Stock Return Predictability of Cross-Market Deviations in Option Prices and Credit Default Swap Spreads

Transcription

1 P Sock Reurn Predicabiliy of Cross-Marke Deviaions in Opion Prices and Credi Defaul Swap Spreads Georgios Angelopoulos, Daniel GiamouridisP, and Georgios Nikolakakis Curren version: January 2012 (Firs version: April 2011) Absrac Cross-marke deviaions in (deep ou-of-he-money) equiy pu opion prices and credi defaul swap spreads of he same firm are emporary and predic fuure movemens in he pu opions and credi defaul swaps (Carr and Wu, 2011). We documen ha large cross-marke deviaions also srongly relae o fuure equiy prices of he reference firm. The pahs of pu opion and equiy prices are consisen wih he percepions implici in he credi defaul swap hisory. Informed rading in credi defaul swaps parly explains his resul. Our evidence also suggess ha capial srucure arbirage aciviy caers for a legiimae alernaive explanaion. JEL Classificaions: G11, G12, G13, G14, D8 Keywords: credi equiy marke inegraion, equiy reurn predicabiliy, capial srucure arbirage Angelopoulos is a Docoral suden a he Deparmen of Accouning and Finance in he Ahens Universiy of Economics and Business. Giamouridis is an Assisan Professor of Finance a he Deparmen of Accouning and Finance in he Ahens Universiy of Economics and Business. He is also Senior Visiing Fellow a Cass Business School, Ciy Universiy, London, UK, and, Research Associae a EDHEC-Risknsiue, EDHEC Business School, Nice, France. Nikolakakis is a Researcher a he Deparmen of Accouning and Finance in he Ahens Universiy of Economics and Business. We are graefully o Keih Miller and Hong Li for providing us wih impac cos daa and also for helpful discussions. Manolis Liodakis is acknowledged for his consrucive feedback hroughou he course of his work. We appreciae helpful discussions on pracical maers wih David Bieber, Ma King, Helen Krause, Chris Monagu, and Rahul Jalan. Financial suppor from he Laboraory of Accouning Applicaions, he Deparmen of Accouning and Finance, and he Research Cener of he Ahens Universiy of Economics and Business is grealy appreciaed. Daniel Giamouridis grealy acknowledges he financial suppor of he Ahens Universiy of Economics and Business Research Cener (ΕΡ ). Any remaining errors are our own responsibiliy. addresses: [email protected] (Georgios Angelopoulos), [email protected] (Daniel Giamouridis, Corresponding Auhor), [email protected] (Georgios Nikolakakis) 1

2 Sock Reurn Predicabiliy of Cross-Marke Deviaions in Opion Prices and Credi Defaul Swap Spreads Absrac Cross-marke deviaions in (deep ou-of-he-money) equiy pu opion prices and credi defaul swap spreads of he same firm are emporary and predic fuure movemens in he pu opions and credi defaul swaps (Carr and Wu, 2011). We documen ha large cross-marke deviaions also srongly relae o fuure equiy prices of he reference firm. The pahs of pu opion and equiy prices are consisen wih he percepions implici in he credi defaul swap hisory. Informed rading in credi defaul swaps parly explains his resul. Our evidence also suggess ha capial srucure arbirage aciviy caers for a legiimae alernaive explanaion. JEL Classificaions: G11, G12, G13, G14, D8 Keywords: credi equiy marke inegraion, equiy reurn predicabiliy, capial srucure arbirage 2

3 1 Inroducion Cross-marke informaion flow is a subjec of widespread ineres. From an academic sandpoin, he sudy of rading on differen venues (e.g. equiies, bonds), or derivaive insrumens (e.g. opions, credi defaul swaps), offers an excellen framework for esing hypoheses peraining o informaion asymmeries. Regulaors are also ineresed in he analysis of cross-marke informaion flow. The analysis may idenify cases where heir inervenion becomes necessary o preven or uncover poenially fraudulen ransacions; or may even simulae discussions for he necessiy of regulaory reforms. Addiionally, invesmen professionals can benefi from idenifying opporuniies ha arise due o emporary informaion delays in he prices of relaed asses. An impressive range of researchers (we review his lieraure below) have empirically invesigaed he links beween differen rading venues, differen derivaive insrumens, as well as cross-marke links. The vas majoriy of hese sudies conclude ha he price or rading in one asse can be informaive for he price or rading in a relaed asse. This finding is consisen wih he predicions of heoreical microsrucure models such as Kyle (1985), and Glosen and Milgrom (1985) which sugges ha he rading process reveals imporan informaion for he asses involved and affecs he fuure pahs of prices. Aricles in his lieraure ypically focus on cross-marke informaion flow beween wo securiies only. One example is he sudy of wheher rading of equiy opions of firm reveal informaion for he price of he firm s equiy (Easley, O Hara, and Srinivas, 1998). Anoher example is he invesigaion of wheher severe changes in credi defaul swap spreads impac he value of he equiy of he reference firm (Acharya and Johnson, 2007). A hird example is he analysis of wheher credi defaul swap spreads predic he defaul probabiliy implici in deep ou of he money pu opions of he same firm and vice versa (Carr and Wu, 2011). Overall, he lieraure on cross-marke informaion flow largely neglecs ha informaion may flow beween more han wo securiies of he same firm. Informaion is expeced o flow beween hree markes for example in he case of credi defaul swap, equiy opions, and he equiy of he same firm, given heir documened pairwise linkages. Sudying he linkages of all poenially relaed securiies of he same firm has imporan implicaions on he inferences regarding fuure prices of hese securiies. More imporanly, 3

4 insances of invesor disagreemen wih respec o he prices of he relaed securiies serve as a paricularly aracive laboraory for he esing of hypoheses peraining o informed rading. In his sudy we focus on he analysis of he credi defaul swap, he equiy opion, and he equiy of he same firm. The curren lieraure has documened pairwise informaion flow beween hese markes and has provided heoreical explanaions for is exisence. Building on his lieraure allows us o generae our priors for he pah of fuure prices of he relaed securiies, idenify insances of disagreemen, explore wha paern fuure valuaions exhibi and explain why. More specifically, we idenify insances of invesor disagreemen hrough he link beween deep ou of he money pu opions and credi defaul swaps developed in Carr and Wu (2011, CW hereafer). We hypohesize ha when hese wo securiies emporarily rade in opposie direcions, hey poenially reflec differen percepions abou he fundamenals of he firm. These, implici, percepions have been documened o srongly correlae wih fuure equiy reurns when sudied separaely. The purpose of his sudy is o reconcile how his conradicing informaion, joinly revealed in CDS and equiy opions markes, maerializes in he cash equiy marke and explain why. We base our analysis on CDS spreads and deep-ou-of-he-money (DOOM hereafer) pu opions of he same firm. Following CW, we define a sandardized credi conrac o make CDS spreads and DOOM pu opion prices direcly comparable from a heoreical viewpoin. This conrac, ermed a Uni Recovery Claim (URC hereafer), pays off $1 if and only if defaul occurs before expiry. The value of his conrac can be compued from he CDS spread. Since he URC can be replicaed hrough DOOM pu opions, is value can also be compued from he prices of DOOM pu opions. We characerize as large cross-marke deviaions he occurrences of unusually large differences in curren URC values obained from DOOM pu opions and CDS on he same firm s deb. We find ha unusually large differences of URC values are only emporary and rever o heir usual level shorly afer hey occur, on average wihin abou one week. The process of reversion involves changes in he CDS and he equiy opion, and, as we show for he firs ime, also involves largely predicable changes in he equiy values of he reference firm. Unusually large differences of URC values are also srongly economically relaed o fuure equiy reurns. In paricular, our porfolio forming analysis concludes ha spread porfolios of 4

5 socks based on he magniude of cross-marke deviaions of URC values from heir usual level earn on average a risk-adjused reurn of 36.3 basis poins per week (20.73 percen annualized) wih a -saisic of These resuls are confirmed wih cross-secional ess and survive several robusness checks. Our principal finding is ha large cross-marke deviaions in equiy opion prices and CDS spreads of he same firm conain imporan informaion for he firm s fuure equiy price. The predicabiliy we documen is an inegral, ye unaended, componen of he predicabiliy of cross-marke deviaions documened in previous work. We observe ha large deviaions in he relaive pricing of equiy opions and CDS are on average followed by equiy (opion and spo) prices ha are consisen wih he price hisory of he CDS conrac (and are conrary o he price hisory of he opion prices). This is generally consisen wih informed rading in credi markes. However we argue ha informed rading in he CDS markes only parly explains he predicabiliy paern we documen. An alernaive, no muually exclusive explanaion, which suggess ha capial srucure arbirage aciviy dicaes he fuure pah of equiy (opion and spo) prices, canno be ruled ou. 1.1 Relaed Lieraure Cross-marke informaion flow has been he subjec of academic invesigaion from as early as he inroducion of exchange raded opions conracs in he 1970 s. Black (1975) firs argues ha...since an invesor can ge more acion for a given invesmen in opions han he can by invesing direcly in he underlying sock, he may choose o deal in opions when he feels he has an especially imporan piece of informaion. Several sudies have subsequenly esed if his predicion is suppored by acual daa. 1 While he evidence in earlier sudies is mixed, more recen sudies provide sufficien evidence o conclude ha opion prices and rading aciviy in he opions marke predic fuure movemens in he underlying equiy reurns. Ang, Bali, and Cakici (2010) highligh ha he documened 1 Examples include: Manaser and Rendleman (1982), Easley, O Hara, and Srinivas (1998), Cao, Chen, and Griffin (2005), Pan and Poeshman (2006), Roll, Schwarz, and Subrahmanyam, (2010), Xing, Zhang, and Zhao (2010), Cremers and Weinbaum (2010), Yan (2011). See Giamouridis and Skiadopoulos (2012) for a review of he more recen lieraure. 5

6 predicabiliy in he shor-erm is consisen wih he mulimarke rading, sequenial rade model of Easley, O Hara, and Srinivas (1998); while he mid-erm predicabiliy can be economically inerpreed hrough he demand-based opion pricing models of Bollen and Whaley (2004) and Garleanu, Pedersen, and Poeshman (2009). Cross-marke informaion flow has also been sudied beween CDS and cash equiy markes. This lieraure is relaively new given ha sufficienly large cross-secions and imeseries of CDS daa have only become available in recen years. Sudies in his srand include Longsaff, Mihal, and Neis (2003), Acharya and Johnson (2007), Bernd and Osrovnaya (2008), Fore and Pena (2009), Norden and Weber (2009), Qiu and Yu (2012) among ohers. The evidence in hese sudies is raher mixed. Fore and Pena (2009), and Norden and Weber (2009) conclude ha he equiy marke leads he CDS marke more frequenly in he price discovery process, while Longsaff, Mihal, and Neis (2003) do no find a clear leader. Acharya and Johnson (2007) find evidence of informaion flow from he CDS marke o he equiy marke before insances of exreme increases in he CDS spreads, which hey aribue o insider rading. Bernd and Osrovnaya (2008), and Qiu and Yu (2012) also find condiional (on exreme CDS moves) flow of informaion from he CDS o he cash equiy marke. Informaion heerogeneiy is used as an argumen o reconcile he resuls in hese sudies oo. 2 Anoher srand of lieraure ha his paper is relaed o is he lieraure linking CDS and equiy opions markes. Several auhors (e.g. Hull, Nelken, and Whie, 2004; Carr and Wu, 2010) have argued ha due o he common saus of a firm s equiy and is deb as coningen claims on he asses of he firm moivaes why equiy opions and CDS wrien on he same reference company should be valued joinly. Cao, Yu, and Zhong (2010), among ohers linking implied volailiy wih credi risk, find ha individual firms pu opion-implied 2 Relaed, alhough o a lesser exen, o he line of research invesigaing he associaion of equiy and credi are papers ha have been concerned wih he he effec of defaul risk on equiy reurns. Examples include Dichev (1998), Vassalou and Xing (2004), Avramov e al. (2007), Garlappi, Shu, and Yan (2008), Campbell, Hilscher, and Szilagyi (2008), Da and Gao (2010), George and Hwang (2010). A recen paper by Friewald, Wagner, and Zechner (2011) nicely reconciles he inconclusive evidence in his lieraure and suggess ha firms equiy reurns and Sharpe raios increase wih credi risk premia. 6

