Firms as Buyers of Last Resort

Transcription

1 Firms as Buyers of Las Resor Harrison Hong Princeon Universiy Jiang Wang MIT and CCFR Jialin Yu Columbia Universiy Firs Draf: May 005 This Draf: April 007 Absrac: We develop a model o explore he asse pricing implicaions of firms being buyers of las resor for heir own socks. Those wih more abiliy o repurchase shares when prices drop far below fundamenal value (i.e., less financially consrained ones) should have lower shor-horizon reurn variance (conrolling for fundamenal variance) han oher firms. Using sandard proxies for financing consrains such as pas repurchases, firm age and he Kaplan and Zingales (1997) index, we find srong suppor for his prediced relaion. Moreover, our heory predics ha his relaion should be sronger in environmens where repurchases are legally easier o execue. Consisen wih our heory, we find ha his relaion is indeed sronger in he U.S. afer 198 when regulaory reforms lowered he legal cos of conducing repurchases; and among he en larges sock markes in he world, hey are sronger in counries where share repurchases are legally easier o execue. We hank an anonymous referee and Heior Almeida, Doug Diamond, Diego Garcia, Jeffrey Kubik, Hamid Mehran, Lasse Pedersen, Ronnie Sadka, Jeremy Sein, Sheridan Timan, and seminar paricipans a he Universiy of Briish Columbia, Ramon Areces Foundaion Conference on Financial Economics, Drexel, New York Federal Reserve Bank, Princeon-New York Federal Reserve Bank Liquidiy Conference, Pompeau Fabra, and Economeric Sociey Meeing, for a number of helpful commens.

2 1. Inroducion In his paper, we explore he idea of firms being buyers of las resor for heir own socks. The phrase buyers of las resor is inspired by he vas lieraure sared by Bageho (1873) on he role of cenral banks as lenders of las resor for heir economies. Jus as cenral banks make funds available o markes in imes of crises, a firm can provide liquidiy o is invesors, when no one else will, by repurchasing shares of is own sock. Such firm inervenion no only influences he price of individual socks, bu also has macroeconomic consequences. For insance, many companies quickly bough back a large fracion of heir shares afer he sock marke crash of Via he coordinaion of sock exchanges, a large number of firms also announced repurchase programs immediaely afer he evens of Sepember 11, 001. These anecdoes sugges ha companies were and can be imporan liquidiy providers. There is evidence beyond hese anecdoes ha firms inervene in heir socks when prices move significanly away from fundamenal value. In a survey by Brav, Graham, Harvey, and Michaely (004) of 384 CFOs, he mos popular response for why firms repurchase socks (86.6% of hose surveyed agree) is ha heir sock is cheap relaive o is rue value. Using large panel daases, several sudies confirm he relaive imporance of valuaion (low price-o-book raios or poor pas reurns) as a moive for his financial decision (see e.g., Dimar (1999) and Sephens and Weisbach (1998)). In addiion, oher works find posiive drif in abnormal reurns following announcemens of firms conducing repurchases (Ikenberry, Lakonishok and Vermaelen (1995, 000)). For insance, Ikenberry, Lakonishok and Vermaelen (1995) find for he U.S. sock marke ha he average abnormal four-year buy-and-hold reurn measured afer he iniial announcemen is 1.1 percen. They also find ha for low price-o-book socks, companies more likely o be repurchasing shares because of undervaluaion, he average abnormal reurn is 45.3 percen. For repurchases announced by high-price-o book socks where undervaluaion is less likely o be an imporan moive, no posiive drif in abnormal reurns is observed. Ikenberry, Lakonishok and Vermaelen (000) find similar evidence for Canada and in addiion ha rades also appear linked o price movemens as managers buy more shares when prices fall. 1

