Informed Options Trading prior to M&A Announcements: Insider …cfe.columbia.edu/files/seasieor/center-financial-engineering/... · Research Design ü Options trading before M&As

Informed Options Trading prior to M&A Announcements:Insider Trading?

Patrick Augustin · McGill University-Desautels Faculty of ManagementMenachem Brenner · New York University-Leonard N. Stern School of BusinessMarti G. Subrahmanyam · New York University-Leonard N. Stern School of Business

Columbia University/Bloomberg Machine Learning in Finance Workshop

New York · March 6, 2015

Motivation

I Unusual Options Trades before M&As

ü 14Feb2013: H.J. Heinz by Berkshire Hathaway and 3G CapitalX Market Price 13 Feb: $60.48.X Purchase of 2,533 Jun $65 OTM calls (13 Feb).X Offer Price 14 Feb: $72.50.X Total Profit: $1.8 million.

ü 14Jan2004: Bank One Corp. by JP MorganX Market Price 14 Jan: $45.X Purchase 2,750 Jan $47.5 OTM calls (14 Jan, 1h before announcement).X Offer Price 14 Jan: $51.77.X Total Profit: $0.825 million.

More Insider Trading Cases

I Are these isolated cases?

I Are there many cases that go undetected?

Marti G. Subrahmanyam Informed Options Trading prior to M&A Announcements: Insider Trading? 2 / 50

A Striking Example: NEXEN Takeover by CNOOC

Unusual Trading Volume

Deal Announcement: 23 July

20 July

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Total Daily Options Trading Volume in Nexen Takeover Bid

SEC reacted because of suspicious stock trading!


Why do we care?

I SEC Enforcement Program for Insider Trading: a high priority area for the SEC.

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FY2004 FY2005 FY2006 FY2007 FY2008 FY2009 FY2010 FY2011 FY2012 FY2013

Total SEC Enforcement Actions Options and M&A Enforcement Actions

I We focus on insider trading in options ahead of M&As≈ 5 cases per year on average (1995-2013).

SEC Statement Definition of Insider Trading


Outline

I Motivation

I Research Question and Hypotheses

I Data

I Empirical Analysis

I Informed vs. Insider Trading

I SEC Litigation Reports

I Acquirer

I Conclusion


Research Question

1. Can we identify and quantify unusual options trading prior to M&As?

ü Random noise or systematic evidence of informed trading in the options market.

2. If yes, where and how do informed investors trade options?

ü Systematic patterns?

ü We focus on trading strategies that someone with private information could exploit toearn abnormal returns as well as the associated effects for prices and liquidity.

ü Forensic Analysis along 3 dimensions.

X VolumeX PricesX Liquidity

3. How does unusual options activity relate to the characteristics of SEC litigations.


Research Design

ü Options trading before M&As is a useful laboratory to study informed trading.

1. M&As are the closest we can get to unexpected corporate announcements.

X Jump in price of Target (31% premium, 16% abnormal return, on average) andvolatility of Acquirer.

X Assumption: Informed traders are capital constrained.X Pre-event activity should be similar to that on random dates.

2. M&As occur frequently enough to construct a meaningful sample.

3. Nature of private information is clearly identified.

X Rise in target’s stock price and flat acquirer stock price.

X We can formulate clear hypotheses to accept or refute pervasive informed trading.

X Target (directional) & Acquirer (Volatility).

4. Rich options data allows for the formulation of hypotheses along multiple dimensions.

X Multiple strike prices.

X Multiple expiration dates.


Hypotheses ... before M&A announcements ...

ü Targets

1. Abnormal trading volume in equity options.

2. Higher ratio of the abnormal trading volume in

(a) OTM call options compared to ATM and ITM call options.(b) ITM put options compared to ATM and OTM put options.

(c) Short-dated “front” options compared to long-dated options. Trading Strategies

3. Excess Implied Volatility.

4. Increase in %Bid-Ask Spread.

5. Increase of the (right) skewness of the option smile/skew.

6. Decrease of the term structure of implied volatility.

ü Acquirers

7. Volume increase in “jump-based” (long-gamma) trading strategies.

(a) Stronger effects for CASH deals.


Literature Literature Details

I Insider Trading (IT) (other than by corporate insiders/EDGAR filings)

ü Literature debates whether unusual options activity is random noise...X Poteshman (JB2006).

ü ...or focuses primarily on stocks...X Keown and Pinkerton (JF1981), Meulbroek (JF1992), Frino et al. (IRF2013).

ü ...or options around other events: 9/11, LBOs, specific companies...X Poteshman (JB2006), Acharya and Johnson (JFE2010), Chesney et al. (WP2011).

ü ...or is limited in the depth and scope of the analysis.X Wang (JEB2013).

I Informed Trading in Options around M&A

ü Literature focuses on information content of volume or prices for future stockreturns/CARs around M&As, focusing on either the target or the acquirer.

X Cao et al. (JB 2005), Chan et al. (JFQA 2013).

ü ...or investigates the predictive power of volume/price measures for stock returns.X Hu (JFE 2013), Jin et al. (JAR 2012), Johnson and So (JFE 2011), Pan and Poteshman (RFS 2006) ...

I Our Contribution

ü We document statistical anomalies consistent with trading by informed investors.X Unusual, pervasive and non-random options activity before M&A announcements.

ü We conduct a forensic analysis of options activity ahead of M&A announcements.X Volume, Prices, Liquidity (IV, Term Structure, Skewness).

ü We quantify randomness of unusual trading.ü We relate characteristics of unusual trading to SEC litigation reports.ü We distinguish between informed vs. insider trading.


Data - 1,859 M&A Deals from Jan 1996 to Dec 2012

1. Thomson Reuters SDC Platinum (U.S. M&As)

X Data filters used:ü Acquirer seeks to own ≥ 50% ex-post, owns ≤ 50% ex-ante.ü Exclude pending & unknown status deals.ü Deal Value ≥ $1 million (exclude small deals).

2. CRSP

ü Minimum of 90 days of stock price/volume info. for target.ü Keep data up to one year before and after the event.

3. OptionMetrics

ü Jan. 1996 - Dec. 2012 = Sample Period.ü Minimum of 90 days of option price/volume info. for target.ü All options that expire after (before) the Announcement Date (iff they are ATM).ü Keep data up to one year before and after the event.

4. SEC Civil Litigation Reports (and DoJ Criminal Litigation Reports, under revision)

ü All civil (criminal) litigations involving options trading and M&As.ü Information hand collected from SEC (DoJ) web site.

5. RavenPack News Analytics

ü Global News Database used in quantitative and algorithmic trading.ü Examines over 19,000 traditional and social media sites, from Jan. 2000 - Aug. 2012

6. Thomson Reuters Insider Filings

ü Table 2: Derivative transactions and holdings by “corporate insiders”.ü Examine transactions filed on Form 4 over 365 days before the announcements.

7. COMPUSTAT

ü Detailed balance sheet used to construct propensity-matched control samples.


Sample Characteristics

ü 1859 M&As, 1279 unique acquirers, 1669 unique targets.ü Subsample of 792: option information on targets only.

Panel A: Deal Information

Offer Structure Cash Only Shares · · · Total

Description No. % of Tot. No. % of Tot. · · · No. % of Tot.

