Unusual Option Market Activity and the Terrorist Attacks of September 11, 2001*

Transcription

1 Allen M. Potehman Univerity of Illinoi at Urbana-Champaign Unuual Option Market Activity and the Terrorit Attack of September 11, 2001* I. Introduction In the aftermath of the terrorit attack on the World Trade Center and the Pentagon on September 11, there wa widepread peculation that the terrorit or their aociate had ued advance knowledge of the attack to profit in the financial market. 1 Much of the attention focued on the trading in the day leading up to September 11 in option written on American Airline (AMR) and United Airline (UAL), the two companie whoe plane were hijacked and crahed by the terrorit. Since the value of a put (call) option i decreaing (increaing) in the price of the underlying tock, the put-call volume ratio i a common meaure of the extent to which poition etablihed by option * I thank Joe Levin, Eileen Smith, and Dick Thaler for aitance with the data ued in thi paper. Jeff Brown, Murillo Campello, George Contantinide, Timothy Johnon, Joef Lakonihok, Stewart Mayhew, George Pennacchi, Michael Weibach, Jutin Wolfer, and eminar participant at the Univerity of Illinoi provided a number of very helpful uggetion. Funding from the Illinoi Center for International Buine Education and Reearch, the George J. Heideman Summer Faculty Reearch Award, and the Office for Future and Option Reearch at the Univerity of Illinoi at Urbana-Champaign i gratefully acknowledged. Thi material i baed on work upported by the Department of Education under award no. P220A Any opinion, finding, and concluion or recommendation expreed in thi publication are thoe of the author and do not necearily reflect the view of the Department of Education. I bear full reponibility for any remaining error. Contact the author at potehma@uiuc.edu. 1. All date in thi paper that do not include a year occur in After September 11, 2001, there wa a great deal of peculation that the terrorit or their aociate had traded in the option market on advanced knowledge of the impending attack. Thi paper generate ytematic information about option market activity that can be ued to ae the option trading that precede any event of interet. Examination of the option trading leading up to September 11 reveal that there wa an unuually high level of put buying. Thi finding i conitent with informed invetor having traded option in advance of the attack. [Journal of Buine, 2006, vol. 79, no. 4] 2006 by The Univerity of Chicago. All right reerved /2006/ $

2 1704 Journal of Buine market trading will profit when the underlying tock price fall rather than rie. It i commonly believed that a typical put-call ratio i in the neighborhood of one, 2 and according to the Option Clearing Corporation (OCC) Web ite ( the September 10 put-call ratio for AMR option wa 6.09 and the September 6 put-call ratio for UAL option wa Many oberver maintained that the AMR and UAL option activity leading up to September 11 contitute trong evidence that there had been trading on advance knowledge of the attack. For example, on September 19 the CBS Evening New reported that the September 10 AMR put trading exceeded the call trading to uch an extent that it ource had never een that kind of imbalance before and the September 6 put and call trading on UAL wa extremely imbalanced. The report cloed by aying that Now US invetigator want to know whether Oama bin Laden wa the ultimate inide trader; profiting from a tragedy he upected of materminding to finance hi operation (Attkion 2001). Univerity of Chicago finance profeor George Contantinide aid that the option market trading wa o triking that it hard to attribute it to chance. So omething i definitely going on (Roeder 2001). Other well-known academic expert uch a Columbia Univerity law profeor John Coffee and Duke Univerity law profeor Jame Cox likewie upected that ome invetor traded in the option market on foreknowledge of the attack (Mathewon and Nol 2001). In addition, ophiticated option market participant uch a Jon Najarian, founder of option pecialit Mercury Trading, alo concluded from the trading that omebody knew ahead of time that the attack would occur (Atkinon and Fluendy 2001). Depite the view expreed by the popular media, leading academic, and option market profeional, there i reaon to quetion the deciivene of the evidence that terrorit traded in the option market ahead of the September 11 attack. One event that cat doubt on the evidence i the crah of an American Airline plane in New York City on November 12. According to the OCC Web ite, three trading day before, on November 7, the put-call ratio for option on AMR tock wa On the bai of the tatement made about the link between option market activity and terrorim hortly after September 11, it would have been tempting to infer from thi put-call ratio that terrorim probably wa the caue of the November 12 crah. Subequently, however, terrorim wa all but ruled out. While it might be the cae that an abnormally large AMR put-call ratio wa oberved by chance on November 7, thi event certainly raie the quetion of whether put-call ratio a large a 7.74 are, in fact, unuual. Beyond the November 12 plane crah, an article publihed in Barron on October 8 (Arvedlund 2001) offer everal additional ground for being keptical about the claim that it i likely that terrorit or their aociate traded AMR and UAL option ahead of the September 11 attack. For tarter, the article note that the heaviet trading in the AMR 2. It will be een below that, in fact, the put-call ratio i uually le than one.