3 In sum, hese findings sugges ha repurchases are consisen wih firms inervening opporunisically much like speculaors or marke-makers would afer price falls significanly below fundamenal value and earning long-run abnormal reurns for hese rading aciviies. 1 There is also a similar se of evidence suggesing ha firms issue equiy when hey perceive heir shares o be over-valued (see Baker, Ruback and Wurgler (004) for a review of his evidence). We develop a model o explore he effecs of firms being buyers of las resor for heir socks. We exend he Grossman and Miller (1988) model o allow firms o inervene in heir own socks when liquidiy shocks are sufficienly large. We are agnosic abou he source of hese shocks leading o deviaions of price from fundamenal value. We will call hese liquidiy shocks, hough we are equally comforable wih idenifying hem as demand shocks due o, say, shifs in invesor senimen. While he Grossman-Miller model is ypically applied o reurns of very shor-horizons, we hink of our exension as applying o longer-horizons in which shocks have o be big enough (accumulae over a long enough ime) for he firm o profiably inervene. 3 Our firs predicion is ha hose firms wih less abiliy o inervene should prices deviae oo far from fundamenal value ough o have a higher shor-horizon reurn variance conrolling for an appropriaely scaled version of fundamenal or long-horizon reurn variance. Inuiively, firms wih low-inervenion abiliy end up wih greaer deviaions of price from fundamenal value and hence greaer reversals as liquidiy shocks are assumed o mean rever over long enough horizons. This means a higher shor-horizon conrolling for fundamenal or long-horizon reurn variance (since longerm reurn variance corresponds o fundamenal variance in our model) compared o high-inervenion abiliy firms. 1 I is also possible ha a firm buys back is own shares due o informaion ha only he firm has. This, however, seems less likely for wo reasons. Firs, repurchases ofen follow a fall in share prices, i.e. hey are predicable given pas reurns or valuaion raios. Second, repurchases are announced publicly, and ye price adjusmens ake several years. Firms are no in he business of being marke makers. They only inervene when he liquidiy shocks are sufficienly large. We model his by assuming ha firms have a higher cos of paricipaing in he marke han oher raders. 3 Recen evidence by Coval and Safford (005) and Frazzini and Lamon (005) confirm ha liquidaion of socks by muual funds lead he prices of hese socks o be depressed relaive o fundamenal value for long-periods of ime, suggesing he possibiliy of firms profiably buying shares o profi from his deviaion, i.e. he fricions imagined in he Grossman-Miller framework apply beyond he very shorhorizon seing o which he model is ypically applied.

4 We es his predicion by measuring he abiliy of differen firms in he crosssecion o be buyers of las resor for heir own socks and relaing his o he sock s reurn variance. Our basic premise is ha he capabiliy of he firm o be he buyer of las resor for is own sock or o inervene more generally depends on he exen o which i is financially consrained. In paricular, firms ha are equiy dependen are unlikely o execue repurchases. As such, he firs predicion of our model is ha more financially consrained firms ough o have a higher shor-horizon reurn variance conrolling for fundamenal variance. To avoid daa-mining biases, we use sandard measures of financing consrains from he recen corporae finance lieraure. In paricular, we use he measures advocaed by Kaplan and Zingales (1997), Lamon, Polk and Saa-Requejo (001), Baker, Sein and Wurgler (003). 4 The firs and closes o our heory is sock repurchases (relaive o dollar urnover or marke capializaion) since our model emphasizes he abiliy of firms o execue share repurchases o couner liquidiy shocks. A broader raionale is ha since repurchases and invesmens are compeing uses of funds, firms facing severe financing consrains would do less buy backs. Our second measure is firm age, which is based on he premise ha younger firms have a harder ime geing access o public deb markes. Corporae-finance consideraions also sugges ha equiy-dependen firms will end o have high leverage (eiher marke or book), low cash balances and pay less dividends. So our hird measure is he Kaplan-Zingales index and various versions of i, which ake ino accoun wheher a firm is paying dividends, leverage, cash balances, cash flow, and a firm s Tobin s Q (i.e. is marke-o-book raio). 5 Using daa from 1963 o 005, we begin our empirical invesigaion by confirming our premise ha financially consrained firms are less likely o inervene in heir socks. No surprisingly, our hree ses of financing consrain measures are quie correlaed. Noneheless, we find ha all hree measures have incremenal predicive power on firm repurchase aciviy: firms ha have done pas repurchases, older firms and 4 Noe ha a number of he variables in hese hree recen papers are used in earlier work on financing consrains such as Gerler and Gilchris (1994) and Fazzari, Hubbard and Peersen (1988). 5 As we explain below, firm leverage and marke-o-book may be difficul o inerpre in cerain conexs, so we will end up conrolling for hese wo firm characerisics in some of our regressions below. 3

