1. Steve Christophe, Mike Ferri, Jim Hsieh (George Mason) Dolly King (UNC Charlotte) NTU, 12/6/2012

2. Why This Study?  Existing theories assert that short sellers are informed traders and their presence enhances price discovery in financial markets. Diamond and Verrecchia (1987), Miller (1977), Chen et al. (2002), Duffie et al. (2002), Scheinkman and Xiong (2003)  A growing number of empirical studies find supporting evidence:  abnormal short selling   future stock returns. Jones and Lamont (2002), Desai et al. (2002), Boehmer et al. (2008), Diether et al. (2009) Data sources: hand-collected, monthly short interest, recently available RegSHO data 2 2

3. Why This Study?  Most existing studies focus on the impact of short selling on equity prices.  However, the implications in theories could AND SHOULD be tested in other financial markets. 3 3

4. Why This Study?  We examine whether the informativeness of short selling in the equity market spills over to the corporate bond market.  A recent related article by Asquith et al. (2012) finds that corporate bond short sellers do not possess private information. However, could it be because informed short sellers have more incentives to trade in the equity market? If that’s the case, equity short trades should be more revealing than bond short trades. 4 4

5. Equity Market vs. Corporate Bond Market  At least three reasons why the equity market could be more informative than the corporate bond market:  Investor Clientele: E: more retail investors B: more institutional investors and money managers  Information Acquisition: E: followed closely by analysts and media B: less coverage with fewer bond analysts  Speed of Prices Adjusting to Information: E: more liquid B: more opaque and information travels slower [Gebhardt et al. (2005) and others] 5 5

6. Equity and Corporate Bond Markets are Correlated  A negative information shock that affects a firm’s fundamentals could change its expected cash flows or risk, which in turn could affect both stock and bond prices.  Short sellers identify overvalued stocks and trade on firms’ fundamentals. Dechow et al. (2001), Christophe et al. (2004), Christophe et al. (2010), Akbas et al. (2010), Karpoff and Lou (2010), Engelberg et al. (2012).  The arguments suggest that an increase in equity short selling could result in lower bond returns. 6 6

7. Alternatively, equity short selling might have little impact on corporate bond prices  The incidence of mispricing could be asymmetric for the equity market and the bond market: Yes for equity, but No for corporate bonds, under normal conditions.  Retail investors are more likely to suffer from behavioral biases [Barberis et al. (1998), Daniel et al. (1998), Hong and Stein (1999)].  Some short-sale transactions are for market making, hedging or arbitrage. They are not informative.  If these effects dominate, we should observe marginal or no bond price reaction to changes in short selling. 7 7

8. Sample Selection  Daily short selling data for Nasdaq firms, 9/2000-7/2001  Bond data are collected from Moody’s/Mergent Bond Record and S&P’s Bond Guide  Filters are applied to ensure enough short selling and liquidity.  Details of the sample screening procedure is described in the paper.  Total 156 bonds issued by 86 firms. 8

9. Measuring Bond Returns  Monthly Bond Return = (BP t – BP t-1 + AI t )/BP t-1  Abnormal Bond Return = Monthly Bond Return – Index Return Index return is calculated based on 11 bond ratings from S&P and 2 maturity categories (Long term and Intermediate term) 9

10. Measuring Short Selling (SS)  Advantages of our short selling data: Daily vs. commonly used monthly short interest Speculative short trades vs. dealer short trades Exempt vs. non-exempt  Only non-exempt speculative short trades are included.  Use daily short selling to construct monthly short selling measures. Goal: To capture persistent or abnormal short selling in a month  Abnormal SS = (median # shorted shares in a month – normal SS)/shrout  Normal SS = average or median SS during the entire sample period  Another abnormal SS is to capture aggregated SS in a month. 10

