Informed Trading in Regulated Industries
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1 Informed Trading in Regulated Industries David Reeb (Na8onal University of Singapore, Temple) Yuzhao Zhang (Oklahoma State University) Wanli Zhao (Southern Illinois University) NTU December 2012
2 Research Focus Rela8on between regulatory supervision and informed trading Regulatory Pressure Hypothesis: Improve governance and reduce informed trading Informed Regulator Hypothesis: Access to private informa8on; inadvertent or mone8za8on of confiden8al informa8on. Addi8onal Considera8ons Not Mutually exclusive: Diligent oversight but s8ll trade Window Dressing: Firms may fool regulators no private informa8on Empirical Capital Market Issue of whether regulatory supervision influences informed trading. 7
3 Capital Market Measures Return Predictability Using Short Sales Short sales t=0 to predict Returns t=2 Pornolios of Supervised and Non- Supervised Firms Informed Trading in the Long Equity Market PIN (Easley et al. 1996) Sequen8al trading model based on # of Buy and Sell Orders Amihud (2002) Annual Avg (absolute value of daily stock return/daily dollar volume) Sample: 5,274 Firms - 39,436 Firm- Year Observa8ons to 2009 Informed Trading in the Op8on Market Beta- t (Anderson et al 2011) Return Predictability in Op8on Skew Op1on Spread - Rela8ve Bid- Ask Spread on OTM Put Op8ons Sample: 5,084 Firms 974,292 Firm- Day Observa8ons to 2009 All Tests: Full and Matched Samples Control Variables Standard: Size, Industry Concentra8on, Analyst, ROA, Blockholders, Vola8lity, Turnover Dis8nc8ve: Liquidity- PS, Opportunis1c Trades 9
4 Variable definitions are given in Appendix A1. Panel A Short Sales: 8,972 Observations Table 1 Summary Statistics Full Sample Mean Median Std. Dev. Supervised t-test statistic Abnorm Short Sales Negative Shock Positive Shock Opp Mgr Trades Liquidity-PS Panel C Option Market: 3,886 Observations Mean Median Std. Dev. Supervised Nonsupervised Panel B Equity Market: 40,016 Observations Mean Median Std. Dev. Supervised Nonsupervised statistic t-test Amihud PIN Nonsupervised Beta-t Option Spread t-test statistic
5 Table 2 Regulatory Supervision and Informed Trading Dependent Variable: Portfolio Return t+2 Full Sample Supervised Non-supervised Supervised Matched Sample Nonsupervised Intercept *** ** (-4.93) (-0.09) (-2.09) (0.06) Short t *** * *** * (-4.86) (-1.93) (-2.79) (-1.74) Mkt t 0.868*** 0.887*** 0.863*** 0.924*** (12.92) (12.09) (10.31) (7.31) HML t 0.274*** 0.164*** 0.306*** 0.115*** (6.68) (6.31) (4.89) (3.25) SMB t 0.300*** 0.546*** 0.131** 0.475*** (10.64) (13.35) (1.97) (12.27) UMD t *** *** (-5.93) (-3.78) (-1.30) (-1.47) Observations Adjusted-R
6 Informed Trading Around Earnings Shocks Examine Abnormal Short Sales Prior to Earnings Informed Trading Should spike before neg shock Informed Trading Should remain flat/low pos shock Compare in Supervised and Non- Supervised Firms Measuring Abnormal Short Sales Posi8ve/Nega8ve Earning Shocks: 30 days prior Simple 8me series model of EPS Sample: 3,696 Firms 23,654 Firm- Quarter Observa8ons ( ) 10
7 Table 3 Informed Trading and Information Shocks: Short Sale Market Evidence Dependent Abnormal Short Sales Variable: Full Sample Matched Sample Shock type = Negative Positive Negative Positive Constant 0.483*** 0.500*** 0.621*** 0.636*** 0.420*** 0.381*** 0.450*** 0.389*** (4.84) (5.08) (4.76) (4.87) (3.00) (2.62) (3.36) (2.89) SUPERVISED 0.113*** *** ** * - (=1) (3.52) (-4.00) (2.39) (-1.79) FINANCE *** *** ** ** (=1) (4.22) (-4.10) (2.38) (-2.51) PHARMA (=1) (0.44) (-0.75) (0.40) (-0.61) UTILITY (=1) (1.35) (-1.31) (1.25) (-0.55) Control Yes Yes Yes Yes Yes Yes Yes Yes Variables Quarter dummy Yes Yes Yes Yes Yes Yes Yes Yes Observations 3,906 3,906 5,066 5,066 2,142 2,142 2,632 2,632 Adjusted R
8 Natural Experiments Decreases in Government Regula8on Airlines (1978) Trucking (1980) Increases in Government Regula8on Gramm- Leach- Blilely Act (1999) Allowed Banks to expand opera8ons Increased Regulatory Oversight 12