5 lower KZ index firms are more likely o execue repurchases. As such, our empirical analysis below feaures all hree proxies. We hen es our firs predicion in he U.S. sock marke by using cross-secional variaion o see wheher shor-horizon reurn variance (anywhere from daily o quarerly reurns) is higher for financially consrained firms, conrolling for fundamenal or longhorizon reurn variance, which we ake o be eiher he variance of reurn-on-equiy (compued along he lines suggesed by Cohen, Polk and Vuoleenaho (006)) or he variance of hree-year reurns. 6 The resuls are similar so we feaure he variance of reurn-on-equiy. Consisen wih our model, we find ha our measures of financing consrains all come in wih he righ sign and are saisically and economically significan, regardless of he frequency a which we measure shor-horizon reurn variance. For insance, a wo-sandard deviaion increase in KZ (more financially consrained) leads o an increase in weekly reurn variance ha is anywhere from 30% o 40% of he sandard deviaion of weekly reurn variance depending on he version of he KZ index used. We hen aemp o rule ou a number of alernaive hypoheses for hese findings. Indeed, one naural explanaion for why financially consrained firms have higher shorhorizon variance conrolling for fundamenal variance migh have o do wih leverage and disress. While we can conrol o some degree for firm leverage and oher covariaes (such as firm size, ec ), i is impossible o fully rule ou he plausibiliy of alernaive hypoheses such as he leverage/disress hypohesis or oher forms of omied variables wih his approach. As such, we urn o our second predicion, which cus more decisively in favor of our inervenion-repurchase effec: he documened relaion beween variance and consrain ough o be sronger in environmens (regimes) where repurchases are legally easier o execue. Our premise is ha he relaionship beween financing consrains (e.g. firm age) and variances is due o he abiliy of firms o repurchase in he firs place (so ha our financing consrain measures accuraely capure he rue cos of inervenion). So in regimes where repurchases are legally cosly o execue or perhaps even illegal, we 6 An imporan cavea is ha reurn on equiy (ROE) and long-horizon reurn variance are noisy measures of fundamenal volailiy. 4

6 should no find an effec since he rue cos of inervenion for a firm is no simply financing consrains. More echnically, our idenificaion sraegy is o consider a difference-indifference (diff-in-diff) esimae of he effec of financing consrains on shor run variance conrolling for fundamenal variance. Loosely, we firs esimae he crosssecional relaion beween consrains and variances (he firs difference) in he difficulo-repurchase regime. We ake for graned ha his relaion may no be due o our inervenion-repurchase hypohesis bu perhaps o some oher mechanisms. We hen esimae he same relaionship during he easy-o-repurchase regime (he second difference). The difference in hese wo differences is aribued o our inervenionrepurchase effec on he basis ha he oher mechanisms such as leverage risk ough no o vary wih legal regimes regarding repurchases. We are expecing a sronger relaionship in he easy-o-repurchase regime han he difficul-o-repurchase regime. We use wo sources of exogenous variaion o beer idenify our heory. The firs is he regulaory reform in he U.S. sock marke in 198 in he form of SEC Rule 10b-18 ha encouraged repurchases. While share repurchases had always been legal in he U.S., companies sill worried abou class-acion lawsuis accusing hem of manipulaing heir sock prices wih repurchases. The passage of SEC Rule 10b-18 shielded firms from such lawsuis. This law is aribued by many for he rise of share repurchases since (see, e.g., Grullon and Michaely (00)). Since he price effecs arise from firms being able o legally execue repurchases in he firs place, our heory predics ha he (cross-secional) relaions beween financing consrains and reurn variances ough o be sronger afer 198 when he legal cos of doing repurchases wen down. 7 We find ha his is indeed he case---our effec is indeed sronger (boh economically and saisically) afer he regulaory reforms regardless of he financing consrain measures we use. The second source of variaion we use o beer idenify our heory comes from he cross-secion of sock markes around he world. Survey evidence from Kim, Schremper and Varaiya (004) on sock repurchases across he en larges sock markes, U.S., Japan, U.K., France, Germany, Canada, Ialy, he Neherlands, Swizerland and 7 More specifically, in periods in which repurchases are difficul or illegal, a firm s financing consrain under-esimaes he rue cos of inervenion and hence he relaion beween financing consrain measures and firm reurn variances will be weaker during hese periods. A similar saemen applies across counries. 5