7 volailiy dominaes hisorical volailiy in explaining he ime-series variaion in CDS spreads. A novel paper by CW, esablishes a simple robus link beween CDS and DOOM American-syle equiy pu opions. The predicions of heir model are empirically confirmed. Cllecively he analysis in CW concludes ha deviaions in he prices of he wo insurance conracs are emporary and forecas fuure movemens in he pu opions and he CDS. Bernd and Osrovnaya (2008) also conclude ha here is informaion flow from he CDS marke o he opions marke and vice versa. Conrad, Dimar, and Hameed (2011) in anoher recen paper find ha defaul probabiliies esimaed hrough equiy opions and CDS of he same firm presen wih srong correlaion, especially pos he Global Financial Crisis. Finally, his paper also relaes o he capial srucure arbirage 3 lieraure. A key paper in his lieraure is Yu (2006). He provides a horough presenaion and analysis of he capial srucure arbirage sraegy a he level of individual rades ha involve simulaneous posiions in he CDS and he equiy of he same firm. He concludes ha porfolios of capial srucure arbirage rades produce aracive Sharpe raios, similar o hose obained wih oher ypes of fixed-income arbirage sraegies and hedge fund indusry benchmarks. Duare, Longsaff, and Yu (2007) also invesigae he risk and reurn aribues of capial srucure arbirage. CW refer o a rading sraegy ha resembles he characerisics of capial srucure arbirage when hey discuss he concep of selling CDS and buying DOOM pus of he same firm o hedge he credi risk. Kapadia and Pu (2010) is anoher recen paper ha uses he concep of capial srucure arbirage o sudy he inegraion of equiy and credi markes. They conclude ha a convergence rading sraegy - ha involves posiions on he CDS and he equiy of a firm - on he average firm earns an excess reurn of 1.04% over a 1-monh 3 Duare, Longsaff, and Yu (2007) define capial srucure arbirage as a class of fixed-income rading sraegies ha exploi mispricing beween a company s deb and is oher securiies (such as equiy). I is one of he mos popular relaive-value sraegies wihin he hedge fund indusry. Fixed-income arbirage invesed capial amouns for 13.3% of he U.S. $2.48 rillion of hedge fund asses as esimaed by evesmen/hfn and Cii ICG analyics in November Duare, Longsaff, and Yu (2007) poin ou he oal amoun of capial devoed o fixed-income arbirage is likely much larger han ha repored in hedge fund daabases due o heir limied coverage and also due o he fac ha many oher firms direcly engage in proprieary fixed income arbirage rading. 7

8 horizon. Buraschi, Trojani, and Vedolin (2011) also sudy capial srucure arbirage in he conex of invesor disagreemen. Relaive o hese works our main conribuion is o provide a horough and rigorous invesigaion of how he join informaion discovery in he CDS and opion markes maerializes in he cash equiy marke and explain why. We carry ou our analysis wih he enire specrum of cross-marke deviaions no jus negaive evens. We are paricularly concerned wih he economic significance of cross-marke informaion flow beween hese hree markes as well as wih he duraion of economically imporan informaion revelaion. These are issues ha have no been sudied in prior works. Wha addiionally makes our invesigaion more robus and, disinc, from prior analyses is ha we incorporae real-life ransacion cos daa in our analysis. Bernd and Osrovnaya (2008) is he only sudy we know ha invesigaes he informaion flow beween CDS and opions markes, as well as he join conribuion of hese markes o he price discovery in he sock marke in he conex ha we also do. Bernd and Osrovnaya (2008) reach several imporan conclusions ha we reflec on, bu is differen han ours in many repsecs. 4 Tang and Yan (2007) also sudy he hree markes 4 We highligh hree main differences. Firs, in our invesigaion of price discovery in he CDS and opions markes we make use of direcly (or more) comparable prices, i.e. URC values based on CDS spreads and DOOM pus. We believe ha his choice allows us o compare how he wo markes price similar oucomes for he firm s equiy price wihin an as similar as possible ime horizon. In Bernd and Osrovnaya (2008) he opion marke informaion is capured hrough sandardized 60-day a-he-money opions (his pracice is followed in oher sudies oo, e.g. Buraschi, Trojani, and Vedolin, 2011, Cao, Yu, and Zhong, 2010), which are very liquid insrumens and hence more reliable in erms of he informaion hey convey. However we argue ha hese opions are no likely o be used by exremely bearish marke paricipans or by marke paricipans wishing o hedge agains severe negaive price jumps. Hence hey are less likely o impound views similar o hose impounded in CDS spreads. Second, in our analysis he relaionship beween CDS spreads and opion prices is governed by srong heoreical foundaions, i.e. arbirage condiions. Bernd and Osrovnaya (2008) moivae he relaionship beween CDS spreads and opion prices on heoreical grounds; however hey inroduce maerial srucure o his relaionship hrough he economeric specificaion hey esimae o purify he informaion obained in he CDS, opions, or equiy markes. Third, our analysis is carried ou in a period when for a leas 8

9 joinly focusing on poenial liquidiy spillovers from he equiy and he equiy opion markes o he CDS marke. Our second conribuion is ha we furher sudy he link beween equiy opion and CDS and, more imporanly, provide new insighs for he process of reversion of he wo securiies afer he occurrence of large cross-marke deviaions. We exend he analysis of CW o a broader cross-secion of firms and a longer period of ime ha also includes he Global Financial Crisis. We documen for he firs ime ha i akes on average abou one week for he cross-marke deviaion o rever from eiher exreme back in he range defined by roughly he 25 h and he 75 h perceniles. This conclusion provides addiional empirical suppor for he link developed in CW; cross-marke deviaions characerized hrough heir link consiue mispricing and are only emporary. Kapadia and Pu (2010) also reach he conclusion ha equiy and credi marke disinegraion is due o mispricing. Our evidence finally also complemens ha of Bernd and Osrovnaya (2008), and Conrad, Dimar, and Hameed (2011), who also invesigae he linkages of he CDS and he equiy opions markes. Our hird conribuion relaes o he lieraure on informaion discovery in opions markes. The overall conclusion in his lieraure suggess ha abnormal increases in pu implied volailiies (e.g. Ang, Bali, and Cakici, 2010) or pu rading (e.g. Easley, O Hara, and Srinivas, 1998; Pan and Poeshman, 2006; Roll, Schwarz, and Subrahmanyam, 2010) are negaive predicors of he fuure move of equiy prices. Our conribuion over he exising lieraure is o show ha in he presence of a raded CDS on he firm s deb, and in insances of CDS and DOOM pu opion prices disagreemen, hese predciions are no confirmed ex pos. In parciular, we documen ha large deviaions in he relaive pricing of he wo securiies are on average followed by equiy prices ha are consisen wih he price hisory of he CDS conrac (and are conrary o he price hisory of he pu opion conrac). Finally, we conribue o he capial srucure arbirage lieraure and also provide useful clues o invesmen professionals engaging in capial srucure arbirage or equiy marke he second half of i neiher CDS spreads nor opion price changes have been moderae. Bernd and Osrovnaya (2008) recognize ha one disadvanage in heir framework is ha moderae move in raes as hose observe in heir sudy period - will be recognized as adverse credi evens for he firm even hough he change in spreads mos likely did no signal a drasic deerioraion of is credi qualiy. 9

10 neural sreegies. Our empirical analysis suggess ha he measure we use for cross-marke deviaions is sufficien o idenify insances of poenially profiable capial srucure arbirage rades. This measure may serve as an alernaive o he measures used in Kapadia and Pu (2010) or Yu (2006). Moreover, our analysis suggess ha such opporuniies, which may simply occur because he equiy price reacs oo slowly o new informaion (Yu, 2006), can be exploied in he equiy marke alone. The ransacion cos analysis wih real-life daa we carry ou is he firs o our knowledge in his conex. The res of his aricle is organized as follows. Secion 2 demonsraes he link beween equiy opion prices and CDS spreads. Secion 3 provides he deails of our sample and he selecion process we follow. Secion 4 conducs exploraory analysis o ge qualiaive insighs on he poenial informaion flow from he CDS and opion markes o he cash equiy markes. Secion 5 presens he resuls of he cross-secion and ime-series analyses ha invesigae he economical and saisical significance of he informaion conen of equiy opion prices and CDS spread deviaions. Secion 6 repors he resuls of a number of robusness checks. Secion 7 presens an inerpreaion of he resuls, and Secion 8 concludes. 2 The link beween DOOM Pus and CDS In order o link American-syle DOOM pus and CDS we implemen he CW approach. CW proposed a simple and robus link beween equiy American-syle DOOM pu opions and a credi insurance conrac on he same reference company. In heir seing, he sock price is bounded below by a sricly posiive barrier B > 0 before defaul, bu drops below a lower barrier A<B a defaul, and says below A hereafer. The range [A, B] defines a defaul corridor in which he sock price can never reside. Given he exisence of he defaul corridor, hey showed ha a spread beween any wo American-syle DOOM pu opions of he same mauriy and wih srike prices falling wihin he defaul corridor, i.e. a long posiion in he high srike pu opion combined wih a shor posiion in he low srike pu opion, replicaes a pure credi insurance conrac ha pays off when and only when he company defauls prior o he opion expiry. Should his spread be scaled hrough he difference in he srike prices, he payoff becomes one uni hence i is ermed a URC. The URC price is: ( 2, ) ( 1, ) UR p (, T) = PK T PK T (1) K K

11 where he superscrip p denoes he informaion source as American pu opions on he underlying sock, and T denoe he ime he URC price is compued and he mauriy of he pu opion respecively, P(K 2,T), P(K 1,T) are he pu opion prices for he conracs replicaing he credi insurance conrac wih srike prices K 2 >K 1. Alernaively, credi insurance can be bough hrough CDS. Assuming fixed and known bond recovery rae (R), consan ineres rae (r) and fixed defaul arrival rae ( λ ) as in CW, we can compue he URC value from a single CDS spread as: [ ξ ] r(, T) + k ( T ) c 1 e UR (, T ) = ξk, ξ = 1(1 R) rt (, ) + ξk (2) where he superscrip c denoes he informaion source as CDS wrien on he corporae bond of a firm and k is he CDS spread which according o he earlier assumpions is known o have a fla erm srucure, proporional o he defaul rae, i.e. k = λ(1 R). rt (, ) denoes he ime coninuously compounding spo ineres rae for he period o T. For simpliciy we p c refer o UR (, T ) and UR (, ) T as p c UR and UR respecively hereafer. 3 Sample selecion and Daa consrucion The sample period of our sudy is January 2004 o Sepember We source opions daa from OpionMerics and CDS daa from CMA. 5,6 Equiy reurns daa and company fundamenal daa are obained hrough CRSP and Compusa respecively. 5 The OTC naure of CDS may cas skepicism on wheher CMA provides he mos accurae CDS informaion for our analysis. A recen paper by Mayordomo, Pena, and Schwarz (2010), argues ha CMA quoes lead he price discovery process in comparison wih he quoes provided by oher daabases, such as GFI, Fenics, Reuers EOD, Marki and JP Morgan. 6 CMA receives CDS spreads from a range of marke conribuors. These conribuors consis of boh buy and sell side insiuions acive in he fixed income markes such as asse managers, hedge funds and banks. These acive marke paricipans provide CMA wih boh real-ime and delayed prices of execued rades, firm or indicaive bid/offers on specific eniies (e.g. company or emerging marke), enors, senioriies (ranking of he deb receiving moneys in case of defaul) and resrucuring ypes (definiion of wha consiues a defaul, ISDA agreemen ypes). To ensure he highes level of accuracy, CMA checks hese prices agains previous quoes and validaes hose using relaed securiies and news. For less liquid eniies where marke aciviy is infrequen, 11

12 We apply a number of filers o minimize he impac of recording errors. Following CW, on each day we look hrough he opions daa o selec a lis of companies wih pu opions ha saisfy he following crieria: (1) he bid price is greaer han zero; (2) he open ineres is greaer han zero; (3) he mid price is lower han he srike price of he opion, K; (4) he mid price is no lower han K S, where S is he curren spo price of he opion s underlying equiy; (5) The ask price is greaer han or equal o he bid price; (6) The bid-ask spread is greaer han or equal o $0.05 for mid price less han $3, and he bid-ask spread is greaer han or equal o $0.1 for mid price greaer han or equal o $3 (following Goyal and Sarreo, 2009); (7) he ime-o-mauriy is greaer han or equal o 360 days; and (8) he absolue value of he pu opion Dela is no greaer han For companies wih muliple pu opions ha saisfy he above crieria, we choose he pu opion wih he highes open ineres. If wo or more opions have he same open ineres we selec he opion wih he lowes moneyness. We define moneyness as K/S. Following CW we idenify he defaul corridor [A, B] ex-ane by assuming ha he sock price drops o zero upon defaul, i.e., A = 0. Thus, we se he lower of he wo srikes in he pu spread o zero so ha we only need a single pu o creae he desired payoff. To locae he srike of his pu opion and o ensure ha he chosen srike is below he upper barrier B, in addiion o he low (absolue) Dela crierion, we require he opion o have low moneyness. 7 Following he characerizaion of ou-of-he money opions in several sudies (e.g. Xing, CMA calculaes he fair CDS spread using a proprieary issuer/secor curve model ha derives an appropriae curve using known liquid CDS spreads, bond spreads and raings daa. Illiquid reference eniies are considered hose for which CMA parses fewer han hree quoes. See he CMA documenaion for addiional informaion. 7 CW require ha he opion has a low srike, i.e. below $5, insead of he opion having low moneyness. Our approach o locae he upper barrier B increases our cross-secion of observaions dramaically wihou maerially changing he srong ime-series co-movemens of he wo ses of URC values. In paricular, he low Dela/low srike crieria (CW) sources 44,210 opion conracs for analysis. The low Dela crierion alone, qualifies 111,982 opion conracs for furher analysis which are reduced o 111,907 when we apply he low moneyness filer. In erms of he ime-series co-movemens of he wo ses of URC values, when opions are obained wih he low Dela/low srike crieria he full sample correlaion of he URC values is (p-value=0.000) and i is (p-value=0.000) when opions are obained wih he low Dela/low moneyness crieria (CW, repor a cross-correlaion of in heir sample). 12