11. Abnormal Short Selling (ABSSA) and Contemporaneous Bond Returns (BDRET, BDABR) - Table 2 11 Split by ABSSA(t) ABSSA(t) ≤ 0 ABSSA(t) > 0Difference MeanMedianMeanMedianMeanMedian (1a)(1b)(2a)(2b) (1a) - (2a)(1b) - (2b) Panel A. Full Sample BDRET(t)0.02710.1206-0.50510.00000.53210.1206* BDABR(t)0.03400.1640-0.51670.00850.55100.1555* Panel B. Bond Rating B.1. Investment-Grade Bonds: BDRET(t)0.26030.24971.12230.2439-0.8620**0.0058 BDABR(t)0.21800.19911.07990.2440-0.8619**-0.0449 B.2. High-Yield Bonds: BDRET(t)-0.17250.0000-1.7496-0.49391.5771*0.4939** BDABR(t)-0.12360.1204-1.7377-0.62441.6141*0.7448** Panel C. Bond Maturity C.1. Intermediate-Term Bonds: BDRET(t)0.12980.1218-0.62880.00000.75860.1218** BDABR(t)0.14110.1959-0.6291-0.01030.77020.2062* C.2. Long-Term Bonds: BDRET(t)-0.58330.00030.43190.0000-1.0152*0.0003 BDABR(t)-0.6032-0.01310.33370.0274 -0.9369-0.0405

12. Abnormal Short Selling (ABSSA) and Contemporaneous Bond Returns (BDRET, BDABR)  Tables 2 to 4 establish that: 1. Abnormal short selling and contemporaneous bond returns are inversely correlated. 2. Intermediate-term and high-yield bonds are more sensitive to shorting activities. 12

13. Abnormal Short Selling (ABSSA) and Subsequent Bond Returns (BDRET, BDABR) - Table 5 13 First Sort by ABSSA(t-1) ABSSA(t-1) ≤ 0ABSSA(t-1) > 0Difference MeanMedianMeanMedianMeanMedian (1a)(1b)(2a)(2b) (1a) - (2a)(1b) - (2b) Panel A. Full Sample (No Second Sort) BDRET(t)0.17940.1217-0.0213-0.11930.2007***0.2410*** BDABR(t)0.18710.1714-2.1499-0.07511.9628***0.2465*** Panel B. Second Sort by Bond Rating B.1. Investment-Grade Bonds: BDRET(t)0.33650.25030.50360.1564-0.16710.0939 BDABR(t)0.29110.19910.49200.1838-0.20090.0153 B.2. High-Yield Bonds: BDRET(t)0.04590.0000-4.2411-0.63974.2870***0.6397*** BDABR(t)0.09880.1229-4.2764-0.79624.3752***0.9191*** Panel C. Second Sort by Bond Maturity C.1. Intermediate-Term Bonds: BDRET(t)0.29460.1226-0.02390.00000.3185***0.1226*** BDABR(t)0.30840.2008-2.4146-0.05602.7230***0.2568*** C.2. Long-Term Bonds: BDRET(t)-0.51220.0104-0.2246-0.7819-0.28760.7923 BDABR(t)-0.54050.0069-0.2382-0.7704 -0.30230.7773

14. Abnormal Short Selling (ABSSA) and Subsequent Bond Returns (BDRET, BDABR) - Table 6 14 Dependent Variable: BDRET(t) BDABR(t) (1)(2)(3) (4)(5)(6) Intercept0.01380.01250.01040.01410.01290.0109 (0.2739)(0.3011)(0.3192)(0.2570)(0.2816)(0.2991) BDRET(t-1) or BDABR(t-1)-0.1303**-0.1308**-0.1338**-0.1147**-0.1153**-0.1177** (0.0138)(0.0155)(0.0196)(0.0306)(0.0333)(0.0411) ABSSA(t-1)-0.0189***-0.0221***-0.0273***-0.0198***-0.0225***-0.0280*** (0.0006)(0.0000) (0.0004)(0.0000) Long-Term-0.01217**-0.0072**-0.0032-0.0120**-0.0072**-0.0031 (0.0108)(0.0299)(0.2719)(0.0103)(0.0239)(0.2760) High-Yield-0.0115*-0.0107-0.0065-0.0110*-0.0102-0.0060 (0.0800)(0.1026)(0.1963)(0.0887)(0.1119)(0.2301) ABSSA(t-1)*Long-Term0.04970.03660.04770.0349 (0.1157)(0.1754)(0.1205)(0.1812) ABSSA(t-1)*High-Yield0.00060.00690.00010.0059 (0.9455)(0.4196)(0.9911)(0.5111) * Additional control variables are omitted. 1   in ABSSA  -1.01% in BDRET or -1.04% in BDABR