Nbr. of Deals 903 48.6% 403 21.7% · · · 1,859 100.0%

Completed Deals 746 40.1% 339 18.2% · · · 1,542 82.9%

Hostile Deals 35 1.9% 7 0.4% · · · 63 3.4%

Same Industry Deals 379 42.0% 268 66.5% · · · 993 53.4%

Challenged Deals 111 6.0% 32 1.7% · · · 216 11.6%

Competing Bidder 83 4.5% 20 1.1% · · · 142 7.6%

Collar Deal 4 0.2% 52 2.8% · · · 120 6.5%

Termination Fee 698 37.5% 292 15.7% · · · 1,422 76.5%

Bidder has a toehold 42 2.3% 7 0.4% · · · 65 3.5%

Panel B: Deal Financials


Description Mean Sd Mean Sd Mean Sd

DVal (mil) $2,242.0 $4,147.2 $5,429.8 $15,158.5 · · · $3,848.4 $9,401.3

P1d 33.6% 31.7% 28.3% 39.5% · · · 31.0% 33.1%

P1w 36.6% 31.0% 33.6% 61.5% · · · 34.7% 39.8%

P4w 41.1% 35.6% 36.7% 45.3% · · · 38.3% 37.7%

ü Cash deals - acquisition price is clear.ü Average Deal Size is $3.8 billion. Cash deals typically smaller. Deal Size Distribution

ü Average 1-day Offer Premium is 31%.







Nbr. of Deals 903 48.6% 403 21.7% · · · 1,859 100.0%

Completed Deals 746 40.1% 339 18.2% · · · 1,542 82.9%

Hostile Deals 35 1.9% 7 0.4% · · · 63 3.4%




Collar Deal 4 0.2% 52 2.8% · · · 120 6.5%

Termination Fee 698 37.5% 292 15.7% · · · 1,422 76.5%





DVal (mil) $2,242.0 $4,147.2 $5,429.8 $15,158.5 · · · $3,848.4 $9,401.3

P1d 33.6% 31.7% 28.3% 39.5% · · · 31.0% 33.1%

P1w 36.6% 31.0% 33.6% 61.5% · · · 34.7% 39.8%

P4w 41.1% 35.6% 36.7% 45.3% · · · 38.3% 37.7%









Nbr. of Deals 903 48.6% 403 21.7% · · · 1,859 100.0%

Completed Deals 746 40.1% 339 18.2% · · · 1,542 82.9%

Hostile Deals 35 1.9% 7 0.4% · · · 63 3.4%




Collar Deal 4 0.2% 52 2.8% · · · 120 6.5%

Termination Fee 698 37.5% 292 15.7% · · · 1,422 76.5%





DVal (mil) $2,242.0 $4,147.2 $5,429.8 $15,158.5 · · · $3,848.4 $9,401.3

P1d 33.6% 31.7% 28.3% 39.5% · · · 31.0% 33.1%

P1w 36.6% 31.0% 33.6% 61.5% · · · 34.7% 39.8%

P4w 41.1% 35.6% 36.7% 45.3% · · · 38.3% 37.7%









Nbr. of Deals 903 48.6% 403 21.7% · · · 1,859 100.0%

Completed Deals 746 40.1% 339 18.2% · · · 1,542 82.9%

Hostile Deals 35 1.9% 7 0.4% · · · 63 3.4%




Collar Deal 4 0.2% 52 2.8% · · · 120 6.5%

Termination Fee 698 37.5% 292 15.7% · · · 1,422 76.5%





DVal (mil) $2,242.0 $4,147.2 $5,429.8 $15,158.5 · · · $3,848.4 $9,401.3

P1d 33.6% 31.7% 28.3% 39.5% · · · 31.0% 33.1%

P1w 36.6% 31.0% 33.6% 61.5% · · · 34.7% 39.8%

P4w 41.1% 35.6% 36.7% 45.3% · · · 38.3% 37.7%




Options Trading Volume


Options Trading Target - Summary Statistics

ü Higher Trading Volume in short-term and medium-term options.

ü Higher Trading Volume in OTM and ITM options.

ü Contrary to the usual pattern of ATM dominance in volume.

Target (N = 2,214,260)

DITM Mean SD Min Med p75 p90 Max

Panel A: All options, TTE = [0,30]

DOTM (3%) 246 1,973 1 20 76 300 94,177

OTM (5%) 370 1,990 1 41 164 596 88,086

ATM (79%) 273 1,291 1 40 152 531 231,204

ITM (5%) 356 6,214 1 20 80 333 539,482

DITM (5%) 275 3,264 1 10 40 171 200,000

Total (100%) 283 2,135 1 35 138 500 539,482

Panel B: All options, TTE = ]30,60]

DOTM (6%) 163 863 1 20 63 229 29,045

OTM (9%) 285 1,201 1 32 128 500 55,222

ATM (71%) 184 855 1 25 95 328 71,822

ITM (6%) 190 3,244 1 20 65 254 475,513

DITM (6%) 208 5,288 1 10 37 137 523,053

Total (100%) 194 1,787 1 23 90 316 523,053

Acquirer Statistics


Abnormal Trading Volume - Event Study

I Event Study over the 30 days preceding M&A announcements.

I ≈ 26% of deals have abnormal volume in calls.

I ≈ 15% of deals have abnormal volume in puts.

I Abnormal volume higher for OTM calls.

I Abnormal volume for ITM Puts? - Weaker evidence.

I Abnormal volume greater for CASH than for STOCK deals. Figure Cash vs. Stock

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I Event Study over the 30 days preceding M&A announcements.

I ≈ 26% of deals have abnormal volume in calls.

I ≈ 15% of deals have abnormal volume in puts.

I Abnormal volume higher for OTM calls.

I Abnormal volume for ITM Puts? - Weaker evidence.

I Abnormal volume greater for CASH than for STOCK deals. Figure Cash vs. Stock


Abnormal Trading Volume - Robustness Tests

1. Different Models to predict normal returns.I Constant Mean Model, Market Model – Mean, Market Model – Median, Market Model

for Volume (MMV), Market Model for Volume with Lags (MMV-L).I Test based on raw volumes and natural log transformations.

2. Multivariate Kolmogorov-Smirnov Test. KS-Test

I Formal statistical Test of a shift in the bivariate Volume-Moneyness Distribution.I Shift stronger for short-dated options (≤ 30 days).I Shift stronger for call options.

3. Identifying the most egregious cases: Strongly Unusual Trading (SUT). SUT Analysis

ü Compare abnormal trading in SUT against Random Sample (RS).

X Zero Bid, Positive Volume, Expiration after Announcement Date, Trades within 30 daysbefore the Announcement, Front Date Option (First Expiration Month).

ü SUT Volume double than that of a matched random sample.

ü Chance that average volume in RS is larger: ≈ 3 in a trillion

4. Equity options are illiquid, there is low volume - exploit zero-volume observations.

ü Chance ≥ 1 in a million that # with positive volumes greater in pseudo-sample.

ü Zero Volume Runs


Characteristics of abnormal Volume

CABVOL = β0 + β1SIZE + β2CASH + β3TOE + β4PRIVATE + β5COLLAR

+ β6TERM + β7FRIENDLY + β8US + γt + ε,

I Call Cumulative Abnormal Volume higher for:

I (Large) deals, with higher SalesI Cash dealsI Collar deals & Termination Fee (More price certainty?)

