Legal insider trading and stock market liquidity Jérémie Lefebvre Tilburg University, TILEC Louvain School of Management Hans Degryse Tilburg University TILEC Frank de Jong Tilburg University TILEC TILBURG LAW AND ECONOMICS CENTER
Motivation This paper brings together 3 strands of literature Legal insider trading literature: Trades by corporate insiders carry information about future stock price performance Market microstructure: Information asymmetry affects stock market liquidity Stock market regulation: Effect of new regulation on trading condition (market liquidity and efficiency) 2
Research questions 1. How do legal insider trades affect stock liquidity? Does the bid-ask spread increase? Does the adverse selection component of the spread increase? 2. Does the implementation of the Market Abuse Directive (European Union Directive 23/6/EC) reduce the effect of insider trading on the liquidity of the stocks? 3. By analyzing the liquidity of the stocks on dates of insider trading, can we infer the information content of the trades? Can it help to predict future abnormal returns? 3
Literature (1) Literature on legal insider trading: Seyhun (1986-1988-1992); Lakonishok and Lee (21); Jeng, Metrick & Zeckhauser (23); Fidrmuc, Goergen & Renneboog (26); Degryse, de Jong & Lefebvre (29) Trades by insiders are good predictors of future price performance (information content of trades) Top executives are more informed than insiders in lower positions Purchases are more informed than sales (liquidity and diversification motives for sales) Trades in small firms are more informed than in large firms Bhattacharya & Daouk (22) Effect of new regulation: What matters is the time of first prosecution, not time of implementation 4
Literature (2) Insider trading and liquidity measures Chung & Charoenwong 1998-FR Stocks with high intensity of insider trading have larger bidask spreads (cross-sectional effect) Market makers do not seem to adjust the bid-ask spread when insiders trade. Insider trading regulation and liquidity Frijns, Gilbert & Tourani-Rad 28-JFR: implementation of strict insider trading regulations on the New Zealand Stock Exchange They find that in average, adverse selection decreased after the introduction of the regulation 5
Contribution to the literature We study change in market liquidity around days of insider trading We decompose the bid-ask spread into its components (temporary and permanent price impact) A study of the effect of the Market Abuse Directive. 6
Institutional features Insider trading regulation Insiders are not allowed to trade upon private and price sensitive information. Trading in advance of earnings announcements and information events is banned. Top executives have to disclose their trades to the AFM within 1 business day. This becomes publicly available information. Market Abuse Directive Introduced in the Dutch regulation starting in October 25 Modification of Wte 1995 Market Abuse Decree of 25 Increased the punishment to illegal insider trading Companies are obliged to publish price-sensitive information, which should reduce the information asymmetry of insiders 7
Data Legal insider trading data Legal insider trading of top executives (board of directors, supervisory board) on Euronext Amsterdam (shares only), on daily frequency Trades and quotes data Intraday stock market data: Trades and quotes from Euronext Amsterdam, from July 24 until December 27. We measure liquidity on a daily basis using trades and quotes Other sources Datastream for market capitalization 8
Liquidity measures Measures of the bid-ask spread: Quoted spread Effective spread Adverse selection component of the spread Price impact (PI) 9
Cross-section: Does more insider trading means less liquidity? Regression of average illiquidity on insider trading intensity, with MAD dummy and control variables (clustered standard errors) Intensity of insider trading: number of shares traded by top executives, scaled by total number of shares outstanding Variable QS ES PI intercept.7479.6887.2312 (13.97) *** (13.23) *** (13.1) *** log MCap -.1255 -.193 -.423 (-6.8) *** (-6.5) *** (-6.13) *** Trading Volume -.215 -.191.66 (-3.1) *** (-2.9) *** (2.26) ** Daily volatility 1.7221 1.718.8593 (4.15) *** (4.38) *** (4.31) *** Price inverse.7544.7693.23 (2.4) *** (21.39) *** (.11) Intensity.1.7.3 (1.57) (1.23) (1.6) MAD -.1222 -.1489.74 (-2.18) ** (-2.82) *** (.35) N 136 136 136 Adj. R 2.8138.8249.7875