15. Abnormal Short Selling (ABSSA) and Subsequent Bond Returns (BDRET, BDABR)  Tables 5 to 9 show that: 1. ABSSA has a significantly negative impact on future bond returns. 2. The relationship between these two variables is even more pronounced than the contemporaneous one. 3. The effect of ABSSA on future bond returns is not limited to certain subsamples. 4. The relationship is robust to different SS measures, additional control variables, and bond illiquidity. 5. Our results cannot be replicated by using abnormal short interest. 15

16. What Drives the Negative Relation between Short Selling and Bond Returns?  Our results clearly show that equity short selling has value implications for corporate bond investors. But why?  Two plausible explanations: 1. Information signaling: A high level of short selling signals a firm’s negative future prospects which affect both of its stock and bond(s). 2. Overvaluation: Short sellers target firms with overvalued stock and bonds. 16

17. What Drives the Negative Relation between Short Selling and Bond Returns?  Use DID approach.  Variables to test the information signaling hypothesis: Default risk: analyst downgrades, Altman’s Z-score Debt & short-term obligations:  TD/TA,  EBIT/Int. Exp. Earnings surprise: SUE Cash & Assets:  TA,  Cash/TA,  DIV/TA Profitability:  EPS,  EBITDA,  ROA,  OM  Variables to test the overvaluation hypothesis: Two proxies of earnings accruals Existing studies show that firms with high accruals tend to be overvalued. Bhojraj and Swaminathan (2009): Accruals anomaly can be extended to the bond market. 17

18. What Drives the Negative Relation between Short Selling and Bond Returns? 18 ABSSA(t)≤0ABSSA(t)>0 MeanMedianMeanMedian Variables Related to Accruals NNI(Q-1)0.04880.0101-0.0322***-0.0084*** WCA(Q-1)-0.0130-0.0154-0.0138-0.0167 Variables Related to Default Risk Downgrade(Q+1)0.02190.00000.0087**0.0000 Z-score(Q+1)2.00171.01611.2405*1.0161** Variables Related to Debt and Short-term Obligations  (Total Debt/TA) 0.00260.0000-0.00010.0000  (EBIT/Int. Exp.) -0.39180.0000-0.33380.0000 Earnings Surprise SUE(Q+1)-0.00060.0006-0.0208**0.0004* Variables Related to Cash and Assets  TA ($MM) 274.477.577.70***-0.20***  (Cash/TA) -0.0064-0.00130.0030***-0.0006  (Dividend/TA) -0.00030.0000-0.0021**0.0000 Variables Related to Profitability  EPS -0.1812-0.02-0.4211***-0.02*  EBITDA ($MM) 6.28442.080.82000.01***  ROA -0.0049-0.0005-0.0029-0.0008  OM 0.0056-0.0012-0.0003*-0.0018 Opposite of the overvaluation story

19. Contributions of This Study  Provides the first look at the relationship between short selling and corporate bond returns: Abnormally high short selling is associated with lower contemporaneous and future bond returns.  Explores the source of information in short selling that moves bond prices. We analyze bond price reactions to distinguish between two oft-cited explanations for the relation between short selling and equity returns. 19