3 Option Market Activity and 9/ option did not occur in the cheapet, hortet-dated put, which would have provided the larget profit to omeone who knew of the coming attack. Furthermore, an analyt had iued a ell recommendation on AMR during the previou week, which may have led invetor to buy AMR put. Similarly, the tock price of UAL had recently declined enough to concern technical trader who may have increaed their put buying, and UAL option are heavily traded by intitution hedging their tock poition. Finally, trader making market in the option did not raie the ak price at the time the order arrived a they would have if they believed that the order were baed on advere nonpublic information: the market maker did not appear to find the trading to be out of the ordinary at the time that it occurred. It i clear both that there i a good deal of prima facie evidence that the terrorit or their aociate traded in the option market ahead of the September 11 attack, but at the ame time that there are a number of reaon to upect it probative value. Conideration of the option market activity leading up to September 11 ugget that, in general, it i difficult to make reaonable judgment about whether unuual option trading ha occurred in the abence of detailed knowledge about the ditribution of option market activity. Thi paper ha two goal. The firt i to compute the hitorical ditribution of everal option market volume tatitic both unconditionally and when conditioning on the overall level of option activity, the return and trading volume on the underlying tock, and the return on the overall market. Thee ditribution can be ued a benchmark to determine whether the option market trading aociated with any event of interet i unuual. The econd goal of the paper i to ue thee ditribution to ae the extent to which the option market trading leading up to September 11 wa out of the ordinary. The paper firt et of reult characterize the unconditional and conditional hitorical ditribution of option market activity. I begin by computing quantile of the daily value of three option market volume tatitic: two volume ratio meaure and a meaure of abnormal long put volume. The quantile are computed over the January 2, 1990, through September 4, 2001, period for option lited at the Chicago Board Option Exchange (CBOE) on the 1,000 larget market capitalization firm, for option on firm in the Standard and Poor airline index, and for option on the Standard and Poor 500 tock market index (SPX). The quantile of the maximum daily value of the option volume tatitic over four trade date window are alo reported, becaue it appear from the cae of the September 11 attack that inference are ometime made on the bai of the larget daily value of an option market volume tatitic that occur over a window of everal trade date leading up to an event. The unconditional ditribution can be ued to ae option market trading leading up to the public releae of important information while controlling for baeline level of option market activity (i.e., peculating, hedging, etc.) that i unrelated to varying condition in the option or underlying tock market. In order to capture the impact of potentially ignificant conditioning in-

4 1706 Journal of Buine formation, quantile regreion i ued to regre option volume tatitic on independent variable that might have an important impact on their ditribution. The independent variable ued are the volume of option traded on the underlying tock, the current and pat return on the underlying tock, the current and pat volume on the underlying tock, and the current and pat return on the tock market a a whole. The reulting conditional ditribution can be employed to evaluate option market trading leading up to the public releae of important information while controlling for baeline level of option market activity (i.e., peculating, hedging, etc.) that vary with changing condition in the option or underlying tock market. The characterization of the unconditional and conditional ditribution of option market activity hould be of interet to everal audience. Option market participant and corporate executive clearly will have ue for tool that help them to better ae when there i unuual activity in the option that they trade or that are written on the firm they manage. Exchange official, regulator, and policy maker can alo ue thi information in the deign and enforcement of inider trading rule. DeMarzo, Fihman, and Hagerty (1998) argue that an optimal inider trading enforcement policy hould balance the benefit of having market maker face a reduced advere election problem againt the cot of enforcement. It may be poible to ue the ditribution provided in thi paper to lower the cot of enforcement with the implication that relatively more monitoring effort hould be devoted to the option market. Finally, invetor, tock analyt, journalit, and the public at large can ue the ditribution to ae whether there wa unuual option market trading leading up to any event of interet. The paper econd et of reult ue the hitorical ditribution of option market activity to ae the option market trading in the day leading up to September 11. I will refer to the four trade date beginning September 5 and ending September 10 a the target period. I invetigate thi period for two reaon. Firt, thee are the day that mot commentator eemed to be focued on. Second, Oama bin Laden claimed that he learned on September 5 that the attack would occur on September One of my option volume tatitic, PutCall, i imilar to the tandard put-call ratio. The maximum daily value that it attained for AMR or UAL during the target period wa Thi value i at the 0.97 quantile of the hitorical daily ditribution of the PutCall tatitic computed from the option activity on the 1,000 larget market capitalization firm that trade at the CBOE. Conequently, againt thi benchmark it appear that during the target period there i evidence of abnormally large option market bet that the airline tock price were going to fall. One reaon to upect inference from thi comparion, however, i that 3. Bin Laden aid that he learned the timing of the attack in Afghanitan on September 6 (Bumiller and Miller 2001). Part of September 6 in Afghanitan include a period in which the U.S. option market were open on September Below I will detail the difference between my PutCall tatitic and the put-call ratio reported by the OCC.

5 Option Market Activity and 9/ the PutCall ratio add together long and hort put volume in the numerator and long and hort call volume in the denominator. A a reult, it doe not divide volume that etablihe option market poition that will be profitable if the underlying tock price fall by volume that etablihe option market poition that will be profitable if the underlying tock price increae. To addre thi problem, I define another ratio, ShortLong, which properly aggregate option market volume that i decreaing in the tock price and alo properly aggregate option market volume that i increaing in the tock price. The ShortLong tatitic ha a maximum daily value for AMR or UAL during the target period that i at only the 0.80 quantile of it daily ditribution. Hence, on thi meaure the option market trading during the target period doe not look very unuual. Another important iue i that market oberver eemed to be chooing for crutiny the mot extreme daily option volume during the target period. Inofar a thi i the cae, the mot extreme daily value of the ShortLong tatitic during the target period hould be judged againt the hitorical ditribution of the daily maximum value of ShortLong over four trade date window. Under thi comparion the ShortLong tatitic during the target period i at the 0.49 quantile of it ditribution. When viewed in thi way, the option market activity during the target period could hardly have been more ordinary. Since the mot traightforward way for terrorit or their aociate to have profited from foreknowledge of the attack would have been for them imply to take long poition in put on tock uch a AMR or UAL, I alo invetigate a daily meaure of abnormal long put volume, AbnLongPut. The maximum value of thi meaure for AMR or UAL during the target period i at the 0.99 quantile of it daily ditribution and the 0.96 quantile of the ditribution of it greatet daily value over four trade date window. Conequently, it appear that long put volume wa elevated during the target period. Since long put volume i a cleaner indicator of option market volume that etablihe option poition that will be profitable if the underlying tock price decline than the volume ratio, I conclude that option market activity doe provide evidence that i conitent with the terrorit or their aociate having traded ahead of the September 11 attack. Conditioning on the variable dicued above (i.e., total option volume, return on the underlying tock, volume on the underlying tock, and return on the market) doe not change the concluion drawn from either the option volume ratio indicator or the put volume indicator. 5 The terrorit or their aociate might have tried to profit in the option market from the decline in the price of tock on airline other than AMR or UAL or from an overall market decline in the wake of the September 11 attack. In order to ae thi poibility, I compare trading during the target period in option on tock in the Standard and Poor airline index and on the SPX index with their hitorical ditribution. Thi comparion doe not 5. Likewie, delta-adjuting the option volume ued in the option market volume tatitic doe not change the concluion.

