THE EFFECTS OF STOCK LENDING ON SECURITY PRICES: AN EXPERIMENT

THE EFFECTS OF STOCK LENDING ON SECURITY PRICES: AN EXPERIMENT Steve Kaplan Toby Moskowitz Berk Sensoy November, 2011

MOTIVATION: WHAT IS THE IMPACT OF SHORT SELLING ON SECURITY PRICES? Does shorting make prices more efficient by reducing overpricing? Miller (1977) predicts differences of opinion and short sales constraints can lead to overpricing. Diamond and Verrecchia (1987) argue traders will adjust to short sale constraints so that there is no overpricing. But skewness may be affected. Does shorting make prices less informative and destabilize markets? Moving prices further away from fundamentals [Lamont (2004)]? Help reduce excess volatility? [Hong and Stein (2003), Abreu and Brunnermeier (2001), Allen and Gale (1991)] 2

EFFECT OF SHORT SELLING CONSTRAINTS IS AN EMPIRICAL QUESTION Attempts to measure the empirical effects from both the demand and supply sides. Holding supply constraints fixed, can use variation in shorting demand to test for overpricing or excess volatility. Holding demand fixed, can use variation in shorting supply to measure degree to which constraints matter. Empirical efforts hampered by difficulty of identifying pure demand or supply variation. E.g., short interest, rebate rates, loan fees. Regulation shocks (2008 Emergency Order, SHO, shorting bans around the world). 3

HOW DOES SHORT SELLING WORK? (COHEN ET AL. (2004)) Investor who wants to short must find a lender. Sells shares short. Then: Short seller must deliver shares to buyer by day T+3. Short seller must maintain margin of >= 30% of short position. Proceeds of short sale deposited with lender. Lender requires 102% of value of shares as collateral. Fluctuates with value of shares. Lender invests collateral and earns interest. Interest is reinvestment rate. Lender also pays borrower a rebate rate which is <= reinvestment rate. Rebate rate can be negative. Lender s profit = Reinvestment rate - Rebate rate = Loan Spread / Fee. Stocks in highest demand (special) can have negative rebate rates. 4

Recall: Lender can recall the shares at any time. Borrower must return shares in 7 business days. 5

PREVIOUS EMPIRICAL WORK Shorting demand: Use direct measures of shorting costs (rebate rate or spread between the rebate and interest rates) [D Avolio (2002), Geczy, Musto, and Reed (2002), Ofek, Richardson, and Whitelaw (2004), and Jones and Lamont (2002)]. Short interest [Desai et al. (2002) for a summary]. Shorting supply: Ofek and Richardson (2003) consider lockup expirations. Chang, Cheng, and Yu (2007), Bris (2008), Diether, Lee, and Werner (2009), Beber and Pagano (2010) on regulation changes. Cohen, Diether, and Malloy (2008) look at both. Mixed results---hard to separate supply and demand. Also, hard to disentangle shorting market changes from changes in underlying security market. 6

WHAT DO WE DO? Working with an anonymous money manager (greater than $15 B in assets) we randomly: Make available for lending 2/3 of Manager s stocks and withhold other 1/3 of Manager s stocks. Focus on high loan fee stocks (loan fee > 25bps per year, with mean > 4%). Provides exogenous shock to supply of lendable shares Exogenous decrease in shorting constraints. Supply shift not driven by changes in The Manager s marginal lending cost. Focus on stocks with high loan fees. Theory suggests this is where we are most likely to see pricing effects. [Duffie, 1996; Duffie, Garleanu, Pedersen 2002]. 7

KEY RESULTS Supply shocks sizeable. Lending fees reduced. Market loan quantities increased. No evidence of adverse effects on average on Returns. Volatility. Skewness. Bid-ask spreads. Inconsistent with overpricing and disagreement theories of shorting activity. In cross-section of returns: Weak evidence of lower returns to stocks with largest supply shocks and highest analyst disagreement. Not robust across two phases of the experiment. 8

EXPERIMENTAL DESIGN AND SAMPLE The Manager Invests in mid and small-cap equities, inside and outside U.S. Had not lent out stocks out of concern that doing so would: lower the stocks prices. increase their volatility. Motivation for experiment Consider fees / benefits from lending shares. vs. Adverse effects / costs. Measure magnitude of net benefit/cost. 9

EXPERIMENT PHASE 1 Shares available for lending on September 5, 2008. Selected sample based on stockholdings as of June 30, 2008. Manager owned 523 stocks worth in excess of $15 billion. Stocks divided into two groups: 1. Revenue stocks projected to have loan fee of at least 10 basis points (138 stocks). 2. Remaining group of 385 stocks we refer to as "non-revenue" stocks. Within each group, randomly selected to lend out 2/3 and withhold 1/3. One exception - lent three stocks in revenue stock group with the highest expected revenue to reduce opportunity cost. Results are the same if we exclude these three stocks. 10