I Put options:

I Weaker evidence.


Excess Implied Volatility - Event Study

I Event Study over the 30 days preceding M&A announcts.

I ATM (|∆ = 50|) ≈ 44% (43%) of deals have EIV in calls (puts) at 5% sign.

I ITM (|∆ = 80|) ≈ 39% (41%) of deals have EIV in calls (puts) at 5% sign.

I OTM (|∆ = 20|) ≈ 43% (36%) of deals have EIV in calls (puts) at 5% sign.I Frequency of Deals with EIV:

X higher for ATM/OTM calls than for ITM calls.

X higher for OTM calls than for OTM puts.

X lower for ITM calls than for ITM puts.

X higher for OTM calls than for ITM puts.

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Average Excess Implied Volatility


Liquidity - Bid-Ask Spreads

I % B-A for targets widens from 35% to 55% before M&As.

I Effect stronger for (and restricted to) OTM and DOTM.

I Effect stronger for short-dated options.

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I No such effects on randomized pseudo-event dates.

Results for IV Smile


Liquidity - Term Structure

I Short-dated Calls/Puts become more expensive than Long-Dated Calls/Puts.

ü Slope Effect in the IV.

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IV-Term Calls (Mean) IV-Term Calls Random (Mean)IV-Term Puts (Mean) IV-Term Puts Random (Mean)

IV-Term Structure (91day - 30day options)

I No such effects on randomized pseudo-event dates.


Investor Ability to Predict Takeovers?

Prob (M&A = 1) = 11+exp(−α−X β)

I Low takeover propensity scores.

I Weak explanatory power: ps.R2(%).

I Difficult to predict:

I Occurrence of Takeover.I Timing of Takeover.

Model (1) (2) (3)

Ln Assets 0.15*** 0.14*** 0.22***

WAVE 0.22*** 0.22*** 0.21***

BLOCK 0.44*** 0.43*** 0.39***

Leverage -0.10*** -0.03 -0.11***

Log Volume 0.07*** 0.07*** 0.08***

Option1 -0.78*** -0.77*** -0.70***

DivYield2 -0.05***

PPENT ratio -0.11

ROA 0.19*** 0.14***

ROE -0.02 -0.03

CumRet -0.00

RE ratio 0.10***

Q 0.00*

MarketEquity -0.00***

Ln Employees -0.03**

EPS -0.03*** -0.02***

CAPEX ratio 0.19

Constant -6.44*** -6.20*** -5.21***

Observations 121,696 119,664 101,306

LL -19,884 -19,643 -16,241

ps.R2(%) 4.35 4.46 4.70

M&A(#) 4,978 4,933 4,061

M&A(%) 4.09 4.12 4.01

M&A in sample(%) 72.83 72.46 67.78


Speculation?

I Merger waves cluster across industries and in time.

I This may give rise to speculative trading in similar firms.

I Compare options volume in treatment and propensity-matched control group.

I Abnormal options statistically greater in treatment than in control group.


News and Rumors?

I RavenPack News Analytics: Identify news and rumors from major newspapers,regulatory/publication relation feeds, social media sites.

I News and rumors exist for only 9% of all deals in the sample.

I Are rumors driving our results?

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I No statistical difference in abnormal options volume between the two samples!


Legal Insider Trading?

I We examine Table 2 of the Thomson Reuters insider filings: derivativetransactions.

I SEC imposes legal requirement on registered corporate insiders (CEO, CFO, majorstakeholders ...) to report all transactions in their company’s stocks and theirderivatives.

I Result: Not a single transaction, purchase or sale, of a derivative security in the 30days before the announcement.

I We document unusual options activity – trades not initiated by legal insiders.

I Registered insiders who trade, but fail to report? – Highly unlikely as great risk ofinvestigation by the SEC.

I Could the unusual trades arise from tippees, tipped by the legal insiders? – Possibly.


Leakage and Trading in Stocks?

I Does leakage lead to insider trading in stocks?

I Abnormal volume robust to contemporaneous and lagged stock returns.

I Only 7% of all deals in the sample have abnormal stock returns in the 30 daysbefore the announcement.

I Cumulative abnormal option volumes greater than cumulative abnormal stockvolumes.

I Marked rise in call-to-stock volume ratio, in particular in the right tail of thedistribution.

I Modest rise in call-to-put volume ratio.


Bottom Line?

I Pervasive abnormal options activity before M&A announcts: ≈ 25% of sample.

I This is indicative of illicit activity ... but cannot be explained by:

1. Ability to predict mergers.2. Speculation.3. News and Rumors.4. Derivative trades by registered insiders.5. Leakage and trading in stocks.

I Legal Insiders: ×I Illegal Insiders: Perhaps.I Legal Outsiders: : ×I Illegal Outsiders : X


SEC Civil Litigation Reports

Characteristics of SEC Cases (Yearly Averages)

Year SEC LRs ABS Sample Illicit Profits Days to Lit. Moneyness S/K Option Mat. Days to Ann.

96-12 6 109 1,567,976 756 0.94 1 16

ü SEC Characteristics consistent with our findings: Abnormal volume in short-datedOTM call options within 30 days before announcement. Statistics by Year

ü Probability of SEC litigation larger for

I Completed deals.

I Larger deals: size, sales, offer price

I Firms with higher post-announcement abnormal returns.

I Foreign bidders.

ü Overall, abnormal volume much more pervasive than what is suggested by thenumber of SEC litigations: ≈ 5% of our sample.


SEC Litigation Reports

Pr (SEC = 1) = F (β0 + β1SIZE + β2CASH + β3TOE + β4PRIVATE

+β5COLLAR + β6TERM + β7FRIENDLY + β8US + γt ) ,

ü Probability of SEC litigation larger for

I Completed deals.I Larger deals: size, sales, offer price.

I Firms with higher post-announcement abnormal returns.

I Foreign bidders.

ü Endogeneity issue

I Is SEC more likely to investigate large deals?

I Are large deals more susceptible of insider trading because of options are more liquid?

I We don’t know!

ü Overal, abnormal volume much more pervasive than what is suggested by thenumber of SEC litigations.


Evidence on the Acquirer

ü Directional Strategies for Targets, but Volatility Strategies for Acquirers.

ü Increase in ATM options Volume, straddle strategies for example.

ü Increase in the number of ATM strike-matched put-call pairs

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How Random is ATM Volume?

I We test the likelihood of unusual trading using ATM volume (for acquirer).

I Compare SUT-A sample vs. Random Sample.

1. ATM options

2. Positive Volume

3. Expiration after Announcement Date

4. Trades within 30 days before the Announcement5. Front Date Option

ü Chance of 6 in a billion that average volume in the pseudo-sample is larger.