6 1708 Journal of Buine yield evidence of trading ahead of the attack in the option market. It hould be borne in mind, however, that even if there had been informed trading ahead of the attack in option on other airline tock or the SPX index, it would be coniderably more difficult to detect becaue of the ubtantially larger baeline of option market activity in the aggregate airline tock and the SPX index. The analyi preented in thi paper i mot cloely related to a trand of literature that invetigate the linkage between option market volume and ubequent price movement of the underlying tock. In a recent contribution, Ealey, O Hara, and Sriniva (1998) argue that there i information in poitive and negative option volume for future tock price change. 6 On the other hand, uing a different methodology, Chan, Chung, and Fong (2002) conclude that igned option volume doe not contain information for ubequent tock price change. Pan and Potehman (2006) employ cleaner meaure of poitive and negative volume and provide evidence that there i ubtantial information in option volume for future tock price. Cao, Chen, and Griffin (2005) how that in the period leading up to takeover announcement, option volume contain information about next day tock price movement. They hypotheize that prior to extreme information event, the option market i the primary venue for informed trading. Thi hypothei i conitent with the terrorit or their aociate having traded in the option market ahead of the September 11 attack. The remainder of the paper i organized a follow. Section II decribe the data. Section III define the option market volume tatitic ued in the paper. Section IV compute the ditribution of thee tatitic both unconditionally and when conditioning on the overall level of option activity, the return and trading volume on the underlying tock, and the return on the overall market. Section V ue thee ditribution to ae the extent to which the option market trading leading up to September 11 wa out of the ordinary. Section VI preent concluion. II. Data The main data for thi paper were obtained from the CBOE. The data conit of a daily record from January 2, 1990, through September 20, 2001, of long and hort open interet for non market maker on all option lited at the CBOE. 7 The long (hort) open interet for a particular option contract on a particular trade date i the number of long (hort) contract that non market maker invetor have outtanding at the end of that trade date. When a CBOElited option i alo lited at another exchange, the data cover non market 6. Poitive option volume i purchae of call or ale of put by non market maker. Negative option volume i ale of call or purchae of put by non market maker. 7. The OCC recognize three origin code for option trade: C (public cutomer), F (firm proprietary account of OCC member), and M (market maker). The data ued in thi paper correpond to the aggregate long and hort open interet for the OCC C and F origin code.

7 Option Market Activity and 9/ maker open interet for all exchange at which the option trade. Option that are not lited at the CBOE on a given trade date, however, do not appear in the data on that trade date. Long (hort) net trading volume i then computed for each option on each trade date by ubtracting the long (hort) open interet on that trade date from the long (hort) open interet on the previou trade date. Conequently, the data analyzed in thi paper correpond to the daily net trading volume of all non market maker in all market at which CBOElited option trade. 8 Thi paper invetigate data on all option on individual tock and on the SPX index. The CBOE data contain the ticker ymbol for the tock or index that underlie each option. Thi ticker ymbol i ued to extract information on the underlying tock or index for each option from the Center for Reearch in Security Price (CRSP) file. For the option on individual tock, when a given option obervation on a particular trade date cannot be matched with a CRSP permanent number (permno), it i dropped from the analyi. For each option on each trade date, the information extracted from CRSP on the underlying tock or index i the cloing price, the daily return for the current and pat 62 trade date, the daily trading volume for the current and pat 147 trade date, and the dividend paid over the remaining life of the option. Daily return for the CRSP value-weighted index are alo obtained from CRSP. Daily one-month London Interbank Offer Rate are obtained from Datatream. III. Option Volume Statitic Thi ection of the paper define the three non market maker option volume tatitic that will be analyzed. Two of the tatitic are option volume ratio that provide meaure of the extent to which option trading reult in net non market maker option poition that will have greater (leer) value if the underlying tock price ubequently decreae (increae). The other tatitic meaure the degree of abnormal net put buying by non market maker. The firt volume ratio, PutCall, correpond cloely to the put-call ratio that i widely reported in the popular pre. In order to define PutCall, let Call Put N,t and N,t be, repectively, the number of call and put lited on underlying ecurity on trade date t. 9 Call LongCall For j p 1,, N,t, let NVol,j,t ShortCall ( NVol,j,t ) be the net long (hort) trading volume by non market maker LongPut on the jth call on underlying ecurity on trade date t. Define NVol,j,t ( ShortPut NVol,j,t ) for put analogouly. The PutCallt tatitic jut divide the trade date t aggregate non market maker net trading volume of put written on 8. Thi method for computing net trading volume implicitly treat option exercie a ale. Unreported reult indicate that the finding below are practically the ame if exercie are factored out when calculating net trading volume. Since exerciing and elling an option both involve getting out of the option poition, thi paper chooe to treat them both in the ame way. 9. Underlying ecurity will typically be an individual tock in the SPX index. For one et of reult, however, the underlying ecurity will be conidered to be any tock in the Standard and Poor airline index.