Figure A-1 - distribution of firm characteristics across the revenue stocks available to lend out and revenue stocks withheld No significant differences between available and withheld groups Figure A-2 (same for) non-revenue stocks No significant differences between available and withheld groups. These stocks were not intended to be lent, but comforting wrt experimental design. Randomization seems to work---observables no different across the treatment and control groups 11

ADDITIONAL RESTRICTIONS Shares traded on U.S. exchanges. Shares that were in high demand relative to supply. Revenue stocks with expected loan fees of at least 25 basis points. Cuts to 40 available and 20 withheld stocks. At the start of the lending program, 8 available stocks no longer eligible for lending because loan fees decreased to less than 25 bp. End up with 32 available and 20 withheld stocks. Loan size restricted to the lesser of: Three times the average daily trading volume (in past 30 days). 5% of outstanding shares of issuer. Concern: Loan size restrictions put a limit on increase in supply from experiment. Response: These stocks are those for which supply shocks should matter the most. Most variation in loan supply comes from ownership and NOT these restrictions. Cross-sectional results. 14

EXPERIMENT PHASE 2 We repeated the experiment from June 5 to September 30, 2009. Same restrictions applied (except required expected fee at least 25 basis points throughout). Randomization results in 22 available stocks and 10 withheld stocks. Manager then asked us to lend 1 of the withheld stocks. Changes to 23 available and 9 withheld stocks. Results are the same if we exclude the selected stock. At start of lending, 3 available stocks no longer eligible for lending because their loan fees had declined to less than 25 bp. End up with 19 available and 9 withheld stocks. On October 1, 2009, all shares were made available for lending with a limit of $500 million. Ends the experiement. 15

SAMPLE DESCRIPTION TABLE I Compare available stocks to withheld stocks on observable dimensions. No differences across a variety of characteristics. For first phase, only significant differences are higher mean (but not median) institutional ownership and marginally higher short interest. For second phase, only significant difference is higher expected loan fee for available stocks. Consistent with random variation. But, if anything, differences will likely bias towards finding an effect. 16

TABLE I: RANDOMIZATION 17

18

ARE THE SAMPLE STOCKS GOOD CANDIDATES FOR TESTING OVERVALUATION/DISAGREEMENT THEORIES Is high shorting demand relative to supply (evidenced by high loan fees) driven by hedging motives? Unlikely: Less than 5-10% of stocks involved in M&A. Less than a quarter had convertible bonds outstanding. Highly valued, high disagreement: M/B ratios above 80 th percentile. 41% of stocks have no analyst coverage. Among ones that do, forecast dispersion is above the 85 th percentile of all stocks with coverage. More on this in the cross-sectional tests. 19

THE LENDING EXPERIMENT AND SUMMARY STATISTICS First phase: Lending period began September 5, 2008. At peak, on September 17, over $700 million of securities lent out. September 18, 2008, Manager asked lending agent to call loans back. Last shares returned on October 3, 2008. We examine effects on stocks lent out vs. those withheld during: "lending period" (September 5 to 17). Max. 9 trading days. "recall period" (September 18 to October 3). Max. 12 trading days. Pre-period is August 1-Sept. 4, 2008. 24 trading days. 20

THE LENDING EXPERIMENT AND SUMMARY STATISTICS Second phase: Lending period began June 5, 2009. Up to $200 M lent out through August 7. After August 7, up to $350 M lent out (and limit not reached) through September 30. Withheld stocks were made available on Oct. 1. Lending period is June 5 Sept. 30. 82 trading days. Pre-period is May 1 June 4, 2009. 24 trading days. 21

TABLE II: SUMMARY STATISTICS 22

DOES EXPERIMENT PROVIDE A SIZEABLE SHOCK TO SUPPLY? Potential loan from experiment is: For first phase, mean of 2.3 times average daily volume, 3.7% of institutional ownership, 18.3% of short interest. For second phase, mean of 2.1 times average daily volume, 6.9% of institutional ownership, 36.8% of short interest. Increase in supply should have largest effect for stocks in our sample to the extent that high loan fees indicate that they are in high demand and illiquid [Kolasinki, Reed, and Ringgenberg (2010)]. 23

