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Detecting Insider Trading
MS&E444 Final Presentation
Manabu Kishimoto
Xu 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 because – 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 $37.50 per share
Daily Option Volume (CNS Inc.)
0
200
400
600
800
1000
1200
1400
1600
1800
2000
call
put
10/99/11/2006 9/27 10/2
News
SEC claims that there wasillegal insider trading onthese four trading days.
Aggregated Call Option Volume (CNS Inc.)Sep 27 - Oct 2, 2006
0
200
400
600
800
1000
1200
1400
1600
17.5 20 22.5 25 30 35
Strike Price ($)
Vol
ume
Stock Price:$28
Aggregated Call Option Volume (CNS Inc.)Sep 27 - Oct 2, 2006
0
100
200
300
400
500
600
700
800
900
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
Year2002/01-2004/06
2005/01-2007/062005/01/01-2007/06/30
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 11
No 55
# of eventsStock jump more than 5%?
Yes No
Detected?Yes 114 360
No 828
Tra
inin
gT
esti
ng
# of eventsStock jump more than 5%?
Yes No
Detected?Yes 417 1485
No 18108
Lit
igat
ion
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%