Panel A: SUT Selection with the historical 792 event dates for the acquirer

Acquirer

Obs # Deals # Options Mean Vol Med Vol 25th pctile 75th pctile 95th pctile 99th pctile

All 5,343 235 1,035 1045.85 202 35 1,020 4,783 10,927

Calls 2,860 228 534 1257.00 244 38 1,276 5,465 12,110

Puts 2,483 223 501 802.65 163 32 774 3,858 7,939

Panel B: 1 random sample of 792 pseudo event dates for the acquirer

Acquirer


All 2,258 127 479 657.79 145 30 584 2,925 7,749

Calls 1,206 120 244 758.42 198 35 700 3,263 9,215

Puts 1,052 119 235 542.42 110 25 469 2,434 5,903

Panel C: Tests for Statistical Significance between SUT and Random Samples

Target

KS (two-sided) KS (one-sided) T-test (Mean) T-test (Mean)

H0: SUT=RS SUT≤ RS SUT=RS SUT≤ RS

Statistic D D t t

Value 0.09 0.09 -5.72 -5.72

p-val 2.69e-11 1.34e-11 1.12e-08 5.61e-09





1. ATM options

2. Positive Volume





Acquirer


All 5,343 235 1,035 1045.85 202 35 1,020 4,783 10,927

Calls 2,860 228 534 1257.00 244 38 1,276 5,465 12,110

Puts 2,483 223 501 802.65 163 32 774 3,858 7,939


Acquirer


All 2,258 127 479 657.79 145 30 584 2,925 7,749

Calls 1,206 120 244 758.42 198 35 700 3,263 9,215

Puts 1,052 119 235 542.42 110 25 469 2,434 5,903


Target



Statistic D D t t

Value 0.09 0.09 -5.72 -5.72

p-val 2.69e-11 1.34e-11 1.12e-08 5.61e-09





1. ATM options

2. Positive Volume





Acquirer


All 5,343 235 1,035 1045.85 202 35 1,020 4,783 10,927

Calls 2,860 228 534 1257.00 244 38 1,276 5,465 12,110

Puts 2,483 223 501 802.65 163 32 774 3,858 7,939


Acquirer


All 2,258 127 479 657.79 145 30 584 2,925 7,749

Calls 1,206 120 244 758.42 198 35 700 3,263 9,215

Puts 1,052 119 235 542.42 110 25 469 2,434 5,903


Target



Statistic D D t t

Value 0.09 0.09 -5.72 -5.72

p-val 2.69e-11 1.34e-11 1.12e-08 5.61e-09





1. ATM options

2. Positive Volume





Acquirer


All 5,343 235 1,035 1045.85 202 35 1,020 4,783 10,927

Calls 2,860 228 534 1257.00 244 38 1,276 5,465 12,110

Puts 2,483 223 501 802.65 163 32 774 3,858 7,939


Acquirer


All 2,258 127 479 657.79 145 30 584 2,925 7,749

Calls 1,206 120 244 758.42 198 35 700 3,263 9,215

Puts 1,052 119 235 542.42 110 25 469 2,434 5,903


Target



Statistic D D t t

Value 0.09 0.09 -5.72 -5.72

p-val 2.69e-11 1.34e-11 1.12e-08 5.61e-09





1. ATM options

2. Positive Volume





Acquirer


All 5,343 235 1,035 1045.85 202 35 1,020 4,783 10,927

Calls 2,860 228 534 1257.00 244 38 1,276 5,465 12,110

Puts 2,483 223 501 802.65 163 32 774 3,858 7,939


Acquirer


All 2,258 127 479 657.79 145 30 584 2,925 7,749

Calls 1,206 120 244 758.42 198 35 700 3,263 9,215

Puts 1,052 119 235 542.42 110 25 469 2,434 5,903


Target



Statistic D D t t

Value 0.09 0.09 -5.72 -5.72

p-val 2.69e-11 1.34e-11 1.12e-08 5.61e-09





1. ATM options

2. Positive Volume





Acquirer


All 5,343 235 1,035 1045.85 202 35 1,020 4,783 10,927

Calls 2,860 228 534 1257.00 244 38 1,276 5,465 12,110

Puts 2,483 223 501 802.65 163 32 774 3,858 7,939


Acquirer


All 2,258 127 479 657.79 145 30 584 2,925 7,749

Calls 1,206 120 244 758.42 198 35 700 3,263 9,215

Puts 1,052 119 235 542.42 110 25 469 2,434 5,903


Target



Statistic D D t t

Value 0.09 0.09 -5.72 -5.72

p-val 2.69e-11 1.34e-11 1.12e-08 5.61e-09





1. ATM options

2. Positive Volume





Acquirer


All 5,343 235 1,035 1045.85 202 35 1,020 4,783 10,927

Calls 2,860 228 534 1257.00 244 38 1,276 5,465 12,110

Puts 2,483 223 501 802.65 163 32 774 3,858 7,939


Acquirer


All 2,258 127 479 657.79 145 30 584 2,925 7,749

Calls 1,206 120 244 758.42 198 35 700 3,263 9,215

Puts 1,052 119 235 542.42 110 25 469 2,434 5,903


Target



Statistic D D t t

Value 0.09 0.09 -5.72 -5.72

p-val 2.69e-11 1.34e-11 1.12e-08 5.61e-09


Summary of Results

1. Directional, abnormal and non-random volume in equity options for targets aheadof M&As.

ü Effects stronger for short-dated OTM call options.

ü We quantify the randomness of these statistical anomalies.

2. Excess Implied Volatility.

3. Liquidity Effects: Price Pressure on Calls

ü Widening of B-A Spreads (OTM).ü Decrease in IV-Term Structure.

4. Evidence consistent with characteristics prosecuted by the SEC, but unusual tradingvolume more pervasive compared to number of litigation reports by SEC.

5. Preliminary evidence on acquirer: based on volatility trading.


Take-aways!

Conclusion

Our findings provide evidence of pervasive statistical anomalies consistent withinvestors trading on private information ahead of M&As.Evidence too strong to be dismissed as speculative noise.

1. Regulators

I Benefits from dedicating more scrutiny to the options market for detecting roguetrading.

I Development of forensic analytics for detection of suspicious trading .

2. Corporate America

I Corporate governance problem of leaking information. Needs to be addressed.

I Obtain trading ids for large suspicious trades prior to corporate announcements.

3. Investors

I Are financial markets fair - Level Playing Field?I Traders/Investors: Watch out for unusual options activity!


A Smoking Gun?

Thank you


More Suspicious Options Trades

I Unusual options trades before M&As1

ü 29May2013: Smithfield Foods by ShuanghuiX 1,300 Jul $29 OTM calls (21 May) + 1,700 Jul $30 OTM calls (28 May).X Offer Price: $34; Price 28 May: $25.97; Total Profit: $3.2 million.

ü 21Dec2010: Martek by DSMX 2,615 $27 OTM calls (10 Dec).X Offer Price: $31.5; Price 20 Dec: $23.36; Total Profit: $1.2 million.

ü 27Sep2010: AirTran by Southwest AirlinesX 200 Jan calls (22 Sep).X Offer Price: $7.69; Price 22 Sep: $4.39; Total Profit: $0.159 million.

ü 2Sep2010: Burger King by 3G CapitalX 300 July $20 ATM calls (17 May) + 2,850 Jul $22.5 OTM calls (18-19 May) + 2,000 Jul $20 ATM calls

(2-17 Jun) + 1,400 Oct $17.5 OTM calls + 206 Oct $19 OTM calls (19 Aug) + 100 Jan $20 OTM calls(25 Aug) + 1,794 Oct $19 OTM calls (26-27 Aug).

X Offer Price: $24; Price 1 Sep: $18.86; Total Profit: $1.68 million.