13 Zhang, and Zhao, 2010; Doran and Krieger, 2010), we se he moneyness hreshold equal o We repea he above procedure every rading day and for every company in order o selec he pu opion ha saisfies our crieria. Once he pu opion is seleced we compue he values of URC from boh American pus on a company s sock and 5-year CDS spreads on he same company s corporae bonds according o equaions (1) and (2). This choice implies a fla erm srucure of CDS spreads which may inroduce bias. We invesigae he poenial impac of his bias in subsecion 6.1. We assume a fixed and known bond recovery rae of 40% as in CW. 8 rt (, ) is compued wih he assumpion ha i is piecewise consan, echnically, hrough inerpolaion of US dollar LIBOR and swap raes which we obain from Bloomberg. We use senior unsecured USD-denominaed CDS. To address liquidiy concerns and monior he qualiy of he informaion we obain from he CDS marke, we exclude CDS spread observaions ha have remained unchanged for five or more days. Addiional filers are applied once URC values are obained as in CW. When we apply he full range of he above filers, we obain a sample of 258 companies wih broad secor coverage. 9 The number of companies on a rading day, deermined by he number of companies for which we can compue URC values from boh CDS and pu opion conracs, ranges from 5 (which occurs in wo rading days in he enire sample) o 138, wih an average of 60 companies per rading day. Table 1 repors summary saisics for our sample. Panel A repors summary saisics for he sample firms characerisics, Panel B 8 The 40% recovery rae assumpion is based on long-erm hisorical averages; see for insance he discussion in Guo, Jarrow and Lin (2009). Using shorer esimaion horizons, Elkamhi, Jacobs, and Pan (2010) find ha he average recovery rae is around 50%. Conrad, Dimar, and Hameed (2011) repor a much higher recovery rae of 65.8% on average (wih 27% sandard deviaion), which hey compue use he join informaion in opionimplied defaul probabiliies and CDS-implied defaul probabiliies. We carry ou our analysis wih he 40% recovery rae assumpion o allow comparisons of our resuls wih CW when possible. We also provide baseline resuls for analysis based on a 50% recovery rae assumpion. 9 The indusry spli of our sample based on he Fama and French classificaion of 10 indusrial secors is as follows: Consumer Non-Durables 10 firms, Consumer Durables 3 firms, Manufacuring 37 firms, Energy 23 firms, HiTec Business Equipmen 17 firms, Telecoms 19 firms, Shops 33 firms, Healh 13 firms, Uiliies 19 firms, and Oher 92 firms. 13

14 repors he sample firms opions conracs characerisics, and Panel C repors he sample firms CDS conracs characerisics. [Table 1 abou here] The median marke capializaion is U.S. $4.90 billion, he median book value of deb is U.S. $3.36 billion, and he median raio of oal deb o book value of equiy is 97% (he median raio of oal deb o marke value of equiy is 78%). Mos firms in our sample are large and hence rading in heir equiy marke is quie liquid, i.e. he median urnover is 1.43% of he ousanding shares per day. The median (annualized) sock reurn idiosyncraic volailiy based on daily sock reurns is 27.3% wih a 90 h percenile of 56.9% and a 10 h percenile of 14.5%. The median sock implied volailiy is 56.3% when i is obained from DOOM pu opions, while i is 43% when we use a-he-money pu opions wih he same mauriy o imply i. The opions we use in our analysis are opions wih median moneyness of and a 90 h percenile moneyness of suggesing ha he vas majoriy of pu opions we use are far ou-of-he money opions. The median CDS level is 256 basis poins wih a 90 h percenile of abou 707 basis poins and a 10 h percenile of 133 basis poins. The disribuion of CDS levels indicaes ha he median firm has been rading in reasonable CDS levels for corporaes in he period we examine. The median S&P credi raing of he firms in sample is BB. 4 The predicabiliy of cross-marke deviaions: pu opions and CDS We sar our empirical analysis wih he invesigaion of he relaionship beween crossmarke deviaions and fuure CDS spreads, and pu opion prices. Our objecive is o improve our undersanding of he join informaion/price discovery in he CDS and opion markes and explore he naure of he relaive mispricing idenified by he cross-marke deviaion measure. We sar by defining our basic measure of cross-marke deviaions and discuss is empirical properies. Nex, we sudy is predicabiliy over fuure price movemens in he corresponding pu and CDS conracs as in CW. We exend heir analysis, however, in wo imporan ways. Firs, we accoun for he fac ha cross-marke deviaions may addiionally depend on 14

15 liquidiy in he markes involved; 10 and second we carry ou he analysis wih a much richer, boh in he cross-secion and in he ime-series, daase. Finally, for he firs ime, we explore he ime-series of he URC values obained from he opions and he CDS marke before and afer he observaion of large cross-marke deviaions (even sudy). 4.1 A simple measure for cross-marke deviaions Cross-marke deviaions may occur for several reasons. Kapadia and Pu (2010) for example find ha equiy marke illiquidiy conribues o equiy and CDS markes disinegraion. They argue ha exising or poenial funding consrains (and liquidiy), and oher coss associaed wih cross-marke rading may preven equiy and CDS markes from resoring heir usual pariy (e.g. Gromb and Vayanos, 2002; Brunnermeier and Pedersen, 2009; Poniff, 1996, 2006). Buraschi, Trojani, and Vedolin (2011) documen also ha larger belief heerogeneiy increases credi spreads and heir volailiy, and conribues o he disinegraion of he equiy and CDS markes. To ake hese consideraions ino accoun, we propose he following measure: p c p c URCS _ DEV = ( UR UR ) mean( UR UR ) (3) p c where mean( UR UR ) is measured over a wo-monh period. We argue ha a shor-erm hisorical average value incorporaes relevan curren informaion hus deermining a usual level of cross-marke deviaion under he prevailing marke condiions. Wih his choice we believe we minimize he impac of limis o arbirage and measuremen errors associaed wih he valuaion of URCs on he characerizaion of cross-marke deviaions as usual or unusual. Our analysis in subsecions 4.2 and 4.3 confirms his conjecure. Measures of unusual marke condiions in he spiri of ours have been used in oher sudies oo. Bernd and Osrovnaya (2008), and Qiu and Yu (2012) for example characerize a 10 For example, if an invesor wans o build her porfolio wih he equiy opions and he CDS conracs, she may no rade he CDS conrac a all if her sock opion posiion is oo cosly o build due o illiquidiy. Tang and Yan (2007) find significan liquidiy spillover from bond, sock, and opion markes o he CDS marke. Qiu and Yu (2012) find ha CDS liquidiy is a key deerminan of he amoun of informaion flow from he CDS o he equiy marke. 15

16 change in he CDS ha exceeds is mean plus four sandard deviaions as a credi even. Yu (2006) defines a variable ha measures mispricing beween equiy and CDS markes. He considers levels beyond wo sandard deviaions in excess of is hisorical mean sufficien o rigger a capial srucure arbirage sraegy. Finally, Kapadia and Pu (2010) invesigae he predicabiliy of a cross-marke disinegraion measure during days of exreme as classified by an in-sample average - equiy marke movemens. Relaive o hese measures, ours is simple, has sound heoreical underpinnings and does no suffer from look-ahead bias. URCS _ DEV exhibis ineresing empirical properies. The average (cross-secional) mean URCS _ DEV is and he average (cross-secional) median value is The 5%, 25%, 75%, and 95% perceniles are , , , and respecively. The median URCS _ DEV has a minimum value of and a maximum value of The disribuion of URCS _ DEV exhibis slighly posiive skew due o a small number of exreme (large) values observed during he Fall of Figure 1 plos he ime series of URCS _ DEV over he sudy period. 4.2 Pooled regressions [Figure 1 abou here] We proceed wih he invesigaion of he predicabiliy of cross-marke deviaions over fuure price movemens in he corresponding pu and CDS conrac. We define p c D = ( UR UR ) and orhogonalize i wih respec o various company, opion, CDS, and liquidiy 11 characerisics X hrough he following ime-series regression: 12 D = a+ bx + δ (4) 11 Our measures for sock and opion liquidiy are raher sandard. To measure CDS liquidiy we use he bid-ask over he mid quoe which has been used in some sudies (e.g. Acharya and Johnson, 2007; Tang and Yan, 2007). More recen works use insead he number of quoe providers (Friewald, Wagner, and Zechner, 2011; Qiu and Yu, 2012). Friewald, Wagner, and Zechner (2011) find however ha he wo measures are empirically similar. 12 Unrepored analysis of he cross-marke deviaion of he URC value esimaes rejecs he null of nonsaionariy. 16

17 This analysis uses daily daa over he pas wo-monh period o calculae he residualδ. Noe ha URCS _ DEV, he measure we define in equaion (3), is equivalen o δ when we se X = 1 in equaion (4). Nex, we perform pooled (cross-secional and ime-series) regressions where he regression residual δ is used o predic fuure uni recovery claim value movemens, as follows: UR UR = α + β δ + e (5) p p p p +Δ +Δ and UR UR = α + β δ + η (6) c c c c +Δ +Δ p c We conjecure ha he null β = β = 0 is consisen wih he hypohesis ha he residualδ conveys no informaion. [Table 2 abou here] Table 2 repors esimaes of he coefficiens in equaions (5) and (6). Our analysis focuses on he predicabiliy of cross-marke deviaions over one- and four-week forecasing horizons. The conclusions from his analysis can be summarised as follows. When he wo markes deviae from each oher, he deviaion predics fuure movemens in boh markes o he direcion of heir fuure convergence. The resuls indicae ha URC values sourced from equiy pu opions are more sensiive o he deviaion of he wo markes han URC values obained hrough CDS spreads. For example for URCS _ DEV (op row), we observe ha over a one-week forecas horizon, he p β = (se=0.007) and he c β = (se=0.005). This paern prevails in he enire Table and conforms o he argumen of Bernd and Osrovnaya (2008) ha changes in opion prices are much more sudden han changes in he CDS spreads due o more ofen rading of he former on unsubsaniaed rumours. The predicabiliy of cross-markes deviaions is no explained away by firm, equiy opion, CDS or liquidiy characerisics. Overall, our analysis conludes ha he resuls in CW hold in he exended sample as well as afer we accoun for liquidiy. Moreover, he measure of crossmarke deviaions we propose is qualiaively as effecive in predicing fuure moves in CDS and equiy opions as oher measures ha accoun also for various company, opion, CDS, and liquidiy characerisics. 17

18 4.3 Even sudy To shed ligh on he pahs of CDS and equiy opion prices before and afer observing a large cross-marke deviaion in he URC values obained from he wo markes we conduc an even sudy. We argue ha if large cross-marke deviaions are due o informaion delays or heerogeneous beliefs, URC values obained from he wo markes should diverge (converge) prior o (pos) he occurrence of he large cross-marke deviaion. If on he oher hand deviaions are eiher due o violaions of he model and/or implemenaion assumpions, we do no expec o observe any disinc paern. We focus on large cross-marke deviaions. In our baseline invesigaion, we characerize an observed deviaion as large if i falls in he op/boom one hird of he cross-secion disribuion of URCS_DEV. Firms are grouped in ercile porfolios based on heir ranking wih respec o heir URCS_DEV. We hen monior he evoluion of URC value changes, i.e. he cross-secional average URC value change in he porfolio, in he period preceding he reference poin of ime by up o one monh unil one monh pos he reference dae. We do ha for URC values obained hrough equiy pu opions as well as for URC values obained hrough CDS spreads and repor he resuls for a weekly rebalance in Figure 2. Panel A repors he average cumulaive change in URC values for porfolios of socks wih low URCS_DEV (boom one hird) and Panel B repors he average cumulaive change in URC values for porfolios of socks wih high URCS_DEV (op one hird). [Figure 2 abou here] Panel A and Panel B provide very ineresing insighs. In he pre-even period, we observe ha URC values obained from CDS and DOOM pu opions move in he opposie direcions. Therefore, if he CDS and opions markes are examined independen of each oher, hey reveal differen percepions. For example, in Panel A, we observe ha over he days ha precede a large cross-marke deviaion occurrence, URC values obained hrough CDS increase (cumulaively). The curren lieraure (e.g. Acharya and Johnson, 2007; Bernd and Osrovnaya, 2008; Qiu and Yu, 2012) suggess ha CDS increases are genearlly negaively correlaed wih fuure equiy reurns. Over he same period, URC values obained hrough DOOM pu opions decrease (cumulaively). Decreasing pu opion prices are associaed wih posiive fuure reurns (e.g. Ang, Bali, and Cakici, 2010). 18