7 Hong Kong, indicaes ha hese counries fall naurally ino hree groups in erms of legal ease of repurchases: easy, medium and difficul. Our ime period of analysis is During his period, he easy group comprises of he U.S., U.K. and Canada, and he difficul group comprises of France and Germany (in which repurchases were basically illegal). The oher five counries in he medium caegory are more heavily regulaed han he U.S. bu repurchases were no illegal during his period. We do no have a consisen se of repurchase and firm age daa across counries bu are able o consruc he KZ measures and use he laer in our analysis. Remarkably, we find, consisen wih our heory and following he same logic (diff-in-diff esimae) as for he US regulaory experimen, ha he prediced relaions beween he KZ measures and reurn volailiy are sronger in he easy group han in he medium group and sronger in he medium group han in he difficul group. Imporanly, for he difficul group, he relaion beween KZ and reurn volailiy is acually of he wrong sign. For he medium group where repurchases are possible, we ge he righ sign and he relaion is marginally significan in some cases. For he easy group, we ge resuls very similar o hose of he U.S. as expeced. Again, hese differences and he ordering of magniude of he coefficiens across hese hree groups are very economically and saisically significan. These wo ess form he crux of our paper. I is imporan o emphasize ha wihou hem, i would be impossible for us o disinguish beween our inervenion sory from he alernaive leverage sory. As such, we make sure ha our ess are robus. Toward his end, we perform diagnosics associaed wih hese diff-in-diff esimaes (as suggesed by Berrand, Duflo and Mullainahan (00)) such as randomizing where o pu he breaks for he US daa and which counries o pu in he differen groups for he inernaional daa. If our findings are spurious, hen we should see he same diff-in-diff resuls as above using hese randomizaion procedures. This is no he case. The randomizaion procedures yield resuls far differen from our diff-in-diff esimaes. Moreover, hese procedures also allow us o confirm ha our sandard errors are reasonable. We also perform a number of addiional robusness checks such as rerunning our regressions as a pooled panel wih clusered sandard errors, rying differen 6

8 specificaions and differen measures of financing consrains and fundamenal variance. And in each insance, we obain remarkably consisen resuls. Finally, we furher srenghen he case for our firm inervenion effec by relaing he skewness of sock reurns o financial consrains. Wih an addiional assumpion ha financing consrain is likely o affec sock repurchases and no issuances, our model delivers a hird predicion---ha hose less financially consrained firms wih more capaciy o repurchase shares quickly afer a marke crash (e.g. crash of 1987) should have more posiively skewed shor-horizon (e.g. daily) reurns. We discuss he meris of he assumpion ha here is an asymmery in he likelihood or cos of inervenion below. Noneheless, we do find suppor for his addiional predicion. Though skewness is more difficul o measure han volailiy and our parameers are esimaed less precisely han in he case of volailiy, we do find ha financially unconsrained firms have more posiively skewed daily reurns and ha his relaionship is sronger afer 198, when repurchases became legally easier o execue. Our paper is novel in exploring he effecs of firm inervenion (paricularly of firms being buyers-of-las resor for heir own sock) on sock reurns and liquidiy. Our findings furher develop he connecion beween corporae finance (e.g. he financing consrains lieraure) and asse pricing/marke micro-srucure (see Sein (1996) and Baker and Wurgler (00)). Our paper inroduces he firm as an imporan se of paricipans in he marke and is of general ineres since he model and is implicaions developed here apply equally well in oher conexs such as he Federal Reserve Bank or he governmen more generally being lenders-of-las resor for he aggregae marke. 8 Our paper proceeds as follows. We develop a simple model o analyze he effec of firm inervenion on sock reurn variance in Secion. We describe he daase in 8 One migh also wonder why we do no exend our model o develop implicaions for expeced reurns and relae hem o financing consrains. One poenial implicaion is ha financing consrained firms have higher expeced reurns precisely because hey are less liquid. There is already a large lieraure ha looks a he relaion beween liquidiy and expeced reurns (see, e.g., Amihud and Mendelson (1986) and Brennan and Subrahmanyam (1996)) and some find ha more illiquid socks indeed have higher expeced reurns. Addiional regressions of reurns on financing consrains would be difficul o inerpre since here are mechanisms oher han liquidiy hrough which financing consrains migh affec expeced reurns (e.g. financially consrained firms underake less of cerain kinds of invesmens, hereby giving he company a differen risk profile). 7