8 1710 Journal of Buine underlying ecurity by the aggregate non market maker net trading volume of call written on underlying ecurity : NPut,t (FNVol LongPut F FNVol ShortPut jp1,j,t,j,t F) PutCall t { N Call,t LongCall ShortCall. (1) (FNVol,j,t F FNVol,j,t F) jp1 Thi meaure ha the virtue of being imilar to the tandard put-call ratio that i frequently reported in the popular pre. It differ in that it ue net trading volume rather than gro trading volume and it include only the volume of non market maker. Daily gro non market maker put and call volume on particular tock are readily available from the OCC Web ite. Dividing the daily gro non market maker put volume by the daily gro non market maker call volume produce a number very cloe to the PutCall tatitic, and it i reaonable to judge thi number againt the PutCall ditribution that are reported below. 10 A drawback of the PutCall meaure (and of the widely reported put-call volume ratio) i that it doe not ditinguih between long and hort volume. Thi i a problem becaue long put poition increae in value when the underlying ecurity price fall wherea hort put poition decreae in value when the underlying ecurity price fall. It can be een, however, from the numerator of equation (1) that the PutCall meaure treat the purchae and the ale of put poition in the ame way. The treatment of the call volume in the denominator uffer from the ame difficulty. I define a econd volume ratio, ShortLong, that avoid thi problem. ShortLong i a ratio whoe numerator add net trading volume that correpond to option poition that increae in value when the underlying ecurity price fall (i.e., the elling of call and the buying of put) and ubtract net trading volume that correpond to option poition that decreae in value when the underlying ecurity price fall (i.e., the buying of call and the elling of put): N Call,t ShortCall LongCall t,j,t,j,t [jp1 NPut,t LongPut ShortPut (NVol,j,t NVol,j,t )] jp1 N Call,t ShortCall LongCall,j,t,j,t [jp1 NPut,t LongPut ShortPut,j,t,j,t ] jp1 ShortLong { (NVol NVol ) (FNVol F FNVol F) (FNVol F FNVol F). (2) 10. For example, for UAL over the period November 6, 2000, through September 4, 2001, the fifth, fiftieth, and ninety-fifth quantile of the PutCall ditribution are, repectively, 0.02, 0.52, and The fifth, fiftieth, and ninety-fifth quantile for the gro non market maker put divided by gro non market maker call volume ditribution (computed from the OCC Web ite data) are, repectively, 0.03, 0.52, and 15.6.

9 Option Market Activity and 9/ The denominator normalize the variable by adding together the abolute value of all the option trading volume. Thi tatitic range from minu one to plu one, with a value of minu one indicating that all option volume correpond to option poition that will increae in value if the underlying ecurity price rie and a value of plu one indicating that all option volume correpond to option poition that will increae in value if the underlying ecurity price decline. Since the mot traightforward way for an invetor to benefit in the option market from private information about impending bad new would be for him imply to buy put, I will alo analyze a tatitic that directly meaure abnormal net long put volume. In particular, the AbnLongPut tatitic will meaure non market maker abnormal net long put volume on trade date t for a particular underlying ecurity. It i defined a the abolute net long put volume on trade date t for ecurity minu the daily average of thi quantity over a ix-month hitorical period from 147 to 22 trade date before t normalized by the tandard deviation of the abolute net long put volume during the hitorical period: 11 AbnLongPut t { NPut 147 NPut,t LongPut,t i LongPut jp1 (NVol,j,t ) (1/126) ip22 jp1 (NVol,j,t i ) td{ N Put,t i (NVol LongPut jp1,j,t i ), i p 22,, 147}. (3) Finally, the maximum daily value attained by the option volume meaure over ome window of trade date from t to t w will alo be analyzed. Statitic that meaure thee quantitie are defined a follow:,dailymax OptVolStat t,t w { max {OptVolStat t i, i p 0,, w}, (4) where OptVolStat i any of the option volume tatitic. For example,,dailymax PutCall t,t w { max {PutCall t i, i p 0,, w} (5) i the maximum daily value obtained by the PutCall tatitic for underlying ecurity over trade date t through t w. Before I preent the ditribution of the option market volume tatitic in the next ection of the paper, it i worth commenting on their ue in detecting option market trading baed on private information. Since the tatitic are built from all option market activity, they contain trading that i motivated by a number of factor uch a uninformed peculation (i.e., noie trading), hedging, trading on public information, and trading on private information. Conequently, when a tatitic obtain a value that i extreme relative to it hitorical ditribution, one can infer that there wa an unuual amount of activity related to one or more of the option trading motivation. Although the tatitic do not ditinguih between trading motivation, if an extreme 11. The notation td{x i, i p a,,b} refer to the ample tandard deviation of the et with element x,,x. a b