ü 15Jan2004: Potash by BHP BillitonX 31 Aug $110 ITM calls + 50 Aug $115 OTM calls + 95 Aug $120 OTM calls + 22 Aug $125 OTM calls +

32 Aug $130 OTM calls (12 Aug) + 5 Aug $115 OTM calls + 12 Aug $120 OTM calls (13 Aug) + 50 Aug$130 OTM calls + 5 Sep $110 ATM calls + 5 Sep $115 OTM calls + 5 Sep $120 OTM calls (16 Aug) +331 Sep $125 OTM calls (12-13 Aug).

X Offer Price: $130; Price 16 Aug: $110.57; Total Profit: $1.073 million.

ü Back to Motivation

1Source: http://www.sec.gov/spotlight/insidertrading/cases.shtml


Why do we care?

SEC Enforcement Actions: Insider Trading Cases

Insider trading continues to be a high priority area for the SEC’s enforcement program.The SEC brought 58 insider trading actions in FY 2012 against 131 individuals and entities.Over the last three years, the SEC has filed more insider trading actions (168 total)than in any three-year period in the agency’s history. These insider trading actions werefiled against nearly 400 individuals and entities with illicit profits or losses avoided totalingapproximately $600 million. Many of these actions involved financial professionals, hedgefund managers, corporate insiders, and attorneys who unlawfully traded on material non-public information, undermining the level playing field that is fundamental to the integrityand fair functioning of the capital markets.2


2https://www.sec.gov/spotlight/insidertrading/cases.shtml


SEC Definition of Insider Trading

Illegal insider trading refers generally to buying or selling a security, in breach of a fidu-ciary duty or other relationship of trust and confidence, while in possession of material,nonpublic information about the security. Insider trading violations may also include “tip-ping” such information, securities trading by the person “tipped”, and securities tradingby those who misappropriate such information.3

ü Breach of fiduciary duty is key.

ü There is a fine line between legal or illegal insider trading - we talk about statisticalanomalies.

ü Insider Trading can come from “registered” corporate insiders or outsiders.X We make no distinction in our statistical analysis: some of our cases could be by insiders who filed

SEC Forms 3 and 4, although unlikely.


3http://www.sec.gov/spotlight/insidertrading.shtml


Options Strategies

ü An informed trader expects an increase in the target’s stock price and benefits from:

1. Long Bullish Strategies (+ replications)

2. Short Bearish Strategies (+ replications)

ü Strategies

1. Long OTM Call K1 (Replication: Long ITM Put K1 + Long Stock)2. Long Call Ratio Backspread (Short OTM Call K1, Long 2 OTM Calls K2 > K1)

I Replication example: Short ITM Put K1, Short Stock, Buy 2 OTM Calls K2 > K1

3. Long Bull Call Spread (Long OTM Call K1, Short OTM Call K2 > K1)I Replication example: Long OTM Call K1, Short ITM Put K2 > K1, Short Stock

4. Long Bull Put Spread (Long ITM Put K1, Short ITM Put K2 > K1)I Replication example: Long ITM Put K1, Short OTM Call K2 > K1, Long Stock

5. Short ITM Put K1 (Short OTM Call K1 + Long Stock = Covered Call)6. Short Put Ratio Backspread (Short 2 ITM Puts K1, Long ITM Put K2 > K1)

I Replication example: Short 2 ITM Puts K1, Long OTM Call K2 > K1, Long Stock

7. Short Bear Call Spread (Long OTM Call K1, Short OTM Call K2 > K1)

8. Short Bear Put Spread (Long ITM Put K1, Short ITM Put K2 > K1)

ü Conclusion: Any strategy leads to abnormal volume in OTM calls/ITM puts.

1. Could be buys or sells. ü Back to Hypotheses

2. OptionMetrics reports non-signed aggregate volume, so ok.

3. Increase in Call/Stock and Call/Put Volume, but “flat” Put/Stock Volume.


Literature

I Insider Trading (IT) (other than by corporate insiders/EDGAR filings)ü Keown and Pinkerton (JF1981): focus on excess stock returns around M&As.ü Meulbroek (JF1992): investigates SEC prosecuted cases, focus on stocks.ü Poteshman (JB2006): unusal put volume trading before 9/11 attack.ü Acharya and Johnson (JFE2010): More insiders (syndicate) in LBOs, more IT.ü Chesney et al. (WP2011): Develop statistical tools for the detection of IT.ü Frino et al. (IRF2013): Determinants of illegal IT in stocks based on SEC litigations.ü Wang (JEB2013): Abnormal volume predicts SEC litigations.

I Informed Trading in options around M&Aü Cao et al. (JB 2005): Targets - call volume imbalance predicts future stock returns prior to

announcements.ü Chan et al. (JFQA 2013): Acquirers - IV spread (IV skew) positively (negatively) predicts CARs.ü Barraclough et al. (RFS 2012): Use options to measure synergies in M&As.ü Spyrou et al. (JFM 2011): UK evidence for abnormal volume before M&As.ü Podolski et al. (JIFMIM 2013): Regulation affects quantity of informed trading.

I Other literature ü Back to Presentation

X Where do insiders trade?ü Easley et al. (JF1998), John et al. (WP2003), Cao and Ou-Yang (RFS2009), ...

X Informational Content of Option Volume/Price for Stock Returns.ü Hu (JFE 2013), Jin et al. (JAR 2012), Driessen et al. (WP 2012), Johnson and So (JFE

2011), Pan and Poteshman (RFS 2006) ...X Price Pressure in options

ü Bollen and Whaley (JF2004) and Garleanu et al. (RFS2009)X Option Pricing Models around informational events

ü Bester et al. (WP2011), Subramanian (JF2004), Johannes (WP2006)


Deal Size Distribution

ü Largest Cash deal: InBev - Anheuser Busch (Jun 11, 2008)

ü Largest Hybrid deal: Pfizer - Wyeth (Jan 26, 2009)

ü Largest Other deal: Comcast - MediaOne (withdrawn, Mar 22, 1999)

ü Largest Stock deal: AOL - Time Warner (Jan 10, 2000)

ü Largest Unknown deal: Hilton Hotel - ITT (withdrawn, Jan 27, 1997)

Deal Transaction Value

Offer Structure Mean Min P1 P5 P25 P50 P75 P95 P99 Max N

Cash Only (48%) $2,242.0 $3.0 $58.8 $143.4 $417.0 $1,012.2 $2,247.4 $7,811.2 $25,065.2 $52,177.7 903

Hybrid (22%) $5,880.9 $34.5 $76.3 $234.1 $885.7 $2,433.9 $5,981.8 $25,818.3 $56,307.0 $67,285.7 415

Other (4%) $5,074.2 $24.4 $24.4 $158.7 $476.7 $1,326.5 $4,502.7 $26,459.1 $58,511.8 $58,511.8 80

Shares (21%) $5,429.8 $30.4 $57.7 $128.4 $424.5 $1,128.4 $3,169.5 $24,517.7 $75,563.2 $164,746.9 403

Unknown (3%) $1,635.7 $16.8 $16.8 $49.7 $250.0 $489.1 $2,318.7 $7,486.2 $13,608.4 $13,608.4 58

Total (100%) $3,848.4 $3.0 $48.2 $141.3 $468.7 $1,245.4 $3,270.3 $14,391.7 $53,414.6 $164,746.9 1,859

N≤pctile 1,460 1 18 92 464 930 1,396 1,766 1,841 1,859 -

ü Back to Sample Characteristics


Options Trading Acquirer - Summary Statistics

ü Trading Volume higher in Short-term and medium-dated options.