DOES EXPERIMENT PROVIDE A SIZEABLE SHOCK TO SUPPLY? What happens to loan fees and quantities? Supplemental data from Data Explorers on loan fees and quantities Available stocks hit by our supply shock. Withheld stocks not shocked. Loan fees If supply shock big enough, loan fees should for available stocks should decline significantly compared to withheld stocks. Size of decline indicates importance of supply change. Table III Measure loan fee changes for available vs. withheld stocks. Difference-in-differences approach comparing pre-lending fees and fees during the lending program. Use multiple measures of fees from multiple sources Data Explorers. Expected fees from lending agent. Actual fees received. Fees the Manager received are highly correlated with Data Explorers fees, but not perfectly so (0.69). Examine cross-section of size of loan. 24

TABLE III: DIFFERENCES-IN-DIFFERENCES FOR LOAN FEES 25

LOAN QUANTITIES TABLE IV 26

TABLE V: RETURN DIFFERENCES Portfolio approach to avoid cross-correlation problem Three sets of weighting schemes: Equal weight. Value weight. Weight by expected loan fee before the lending experiment. If loan supply has pricing effect (at amounts being lent), then expect decrease in returns of available relative to withheld stocks during lending period (when supply is increased) reversal or increase in returns during recall period (when increase in supply is taken away) 27

TABLE IV: RETURN DIFFERENCES Pre-period Lending period Recall period Available Withheld Difference Available Withheld Difference Available Withheld Difference Panel A: First Phase Equal-weight 0.16 0.15 0.01-0.26-0.72 0.47-0.69-0.27-0.42 [0.47] [0.47] [0.26] [0.86] [1.05] [0.37] [1.50] [1.49] [0.50] (0.98) (0.24) (0.42) Value-weight 0.14 0.01 0.13-0.19 0.09-0.28-0.70 0.01-0.71 [0.48] [0.40] [0.29] [0.86] [0.94] [0.47] [1.47] [1.46] [0.77] (0.67) (0.57) (0.38) Expected loan fee-weight 0.23-0.09 0.32 0.31-0.80 1.11*** -0.85-0.55-0.29 [0.52] [0.60] [0.41] [0.84] [0.93] [0.28] [1.59] [1.58] [0.49] (0.44) (0.00) (0.56) Panel B: Second Phase Equal-weight 0.67 0.44 0.23 0.36 0.23 0.13 [0.66] [0.53] [0.31] [0.23] [0.20] [0.13] (0.46) (0.35) Value-weight 0.53 0.67-0.14 0.34 0.13 0.21* [0.56] [0.51] [0.35] [0.20] [0.19] [0.13] (0.69) (0.09) Expected loan fee-weight 1.59 0.27 1.32* 0.35 0.22 0.13 [1.02] [0.61] [0.75] [0.31] [0.21] [0.24] (0.09) (0.59) 28

POWER OF THE TESTS Each phase individually has only moderate statistical power. Since two phases are independent, joint power is much higher. Consider Miller s (1977) overvaluation hypothesis that returns during the lending period are negative (a onetailed test) equal-weighted results, the joint probability observe at least 47 basis points (p-value = 0.12) in first phase (trial) 13 basis points (p-value = 0.175) in second phase (trial) relative to the null that returns in each phase are less than or equal to zero = 2.1% Alternatively, can ask what level of returns can we reject at conventional levels of significance taking into account both phases? Rejection regions that combine both phases---table VI 29

Table V: Power of the Tests Rejection Cutoff Values for Return Differences (in %) Significance level Lending (lower bound) First phase Recall (upper bound) Second phase Lending (lower bound) Combined phases Lending (lower bound) Equal-weighted 10% -0.04 0.26-0.05 0.01 5% -0.21 0.48-0.10-0.03 1% -0.60 0.94-0.19-0.12 Value-weighted 10% -0.94 0.34 0.05 0.01 5% -1.16 0.67 0.00-0.03 1% -1.65 1.38-0.08-0.12 Expected loan fee-weighted 10% 0.72 0.38-0.18 0.31 5% 0.59 0.59-0.27 0.25 1% 0.30 1.04-0.43 0.12 30

EVENT STUDIES FOR RETURNS TABLE VII No adverse return effects over entire lending or recall periods. Perhaps effects show up at higher frequencies that are masked by overall period. Event studies also address concern that termination decision in the second phase is endogenous to results. But event studies at 1 day, 2 days, 3 days, 1 week, and for second phase 1 month, 2 months, and 3 months also reveal no adverse return effects. 31

TABLE VII 32

THE CROSS-SECTION OF RETURNS Previous results are for the average stock. May mask important cross-sectional information. Returns may be related to certain stock characteristics or magnitude of the supply shock. 33