10 1712 Journal of Buine value i oberved jut before an important piece of new become public, then it i reaonable to infer that there wa option market trading baed on private information rather than a hock to the trading from one of the other motivation. Indeed, the fact that the tatitic ha obtained an extreme value indicate that a hock to trading from another motivation would have to be unuually large to account for the oberved option market trading. Of coure, it i poible that the typical option trading from the other motivation varie ytematically with change in the tate of the option or underlying ecurity market. Thi i the reaon that conditional a well a unconditional ditribution for the tatitic will be computed in the next ection. 12 IV. The Ditribution of Option Market Volume Statitic Thi ection of the paper compute the ditribution of the option market volume tatitic defined above both unconditionally and when conditioning on a number of variable that may be aociated with ytematic change in the ditribution. Thee ditribution can be ued to ae option market activity around any event of interet. In the next ection of the paper, they are ued to evaluate the option market trading in the day leading up to the September 11 attack. Table 1 report the minimum, maximum, and quantile of the option market volume tatitic computed on a daily bai over the January 2, 1990, through September 4, 2001, period. For the AbnLongPut tatitic, value are included in the ditribution for all trade date t that have option data on the underlying tock for at leat 100 of the trade date between t 147 and t 22. Panel A of table 1 report the ditribution obtained from all option that trade at the CBOE that have underlying tock in the top 1,000 CRSP market capitalization on the firt trading day of each calendar year. 13 The median value of the PutCall ditribution i only 0.32, which ugget that, ceteri paribu, a belief that one i the typical value for thi tatitic might actually caue oberver to underetimate the extent to which large value of thi tatitic are unuual. It i alo intereting to note that the tatitic i highly variable. At the 0.25 quantile the tatitic i 0.05 (which i cloe to it minimum value of zero), wherea at the 0.95 quantile it i The ditribution of the ShortLong tatitic i roughly imilar once it i taken into account that it 12. It hould be noted that if invetor trade on private information in the market for the underlying ecurity and hedge their trading in the option market, there may be a bia againt detecting private information trading in the option market. For example, uppoe that there are two invetor with private poitive information about a tock. The firt invetor exploit it by buying the tock and hedge hi poition by elling a call, wherea the econd invetor exploit it imply by buying a call. The option market activitie of thee two invetor will tend to cancel one another out in the computation of the volume ratio, even though both are trading on poitive private information. 13. Market capitalization i defined a the price per hare time the number of hare outtanding. Ditribution obtained from all CBOE option or all CBOE option with underlying tock that are among the 500 larget market capitalization on CRSP on the firt trading day of each calendar year are imilar to thoe preented in panel A of table 1.

11 TABLE 1 Ditribution of Daily Option Market Volume Statitic for 1,000 Larget Market Capitalization Firm, Standard and Poor Airline Index Firm, and the SPX index, January 2, 1990, through September 4, 2001 Volume Statitic N Minimum Quantile A. 1,000 Larget Market Capitalization Firm Maximum PutCall 953, Inf Inf Inf ShortLong 953, AbnLongPut 777, B. Standard and Poor Airline Index Firm PutCall 2, ShortLong 2, AbnLongPut 2, C. SPX Index PutCall 2, ShortLong 2, AbnLongPut 2, Note. Thi table preent the minimum, maximum, and quantile of the daily value of three option market volume tatitic over the period January 2, 1990, through September 4, The underlying data from which the tatitic are computed are the daily cloing non market maker long and hort open interet for each option lited at the CBOE. Daily net long (hort) volume are defined a the firt difference in the daily long (hort) open interet on an option. Panel A report the ditribution computed from option written on the 1,000 larget market capitalization tock in the CRSP databae on the firt trading day of the calendar year. Panel B report the ditribution when the volume tatitic are computed on each trade date from all net option volume on Standard and Poor airline index firm. Panel C report the ditribution from option on the SPX index. Option Market Activity and 9/

12 1714 Journal of Buine range from minu one to plu one. It will be een below, however, that the ShortLong tatitic can lead to different inference about option market trading. The AbnLongPut tatitic meaure the number of tandard deviation that net long put volume for a given underlying tock on a given trade date varie from the average for the underlying tock. The median value i cloe to zero, and the ditribution around the median i roughly ymmetric. Panel B and C of table 1 report the ditribution of the tatitic when the underlying ecurity on each trade date i the 18 tock in the Standard and Poor airline index a of September 2001 or the SPX index. The ditribution in table 1 can be ued to compare the option market activity on a trade date againt it daily ditribution. On the bai of the new report in the week after September 11, it appear that ometime the mot extreme daily value of an option market volume tatitic over ome period of trade date i ued to judge option market activity. For thi reaon, I report in table 2 the ditribution of the daily maxima of the option market volume tatitic over dijoint four trade date interval. I chooe four trade date interval becaue they will be ueful in evaluating the option market activity in the day leading up to September 11. A expected, all the ditribution are hifted upward in table 2 relative to the ditribution in table 1. For example, the median value of the PutCall tatitic increae from 0.32 to It will not be urpriing if different inference are made about whether unuual option market activity ha occurred around ome event depending on which of the ditribution i ued a a benchmark. It eem plauible a priori that the ditribution of the option market volume ratio will be influenced by a number of factor. One factor that probably i important i the total number of option contract traded on an underlying aet on a given trade date. To ee why, conider the cae of the PutCall tatitic. When the total number of option contract tranacted on a trade date i very mall, there i a relatively high probability that all the contract that traded were either put or call. When only put trade, the value of the tatitic i infinity; when only call trade, the value of the tatitic i zero. Conequently, one would expect that the lower (upper) quantile of the PutCall tatitic will have leer (greater) value when the total number of option contract traded i maller. The ditribution of the option volume tatitic may well alo change a a function of the return on the underlying tock. For example, momentum or contrarian invetor may place option market bet on future movement in the underlying tock price in repone to pat return. Another poibility i that invetor place bet directly in the underlying tock market on the bai of pat return and hedge their bet in the option market. The option market volume aociated with the hedging would affect the option volume tatitic and, hence, would potentially affect their ditribution. The trading volume of the underlying tock might be important a well inofar a it indicate the extent to which there i information being releaed or attention being paid to