ü Higher Trading Volume in ATM options.

Acquirer (N = 3,582,394)

DITM Mean SD Min Med p75 p90 Max

Panel A: All options, TTE = [0,30]

DOTM (10%) 127 594 1 20 71 231 27,377

OTM (22%) 497 1,497 1 79 355 1,207 55,167

ATM (26%) 1,084 3,038 1 204 927 2,744 198,146

ITM (23%) 398 5,209 1 42 175 624 679,620

DITM (16%) 214 3,286 1 16 54 191 300,841

Total (100%) 547 3,361 1 52 279 1,146 679,620

Panel B: All options, TTE = ]30,60]

DOTM (14%) 141 838 1 20 76 245 95,000

OTM (27%) 384 1,388 1 69 269 830 94,552

ATM (25%) 551 1,666 1 101 425 1,299 90,497

ITM (20%) 236 3,488 1 30 108 367 458,019

DITM (12%) 334 12,543 1 11 40 133 1,609,002

Total (100%) 354 4,841 1 41 183 659 1,609,002

ü Back to Target Statistics



-100

00

1000

2000

Ave

rage

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000

1500

020

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Cash Stock


ü Back to Abnormal Trading Volume


Shifts in Option Trading Volume Density

I Formal statistical Test of a shift in the bivariate Volume-Moneyness Distribution:Multivariate Kolmogorov-Smirnov.

I Statistic measures the distance between empirical cumulative distribution functionsin 2 event windows [t1, t2].

I Shift stronger for short-dated options (≤ 30 days).

I Shift stronger for call options.


Shifts in Option Trading Volume Density...continued

050

100

150

Vol

ume

(# C

ontr

acts

) -

Pol

ynom

ial F

it

0 .5 1 1.5 2S/K

Full Sample ex-EW [-29,-25] [-24,-20] [-19,-15][-14,-10] [-9,-5] [-4,-1] [0,0]

Call Options - Target

ü Back to Empirical Analysis



050

100

150

Vol

ume

(# C

ontr

acts

) -

Pol

ynom

ial F

it

0 .5 1 1.5 2S/K

Full Sample ex-EW [-29,-25] [-24,-20] [-19,-15][-14,-10] [-9,-5] [-4,-1] [0,0]





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150

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ume

(# C

ontr

acts

) -

Pol

ynom

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Full Sample ex-EW [-29,-25] [-24,-20] [-19,-15][-14,-10] [-9,-5] [-4,-1] [0,0]





050

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acts

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Pol

ynom

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Full Sample ex-EW [-29,-25] [-24,-20] [-19,-15][-14,-10] [-9,-5] [-4,-1] [0,0]





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(# C

ontr

acts

) -

Pol

ynom

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Full Sample ex-EW [-29,-25] [-24,-20] [-19,-15][-14,-10] [-9,-5] [-4,-1] [0,0]





050

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ume

(# C

ontr

acts

) -

Pol

ynom

ial F

it

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Full Sample ex-EW [-29,-25] [-24,-20] [-19,-15][-14,-10] [-9,-5] [-4,-1] [0,0]





050

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ume

(# C

ontr

acts

) -

Pol

ynom

ial F

it

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Full Sample ex-EW [-29,-25] [-24,-20] [-19,-15][-14,-10] [-9,-5] [-4,-1] [0,0]





050

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ume

(# C

ontr

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ynom

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Full Sample ex-EW [-29,-25] [-24,-20] [-19,-15][-14,-10] [-9,-5] [-4,-1] [0,0]





020

4060

8010

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e (#

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- P

olyn

omia

l Fit

0 .5 1 1.5 2S/K

Full Sample ex-EW [-29,-25] [-24,-20] [-19,-15][-14,-10] [-9,-5] [-4,-1] [0,0]

Put Options - Target




020

4060

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e (#

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- P

olyn

omia

l Fit

0 .5 1 1.5 2S/K

Full Sample ex-EW [-29,-25] [-24,-20] [-19,-15][-14,-10] [-9,-5] [-4,-1] [0,0]





020

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8010

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olyn

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0 .5 1 1.5 2S/K

Full Sample ex-EW [-29,-25] [-24,-20] [-19,-15][-14,-10] [-9,-5] [-4,-1] [0,0]





020

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Full Sample ex-EW [-29,-25] [-24,-20] [-19,-15][-14,-10] [-9,-5] [-4,-1] [0,0]





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Full Sample ex-EW [-29,-25] [-24,-20] [-19,-15][-14,-10] [-9,-5] [-4,-1] [0,0]





020

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Full Sample ex-EW [-29,-25] [-24,-20] [-19,-15][-14,-10] [-9,-5] [-4,-1] [0,0]





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0 .5 1 1.5 2S/K

Full Sample ex-EW [-29,-25] [-24,-20] [-19,-15][-14,-10] [-9,-5] [-4,-1] [0,0]




Shift in Volume Distribution

I Rise in interquartile range and upper percentiles of the distribution.

5010

015

020

0In

terq

uart

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ange

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90th percentile 95th percentile Interquartile Range

Call Options Volume Distribution - Target

4060

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90th percentile 95th percentile Interquartile Range

Put Options Volume Distribution - Target



Bivariate Kolmogorov-Smirnov Test

I Non-parametric test for equality of 2 continuous distribution functions.

I KS statistic quantifies the distance between 2 empirical cumulative distributionfunctions (ECDFs).

I Fasano and Franceschini (FF) generalization of the two-sample bivariate KS test.

I Two samples {(x1j , y1

j

): 1 ≤ j ≤ n} and {

(x2j , y2

j

): 1 ≤ j ≤ m},

I with ECDFs H(k)n and H

(k)m for k = 1, 2, 3, 4.

H(1) (x , y) = P [X ≤ x ;Y ≤ y ] H(2) (x , y) = P [X ≤ x ;Y ≥ y ]

H(3) (x , y) = P [X ≥ x ;Y ≤ y ] H(4) (x , y) = P [X ≥ x ;Y ≥ y ]

I FF-statistic defined as

Zn,m = max{T (1)n,m,T

(2)n,m,T

(3)n,m,T

(4)n,m},

I where

T(k)n,m = sup(x ,y )∈R2

√nm

n+m

∣∣∣H(k)n (x , y)−H

(k)m (x , y)

∣∣∣Marti G. Subrahmanyam Informed Options Trading prior to M&A Announcements: Insider Trading? 45 / 50


Panel A: Calls

Full Sample

Event Window [−29,−25] [−24,−20] [−19,−15] [−14,−10] [−9,−5] [−4,−1] [0, 0]

[−29,−25] . 0.0279∗∗∗ 0.0482∗∗∗ 0.0616∗∗∗ 0.1007∗∗∗ 0.1592∗∗∗ 0.4070∗∗∗

[−24,−20] . . 0.0228∗∗∗ 0.0368∗∗∗ 0.0744∗∗∗ 0.1334∗∗∗ 0.3911∗∗∗

[−19,−15] . . . 0.0173∗∗ 0.0556∗∗∗ 0.1134∗∗∗ 0.3694∗∗∗

[−14,−10] . . . . 0.0410∗∗∗ 0.0988∗∗∗ 0.3581∗∗∗

[−9,−5] . . . . . 0.0606∗∗∗ 0.3256∗∗∗

[−4,−1] . . . . . . 0.2798∗∗∗

[0, 0] . . . . . . .