TABLE VIII 34

TABLE VIII 35

CROSS-SECTIONAL RESULTS Results mildly suggestive of lower returns to available stocks with high loan supply or high analyst disagreement. Not robust across phases. Results for M/B opposite of overvaluation theories. Considerable potential for spurious inference if control group is ignored. 36

VOLATILITY, SKEWNESS, AND BID-ASK SPREADS Differences-in-differences between stocks made available vs. those withheld from pre-lending to lending period. lending period to recall period. Cross-sectional average of volatilities and skewness from daily returns over each period. Time-series average of daily bid-ask spreads of each stock (as % price) over the specified period. If short sale constraints are important for price discovery: Expect decrease in volatility, skewness, and bid-ask spread over the lending period. Expect reversal over the recall period. If short sales are destabilizing, expect the opposite pattern. 37

TABLE IX: CHANGES IN VOLATILITY, SKEWNESS, AND BID-ASK SPREAD Differences-in-Differences Between Available and Withheld Stocks from Pre-, Lending, and Recall Periods Volatility differences Skewness differences Bid-ask spread differences Lending - pre-period First phase Recall - lending Second phase First phase Second phase First phase Second phase Lending - Lending - Recall - Lending - Lending - Recall - Lending - pre-period pre-period lending pre-period pre-period lending pre-period Equal-weight -0.82 0.50-0.59 0.09-0.06-0.46-0.04-0.68** -0.04 (0.14) (0.59) (0.38) (0.80) (0.78) (0.43) (0.36) (0.04) (0.31) Value-weight -0.54-0.31-0.48 0.08 0.07-0.56 0.00-0.33** -0.04 (0.50) (0.79) (0.39) (0.86) (0.82) (0.28) (0.88) (0.03) (0.18) Expected loan fee-weight -0.07 0.01-1.15-0.13 0.48-0.68-0.05-0.96-0.08 (0.94) (1.00) (0.49) (0.85) (0.29) (0.19) (0.63) (0.13) (0.30) 38

Increasing supply decreases volatility, but insignificant. No results on skewness. Some evidence that bid-ask spreads decline when lending supply is reduced. Also do the same cross-sectional analysis as for returns. Find no robust patterns. 39

ROBUSTNESS Other perturbations of the sample: Including all available and withheld stocks (40 vs. 20; 23 vs. 9). Removing the high loan fee stocks the Manager requested we lend (37 vs. 20; 22 vs. 9). Removing all stocks whose loan fees decline to < 25 bps before the lending program (32 vs. 17; 19 vs. 8). Removing the high loan fee stocks the Manager requested we lend and stocks whose loan fees decline to < 25 bps before the lending program (29 vs. 17; 18 vs. 8). Results unchanged, presented in Appendix. 40

IMPLICATIONS Theory: We find supply shocks impact loan fees, but not asset prices. No evidence for Miller (1977) theory. Why? Duffie, Garleanu, and Pedersen (2002) show direct link between fees and prices, though link is not one-to-one. Diamond and Verrechia (1987) show no price effect, but have no loan fees in their model. Perhaps loan fees are not market clearing (agents ration shares, bundle them with other services). Or, market for stock borrowing segmented from underlying market. Hedgers may exhibit price pressure in loan market but are too small to affect underlying share prices. Future work to consider wedge between lending and underlying markets. 41

IMPLICATIONS Fund manager behavior: Motivation for the experiment from the Manager s point of view. Our results suggest managers (at the margin) can earn revenue from lending shares without adversely affecting share prices. Our Manager came to this conclusion, lifting restrictions on Oct. 1. How much revenue from lending? Manager earned about 10 bp annualized from lending in first phase, about 2 bp in second phase. Does not include withheld stocks. Millions of $, and large compared to the administrative costs of setting up a lending program. Difficult to generalize and can t say much about equilibrium effects. All else must be equal. 42

IMPLICATIONS Policy: Results consistent with the view that policies designed to restrict or alter lending supply of shares will not be effective or useful. Consistent with other studies on the supply side. [Cohen, Diether, and Malloy (2007), Diether, Lee, and Werner (2009)]. Caution: Hard to assess general equilibrium effects. Policy debates could be better informed by experiments, where one channel can be isolated holding everything else fixed. 43

CONCLUSION Experiment producing exogenous and sizeable supply shocks to lendable shares. We find no adverse affects on underlying stock prices, despite moving loan fees. Cross-sectional analysis yields similar findings. No evidence of supply effects for level of supply changes we generate. Implications for theory, manager behavior and policy Strong conclusions for money manager behavior at the margin. Harder to draw conclusions for general equilibrium. May inform policy debates. More experimentation worthwhile and useful. 44