13 TABLE 2 Ditribution of Daily Maxima of Option Market Volume Statitic over Four Trade Date Interval for 1,000 Larget Market Capitalization Firm, Standard and Poor Airline Index Firm, and the SPX index, January 2, 1990, through September 4, 2001 Volume Statitic N Minimum Quantile A. 1,000 Larget Market Capitalization Firm Maximum PutCall DailyMax 238, Inf Inf Inf Inf Inf ShortLong DailyMax 238, AbnLongPut DailyMax 194, B. Standard and Poor Airline Index Firm PutCall DailyMax ShortLong DailyMax AbnLongPut DailyMax C. SPX Index PutCall DailyMax ShortLong DailyMax AbnLongPut DailyMax Note. Thi table preent the minimum, maximum, and quantile of the daily maxima over four trade date interval of three option market volume tatitic over the period January 2, 1990 through September 4, See alo the note to table 1. Option Market Activity and 9/

14 1716 Journal of Buine a firm. Finally, the return on the overall market might matter becaue it contain information about macroeconomic factor or overall invetor entiment. I will ue quantile regreion to etimate the quantile of the option market volume tatitic conditional on total option volume, the return on the underlying aet, the abnormal trading volume of the underlying aet, and the return on the overall tock market. Claical linear regreion i ued to etimate conditional mean function. Median regreion i a imilar tatitical technique that i ued to etimate conditional median function. Quantile regreion i a generalization of median regreion that can be ued to etimate conditional quantile function. Detail on quantile regreion can be found in Koenker and Baet (1978), Koenker and Hallock (2001), and Koenker (2002). The regreion model that will be etimated i OptVolStatt p b0 b1optvol t b2rdayt b3rweek t b RMonth b AbnVolDay 4 t 5 t b6abnvolweek t b7abnvolmontht b8rvwdayt b9rvwweek t b10rvwmontht t, (6) where OptVolStat t i a tandardized verion of either the PutCall tatitic or the AbnLongPut tatitic. The PutCall variable cannot be ued becaue it range up to infinity. The tandardized verion of PutCall, which will be called PutCallStand, i defined a the net put volume divided by the net put plu net call volume. PutCallStand range from zero to one. The regreion will be performed only for cae in which the underlying ecuritie are individual tock. The firt independent variable, OptVol t, i the total net option volume on underlying tock on trade date t (i.e., it i the um of the abolute value of the net long and hort, put and call trading). The next three independent variable, RDayt, RWeekt, and RMontht, are, repectively, the return on underlying tock on trade date t, the average daily return on tock over trade date t 5 through t 1, and the average daily return on tock over trade date t 21 through t 6. The next three variable, AbnVolDay t, AbnVolWeek t, and AbnVolMontht, are, repectively, the abnormal trading volume on tock on trade date t and the average daily abnormal trading volume on trade date t 5 through t 1 and trade date t 21 through t 6. Here abnormal trading volume i obtained by ubtracting from the trading volume on trade date t or the daily average trading volume on trade date t 5 through t 1 or trade date t 21 through t 6 the daily average trading volume for tock over trade date t 147 through t 22 and then dividing by the tandard deviation of the daily trading volume for tock over trade date t 147 through t 22. The variable RVWDay t, RVWWeek t, and RVWMontht are, repectively, the CRSP value-weighted market return on trade date t and the daily average CRSP value-weighted

15 Option Market Activity and 9/ market return on trade date t 5 through t 1 and trade date t 21 through t 6. Table 3 report the reult of performing quantile regreion over the period January 2, 1990, through September 4, 2001, when the univere of underlying tock i the 1,000 larget CRSP market capitalization firm at the beginning of each calendar year. The t-tatitic for the coefficient etimate reported in parenthee are computed from tandard error that aume non independently and identically ditributed (non-iid) regreion reidual. 14 The coefficient etimate in panel A of table 3 can be ued to ae the option trading around any event of interet a follow. Firt, collect the value of the independent variable for the underlying tock and trade date of interet. Next, um the product of thee value and the coefficient etimate from model (6) to compute the conditional quantile of the option volume tatitic. Finally, calculate the value of the tatitic for the underlying tock and trade date of interet, and compare it to the computed quantile. In the final tep, ue data for the put and call activity by non market maker. For PutCallStand, thee data are readily available at the OCC Web ite. 15 Exchange official, regulator, and proecutor hould have no problem acquiring the neceary data for the AbnLongPut tatitic a well. 16 V. Option Market Trading in the Day Leading Up to September 11 Thi ection of the paper invetigate whether there wa unuual option market activity in the day leading up to September 11 that i conitent with the terrorit or their aociate trading ahead of the attack. The target period that I examine for unuual option market activity i the four trade date leading up to September 11 (i.e., September 5, 6, 7, and 10). A explained above, I conider thi target period becaue it contain the trade date mot market oberver eemed to be focuing on and becaue Oama bin Laden appear to have learned on September 5 that the attack would occur on September 11. Table 4 contain the value of the option market volume tatitic for AMR, UAL, the airline index tock, and the SPX index on the trade date urrounding September 11. Conitent with the report in the popular pre, during the target period the option market volume ratio had their greatet value for 14. With non-iid regreion reidual, the limiting covariance matrix for the coefficient etimate take the form of a Huber andwich. Thi andwich i etimated uing the parity etimation method decribed in Koenker (2002). 15. The data at the OCC Web ite pertain to gro rather than net trading. However, a wa dicued in n. 10, thi difference hould not have a ignificant impact on the comparion. 16. Conditional quantile were alo computed for ShortLong, for a delta-adjuted verion of the tatitic, and for the cae in which the option volume tatitic correpond to the daily maximum over four trade date interval. It turn out that in the analyi performed in the next ection of the paper, there wa no difference in the inference obtained from the unconditional and conditional ditribution. Conequently, the reult from thee other conditional quantile etimation are not reported here.

