,t k 1 k Note, our DMC is just The basic pattern is the same if we instrument Pingcang Line by the average Pingcang Line on its opening day 17

EVENT STUDY: REGULATION TIGHTENING Regulations on shadow-financed margin system released on June 12th, 2015 Compare selling intensity in week before and after announcements for brokerage and shadow accounts This regulatory shock is more relevant for shadow accounts Identification: Stock fundamentals are unlikely to change at the same time as these announcements) 18

STOCK-LEVEL EVIDENCE If stock is disproportionately held by fire sale accounts, it should be sold more heavily by these accounts (we confirm this in the data) Fire sale accounts: accounts with at the beginning of is stock ’s fire sale exposure Total shares of stock i in fire-sale accounts at the beginning of date t FSEi ,t Outstanding shares of stock i at date t Which stocks fire sale accounts choose to sell is endogenous We instead use each stock’s fire sale exposure: fraction of shares held in fire sale accounts (Edmans-Goldstein-Jiang, 2012) 19

STOCK-LEVEL EVIDENCE Stocks with higher FSE are correlated with 1) worse past performance and 2) higher volatility Do stocks with higher FSE has more net sellings from fire-sale accounts? (1) Fire Sale Exposure (FSE) (2) (3) Net selling of stock from fire sale accounts 0.106*** (0.0228) 0.111*** (0.0343) 0.111*** (0.0344) 0.110*** (0.0344) X X X X X X X X X X X X X X X 116,809 0.186 116,809 0.186 116,809 0.187 Return Volatility Size (Market Cap) Turnover Past 10-day cum. return Past 10-day daily return Stock FE Date FE Observations R-squared 116,809 0.144 (4) 20

NET SELLING BY FIRE SALE ACCOUNTS TO TOTAL VOLUME Sample restricted to stocks in the top decile of FSE on each day On average, net selling by fire sale accounts corresponds to 0.3% of volume Our sample approximately 5% of margin market! 21

RETURNS AND FIRE SALES Stocks with high should underperform in the short-run but not in the long-run Potential concern: High stocks would have fallen for other reasons (say, prior returns) Long-run reversal suggests a fire sale rather than only a drop in fundamentals Non-parametric portfolio tests: At the start of each day Sort stocks into quartiles by past returns Sort each quartile into deciles by Long the top decile and short the bottom decile Regression results Similar results using a regression controlling for return volatility, market cap, past 10-day daily and cumulative returns; turnover; stock and date FE Event study shows increased selling pressure immediately after regulatory announcements 22


RETURNS FOLLOWING FIRE SALES CARi ,t h h FSEi ,t controls i ,t h Abnormal return is based on CAPM with stock beta calculated using 2014 data and Model prediction for small but for large 24

RETURNS FOLLOWING FIRE SALES CAR % 1 Day 3 Days FSE -0.103*** -0.255*** SE % (0.03) (0.06) 5 Days 10 Days 20 Days -0.398*** -0.506*** -0.162*** (0.08) (0.11) (0.08) 40 Days 0.0438 (0.06) Standard errors clustered at date level Controls: return volatility, market cap, past 10-day daily and cumulative returns; turnover; stock fixed effect; date fixed effect We have standardized FSE measure here 25

FURTHER EVIDENCE The relation b/w FSE and price drops is substantially stronger immediately following regulatory tightening announcements. The reversal is unlikely to be caused by Chinese government bailout effort Current literature shows that the government does not know details about the margin system in China (Bian, Da, Lou, Zhou (2018), and Bian, He, Shi, Zhu (2018)) Correlation between government purchase and individual stock FSE is close to 0 26


: BROKERAGE VS SHADOW Fire sale account cut-off ; more shadow accounts are fire-sale ones! 28

SHADOW OR BROKERAGE? CAR % 1 Day 3 Days 5 Days 10 Days 20 Days 40 Days FSE of shadow -0.108*** -0.269*** -0.414*** -0.523*** -0.112 0.030 SE (0.03) (0.07) (0.09) (0.12) (0.099) (0.048) FSE of brokerage -0.0187*** -0.0441*** -0.0784** -0.106*** -0.118*** 0.0326 SE (0.008) (0.0141) (0.0228) (0.0211) (0.0339) (0.0463) Regress CAR on FSE, constructed using just the Shadow or Brokerage samples Coefficients represent the change in CAR for a std dev change in FSE FSE constructed using the Shadow sample has larger effect and explanatory power 29

MARKET FEEDBACK Positive feedback of leverage spiral stronger fire sale in market downturns Our results is consistent with the General Equilibrium effect 30

CONCLUSION Direct evidence of leverage-induced fire sales The closer to the maximum allowable leverage, the more investors sell (both preemptive sales and forced sales) Fire sales led to negative abnormal returns in the short-run that reverted High stocks dropped more in value than other stocks and reverted back Asymmetric effect, consistent with feedback loop with market returns Brokerage accounts owned a greater fraction of market assets, but unregulated shadow accounts contributed more to fire sales constructed from shadow accounts offers greater explanatory power for shortterm underperformance and long-term reversal Caveat: We don’t argue that fire-sales caused the entire market crash Results on the regulatory shock suggest fire sales played some role, but there were other forces (e.g. fundamentals) contributing to the crash (e.g., general equilibrium) Acharya and Viswanathan 2011 JF 31

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