19 The pos-even paerns of URC value changes are opposie o heir respecive pre-even paerns and hence also opposie o each oher. The only excepion is he paern of CDS changes afer he occurrence of large negaive cross-marke deviaions. The resuls from he even-sudy are consisen wih he predicions of he pooled regression model. There are wo imporan new findings hough. Firs, URC values rever o heir usual relaive levels hrough a process ha is relaively smooh and is no dicaed on average by large jumps. Second, and more imporan, he process of reversion is differen in he wo exreme cross-marke deviaion porfolios. This is a paern ha we documen for he firs ime and is raher criical in our explanaion of he predicabiliy of cross-marke deviaions over fuure equiy reurns ha we discuss below. We observe he same pre- and pos-even paerns when we repea he analysis wih δ obained hrough all alernaive specificaion of equaion (4). Collecively, his secion finds ha discrepancies of he curren cross-marke deviaion of URC values and heir usual level are significan predicors of fuure URC values. This predicabiliy is no explained away by firm, equiy opion, CDS or liquidiy characerisics. Our even sudy analysis suggess ha prior o he observaion of large cross-marke devaions, CDS and pu opion prices move on average in opposie direcions. Pos he even, CDS and pu opion prices move in order o resore heir fair relaive valuaions. These findings are robus o he measure of cross-marke deviaion we use. Hence we mainain our basic measure, ha is URCS _ DEV in equaion (3), for he res of he paper. 5 The predicabiliy of cross-marke deviaions: equiy reurns The earlier analysis indicaes ha he occurrence of large cross-marke deviaions is he resul of significan price changes in he CDS and he equiy opions markes and ha hose deviaions predic fuure movemens in boh markes due o he fuure convergence. CDS, equiy opions, and he equiy of he same firm are however relaed securiies. Provided ha pairwise linkages have been documened in he liarure, we expec ha cross-marke deviaions predic fuure movemens in cash equiy markes oo. To invesigae his conjecure we perform sandard cross-secional and porfolio forming analysis in subsecions 5.1 and 5.2 respecively. In subsecion 5.3, we examine he decay of he predicabiliy of cross-marke deviaions. 19

20 5.1 Fama-MacBeh Regression We conduc cross-secional reurn predicabiliy ess (Fama and McBeh, 1973) by means of hree differen specificaions, all based on he following generic specificaion: RET = b + b URCS _ DEV + b CONTROLS + e (7) i, 0, 1, i, 1 i, i, 1 i, i= 2 n where RET is firm i s reurn for week 13, i, URCS _ DEVi, is he normalized cross-marke 1 deviaion for firm i on week -1 defined in equaion (3) wih averaging over he pas wo monhs, and CONTROLS i,-1 are he n-1 conrol variables for firm i observed a week -1. The hree differen specificaions we consider involve an implemenaion of equaion (7): i) wihou any conrol variables (specificaion [1]); ii) wih conrols for firm size, book-omarke raio, and previous 1-monh reurn, (specificaion [2]); and iii) wih conrols for firm size, book-o-marke raio, he previous 1-monh reurn, Chang, Chrisoffersen, and Jacobs (2010) skewness measure, and Amihud s (2002) illiquidiy measure (specificaion [3]). Firm size and book-o-marke conrols are ypical conrols in he lieraure. We choose o conrol for shor-erm momenum as opposed o a longer-erm momenum variable given he naure of cross-marke deviaions, i.e. emporary, expeced o reverse in he shor-erm. We use he skewness measure proposed by Chang, Chrisoffersen, and Jacobs (2010) which is based on he opion marke o capure he marke skewness risk premium, documened in Harvey and Siddique (2000), Conrad, Dimar, and Ghysels (2009), and Chang, Chrisoffersen, and Jacobs (2010). Chang, Chrisoffersen, and Jacobs (2010) show ha his measure is more effecive han ohers based on he sock marke. Finally, we use Amihud s (2002) facor which has been shown in he lieraure o be predicive of he fuure crosssecion of equiy reurns. [Table 3 abou here] 13 Like Hou and Moskowiz (2005), Cremers and Weinbaum (2010), and CW among ohers, we compue reurns beween adjacen Wednesdays raher han Mondays or Fridays. Friday-o-Friday reurns have high auocorrelaions, while Monday-o-Monday reurns have low auocorrelaions (e.g. Chordia and Swaminahan, 2000). 20

21 Table 3 repors coefficien esimaes, i.e. averages of weekly esimaes, along wih - saisics obained wih he Newey-Wes (1987) adjusmen. The coefficien (saisic=3.71) in he firs column of Table 3 suggess ha a one-sandard deviaion change in URCS_DEV is associaed wih a weekly reurn of 24 basis poins (13.28 percen annualized). The resuls repored in he second column of Table 3 sugges ha he predicabiliy of URCS_DEV is independen of he predicabiliy of oher well-known facors predicing he cross-secion of equiy reurns. The coefficien (-saisic=3.20) suggess ha even afer conrolling for size, book-o-marke, and shor-erm momenum effecs, he predicabiliy of URCS_DEV remains economically and saisically significan. The alernaive riskadjusmen approach of specificaion [3] also indicaes ha he predicabiliy of URCS_DEV over he subsequen week reurns is significan, i.e. he coefficien is (-saisic=2.93). 14 We now ake a closer look a he coefficiens in he conrol variables as esimaed hrough specificaion [2]. The size variable carries a negaive and only marginally significan coefficien, i.e (-saisic=-1.63). The sign of he coefficien is consisen wih he size effec. The large capializaion of he firms in our sample, he relaively poor performance of he size facor over our specific sample period of 2004 o 2010, and he shor-erm naure of he invesigaion of predicabiliy could possibly explain why he size effec is no sronger. The coefficiens of he BM and MOM variables are boh insignifican. In specificaion [3], he coefficien of SKEW is negaive bu insignifican, i.e (-saisic=-0.88), consisen wih a negaive correlaion beween reurn and skewness. The coefficien of illiquidiy is posiive bu insignifican, i.e (-saisic=0.74). A possible concern for he genuine drivers of he cross-marke deviaion predicabiliy is non-synchroniciy. Evidence ha deviaions in URC values conain informaion no ye incorporaed in he prices of he underlying securiies could simply reflec he fac ha CDS, opion, and sock price quoes are no observed a he same poin of ime. Opion markes close a 4:02 PM Easern Sandard Time (EST), sock exchanges close a 4:00 PM EST, and 14 These resuls are obained wih a 40% recovery rae assumpion. Wih a 50% recovery rae assumpion we obain qualiaively similar resuls. In paricular one-sandard deviaion change in URCS_DEV is associaed wih a weekly reurn of 21 basis poins (-saisic=3.68), 21 basis poins (-saisic=3.68), and 21 basis poins (saisic=3.68) as specificaions [1], [2], and [3] indicae respecively. 21

22 CDS quoes are snapshos obained a 5:00 PM EST. Xing, Zhang, and Zhao (2010), and Cremers and Weinbaum (2010) among ohers raise his issue in heir analysis ha involves opions and underlying equiies and conduc heir ess also by assuming ha: (a) purchases and sales of socks ake place a he opening of rading on he day afer he signal is observed, hus ignoring he firs overnigh reurn (Cremers and Weinbaum, 2010), and (b) purchases and sales of socks ake place a he close of rading on he day afer he signal is observed, hus ignoring he firs day reurn (Xing, Zhang, and Zhao, 2010). 15 When we conduc analysis (available on reques) o examine he impac of nonsynchroniciy of he quoes on our resuls we find ha he predicabiliy of URCS_DEV deerioraes, however i remains highly economically and saisically significan. In paricular, when we assume ha he sales and purchases of socks ake place a he opening of rading on he day afer he signal is observed, he facor coefficiens for specificaions [1], [2], and [3] are (-sa=3.60), (-sa=3.09), and (-sa=2.86) respecively. When we assume ha purchases and sales of socks ake place a he close of rading on he day afer he signal is observed he facor coefficiens for specificaions [1], [2], and [3] are (-sa=3.04), (-sa=1.98), and (-sa=1.67) respecively. These resuls sugges ha he non-synchroniciy of he price quoes does no explain he predicabiliy of cross-marke deviaions. Summarizing, he cross-secional evidence, we find ha cross-marke deviaions in CDS spreads and equiy pu opion prices are srongly relaed o fuure equiy reurns. The predicabiliy holds even afer conrolling for firm and marke characerisics and for he nonsynchroniciy of equiy, opions, and CDS prices. This evidence complemens Bernd and Osrovnaya (2008) who find informaion flow however only condiional on adverse credi evens. The addiional conribuion over he exising lieraure is ha we documen ha he 15 We argue ha boh approaches are raher conservaive. Barclay, Hendersho, and Jones (2008) for example sress ha he opening price mus be deermined wih lile or no rading a a ime when uncerainy abou fundamenal values is high and hence opening a financial marke creaes unusual sress. They also argue ha his sress is compounded when here are large order imbalances a he open, even if hese order imbalances are unrelaed o changes in fundamenal values. Ignoring he firs day reurn on he oher hand may also be criical given he naure of he phenomenon we sudy and he shor horizon we expec i o las for. 22

23 join informaion discovery in equiy opions and CDS markes manifess iself in he cash equiy markes in a way ha is economically significan. 5.2 Porfolio Forming Approach In his subsecion we demonsrae he predicabiliy of URCS_DEV using he porfolio formaion approach. Every week we compue URCS_DEV for every firm and sor socks in ercile porfolios. We hen compue he subsequen week porfolio reurns and esimae he following ime-series regression: RET RF = b + b EXMARKET + b SMB + b HML + b MOM + b SKEW + u (8) p, i, In equaion (8), RET is he reurn of he porfolio of socks in each ercile over one week, p, RF is he shor-erm risk-free rae a ime, EXMARKET, SMB, HML, and MOM are he reurn of he marke in excess of he shor-erm risk-free rae, he size, value, and 1-monh momenum risk facors. We consruc a sysemaic skewness facor as in Chang, Chrisoffersen, and Jacobs (2010) and denoe i wih SKEW. 16 [Table 4 abou here] Panel A of Table 4 repors he characerisics for he porfolios sored on URCS_DEV. The evidence in Panel A suggess ha firms in he exreme URCS_DEV porfolios are similar in erms of heir marke capializaion, book-o-marke, and sock marke liquidiy, bu also in erms of he implied volailiy of heir opions, and heir CDS levels. We observe a monoonic paern in erms of he las monh reurn (decreasing), bid/ask spreads in pu opions (decreasing) and CDS (increasing). The paern of las monh reurn migh be relaed o overor under-reacion o public informaion or negligence/possession of non-public informaion. The paerns of bid/ask spreads provide imporan insighs ha we discuss in secion 7. To furher undersand he ineracion of URCS_DEV wih firm, opion, and CDS characerisics, we compue he firm-level cross-secional correlaions of all he variables for 16 We sor all socks of he NYSE, AMEX, and NASDAQ ino quinile porfolios according o heir sensiiviies o innovaions in implied marke skewness. SKEW is he reurn of a porfolio ha buys he sock wih he lowes sensiiviies, and sells he sock wih he highes sensiiviies, o innovaions in implied marke skewness. 23