16 TABLE 3 Quantile Regreion of Option Market Volume Statitic on Option Volume, Underlying Return, Underlying Abnormal Trading Volume, and Market Return Quantile Intercept OptVol RDay RWeek RMonth AbnVol Day AbnVol Week A. Dependent Variable I PutCallStand ( 11.83) (8.18) ( 19.97) ( 18.31) ( 4.25) (.74) (5.84) (5.35) ( 6.53) (1.26) (.88) ( 19.56) (61.27) ( 23.84) ( 20.20) ( 8.63) (6.40) (5.52) (3.14) ( 4.08) ( 5.09) ( 6.74) (6.67) (63.77) ( 6.95) ( 7.00) ( 4.57) (6.62) (4.66) (.29) ( 3.31) ( 3.28) ( 4.53) (501.38) (39.45) ( 57.85) ( 22.78) (2.38) (2.91) (11.79) (8.93) ( 16.98) ( 16.59) ( 20.00) (984.12) ( 36.72) ( 56.03) ( 27.59) ( 9.40) ( 76.63) ( 9.73) ( 6.55) ( 8.67) ( 14.26) ( 16.59) (1,287.51) ( 67.27) ( 46.94) ( 39.19) ( 16.26) ( 36.68) ( 13.74) ( 6.97) ( 4.64) ( 12.38) ( 10.24) (739,614.15) ( ) ( 11.90) ( 12.63) ( 12.73) ( 7.38) ( 7.59) ( 1.35) (2.90) (.80) (.96) AbnVol Month RVW Day RVW Week RVW Month 1718 Journal of Buine

17 B. Dependent Variable I AbnLongPut ( 57.41) ( 23.95) (9.88) (9.09) ( 4.27) ( 16.37) ( 9.40) ( 4.66) (7.01) ( 6.12) (3.24) ( 56.58) ( 32.70) (23.49) (32.37) (4.12) ( 12.27) ( 21.60) ( 4.64) (4.34) (.06) (7.22) ( 68.93) ( 37.51) (42.67) (64.77) (10.73) ( 17.60) ( 16.74) ( 4.46) (1.21) (1.21) (7.73) (53.55) ( 15.46) (51.22) (82.52) (38.93) (37.47) ( 4.00) ( 26.89) ( 11.39) ( 9.10) ( 6.62) (136.85) (23.27) ( 1.39) (31.92) (29.59) (68.06) (.66) ( 3.30) ( 15.19) ( 19.49) ( 20.93) (108.43) (17.21) ( 6.91) (15.12) (18.95) (51.38) (.19) (.28) ( 10.19) ( 12.73) ( 14.66) (68.18) (11.48) ( 7.58) (2.18) (8.53) (27.50) (.64) (1.36) ( 6.53) ( 6.81) ( 10.97) Note. Thi table report the reult of performing quantile regreion of two option market volume tatitic on a number of explanatory variable. The data conit of option on the 1,000 larget market capitalization firm over the period from January 2, 1990 through September 4, The option volume data were obtained directly from the CBOE, and all other data come from CRSP. The regreion pecification i eq. (6). The t-tatitic reported in parenthee are computed auming non-iid error term uing the parity etimation method decribed in Koenker (2002). Option Market Activity and 9/

18 1720 Journal of Buine TABLE 4 Volume Statitic AMR, UAL, Standard and Poor Airline Index, and SPX Option Market Volume Statitic on the Trading Day Surrounding September 11 Prior to September 11 After September 11 Sept. 5 Sept. 6 Sept. 7 Sept. 10 Sept. 17 Sept. 18 Sept. 19 Sept. 20 A. AMR PutCall ShortLong AbnLongPut B. UAL PutCall ShortLong AbnLongPut C. Standard and Poor Airline Index Firm PutCall ShortLong AbnLongPut D. SPX Index PutCall ShortLong AbnLongPut Note. Thi table report the value of three option market volume tatitic on AMR, UAL, the Standard and Poor airline index firm, and the SPX index over the four trade date leading up to and following September 11, The underlying data from which the tatitic are computed are the daily cloing non market maker long and hort open interet for each option. Daily net long (hort) volume are defined a the firt difference in the daily long (hort) open interet on an option. AMR on September 10 and for UAL on September 6. The PutCall tatitic wa 7.07 on September 10 for AMR and on September 6 for UAL. Upon caual conideration, it i eay to believe that thee number epecially the one for UAL indicate that there wa an unuual level of option market poition etablihed during the target period that would profit from a drop in the price of AMR or UAL. Since the option volume tatitic on the airline index tock and the SPX index are le variable than thoe on the individual tock, it alo appear from panel C and D of table 4 that the option market volume ratio may have been elevated for the airline index tock and the SPX index on September 5 when they had PutCall value of 7.31 and 3.96, repectively. 17 Table 5 evaluate the maximum daily value obtained by each of the option market volume tatitic for the variou group of underlying ecuritie during the target period. In particular, it report the quantile of thee maximum daily value computed from the unconditional ditribution for the tatitic contructed either from the daily value of the tatitic or from the maximum daily value over dijoint four trade date interval. Thee unconditional di- 17. When AMR and UAL are removed from the airline index, the September 5 PutCall value drop from 7.31 to 5.04.