9 Table 4 Natural Experiments with Difference-in-Difference Test Event Airline Deregulation Trucking Deregulation Banking Regulation Dependent Variable: Amihud Amihud Amihud PIN Option Spread Constant * *** 0.031*** (-0.19) (-1.03) (1.92) (-5.69) (4.30) AIRLINES (=1) * (-1.95) TRUCKING (=1) ** (-2.11) BANK (=1) ** 0.012** 0.025** (2.42) (2.08) (2.17) Control Variables Yes Yes Yes Yes Yes Observations ,155 1, Adjusted R
10 Disclosure Timing Test Commercial Bank Call Reports Private Data Provided to Regulators Receive 40 days prior public Quarterly Data Informed Trading using Amihud (2002) 13
11 Table 5 Information Flows and Informed Trading: Evidence from Call Reports Panel A Short Sales Evidence Dependent Variable: Abnormal Short Sales Shock type = Negative Positive Negative Positive Negative Positive Window: t1-10 t11-20 t21-40 Constant 0.351** 0.202** 0.333** 0.222** 0.211** 0.333* (2.25) (2.00) (2.30) (2.11) (2.22) (1.90) Commercial Bank (=1) 0.047** * 0.044* * (2.17) (-1.70) (1.90) (-1.89) (1.32) (-1.28) Earnings Shock 0.029** ** * 0.031* * (2.22) (-1.60) (2.01) (-1.77) (1.95) (-1.90) Control Variables Yes Yes Yes Yes Yes Yes Quarter dummy Yes Yes Yes Yes Yes Yes Observations Adjusted R
12 Federal v State Chartered Banks Dual Banking System Fed Substan8ve Oversight State Regulators Same Private Disclosures: Call Reports Same Informa8on Higher Ra8ngs Agrawal et al. (2012) ID States with greater regulatory cronyism Differing Federal Reserve Districts: Same Private Disclosures Category 1: NYC/Chicago Category 3: Kansas/Dallas Category 2: All others 14
13 Dependent Variable: Matched Sample: Table 6 Federal versus State Bank Regulatory Oversight State Banks & National Banks Abnormal Amihud State Banks & Non-Regulated Firms State & National Banks & Non-regulated Firms Window: t1-10 t11-20 t21-40 t1-10 t11-20 t21-40 t1-10 t11-20 t21-40 Constant (0.87) (0.72) (1.54) (0.44) (0.66) (0.16) (0.21) (1.14) (0.07) Bank (=1) ** 0.118*** 0.106*** Regulatory Duplicity (=1) (1.15) (0.94) (0.81) (2.33) (2.98) (2.90) 0.099* 0.098* ** 0.079** * 0.038* (1.93) (1.74) (1.16) (2.47) (1.98) (1.45) (1.93) (1.79) (1.52) Control Variables Yes Yes Yes Yes Yes Yes Yes Yes Yes Quarter Dummy Yes Yes Yes Yes Yes Yes Yes Yes Yes Observations Adjusted R
14 Constant Appendix A3 National Level Supervision Differentiating Among Federal Relative to OCC Oversight Reserve Districts Dependent Variable: Amihud PIN Amihud PIN 0.550*** 0.512*** 0.269*** 0.468*** (4.45) (2.74) (19.16) (23.53) Fed (=1) * ** - - (-1.77) (-2.17) FDIC (=1) * *** - - Banks HQ (NY and Chicago) Banks HQ (KC and Dallas) (-1.69) (-3.63) * * (-1.89) (-1.90) ** 0.025** (2.20) (2.13) Control Variables Yes Yes Yes Yes Year dummy Yes Yes Yes Yes Observations ,237 7,475 Adjusted R
15 State v State Insurance and U8li8es: State Regulated States differ in Regulatory Environment Index of Poli8cal Corrup8on State Level Beder Government Associa8on Index of State Integrity Regulatory Induced Trading Higher in Corrupt States 15
16 Table 7 Political Corruption and Informed Trading: Evidence from Insurance and Utility Firms One-to-one Match One-to-one Match Dependent Variable: Amihud PIN Beta-t Option Spread Constant 0.939*** 0.329*** 0.864** 0.287*** Supervised (=1) Corruption Supervised * Corruption (4.18) (3.37) (2.02) (7.36) 0.123*** 0.016** 0.080** 0.045* (2.72) (2.01) (2.18) (1.87) * 0.003* 0.000* (1.24) (1.77) (1.71) (1.79) 0.002** 0.001* 0.007** 0.001* (2.15) (1.89) (2.04) (1.88) Control Variables Yes Yes Yes Yes Year dummy Yes Yes Yes Yes Observations 3,960 2, Adjusted R
17 Conclusion Each Test Mul8ple Interpreta8ons Incorporate Liquidity and Managerial Trading Series of Test Point In One Direc8on First 3: Informed Trading é in regulatory supervision Second 3: Informed Trading a func8on of private disclosures to regulators and degree of poli8cal corrup8on Policy Implica8ons: Disclosure Regula8on Profitable Trading Entails Informa8on Asymmetries Regulator Incen8ves to Facilitate Non- Disclosure 18
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