24 each week from January 2004 o Sepember Panel B of Table 4 repors he ime-series averages of he cross-secional correlaions. Cross-marke deviaions presen lile correlaion wih he majoriy of he characerisics, which probably reflecs he U-shaped relaionship we documened in Panel A. The sronges correlaion is observed beween URCS_DEV and he pu illiquidiy measure, followed by he correlaion wih he las monh reurn, he CDS level and he CDS illiquidiy. These observaions sugges for example ha pu opions are more expensive han heir respecive CDS when heir bid/ask spread is higher, he equiy reurn of he reference firm over he pas monh and is CDS are higher, and he bid/ask spread of he CDS is lower. We now urn o Table 5 where we presen he weekly ercile porfolio excess reurns of porfolios sored on he basis of URCS_DEV. Each ercile porfolio conains on average abou 20 socks. This number rises significanly in he period Augus 2007 o Sepember 2010 (see Table 11 below) o abou 28 socks. The Low Porfolio, which comprises socks of firms wih he lowes URCS_DEV, produces a weekly reurn in excess of he risk-free rae of -8.8 basis poins (-4.68 percen annualized). The High Porfolio, which comprises socks of firms wih he highes URCS_DEV, produces a weekly reurn in excess of he risk-free rae of 31.8 basis poins (17.95 percen annualized). Hence, he Low Porfolio underperforms he High Porfolio by a weekly reurn in excess of he risk-free rae of 40.6 basis poins (23.45 percen annualized). [Table 5 abou here] When we adjus for risk hrough equaion (8), alphas 17 for he Low Porfolio and High Porfolio are basis poins per week ( percen annualized) and 14.5 basis poins per week (7.82 percen annualized) respecively. If we buy he High Porfolio and shor he Low Porfolio he alpha of he long/shor sraegy is 36.3 basis poins per week (20.73 percen annualized) wih a -saisic of The conribuion of he Low Porfolio o he 17 We erm alphas he esimae of he inercep in equaion (8), which essenially is he risk-adjused reurn. 18 These resuls are obained wih a 40% recovery rae assumpion. Wih a 50% recovery rae assumpion we obain qualiaively similar resuls. If we buy he High Porfolio and shor he Low Porfolio he alpha of he long/shor sraegy is 35.4 basis poins per week (20.17 percen annualized) wih a -saisic of

25 alpha is higher han ha of he High Porfolio in he enire period, alhough he conribuion of he laer is economically large. 19 We now ake a closer look a he coefficiens in he risk facors and he risk/reward characerisics of he ercile porfolios. The long/shor sraegy described earlier presens wih insignifican exposure o marke risk, and saisically negligible bias o size and value. The negaive loading on momenum, i.e (-saisic=-3.43) indicaes ha he long/shor sraegy encompasses a reversal sraegy. This observaion provides addiional evidence ha he deviaions in URC values are emporary and hence prices should rever shorly o reflec no arbirage condiions. The Sharpe and Informaion (no repored) Raios are 1.33 and 1.24 respecively. Over he same period he reward o risk raios for he aggregae marke, a small minus big firms long/shor sraegy, a high minus low book-o-marke firms long/shor sraegy, and a 1-monh reversal sraegy were 0.15, 0.24, 0.26, and 0.20 respecively. We complemen our analysis wih an examinaion of he impac of non-synchroniciy in he price quoes as we did in secion 5.1. When we assume ha he sales and purchases of socks ake place a he opening of rading on he day afer he signal is observed, he spread porfolio generaes a risk-adjused reurn of 27.5 basis poins per week (15.35 percen annualized) wih a -saisic of When we assume purchases and sales of socks ake 19 We conduc addiional analysis o invesigae wheher significan reurns can be obained afer accouning for ransacion coss. We obain ransacion coss daa from Ciigroup Invesmen Research. Transacion coss are calculaed hrough an impac cos model which measures equiy rades impac as a power law of block size, wih specific dependence on rade duraion, daily volume, volailiy and shares ousanding. The model is deailed in Almgren e al. (2005). Over he period of our sudy he impac cos daa we use in our analysis sugges ha he average of he ransacion cos we subrac from each securiy reurn in he long/shor porfolio is abou 22 basis poins. The respecive average bid/ask spread (as a percenage of he mid-price) is abou 13 basis poins. We find ha he alpha of a long/shor sraegy ha invess USD 1 million on each securiy of he porfolio (equallyweighed porfolio) is 24.8 basis poins per week (13.75 percen annualized) wih a -saisic of 2.30 afer ransacion coss are aken ino accoun. Also, we find ha he alpha becomes marginally insignifican when he sraegy invess USD 3 million on each securiy of he porfolio (equally-weighed porfolio). We highligh ha while saisical and economic significance are no los afer we accoun for real-life ransacion coss, we consider our analysis conservaive a leas in wo frons. Firs, in ha i uses a very naïve porfolio consrucion sraegy. Second, in ha he ransacion coss incorporaed are more likely an upper bound of impac cos given he respecive bid/ask spreads. 25

26 place a he close of rading on he day afer he signal is observed, he risk-adjused reurn of he long/shor porfolio becomes 19.3 basis poins per week (10.55 percen annualized) wih a -saisic of These resuls sugges, as in he cross-secional analysis, ha alhough here is a drop in he esimaed alphas (and a deerioraion in heir significance), hey remain significan and hence we conclude ha non-synchroniciy canno explain he predicabiliy of URCS_DEV. To summarize, we find ha firms wih large negaive URCS_DEV underperform firms wih large posiive URCS_DEV. Therefore, when he pu conracs are unusually more expensive (cheaper) han heir CDS counerpars, i.e. unusually more expensive (cheaper) relaive o how expensive (cheap) hey have been on average in he pas, equiy markes reac as if pu conracs were overpriced (underpriced) and he underlying equiy underpriced (overpriced). The reurn difference ha can be obained hrough his observaion is economically large and saisically significan irrespecive of our adjusmen for ransacion coss or of non-synchroniciy in price quoes in he CDS, he opions, and he sock markes. Our sudy is he firs o show how o exploi disinegraion in he credi and equiy markes, solely in equiy markes. 5.3 How Long Does he Predicabiliy Las? In subsecions 5.1 and 5.2 we find ha URCS_DEV provides economically and saisically significan predicabiliy for he cross-secion of equiy reurns over a period of one week. In his subsecion we examine wheher his predicion lass over longer horizons. Michell, Pedersen, and Pulvino (2007) argue ha while arbirage is reasonably fas when marke paricipans are no capial consrained, i can be slow following major capial dislocaions. Closer o he seing we conduc our invesigaion, Kapadia and Pu (2010) argue ha pricing discrepancies across firms equiy and credi markes are relaed o impedimens o arbirage. If he sock marke is very efficien in incorporaing he informaion conained in URCS_DEV, he predicabiliy would be emporary and unlikely o persis over a long period. We firs conduc an even sudy where we monior he evoluion of URCS_DEV, for deviaions observed for firms in he op (large posiive) and boom (large negaive) erciles porfolios. Our aim is o shed ligh on he average ime hese deviaions ake o rever o he normal levels and hence become uninformaive for equiy prices. Figure 3 illusraes he ime 26

27 evoluion of he average cross-marke deviaion when i is negaive (Panel A), and when i is posiive (Panel B). Τhe evidence in Figure 3 combined wih descripive saisics of URCS_DEV (unrepored) which sugges ha he 25% and 75% of URCS_DEV are , respecively, srikingly sugges ha i akes on average abou one week for he crossmarke deviaion o rever from eiher exreme back in he 25% o 75% range. [Figure 3 abou here] We addiionally conduc cross-secional as well as porfolio forming analysis o invesigae his issue in a seup similar o subsecions 5.1 and 5.2. Table 6 repors resuls for he porfolio formaion approach. 20 The resuls are obained using he same approach as in subsecion 5.2, however porfolios are now also held for wo, hree, and four weeks. The spread reurn over he second week is 2.3 basis poins (-saisic=0.20), over he hird week basis poins (-saisic=-1.56), and over he fourh week -2.3 basis poins (-saisic=- 0.20). We noe ha he risk-adjused reurn of he spread porfolio becomes insignifican afer he firs week and even reverses in he hird week. The resuls from he cross-secional analysis are similar and all ogeher suppor he conclusion ha he sock marke is fas in incorporaing informaion embedded in cross-marke deviaions of equiy opion and CDS prices. [Table 6 abou here] In summary, his subsecion finds ha i akes abou one week for URCS_DEV o rever back o is normal levels. This is addiional evidence ha he deviaions are more likely o be due o emporary informaion delays in eiher marke. We also find ha he economic significance of he predicabiliy of URCS_DEV does no exend beyond he firs week afer is observaion. 6 Robusness checks In his secion we invesigae wheher he predicabiliy of cross-marke deviaions beween equiy opion prices and CDS spreads we documen so far is sensiive o various choices we make in our empirical framework. 20 The resuls from he cross-secional analysis are available on reques. 27

28 6.1 Mauriy mismach One of he main choices we have made in our analysis was o use CDS quoes from conracs wih five years o mauriy. This choice was made on he grounds ha CDS a five years o mauriy are he mos liquid CDS conracs. However he majoriy of he opions we used have a ime o mauriy beween wo and hree years. In he case of opions, rading volume is mosly concenraed in shorer mauriy opions (see Wei and Zheng, 2010). This mauriy mismach inroduces bias and may have an impac on he conclusions of our analysis. To address his issue, and under he consrain ha here do no exis CDS a any mauriy, we use an inerpolaion mehod o consruc a erm srucure of differen CDS. In his analysis we linearly inerpolae CDS quoes for conracs wih one, wo, hree, four, and five years o mauriy o consruc he erm srucure of differen CDS. We hen mach he mauriies beween he opions and he inerpolaed CDS. The correlaion of he URC values obained hrough American pus and CDS is (p-value=0.000) for his sample. When we do no mach he mauriies of he CDS and he opion conracs he full sample correlaion of he URC values is The firms we mainain for analysis are now 201 (were 258 before) and he opion conracs we use are 66,159 (were 111,907 before). We conduc cross-secional as well as porfolio forming analysis. [Table 7 abou here] Table 7 presens he resuls from he porfolio forming analysis. 21 The resuls in Table 7 are similar wih hose presened in Table 5. The Low Porfolio for example which comprises socks of firms wih he lowes URCS_DEV produces a weekly reurn in excess of he riskfree rae of basis poins (-8.8 basis poins before). The High Porfolio which comprises socks of firms wih he highes URCS_DEV produces a weekly reurn in excess of he riskfree rae of 30.4 basis poins (31.8 basis poins before). Hence, he Low Porfolio underperforms he High Porfolio by a weekly reurn in excess of he risk-free rae of 45.8 basis poins (40.6 basis poins before). Noe ha due o daa availabiliy he long/shor porfolio sraegy is implemened wih firms on average which is less han half he 21 The resuls from he cross-secional analysis are available on reques. 28

29 number of firms used when we did no mach he opion and he CDS conrac mauriies. The resuls from he cross-secional analysis are similar. The evidence gahered in his subsecion suggess ha, while he mauriy mismach and he associaed liquidiy issues may raise heoreical concerns, heir impac on he predicabiliy of URCS_DEV is no severe; a leas i is no severe enough so as o explain he predicabiliy of URCS_DEV away. 6.2 Disress: Negaive Book Value firms and Credi Raing impac Negaive book value firms are ofen regarded as firms in financial disress, wih low probabiliy of remaining in business for long. Jan and Ou (2008) find ha of all Compusa firms (excluding financial and uiliy firms) he yearly average percenage of firms reporing negaive book value has increased from 5% during o nearly 15% during They also find ha in he period , of all firms reporing losses, over 23% also repored negaive book value concurrenly. In our sample we observe on average 2.7 firms wih negaive book value per rebalance, i.e. 1 in he Low Porfolio, less han 0.6 in he middle porfolio, and 1.1 in he High Porfolio. If negaive book value is aribued o financial disress 22 hen i is naural o argue ha he predicabiliy of URCS_DEV could largely be influenced by hese exreme cases. To rule ou ha our resuls are influenced by firms wih negaive book value of equiy, we remove hem and conduc cross-secional as well as porfolio forming analysis. We repor he resuls from he porfolio forming analysis in Table The resuls from his analysis sugges ha our earlier conclusions are robus o he removal of firms wih negaive book value of equiy Jan and Ou (2008) argue ha negaive book values can be observed also for oher reasons such as sar-ups, large goodwill wrie-offs following business acquisiions, conservaive accouning rules ha lead o undervalued asses, i.e. research and developmen (R&D) and adverising expendiures are wo examples of poenially valuable inangibles ha are hidden from he balance shee. 23 The resuls from he cross-secional analysis are available on reques. 24 Abou 1 firm on average is included in he porfolio of socks ha should be shored per rebalance period or 15 in oal. From hese firms, all excep wo coninue heir operaions for many years afer firs reporing of negaive 29