19 Option Market Activity and 9/ TABLE 5 Volume Statitic Quantile of Maximum Oberved Value of Option Market Volume Statitic, September 5 through September 10 Maximum Oberved Quantile of Daily Ditribution A. AMR/UAL Quantile of Maximum over Four Trade Date Ditribution PutCall ShortLong AbnLongPut B. Standard and Poor Airline Index Firm PutCall ShortLong AbnLongPut C. SPX Index PutCall ShortLong AbnLongPut Note. Thi table report the quantile of the maximum daily value of three option market volume tatitic obtained over the four trade date leading up to September 11, The underlying data from which the tatitic are computed are the daily cloing non market maker long and hort open interet for each option. Daily net long (hort) volume are defined a the firt difference in the daily long (hort) open interet on an option. Quantile of the maximum oberved value are reported for both the daily ditribution of the tatitic and the ditribution of the maximum value of the tatitic over dijoint four trade date interval. The ditribution were computed over the January 2, 1990, through September 4, 2001, time period. tribution are jut the one reported in table 1 and Panel A of table 5 report the quantile for AMR and UAL. When the benchmark ditribution are built from the daily value of the tatitic, the maximum value of PutCall during the target period i een to be at the 0.97 quantile. Conequently, if thi comparion i the appropriate way to decide whether option market trading wa unuual in the day leading up to September 11, then there i evidence that i ignificant at conventional level that an unuual quantity of option market poition that would profit from a decreae in the price of AMR or UAL wa etablihed during the target period. Thi comparion, however, i not appropriate for two reaon. Firt, a wa dicued above, the PutCall tatitic doe not correctly aggregate option market poition that will increae (or decreae) in value when the underlying tock price decline. ShortLong, on the other hand, doe aggregate thee volume correctly, and table 5 how that it maximum daily value for AMR or UAL during the target period wa at the 0.80 quantile of it daily ditribution. Hence, when an option market ratio that correctly aggregate volume i conidered, the trading during the target period doe not look very unuual. The econd problem with the comparion in the previou paragraph i that it 18. Recall that the ditribution are contructed over the January 2, 1990, through September 4, 2001, period, and the univere of underlying tock conidered in the ditribution i the 1,000 larget market capitalization firm in the CRSP databae on the firt trade date of each calendar year. At the beginning of 2001, AMR and UAL were, repectively, the 426th and 863rd larget market capitalization firm on CRSP.

20 1722 Journal of Buine judge the maximum value of a tatitic over a four trade date period againt it daily ditribution. Clearly, the maximum daily value of a tatitic over the four trade date target period hould be aeed againt the hitorical ditribution of the maximum value of the tatitic over four trade date interval. Thi comparion i alo reported in table 5, and the quantile of the maximum oberved ShortLong tatitic over the four trade date window drop from 0.80 to Hence, the option market volume ratio (at leat for AMR and UAL option) do not provide any evidence that the trading leading up to September 11 wa unuual. In fact, the 0.49 quantile for the ShortLong tatitic ugget that the trading wa not in any way out of the ordinary. 19 Simply buying put on AMR or UAL would have been the mot traightforward way for terrorit or their aociate to have profited in the option market. The value of the volume ratio tatitic, on the other hand, are affected not only by long put volume but alo by hort put volume and long and hort call volume. The AbnLongPut tatitic meaure only (abnormal) non market maker net long put trading. Table 5 report that the maximum daily value that it attain for either AMR or UAL during the target period wa 3.83, which indicate that during one of the four trade date of the target period the net long put trading wa 3.83 tandard deviation greater than average. The 3.83 value of the tatitic i at the 0.99 quantile of it daily ditribution and the 0.96 quantile of the ditribution of daily maxima over four trade date window. Hence, on thi meaure it doe appear that ignificant abnormal option market poition were etablihed that would profit from the decline of one of the airline tock mot directly affected by the attack. Recall that the hitorical ditribution of AbnLongPut, from which the quantile were computed, control for option trading that i not motivated by private information. Since AbnLongPut i a more direct meaure than the option volume ratio of the option market poition that would mot likely be etablihed to profit from a decline in the price of the airline tock, I conclude that the unconditional evidence upport the propoition that there wa unuual trading in the option market leading up to September 11, which i conitent with the terrorit or their aociate having traded on advance knowledge of the impending attack. Given the oppoite concluion that i drawn from the ShortLong tatitic, a more general leon appear to be that option market volume ratio may not be reliable indicator of the preence of unuual trading in the option market. In unreported reult, the quantile of the AMR and UAL tatitic during 19. Given that airplane from two airline were crahed, in the cae of the September 11 attack it would alo be of interet to compare the maximum daily value of the tatitic for either AMR or UAL over the four trade date target period to the hitorical ditribution of the daily maximum of the tatitic for pair of underlying tock over four trade date window. Since there i no reaon to believe that event will tend to naturally involve two underlying tock (and even in the cae of September 11, one could reaonably include firm headquartered at the World Trade Center, inurance companie with expoure from the attack, etc.), in the previou ection I did not develop the tool to make thi comparion.