I Shift stronger for short-dated options (≤ 30 days).

I Shift stronger for call options.



Is Unusual Options Trading Volume Random?

I We test the likelihood of unusual trading using the most obvious cases.

I Compare SUT sample vs. Random Sample. ü Back to Empirical Analysis

1. Zero Bid

2. Positive Volume



ü Chance of 3 in a trillion that average volume in the pseudo-sample is larger.

Panel A: SUT Selection with the historical 1,859 event dates for the target - Zero Bid

Target


All 2,042 437 1,243 123.78 20 6 62 479 2,076

Calls 1,106 299 570 137.23 20 5 65 543 2,517

Puts 936 316 673 107.9 20 7.5 60 390 1,494

Panel B: 1 random sample of 1,859 pseudo event dates for the target

Target


All 3,412 574 1,901 57 10 5 32 200 813

Calls 1,813 351 941 64 11 5 40 232 893

Puts 1,599 387 960 49 10 5 30 182 759

Panel C: Tests for Statistical Significance between SUT and Random Samples with All Options

Target



Statistic D D t t

Value 0.12 0.12 -6.90 -6.90

p-val 2.80e-12 4.14e-17 5.99e-12 2.99e-12





1. Zero Bid

2. Positive Volume





Target


All 2,042 437 1,243 123.78 20 6 62 479 2,076

Calls 1,106 299 570 137.23 20 5 65 543 2,517

Puts 936 316 673 107.9 20 7.5 60 390 1,494


Target


All 3,412 574 1,901 57 10 5 32 200 813

Calls 1,813 351 941 64 11 5 40 232 893

Puts 1,599 387 960 49 10 5 30 182 759


Target



Statistic D D t t

Value 0.12 0.12 -6.90 -6.90

p-val 2.80e-12 4.14e-17 5.99e-12 2.99e-12





1. Zero Bid

2. Positive Volume





Target


All 2,042 437 1,243 123.78 20 6 62 479 2,076

Calls 1,106 299 570 137.23 20 5 65 543 2,517

Puts 936 316 673 107.9 20 7.5 60 390 1,494


Target


All 3,412 574 1,901 57 10 5 32 200 813

Calls 1,813 351 941 64 11 5 40 232 893

Puts 1,599 387 960 49 10 5 30 182 759


Target



Statistic D D t t

Value 0.12 0.12 -6.90 -6.90

p-val 2.80e-12 4.14e-17 5.99e-12 2.99e-12





1. Zero Bid

2. Positive Volume





Target


All 2,042 437 1,243 123.78 20 6 62 479 2,076

Calls 1,106 299 570 137.23 20 5 65 543 2,517

Puts 936 316 673 107.9 20 7.5 60 390 1,494


Target


All 3,412 574 1,901 57 10 5 32 200 813

Calls 1,813 351 941 64 11 5 40 232 893

Puts 1,599 387 960 49 10 5 30 182 759


Target



Statistic D D t t

Value 0.12 0.12 -6.90 -6.90

p-val 2.80e-12 4.14e-17 5.99e-12 2.99e-12





1. Zero Bid

2. Positive Volume





Target


All 2,042 437 1,243 123.78 20 6 62 479 2,076

Calls 1,106 299 570 137.23 20 5 65 543 2,517

Puts 936 316 673 107.9 20 7.5 60 390 1,494


Target


All 3,412 574 1,901 57 10 5 32 200 813

Calls 1,813 351 941 64 11 5 40 232 893

Puts 1,599 387 960 49 10 5 30 182 759


Target



Statistic D D t t

Value 0.12 0.12 -6.90 -6.90

p-val 2.80e-12 4.14e-17 5.99e-12 2.99e-12





1. Zero Bid

2. Positive Volume





Target


All 2,042 437 1,243 123.78 20 6 62 479 2,076

Calls 1,106 299 570 137.23 20 5 65 543 2,517

Puts 936 316 673 107.9 20 7.5 60 390 1,494


Target


All 3,412 574 1,901 57 10 5 32 200 813

Calls 1,813 351 941 64 11 5 40 232 893

Puts 1,599 387 960 49 10 5 30 182 759


Target



Statistic D D t t

Value 0.12 0.12 -6.90 -6.90

p-val 2.80e-12 4.14e-17 5.99e-12 2.99e-12





1. Zero Bid

2. Positive Volume





Target


All 2,042 437 1,243 123.78 20 6 62 479 2,076

Calls 1,106 299 570 137.23 20 5 65 543 2,517

Puts 936 316 673 107.9 20 7.5 60 390 1,494


Target


All 3,412 574 1,901 57 10 5 32 200 813

Calls 1,813 351 941 64 11 5 40 232 893

Puts 1,599 387 960 49 10 5 30 182 759


Target



Statistic D D t t

Value 0.12 0.12 -6.90 -6.90

p-val 2.80e-12 4.14e-17 5.99e-12 2.99e-12


Is Unusual Options Trading Volume Random? - 2

I Equity options are illiquid, there is low volume - exploit zero-volume observations