30 [Table 8 abou here] A more appropriae indicaor of firm disress on he oher hand is is credi raing. Norden and Weber (2009) argue ha he informaion flow beween equiy and credi markes depends on he level of credi risk of he reference eniy. Hence one migh expec ha he predicabiliy of URCS_DEV could vary across firms wih differen credi raings. To es his hypohesis we conduc a cross-secional analysis where we condiion on he credi raings of he individual firms. This analysis pools weekly daa and compues esimaes of a panel regression for a specificaion similar o ha described in equaion (7). Resuls for his analysis are repored in Table 9. [Table 9 abou here] The coefficien of he ineracion variable, ha is he variable DUMMYxURCS_DEV, where DUMMY equals 1 for non-invesmen grade firms, is negaive and significan in all four specificaions we consider. In sharp conras, he coefficien of URCS_DEV is posiive and significan in all four specificaions we consider. Hence, i appears ha one sandard deviaion move in URCS_DEV predics a move in he subsequen week s firm reurns of abou 63 basis poins for invesmen grade firms and of abou 15 basis poins for noninvesmen grade firms. To sum up, we conclude ha while he predicabiliy of URCS_DEV is significan for all firms, i is sronger for firms raed as invesmen grade; hese firms raing in our sample is (on average) BBB+, while non-invesmen grade firms are (on average) raed BB. To he exen ha he predicabiliy of URCS_DEV can be aribued o more informed CDS (relaive o equiy) quoes, his resul can be easily reconciled. Qiu and Yu (2012) repor ha he CDS of firms near he invesmen-grade/speculaive-grade boundary end o be he mos liquid. They argue ha more liquidiy is associaed wih more informaion flow from he CDS o he equiy markes which is consisen wih he argumen of endogenous liquidiy provision by informed raders in he CDS marke. book value. Furhermore, many of hese firms book values can remain negaive for a prolonged period, i.e. 5 firms, or abou 33% of he firms, operae in negaive book values for he enire period pos heir firs repored negaive book value of equiy. On he oher hand, 8 firms, or abou 53% of he firms, reurn o posiive book value of equiy afer on average 6.6 quarers. Only wo firms evenually defauled. 30

31 6.3 Is he Informaion Conained in URCS_DEV unique? The earlier analysis suggess ha when URCS_DEV deviaes from is normal level, CDS spreads and pu opion prices move in order o resume o levels ha are consisen wih heir expeced levels. p UR changes however exhibi much higher (ime-series) volailiy han c UR changes, ha is vs This is also observed in Figure 2 which demonsraes ha in he pre-even period p c UR changes much more rapidly han UR. This phenomenon can be explained wih he argumen ha opions markes rade on unsubsaniaed rumours more ofen han he CDS marke does (Bernd and Osrovnaya, 2008). I is hus possible ha deviaions in URCS_DEV are dominaed by deviaions in p p UR and hence deviaions in UR alone could be as predicive as deviaions in URCS_DEV. On he oher hand deviaions in c UR migh be so informaive, ha even small changes may be able o predic fuure equiy reurns on heir own. To es hese conjecures we explore he predicabiliy of each componen of URCS_DEV separaely. We conduc our analysis in a porfolio forming seing. Firs, we examine he predicive abiliy of changes in DOOM pu opion prices and change in CDS spreads. To mainain consisency in he variables we define changes as in equaion (3). Tha is: p p p URCS _ DEV = UR mean( UR ) (9) c c c URCS _ DEV = UR mean( UR ) (10) c In equaions (9) and (10) URCS _ DEV and URCS _ DEV are he ime-series deviaions of p URC values obained hrough DOOM pu opion prices and CDS spreads respecively. Means c are esimaed over a wo-monh period. We find ha socks in he low URCS _ DEV c porfolio ouperform socks in he high URCS _ DEV porfolio by a risk-adjused reurn of 30.5 basis poins per week (17.16 percen annualized) wih a -saisic of Socks in he low URCS _ DEV porfolio ouperform socks in he high URCS _ DEV porfolio by a p risk-adjused reurn of 19.0 basis poins per week (10.37 percen annualized) wih a -saisic of We now use he reurns of each of hese long/shor porfolios as addiional risk facors when risk-adjusing he reurns of he long/shor porfolio based on URCS_DEV. If he p 31

32 predicabiliy of URCS_DEV is subsumed by eiher he predicabiliy of URCS _ DEV or URCS _ DEV, he respecive alpha - esimaed hrough he specificaion in equaion (8) c augmened wih eiher of he wo facors - will become insignifican. We presen he resuls of his analysis in Table 10. [Table 10 abou here] The resuls in Table 10 indicae ha here is a srong correlaion beween he reurns of he long/shor porfolio obained hrough URCS_DEV and he reurns of he porfolios c obained hrough eiher URCS _ DEV or URCS _ DEV. The respecive bea coefficiens are p (-saisic=-3.48) and (-saisic=7.59). However, he risk-adjused reurn of he long/shor porfolio based on URCS_DEV remains significan and economically large even c afer accouning for he effec of eiher URCS _ DEV or URCS _ DEV. In paricular, when we risk-adjus for he effec of URCS _ DEV he alpha says high a 34.5 basis poins per p c week wih a -saisic of When we risk-adjus for he effec of URCS _ DEV drops only slighly o 31.4 basis poins per week wih a -saisic of Ineresingly, when we risk- c adjus he reurn of he long/shor porfolio based on URCS _ DEV wih he reurn of he long/shor porfolio based on URCS_DEV, is alpha vanishes. Hence we conclude ha he predicabiliy of URCS_DEV is no subsumed by he predicabiliy of eiher of is componens. 6.4 Sub-sample analysis This secion invesigaes wheher he predicabiliy of URCS_DEV is significan in cerain periods of our sample and hence possibly drives he predicabiliy we find in he whole sample. We divide our sample in wo subsamples. The firs covers he period January 2004 o July July 2007 has been argued o idenify a criical urning poin in he global capial markes, in paricular given he quaniaive invesing meldown in Augus 2007 (e.g. Conrad, Dimar, and Hameed, 2011, Friewald, Wagner, and Zechner, 2011, Khandani and Lo, 2007, 2008). p p 32

33 We conduc boh he cross-secional and he porfolio forming analysis. Table 11 presens he resuls of he porfolio formaion analysis for hese wo sub-periods. 25 Given he evens of he Global Financial Crisis (GFC hereafer) in he second sub-period we repor resuls also for Augus 2007 o Sepember 2010 afer we exclude he period of shor selling ban in he US equiy markes. This period is from July 21, 2008 o Augus 12, 2008, and from Sepember 19, 2008 o Ocober 8, Ni and Pan (2011) find ha in he presence of shor sale ban, i akes ime for he negaive informaion conained in eiher he opions marke or he CDS marke o ge incorporaed ino sock prices. [Table 11 abou here] The resuls from his analysis indicae ha he predicabiliy of cross-marke deviaions is significan regardless of he sub-sample period examined and regardless of wheher he shorselling ban period is included in he analysis. The minimum alpha is observed in he firs period and i is 29.5 basis poins per week wih a -saisic of We reach similar conclusions wih he cross-secional analysis. To ge addiional insigh in he predicabiliy of URCS_DEV across ime, we plo he cumulaive reurn of $1 invesed in he hedge porfolio which is formulaed weekly on he basis of he firms URCS_DEV. We also plo he low and high URCS_DEV porfolio cumulaive reurns in excess of he marke reurn, as well as he cumulaive reurn of he marke for he same period. We observe a consisen paern over he enire sample period. [Figure 4 abou here] This analysis concludes ha he predicabiliy of URCS_DEV has been srong in he enire sample period. The evidence suggess ha i has been sronger in he more recen period. This is in our view due o wo main reasons. The sronger co-movemen of he wo markes in he second sub-period due o deerioraing credi condiions. And also due o he fac ha here has been an increased acion in he wo markes during his period and hence a larger cross-secion of firms wih which he predicabiliy of URCS_DEV is invesigaed. 25 The resuls from he cross-secional analysis are available on reques. 33

34 7 Inerpreaion of resuls The preceding analysis suggess ha large cross-marke deviaions conain informaion ha predics equiy reurns for up o abou one week in a consisen way. Large negaive (posiive) cross-marke deviaions predic negaive (posiive) equiy reurns. This finding is saisically and economically significan, and robus o various ess we conduced. Before discussing our explanaion of his phenomenon we explore he naure of firms for which unusually large deviaions are observed. This will enlighen us furher as o why cross-marke deviaions may occur. While a deailed invesigaion of his issue is beyond he scope of his paper, we will ry o reflec on he conclusions of he curren lieraure, he saisics repored in Table 4 as well as (unrepored) evidence we obain hrough addiional analysis. Perhaps he mos comprehensive and rigorous sudy ha we can reflec on is Buraschi, Trojani, and Vedolin (2011). They derive a heoreical model where invesors have differen percepions of fuure cash flows and heir degree of uncerainy, and empirically es he equilibrium link beween belief heerogeneiy, credi spreads and sock reurns. Their conclusions sugges ha larger belief heerogeneiy increases credi spreads and heir volailiy, and implies a higher frequency of capial srucure arbirage violaions. In fac, he properies of he firms in our exreme porfolios coincide wih he properies of firms ha are subjec o large belief heerogeneiy. More specifically, Table 4 illusraes ha he firms in he exreme porfolios are on average smaller han he firms in he mid porfolio. They have higher book-o-marke raios. They exhibi higher implied volailiies and heir sock is more illiquid. In addiion (unrepored analysis) firms in he exreme porfolios exhibi higher sandard deviaions in earnings per share esimaes and higher changes (over he previous and nex one year) in heir book value of deb relaive o firms in he mid porfolio. Prior research (e.g. LaPora e al., 1997; Dieher, Malloy, and Scherbina, 2002; Sadka and Scherbina, 2007) has associaed many of hese aribues o uncerainy/differences of opinion. Finally, firms in eiher of he exreme porfolios have higher CDS and we find (unrepored analysis) ha hey also experience more credi raing changes. These observaions are consisen wih he predicions of he heoreical model of Buraschi, Trojani, and Vedolin (2011). Therefore, we conclude 34

35 ha large cross-marke deviaions are observed for firms ha are more likely o be subjec o high uncerainy/differences of opinion. We now proceed wih he discussion of our explanaions for he specific paern of he predicabiliy of unusually large cross-marke deviaions ha we documen. Our analysis suggess ha afer he occurrence of large cross-marke deviaions, equiy (boh opion and cash) markes move in line wih he predicions of prior movemens of he CDS marke. Socks in he low porfolio for example, exhibi negaive reurns which are consisen wih he pah of CDS prior o he occurrence of large (negaive) cross-marke deviaions (Figure 2, Panel A). Negaive sock reurns however are no o be expeced afer decreases in pu prices which are observed for hese firms prior o he even. We believe here are wo poenial explanaions for his phenomenon. Firs, he CDS conrac migh be generally more informed han he opion conrac and hence he equiy opion and he cash equiy prices reac wih some delay o new informaion (e.g. Acharya and Johnson, 2007; Bernd and Osrovnaya, 2008, Qiu and Yu, 2012). 26 Second, none of he wo conracs is more informed han he oher, bu a poin migh come a which he cross-marke deviaions are perceived as sufficienly large o rigger capial srucure arbirage aciviy (e.g. Duare, Longsaff, and Yu, 2007; Yu, 2006). One poenial form of he capial srucure arbirage sraegy requires ha CDS are bough (sold) and hedged wih eiher shor (long) posiions in pus or long (shor) posiions in he underlying equiy. We sress ha hese wo explanaions are no necessarily muually exclusive. Figure 2, Panel A, indicaes ha pos he observaion of a large negaive cross-marke deviaion (afer CDS become unusually more expensive han pu opions) he CDS remains relaively unchanged; pu opion prices increase and (in conras o he opions relaed lieraure) equiy prices decrease rapidly. These observaions are consisen wih informed rading in he CDS marke and subsequen adjusmen of prices in he equiy markes. In addiion, in Table 4 we observe ha he CDS of firms in he Low Porfolio exhibi he 26 This explanaion is consisen wih he use of non-public informaion by informed raders ha has recenly been sudied in differen conexs, like syndicaed loan agreemens (Bushman, Smih, and Wienberg-Moerman, 2010, Massoud e al., 2011), analyss forecass (Chen and Marin, 2011), and loan renegoiaions (Ivashina and Sun, 2011). 35