Cross-section: Does more insider trading means less liquidity? Results: Intensity has the right sign, close to be significant Market Abuse Directive: stocks are more liquid after MAD than before (except for Price impact, for which there is no change) Other control variables: same as in literature
Price Impact of trades as a function of time (data: all trades and quotes) 12
Price Impact: Insider trading days versus non insider trading days 13
The impact of insider trading on stock liquidity: Abnormal illiquidity Abnormal illiquidity is a measure of change in liquidity around days of insider trading Similar to Abnormal Returns, but using liquidity measures: Abnormal illiquidity t = Illiquidity t benchmark illiquidity Event window: 5 days starting on the insider trading day (day until day 4) Benchmark window: 1 days before and after the insider trading day, except day to day 4. The Abnormal illiquidity s are cumulated: Cumulative Abnormal illiquidity (CAI) over day to day 4. 14
.5 Abnormal illiquidity: Small firms Quoted Spread (N=153) -.5.5 Effective Spread (N=153) -.5.2 Price Impact (N=153) -.2 15
.1 Abnormal illiquidity: Medium firms Quoted Spread (N=181) -.1.1 Effective Spread (N=181) -.1.5 Price Impact (N=181) -.5 16
.1 Abnormal illiquidity: Large firms Quoted Spread (N=216).5.1 Effective Spread (N=216).5.1 Price Impact (N=216) -.1 17
Determinants of change in illiquidity Dependent variable: Cumulative abnormal illiquidity over day and 1 Variable Quoted spread Effective spread Price impact cons -.3177 -.3254 -.251 (t-stat) (-4.65) *** (-4.28) *** (-.26) Medium.1751.1718.322 (t-stat) (3.43) *** (3.6) *** (.5) Large.691.498 -.211 (t-stat) (1.1) (.65) (-1.66) * logavgto.12.111.861 (t-stat) (6.76) *** (5.86) *** (1.84) * Quoted spread.752.663.3516 (t-stat) (9.12) *** (7.18) *** (1.41) Price inverse -.5858 -.5425.1426 (t-stat) (-6.1) *** (-5.37) *** (.84) MAD.626.138 -.175 (t-stat) (1.68) * (2.52) ** (-.28) N 612 612 612 Adj. R 2.4296.3488.1176 18
Determinants of change in illiquidity The effect of insider trading on Quoted Spread and Effective Spread can be better explained than the effect on Price Impact The larger the average turnover, the larger the effect of insider trading on liquidity Stocks with larger level of bid-ask spread have larger effect of insider trading on their liquidity High price stocks have lower effect of insider trading on liquidity No evidence that the Market Abuse Decree decreased the effect of insider trading on liquidity Anomaly: Insiders have a larger effect of Medium size firms than on small of large firms 19
Summary and Conclusion There are signs that average liquidity of stocks is related to the intensity of insider trading (not statistically significant) Stock market liquidity does change when insiders trade Some firms have a larger change in liquidity when insiders trade The determinants are size, average volume, price level, bidask spread level Market Abuse Directive: We did not find a reduction of the effect of insider trading on market liquidity due to MAD 2
.1 Extra slide Graphs of Abnormal illiquidity before (left) and after (right) MAD- Small firms Quoted Spread (N=38) Quoted Spread (N=115).5 -.1 -.5.1 Effective Spread (N=38).1 Effective Spread (N=115) -.1 -.2 -.1.2 Price Impact (N=38).2 Price Impact (N=115) -.2 -.2 21
Quoted Spread (N=86) Extra slide 2 Graphs of Abnormal illiquidity before (left) and after (right) MAD- Medium firms Quoted Spread (N=95).5 -.5 -.1 -.5.1 Effective Spread (N=86).2 Effective Spread (N=95) -.2 -.1 -.4.5 Price Impact (N=86).5 Price Impact (N=95) -.5 -.5 22
.2 Quoted Spread (N=76) Extra slide 3 Graphs of Abnormal illiquidity before (left) and after (right) MAD- Large firms Quoted Spread (N=14).4.1.2 -.2.2 Effective Spread (N=76).5 Effective Spread (N=14).1 -.5.2 Price Impact (N=76).1 Price Impact (N=14) -.2 -.1 23