Empirical Analysis DOTM OTM ATM ITM DITM Full Sample

Panel B: Full Sample

N 3,411,873 1,428,467 2,380,397 1,428,286 3,412,545 12,061,568

P(Vt > 0) 0.1033 0.2581 0.3487 0.1584 0.0688 0.1668

P(Vt ≥ 1000) 0.0022 0.0076 0.0144 0.0034 0.0010 0.0050

Panel C: t ∈ [−5,−1] - Actual vs. Random

N 78,424 32,500 27,074 32,540 78,436 248,974

NRS 34,508 15,185 21,066 15,192 34,553 120,504

P(Vt > 0) Actual 0.1155 0.3681 0.4265 0.2408 0.0922 0.1913

Random 0.0982 0.2519 0.3239 0.1502 0.0695 0.1554

# SD away 11 33 32 31 17 34

P(Vt ≥ 1000) Actual 0.0038 0.0165 0.0260 0.0067 0.0023 0.0078

Random 0.0016 0.0052 0.0110 0.0024 0.0008 0.0036

# SD away 10 19 21 11 10 24

P(Vt > 0|∑5i=1 Vt−i = 0) Actual 0.0676 0.0799 0.0481 0.1004 0.0650 0.0705

Random 0.0568 0.0583 0.0371 0.0623 0.0485 0.0518

# SD away 9 11 8 19 14 29

P(Vt ≥ 1000|∑5i=1 Vt−i = 0) Actual 0.0021 0.0036 0.0025 0.0023 0.0017 0.0022

Random 0.0009 0.0014 0.0015 0.0011 0.0007 0.0010

# SD away 7 7 4 5 7 13







N 3,411,873 1,428,467 2,380,397 1,428,286 3,412,545 12,061,568

P(Vt > 0) 0.1033 0.2581 0.3487 0.1584 0.0688 0.1668

P(Vt ≥ 1000) 0.0022 0.0076 0.0144 0.0034 0.0010 0.0050


N 78,424 32,500 27,074 32,540 78,436 248,974

NRS 34,508 15,185 21,066 15,192 34,553 120,504

P(Vt > 0) Actual 0.1155 0.3681 0.4265 0.2408 0.0922 0.1913

Random 0.0982 0.2519 0.3239 0.1502 0.0695 0.1554

# SD away 11 33 32 31 17 34

P(Vt ≥ 1000) Actual 0.0038 0.0165 0.0260 0.0067 0.0023 0.0078

Random 0.0016 0.0052 0.0110 0.0024 0.0008 0.0036

# SD away 10 19 21 11 10 24

P(Vt > 0|∑5i=1 Vt−i = 0) Actual 0.0676 0.0799 0.0481 0.1004 0.0650 0.0705

Random 0.0568 0.0583 0.0371 0.0623 0.0485 0.0518

# SD away 9 11 8 19 14 29

P(Vt ≥ 1000|∑5i=1 Vt−i = 0) Actual 0.0021 0.0036 0.0025 0.0023 0.0017 0.0022

Random 0.0009 0.0014 0.0015 0.0011 0.0007 0.0010

# SD away 7 7 4 5 7 13







N 3,411,873 1,428,467 2,380,397 1,428,286 3,412,545 12,061,568

P(Vt > 0) 0.1033 0.2581 0.3487 0.1584 0.0688 0.1668

P(Vt ≥ 1000) 0.0022 0.0076 0.0144 0.0034 0.0010 0.0050


N 78,424 32,500 27,074 32,540 78,436 248,974

NRS 34,508 15,185 21,066 15,192 34,553 120,504

P(Vt > 0) Actual 0.1155 0.3681 0.4265 0.2408 0.0922 0.1913

Random 0.0982 0.2519 0.3239 0.1502 0.0695 0.1554

# SD away 11 33 32 31 17 34

P(Vt ≥ 1000) Actual 0.0038 0.0165 0.0260 0.0067 0.0023 0.0078

Random 0.0016 0.0052 0.0110 0.0024 0.0008 0.0036

# SD away 10 19 21 11 10 24

P(Vt > 0|∑5i=1 Vt−i = 0) Actual 0.0676 0.0799 0.0481 0.1004 0.0650 0.0705

Random 0.0568 0.0583 0.0371 0.0623 0.0485 0.0518

# SD away 9 11 8 19 14 29

P(Vt ≥ 1000|∑5i=1 Vt−i = 0) Actual 0.0021 0.0036 0.0025 0.0023 0.0017 0.0022

Random 0.0009 0.0014 0.0015 0.0011 0.0007 0.0010

# SD away 7 7 4 5 7 13







N 3,411,873 1,428,467 2,380,397 1,428,286 3,412,545 12,061,568

P(Vt > 0) 0.1033 0.2581 0.3487 0.1584 0.0688 0.1668

P(Vt ≥ 1000) 0.0022 0.0076 0.0144 0.0034 0.0010 0.0050


N 78,424 32,500 27,074 32,540 78,436 248,974

NRS 34,508 15,185 21,066 15,192 34,553 120,504

P(Vt > 0) Actual 0.1155 0.3681 0.4265 0.2408 0.0922 0.1913

Random 0.0982 0.2519 0.3239 0.1502 0.0695 0.1554

# SD away 11 33 32 31 17 34

P(Vt ≥ 1000) Actual 0.0038 0.0165 0.0260 0.0067 0.0023 0.0078

Random 0.0016 0.0052 0.0110 0.0024 0.0008 0.0036

# SD away 10 19 21 11 10 24

P(Vt > 0|∑5i=1 Vt−i = 0) Actual 0.0676 0.0799 0.0481 0.1004 0.0650 0.0705

Random 0.0568 0.0583 0.0371 0.0623 0.0485 0.0518

# SD away 9 11 8 19 14 29

P(Vt ≥ 1000|∑5i=1 Vt−i = 0) Actual 0.0021 0.0036 0.0025 0.0023 0.0017 0.0022

Random 0.0009 0.0014 0.0015 0.0011 0.0007 0.0010

# SD away 7 7 4 5 7 13


Liquidity - IV Skewness

I IV-Skew jumps on Announcement Date.

.012

.014

.016

.018

.02

IVp-

delta

80 -

IVp-

delta

50

.015

.02

.025

.03

.035

.04

IVc-

delta

20 -

IVc-

delta

50

0 5 10 15EWlabel

]...,-30] [-24,-20] [-14,-10] [-4,-1] [1,5] [11,15] [21,25] [31,...[Event Time

Call-Skew (Mean) Call-Skew Random (Mean)Put-Skew (Mean) Put-Skew Random (Mean)

IV-Skew (30-day options)

.04

.05

.06

.07

.08

.09

IVp-

delta

20 -

IVc-

delta

50

.01

.02

.03

.04

.05

.06

(IV

p-de

lta25

- IV

c-de

lta25

)/de

lta50

0 5 10 15EWlabel

]...,-30] [-24,-20] [-14,-10] [-4,-1] [1,5] [11,15] [21,25] [31,...[Event Time

Carr-Wu (Mean) Carr-Wu Random (Mean)Cremers et al. (Mean) Cremers et al. Random (Mean)

IV-Skew (30-day options)

I Flat evolution for randomized pseudo-event dates.

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SEC Litigation Reports

Year SEC LRs Cash ABS Sample Illicit Profits Fines Days to Lit. Moneyness S/K Option Mat. Days to Ann. Defend.

1990 1 1 . 350,000 . . . . . 1

1993 2 0 . 87,593 60,474 1,427 . . 20 5

1994 5 2 . 141,456 365,100 953 0.90 1 4 3

1995 3 0 . 377,113 779,102 1,987 . . 50 12

1996 2 2 70 527,500 1,770,000 202 0.93 1 2 .

1997∗ 4 3 133 185,830 106,341 288 1.02 2 3 2

1998 7 1 175 339,588 2,128,255 460 0.97 1 7 2

1999 0 0 217 . . . . . . .

2000 7 3 164 150,996 193,561 1,356 1.09 1 4 2

2001 2 0 86 300,000 . 2,813 0.96 0 0 .

2002 1 0 36 250,000 61,714 933 . . 72 4

2003 2 1 54 452,871 1,017,857 670 0.91 1 13 3

2004 2 2 72 1,221,753 5,963,326 497 0.90 1 6 .

2005 8 2 109 1,478,949 971,151 1,162 0.97 1 18 3

2006 9 3 119 586,125 827,605 490 0.94 1 10 3

2007 14 2 159 2,219,556 12,489,449 879 0.92 2 21 2

2008 5 1 98 595,769 1,223,737 849 0.95 2 15 2

2009 6 2 74 8,751,193 762,375 1,031 0.87 1 21 2

2010 11 3 93 409,832 2,830,969 463 0.95 1 19 2

2011 4 2 114 902,457 324,777 537 0.80 3 21 6

2012 4 1 86 4,191,446 324,422 91 1.11 1 17 2

2013 3 2 . 3,200,000 500,000 12 0.96 2 4 1

90-13 5 2 . 1,470,056 3,539,593 770 0.94 1 16 3

96-12 6 2 109 1,567,976 3,770,741 756 0.94 1 16 3

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Informed Options Trading prior to M&A Announcements: Insider …cfe.columbia.edu/files/seasieor/center-financial-engineering/... · Research Design ü Options trading before M&As