36 highes liquidiy, alhough he difference wih he liquidiy of CDS in he oher porfolios is no exremely large. This observaion provides addiional suppor o our inerpreaion in ligh of he conclusion in Qiu and Yu (2012) ha more CDS liquidiy is associaed wih more informaion flow from he CDS o he equiy marke. Finally, when we compue he number of insances ha firms experience downgrades (unrepored analysis), we find ha firms in he Low Porfolio experience more downgrades in he six-monh period afer heir inclusion han firms in he oher porfolios do. This is an ex-pos confirmaion ha rading in he CDS marke is likely o have been informed. We canno compleely rule ou ha capial srucure arbirage may also conribue o he predicabiliy of cross-marke deviaions for firms in he Low Porfolio. However, ha CDS remain relaively unchanged on average afer he even makes us relucan o infer ha he CDS is subsequenly raded aggressively by capial srucure arbirage raders. Το sum up, he predicabiliy of negaive cross-marke deviaions can eiher be explained wih he informed rading or he capial srucure arbirage rading hypoheses, alhough he former caers for a more likely explanaion. The resuls in Panel B demonsrae ha pos he observaion of a large posiive crossmarke deviaion (afer he pu opion becomes unusually more expensive han he CDS), he CDS increases; pu opion prices decrease and (in conras o he opions relaed lieraure) equiy prices increase rapidly. The explanaion ha informed rading in CDS markes drives he resuls we documen is consisen wih our findings for he firms in he High Porfolio oo. However, he explanaion ha capial srucure arbirage aciviy conribues o he paern of prices we observe in his insance becomes more relevan and he informed rading explanaion less dominan for a number of reasons. Firs, we observe ha boh CDS and opion prices change afer large deviaions occur, which suggess ha he demand for buying boh conracs increases. Noably, changes in he respecive URCs are almos of he same magniude. Second, he bid-ask spreads for CDS and equiy opions we observe a he even are less consisen wih he predicions of microsrucure models in relaion o informed rading. For example low (in relaive erms) bid-ask spreads in opions are no consisen wih he predicions of Easley, O Hara, and Srinivas (1998) pooling equilibrium; high (in relaive erms) bid-ask spreads in CDS are no reconciled wih he model of endogenous liquidiy provision of Boulaov and George (2011). Third, our (unrepored) analysis suggess ha firms in he High Porfolio experience downgrades less ofen han firms in he Low 36

37 Porfolio (alhough more ofen han firms in he mid porfolio) which is consisen wih he CDS being less likely o be informed. Collecively, he predicabiliy of posiive crossmarke deviaions can eiher be explained wih he informed rading or he capial srucure arbirage rading hypoheses. Our evidence is no sufficien o favour one explanaion over he oher. 8 Conclusion Cross-marke informaion flow is a subjec of widespread ineres. The vas majoriy of he curren sudies focus on cross-marke informaion flow beween wo securiies only. We argue ha his lieraure neglecs ha informaion may flow beween more han wo securiies of he same firm. Sudying he linkages of all poenially relaed securiies of he same firm has imporan implicaions on he inferences regarding fuure prices of hese securiies. In his sudy we focus on hree securiies of he same firm: a credi defaul swap on a firm s deb, an opion on is equiy, and he equiy of he firm. Our saring poin is he link beween deep ou of he money pu opions and credi defaul swaps developed in CW. We sudy cross-marke informaion flow by means of he impac of large deviaions of deep ou of he money pu opions and credi defaul swaps from heir fair, relaive valuaions, on equiy valuaions. We find ha hese deviaions are economically and saisically significan, robus, predicors of fuure equiy reurns. The predicabiliy we documen is an inegral, hus far unaended, componen of he predicabiliy of cross-marke deviaions documened in previous work. Α possible explanaion for his finding is ha he CDS conrac is more informed han he opion conrac. One oher no muually exclusive explanaion is ha when CDS and opion prices largely deviae from heir expeced relaive levels, porfolio managers engaging in capial srucure arbirage iniiae rades ha drive CDS, equiy opion, and equiy prices back o heir normal levels. The firs explanaion seems o sufficienly reconcile he predicabiliy of cross-marke deviaions when CDS are unusually more expensive ha pu opions. While he firs explanaion also possibly reconciles he predicabiliy of cross-marke deviaions when pu opions are unusually more expensive ha CDS, he capial srucure arbirage explanaion we provide caers for a reasonable alernaive. 37

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44 Figures and Tables Figure 1: Abnormal cross-marke deviaions in uni recovery claim values over differen reference daes The solid blue line plos he median excess difference a each reference dae beween he spread in uni recovery p c claim values esimaed from he American pu marke ( UR ) and ha from he CDS marke ( UR ) and heir hisorical rolling mean. The wo dash-doed lines represen he 25h- and 75h-perceniles URCS_DEV Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan Time Percenile 25% Percenile 50% Percenile 75% 44

45 Figure 2: Pre- and pos-even uni recovery claim value changes An even is defined as a cross-marke deviaion of he difference in he uni recovery claim values from is expeced value. The even-dae is se a ime 0 and a ime window of -21 days o +21 days is sudied (x-axis). Changes in uni recovery claim values are measured on he y-axis. Panel A: Uni recovery claim value changes for large negaive cross-marke deviaions, i.e. p c p c ( UR UR mean UR UR ) ( ) ( ) < 0 Cross-secional mean URC value change Days Low Por. -- URp Low Por. -- URc Panel B: Uni recovery claim value changes for large posiive cross-marke deviaions, i.e. p c p c ( UR UR mean UR UR ) ( ) ( ) > 0 Cross-secional mean URC value change Days High Por. -- URp High Por. -- URc 45

46 Figure 3: Pre- and pos-even cross-marke deviaion from expeced values An even is defined as a cross-marke deviaion of he difference in he uni recovery claim values from is expeced value. The even-dae is se a ime 0 and a ime window of -21 days o +21 days is sudied (x-axis). Deviaions from expeced values are measured on he y-axis. p c p c Panel A: Large negaive cross-marke deviaions, i.e. ( UR UR mean UR UR ) URCS_DEV ( ) ( ) < Days Low Porfolio p c p c Panel B: Large posiive cross-marke deviaions, i.e. ( UR UR mean UR UR ) URCS_DEV ( ) ( ) > Days High Porfolio 46

47 Figure 4: Long/Shor (cash) equiy sraegy reurns This graph shows he wealh curves of 1 dollar invesed in he hedge porfolio which is formulaed weekly on he basis of he firms URCS_DEV (H-L), in he low (L-M) and high (H-M) URCS_DEV porfolio in excess of he marke, and in he marke (M) for he period March 2004 o Sepember Wealh Mar-04 May-04 Aug-04 Oc-04 Jan-05 Mar-05 Jun-05 Aug-05 Nov-05 Jan-06 Apr-06 Jun-06 Sep-06 Nov-06 Feb-07 May-07 Jul-07 Oc-07 Dec-07 Mar-08 May-08 Aug-08 Oc-08 Jan-09 Mar-09 Jun-09 Aug-09 Nov-09 Jan-10 Apr-10 Jun-10 Sep-10 Dae H-L H-M L-M M 47

48 Table 1: Sample descripive saisics This able provides informaion for he firms, he firms opions conracs, and he firms CDS conracs. Daa are sourced from CRSP and Compusa (for socks), OpionMerics (for opions), and CMA (for CDS). Our sample period is January 2004 o Sepember Panel A repors he sample firms characerisics which include he marke capializaion in billion $ (SIZE), he book value of deb in billion $ (DEBT), he oal deb over he book value of equiy (TD/BE), he oal deb over he marke value of equiy (TD/MC), he fracion of he oal shares ousanding raded on a given day (TURNOVER), and idiosyncraic volailiy (IDIOVOL) obained afer adjusing daily firm excess reurns for marke risk, size and value premiums, and momenum over a one-monh period as in Ang e al. (2006). Panel B repors he sample firms opions conracs characerisics which include he opions moneyness (K/S), he deep ou of he money pu opions implied volailiies (IV P ), he inerpolaed one year 50-dela pu opion implied volailiy (ATMV P ), and he deep ou of he money pu opions open ineres (OI). Panel C repors he sample firms CDS conracs characerisics which include he mid CDS spread in basis poins (CDS), and he firms credi raing (CREDIT RATING). We also repor he number of firms (No) in each indusry group. Panel A: Firm characerisics Panel B: Equiy opion characerisics Panel C: Credi and CDS characerisics SIZE 10% 1.39 K/S 10% CDS 10% Median 4.90 Median Median % % % DEBT 10% 0.97 IV P 10% CREDIT RATING 10% B Median 3.36 Median Median BB 90% % % BBB+ BM 10% 0.18 ATMV P 10% Median 0.64 Median % % TD/BE 10% 0.29 ΟΙ 10% 35 Median 0.97 Median % % TD/MC 10% 0.23 Median % 3.02 TURNOVER 10% 0.51% Median 1.43% 90% 4.24% IDIOVOL 10% Median %

49 Table 2: Fuure Marke Movemens Based on Curren Cross-Marke Deviaions of Uni Recovery Esimaes p c The resuls in his able refer o a wo-sage procedure. In he firs sage we define D = ( UR UR ) and regress i on various company, opion, CDS, and liquidiy characerisics( X ) ha is: D = a+ bx + δ This analysis uses daily daa over he pas wo-monh period o calculae he residualδ. In he second sage he regression residual δ is used o predic fuure uni recovery claim value movemens, as follows: and UR UR = α + β δ + e p p p p +Δ +Δ The able repors UR UR = α + β δ + η c c c c +Δ +Δ 2 R which is he average value of he R-squares from he firs regression, esimaes of c β from he second-sage pooled regressions and he R-squares from he second-sage pooled regressions. The superscrips p and c denoe he informaion source as he pu opion conrac on a firm s equiy and he CDS wrien on he corporae bond of a firm respecively. We consider wo forecasing horizons: Δ = 1 week and Δ = 4 weeks. The op row refers o he case where X = 1, ha is when he cross-marke deviaions is jus demeaned by is average value over he pas wo-monh period. The characerisics X include a proxy for he p c average level of URC value ( UR + UR ) 2, he Black and Scholes (1973) dela of he pu opion in absolue magniude DELTA, he DOOM pu opion moneyness ln(k/s) and implied volailiy IV p, he inerpolaed one year 50-dela pu opion implied volailiy ATMV p, 30- and 360-business-day realized variance of he opion underlying equiy RV 30 and RV 360 respecively, he oal deb over he marke value of equiy (TD/MC), a defaulprobabiliy measure DF esimaed based on he srucural model of Meron (1974) using oal deb, one-year ahe-money opion implied volailiy, and marke capializaion, he Amihud s (2002) equiy illiquidiy measure ILLIQ, he CDS bid-ask spread (ILLIQ CDS ) as an illiquidiy measure for he CDS marke, and he opion premium bid-ask spread (ILLIQ p ) as an illiquidiy measure for he opions marke. The las row repors resuls for using all illiquidiy measures (equiy, CDS, and opions marke) in a muliple variable regression. R 2 p β Δ = 1 week R 2 c β R 2 p β p β Δ = 4 weeks % (0.007) 5.60% (0.005) 0.54% (0.011) 5.33% (0.009) 0.42% p c UR + UR 51.06% (0.010) 2.71% (0.007) 0.59% (0.017) 2.17% (0.013) 0.47% DELTA 59.48% (0.010) 0.95% (0.007) 0.66% (0.017) 0.96% (0.013) 0.46% ln(k/s) 50.04% (0.010) 1.10% (0.007) 0.61% (0.016) 1.24% (0.012) 0.30% IV p 35.17% (0.009) 3.82% (0.006) 0.43% (0.015) 2.56% (0.011) 0.45% ATMIV p 29.43% (0.009) 6.82% (0.006) 0.44% (0.015) 4.88% (0.012) 0.30% RV % (0.009) 4.87% (0.006) 0.77% (0.015) 3.47% (0.011) 0.58% RV % (0.009) 4.73% (0.007) 1.01% (0.016) 2.33% (0.012) 0.46% TD/MC 29.88% (0.009) 5.19% (0.006) 0.69% (0.015) 3.54% (0.012) 0.31% DF 14.16% (0.010) 4.27% (0.008) 0.35% (0.017) 2.20% (0.014) 0.40% ILLIQ 4.85% (0.007) 5.81% (0.005) 0.50% (0.012) 5.24% (0.009) 0.32% ILLIQ CDS 11.32% (0.007) 5.52% (0.005) 0.55% (0.013) 5.39% (0.010) 0.22% ILLIQ p 28.02% (0.009) 3.05% (0.006) 0.65% (0.015) 2.93% (0.011) 0.25% ILLIQ, ILLIQ CDS, ILLIQ p 39.30% (0.010) 2.88% (0.007) 0.65% (0.017) 2.95% (0.013) 0.13% ( ) 2 R 2 c β and 2 R 49

50 Table 3: Predicabiliy of Cross-Marke Deviaions in Equiy Opions and Credi Defaul Swaps afer Conrolling for Oher Effecs (Fama and McBeh, 1973) This able sources daa from CRSP and Compusa (for socks), OpionMerics (for opions), and CMA (for CDS). Our sample period is January 2004 o Sepember Every Wednesday we compue he deviaion of he difference (UR p -UR c ) and is mean value over he previous wo-monh period for each firm, URCS_DEV. We normalize his variable. Ln(SIZE) is he logged firm marke capializaion. BM is he book-o-marke raio. MOM is he previous 1-monh reurn. SKEW is he skewness facor consruced as in Chang, Chrisoffersen, and Jacobs (2010). ILLIQ is he Amihud s (2002) equiy illiquidiy measure. We repor Fama-MacBeh (1973) regression esimaes for weekly reurns, as specified in equaion (7), along wih -saisics obained wih Newey- Wes (1987) adjusmen. Three ses of regression esimaes are repored. Firs, esimaes from a sraigh regression of firm reurns agains heir previous week respecive normalized URCS_DEV value (specificaion [1]). Second, esimaes from a regression of firm reurns agains heir previous week respecive normalized URCS_DEV value and addiional predicive variables for size and value premiums, and momenum (specificaion [2]). Third, esimaes from a regression of firm reurns agains heir previous week respecive normalized URCS_DEV value and addiional predicive variables for size and value premiums, momenum, Chang, Chrisoffersen, and Jacobs (2010) skewness measure, and Amihud s (2002) illiquidiy measure (specificaion [3]). [1] [2] [3] Consan sa URCS_DEV sa Ln(SIZE) sa BM sa MOM sa SKEW sa ILLIQ sa Adj R % 9.60% 12.71% 50

