Detecting Insider TradingMS&E444 Final Presentation

Manabu KishimotoXu Tian

Li Xu

June 2, 2008

Overview• Motivation & Focus• Litigation Case Study (CNS Inc.) • Detecting Strategy• Automation and Optimization• Performance Evaluation• Conclusion

Motivation & Focus• If we can detect insider trading before the news

release, we can generate excess returns.• In our project, we focus on the option market b

ecause – It gives leveraged return for insiders;– It is more thinly traded than the stock market;– It is more informative than the stock market.

• We also focus on good news (e.g. Acquisition).

Daily Stock Price (CNS Inc.)

36.72

28.56

0

5

10

15

20

25

30

35

40

$

10/9/2006 11/9/20068/9/2006Acquisition News Release

28.5% increase

GlaxoSmithKlinewould acquire CNSfor $37.50 per share

Daily Option Volume (CNS Inc.)

0

200

400

600

800

1000

1200

1400

1600

1800

2000

call

put

10/99/11/2006 9/27 10/2News

SEC claims that there wasillegal insider trading onthese four trading days.

Aggregated Call Option Volume (CNS Inc.)Sep 27 - Oct 2, 2006

0

200

400

600

800

1000

1200

1400

1600

17.5 20 22.5 25 30 35

Strike Price ($)

Vol

ume

Stock Price:$28

Aggregated Call Option Volume (CNS Inc.)Sep 27 - Oct 2, 2006

0100200300400500600700800900

3 weeks(Oct 21)

7 weeks(Nov 18)

11 weeks(Dec 16)

24 weeks(Mar 17, 2007)

Time to Expiration

Vol

ume

Salient Statistical Patterns

1. Call-put imbalance is large;2. Total option volume is high; 3. Insiders prefer slightly in-the-money

or out-of-the-money option;4. Near-term option is preferred.

Detecting Strategy (1)

• Use moving windows: take 100 trading days as background data and 10 days as the signal

• Filter the data: focus on the data which satisfy the following two conditions:1. Strike Price Filter Criterion Stock price – Strike price Stock price2. Expiration Date Filter Criterion Expiration date – Current date < 6 months

< +0.15

SignalBackground

News?100 days 10 days

Insider?

Detecting Strategy (2)

• Apply the following criteria:1. Call Ratio Criterion　 Call volume

Call volume + Put volume 2. Total Volume Criterion Signal daily average volume

Background daily average volume

> 1

SignalBackground

News?100 days 10 days

> 75%

Insider?

Automation• Automatic processing script (PERL)• Optimize detection criteria• Use several benchmarks to evaluate the effectiveness

of detection strategy

Litigation Database Training Database Testing Database

CNXS, DJ, INVN Event Database2007 First HalfOptionMetrics

Database

# of Tickers 3 99 3068

Year2002/01-2004/062005/01-2007/06

2005/01/01-2007/06/30

2007/01/01-2007/06/30

# of events 15 474 1902

Optimize Detection Criteria

• Define:– Right Detection: stock price rallies ≥ 10%– Wrong Detection: stock price sinks ≥ 10%

• Optimization on Training database– Optimize to maximize Right/Total Ratio– Optimize the criteria to maximize Right/Wrong

Ratio• Change only one parameter at a time

Performance EvaluationBenchmark #1: Histogram of Stock Return

• If we buy 1 share of stock when the signal suggests insider events, and sell it after holding it for 10 days, we obtained the histogram of the percentage return for all tickers in the database.

Training Database Testing DatabaseLitigation Database

Performance EvaluationBenchmark #2: Percentage Return of

Non-leveraged Simple Trading Strategy• Non-leveraged Simple Trading Strategy (NSTS):

– Allocate $1 for every ticker in the database– Check whether there is possible insider trading just before the market closes

Yes: Use all balance allocated to buy shares of stocks and sell it after 10 days. No: Do nothing.

– Calculate annualized percentage returns for all the funds allocated at the end of the period

– Compare the return with the Buy-and-Hold strategy

Litigation Database Training Database Testing Database

NSTS Return +15% +5.7% +7.47%Buy and hold

Return+39%

(Acquisition rich)+28%

(Acquisition rich) +2.82%

Performance EvaluationBenchmark #3: Histogram of Signal’s Lead

Time before the News Announcement

Training Database Testing Database

Performance EvaluationBenchmark #4: Prediction Errors

# of eventsStock jump more than 5%?

Yes No

Detected?Yes 4 11No 55

# of eventsStock jump more than 5%?

Yes No

Detected?Yes 114 360No 828

Trai

nin

gTe

stin

g

# of eventsStock jump more than 5%?

Yes No

Detected?Yes 417 1485No 18108

Litig

atio

n

Conclusion• There are salient statistical patterns of insider trading

in the option market. 1. Call-put imbalance is large; 2. Total option volume is high; 3. Slightly in-the-money or out-of-the-money is preferred; 4. Near-term option is preferred.• By detecting insider trading before the news release,

excess returns can be generated.- Based on 2007 data, Market return = + 2.82% 　　 Our return = + 7.47%