51 Table 4: Predicabiliy of Cross-Marke Deviaions in Equiy Opions and Credi Defaul Swaps, Porfolio Forming Approach Porfolio Descripive Saisics This able sources daa from CRSP and Compusa (for socks), OpionMerics (for opions), and CMA (for CDS). Our sample period is January 2004 o Sepember Every Wednesday we compue he deviaion of he difference (UR p -UR c ) and is mean value over he previous wo monhs for each firm. We sor socks in ercile porfolios. URCS_DEV is he deviaion of he difference (UR p -UR c ) and is mean value over he previous wo monhs. SIZE is he firm marke capializaion. BM is he book-o-marke raio. MOM is he previous 1- monh reurn. SKEW is he skewness measure consruced as in Chang, Chrisoffersen, and Jacobs (2010). ILLIQ is he Amihud s (2002) illiquidiy measure. IV p is he DOOM pu opion implied volailiy. ILLIQ p is he opion premium bid-ask spread as a percenage of he mid-spread. CDS is he CDS spread of he reference eniy, and ILLIQ CDS is he CDS bid-ask spread as a percenage of he mid-spread. Panel A repors he ime-series average value of each porfolios consiuen firms cross-secional averages. Panel B repors he ime-series averages of he cross-secional correlaions of all he variables. Panel A: Mean characerisic values Facor SIZE BM MOM SKEW 10 6 xilliq IV p ILLIQ p CDS ILLIQ CDS Low Porfolio High Porfolio Panel B: Average correlaions Facor SIZE BM MOM SKEW 10 6 xilliq IV p ILLIQ p CDS ILLIQ CDS URCS_DEV SIZE BM MOM SKEW ILLIQ IV p ILLIQ p CDS ILLIQ CDS 1 51

52 Table 5: Predicabiliy of Cross-Marke Deviaions in Equiy Opions and Credi Defaul Swaps, Porfolio Forming Approach This able sources daa from CRSP and Compusa (for socks), OpionMerics (for opions), and CMA (for CDS). Our sample period is January 2004 o Sepember Every Wednesday we compue he deviaion of he difference (UR p -UR c ) and is mean value over he previous wo monhs for each firm, URCS_DEV. We sor socks wih based on URCS_DEV in ercile porfolios. EXRET is he weekly excess reurn over he risk-free rae. ALPHA is he weekly risk-adjused reurn. MARKET, SIZE, VALUE, MOM, and SKEW are esimaed loadings on he marke, size, value premiums, momenum, and skewness premiums respecively. SR is he annualized Sharpe Raio. No is he average number of firms in each porfolio. EX RET ALPHA MARKET SIZE VALUE MOM SKEW SR No Low Porfolio % % % % High Porfolio 0.318% 0.145% High Low 0.406% 0.363% sa

53 Table 6: Decay of he Predicabiliy of Cross-Marke Deviaions in Equiy Opions and Credi Defaul Swaps, Porfolio Forming Approach This able sources daa from CRSP and Compusa (for socks), OpionMerics (for opions), and CMA (for CDS). Our sample period is January 2004 o Sepember Every Wednesday we compue he deviaion of he difference (UR p -UR c ) and is mean value over he previous wo monhs for each firm, URCS_DEV. We sor socks wih based on URCS_DEV in ercile porfolios. EXRET is he weekly excess reurn over he risk-free rae. ALPHA is he weekly risk-adjused reurn. MARKET, SIZE, VALUE, MOM, and SKEW are esimaed loadings on he marke, size, value premiums, momenum, and skewness premiums respecively. SR is he annualized Sharpe Raio. No is he average number of firms in each porfolio. Panel A, B, C, and D repor average reurns, regression esimaes, and firm characerisics for porfolios rebalanced afer one, wo, hree, and four weeks afer he iniial porfolio formaion respecively. Panel A: Week 1 EX RET ALPHA MARKET SIZE VALUE MOM SKEW SR No Low Porfolio % % % % High Porfolio 0.318% 0.145% High Low 0.406% 0.363% sa Panel B: Week 2 Low Porfolio 0.072% % % % High Porfolio 0.133% % High Low 0.061% 0.023% sa Panel C: Week 3 Low Porfolio 0.149% % % % High Porfolio 0.020% % High Low % % sa Panel D: Week 4 Low Porfolio 0.144% % % % High Porfolio 0.172% % High Low 0.028% % sa

54 Table 7: Predicabiliy of Cross-Marke Deviaions in Equiy Opions and Credi Defaul Swaps for inerpolaed CDS, Porfolio Forming Approach This able sources daa from CRSP and Compusa (for socks), OpionMerics (for opions), and CMA (for CDS). Our sample period is January 2004 o Sepember Every Wednesday we compue he deviaion of he difference (UR p -UR c ) and is mean value over he previous wo monhs for each firm, URCS_DEV. We sor socks wih based on URCS_DEV in ercile porfolios. EXRET is he weekly excess reurn over he risk-free rae. ALPHA is he weekly risk-adjused reurn. MARKET, SIZE, VALUE, MOM, and SKEW are esimaed loadings on he marke, size, value premiums, momenum, and skewness premiums respecively. SR is he annualized Sharpe Raio. No is he average number of firms in each porfolio. EX RET ALPHA MARKET SIZE VALUE MOM SKEW SR No Low Porfolio % % % % High Porfolio 0.304% 0.142% High Low 0.458% 0.476% sa

55 Table 8: Predicabiliy of Cross-Marke Deviaions in Equiy Opions and Credi Defaul Swaps for posiive Book Value firm, Porfolio Forming Approach This able sources daa from CRSP and Compusa (for socks), OpionMerics (for opions), and CMA (for CDS). Our sample period is January 2004 o Sepember Every Wednesday we compue he deviaion of he difference (UR p -UR c ) and is mean value over he previous wo monhs for each firm, URCS_DEV. We sor socks wih based on URCS_DEV in ercile porfolios. EXRET is he weekly excess reurn over he risk-free rae. ALPHA is he weekly risk-adjused reurn. MARKET, SIZE, VALUE, MOM, and SKEW are esimaed loadings on he marke, size, value premiums, momenum, and skewness premiums respecively. SR is he annualized Sharpe Raio. No is he average number of firms in each porfolio. EX RET ALPHA MARKET SIZE VALUE MOM SKEW SR No Low Porfolio % % % % High Porfolio 0.273% 0.101% High Low 0.376% 0.334% sa

56 Table 9: Predicabiliy of Cross-Marke Deviaions in Equiy Opions and Credi Defaul Swaps afer Conrolling for Oher Effecs (Fama and McBeh,1973) and Credi Raing This able sources daa from CRSP and Compusa (for socks), OpionMerics (for opions), and CMA (for CDS). Our sample period is January 2004 o Sepember Every Wednesday we compue he deviaion of he difference (UR p -UR c ) and is mean value over he previous wo-monh period for each firm, URCS_DEV. We normalize his variable. Ln(SIZE) is he logged firm marke capializaion. BM is he book-o-marke raio. MOM is he previous 1-monh reurn. SKEW is he skewness facor consruced as in Chang, Chrisoffersen, and Jacobs (2010). ILLIQ is he Amihud s (2002) equiy illiquidiy measure. We repor Fama-MacBeh (1973) regression esimaes for weekly reurns, as specified in equaion(7), along wih -saisics obained wih Newey- Wes (1987) adjusmen. Three ses of regression esimaes are repored. Firs, esimaes from a sraigh regression of firm reurns agains heir previous week respecive normalized URCS_DEV value (specificaion [1]). Second, esimaes from a regression of firm reurns agains heir previous week respecive normalized URCS_DEV value, a dummy variable which equals 1 if a company is classified as non-invesmen grade, which is raing below BBB, and an ineracion variable beween he dummy variable and he normalized URCS_DEV value (specificaion [2]). Third, esimaes from a regression of firm reurns agains heir previous week respecive normalized URCS_DEV value, a dummy variable which equals 1 if a company is classified as noninvesmen grade, which is raing below BBB, and an ineracion variable beween he dummy variable and he normalized URCS_DEV value and addiional predicive variables for size and value premiums, and momenum (specificaion [3]). Fourh, esimaes from a regression of firm reurns agains heir previous week respecive normalized URCS_DEV value, a dummy variable which equals 1 if a company is classified as non-invesmen grade, which is raing below BBB, and an ineracion variable beween he dummy variable and he normalized URCS_DEV value and addiional predicive variables for size and value premiums, momenum, Chang, Chrisoffersen, and Jacobs (2010) skewness measure, and Amihud s (2002) illiquidiy measure (specificaion [4]). [1] [2] [3] [4] Consan sa D sa URCS_DEV sa URCS_DEV x D sa Ln(SIZE) sa BM sa MOM sa SKEW sa ILLIQ sa Adj R % 0.11% 0.17% 0.21% 56

57 Table 10: Predicabiliy of Cross-Marke Deviaions in Equiy Opions and Credi Defaul Swaps afer conrolling for each componen s facor reurns, Porfolio Forming Approach This able sources daa from CRSP and Compusa (for socks), OpionMerics (for opions), and CMA (for CDS). Our sample period is January 2004 o Sepember Every Wednesday we compue he deviaion of he difference (UR p -UR c ) and is mean value over he previous wo monhs for each firm, URCS_DEV. We sor socks wih based on URCS_DEV in ercile porfolios. EXRET is he weekly excess reurn over he risk-free rae. ALPHA is he weekly risk-adjused reurn. MARKET, SIZE, VALUE, MOM, and SKEW are esimaed loadings on he marke, size, value premiums, momenum, and skewness premiums respecively. URCS_DEV c (Panel A) is he esimaed loading on reurns of a long/shor sraegy based on he difference of CDS uni recovery claim value from is previous wo-monh average value, and URCS_DEV p (Panel B) is he esimaed loading on reurns of a long/shor sraegy based on he difference of DOOM pu opion uni recovery claim value from is previous wo-monh average value. SR is he annualized Sharpe Raio. No is he average number of firms in each porfolio. Panel A: EX RET ALPHA MARKET SIZE VALUE MOM SKEW URCS_DEV c SR No Low Porfolio % % % % High Porfolio 0.318% 0.186% High Low 0.406% 0.314% sa EX RET ALPHA MARKET SIZE VALUE MOM SKEW URCS_DEV p SR No Panel B: Low Porfolio % % % % High Porfolio 0.318% 0.181% Low High 0.406% 0.345% sa

58 Table 11: Predicabiliy of Cross-Marke Deviaions in Equiy Opions and Credi Defaul Swaps, Porfolio Forming Approach in subsamples This able sources daa from CRSP and Compusa (for socks), OpionMerics (for opions), and CMA (for CDS). Our sample period is January 2004 o Sepember Every Wednesday we compue he deviaion of he difference (UR p -UR c ) and is mean value over he previous wo monhs for each firm, URCS_DEV. We sor socks wih based on URCS_DEV in ercile porfolios. EXRET is he weekly excess reurn over he risk-free rae. ALPHA is he weekly risk-adjused reurn. MARKET, SIZE, VALUE, MOM, and SKEW are esimaed loadings on he marke, size, value premiums, momenum, and skewness premiums respecively. SR is he annualized Sharpe Raio. No is he average number of firms in each porfolio. Resuls are repored for wo sub-periods. For January 2005 o July For Augus 2007 o Sepember For he laer period we also repor resuls afer excluding he period of he Global Financial Crisis (GFC), in paricular he weeks of shor-selling ban (This period is from July 21, 2008 o Augus 12, 2008, and from Sepember 19, 2008 o Ocober 8, 2008). EX RET ALPHA MARKET SIZE VALUE MOM SKEW SR No Panel A: January 2005 July 2007 Low Porfolio 0.161% % % % High Porfolio 0.450% 0.237% High Low 0.289% 0.295% sa Panel B: Augus 2007 Sepember 2010 Low Porfolio % % % % High Porfolio 0.222% 0.160% High Low 0.547% 0.466% sa Panel C: Augus 2007 Sepember 2010 (ex-gfc) Low Porfolio % % % % High Porfolio 0.350% 0.075% High Low 0.490% 0.378% sa