9 Secion 3 and he main empirical resuls in Secion 4. We conclude in Secion 5. All proofs are in he Appendix.. Model In his secion, we develop a simple model which capures how a firm's inervenion in he marke in response o large liquidiy shocks affecs he price behavior of is own sock. The framework we use is similar o ha of Grossman and Miller (1988), in which liquidiy shocks o a subse of invesors give rise o emporary shifs in he demand of a sock. 9 These shifs in demand cause emporary deviaions in he sock price, given limied marke making capaciy in he marke. When he firm inervenes in he marke for is own sock, i effecively serves as a marke maker ogeher wih he oher marke makers. We wan o use he erm marke-maker in he broades possible sense---he firm acs a speculaor (buyer) of las resor in is own sock in conjuncion wih oher speculaors in he marke such as hedge funds. Thus, when a firm is less consrained and more willing o ac as a marke maker, he liquidiy for is own sock also increases. We do no explicily model he overall objecive of he firm (i.e. he agen running he firm). We simply assume he reduced form ha he firm inervenes when prices deviae significanly from fundamenal value. One jusificaion is ha accommodaing liquidiy shocks can someimes be a profiable aciviy because of fricions oulined in Grossman and Miller (1988). Suppose invesors are heerogeneous in facing liquidiy shocks. If some invesors wan o cash ou for liquidiy reasons, oher exising invesors (he firm) can provide liquidiy by buying heir shares if here are no enough marke makers around Se-up 9 Here, we ake he liquidiy shock as exogenous, as in Grossman and Miller (1988). In a recen paper, Huang and Wang (006) show ha hese liquidiy shocks can arise endogenously in he presence of marke fricions. 10 Anoher jusificaion is based on agency heory in which he manager ges compensaed for a high sock price and couners liquidiy shocks so ha he sock price more accuraely reflecs his abiliy (i.e. fundamenals). See Sein (1996) and Baker, Ruback and Wurgler (004) for addiional jusificaions. 8

10 Suppose here are hree daes: = 0,1,. A sock is raded in a compeiive marke, whose cash flow is v ~ a = 1, and v ~ is an i.i.d. normal random variable wih a mean of zero and a variance of σ v. A = 1, ~ x shares of he sock is dumped ino he marke by a se of invesors for liquidiy reasons, where x ~ is a normal random variable (hus can be negaive) wih a mean of zero and a variance of σ x. There is a se of marke makers in he marke who can absorb he liquidiy shock. For now we assume ha heir populaion is µ and heir risk olerance is τ. The oal risk olerance of marke makers is τ M = µτ. 11 Moreover, he firm can also inervene in he marke of is own shares when shor-erm liquidiy shocks move he price of he sock far away from is fundamenal value. In deciding on is inervenion policy, he firm has an effecive risk olerance of τ F and faces a cos o inervene. For convenience, we assume ha boh he marke makers and he firm are iniially endowed wih no shares of he sock. 1 Le θ F denoe he posiion he firm akes in he sock marke o moderae is share price. We assume ha he inervenion cos is linear in he size of he posiion: κ + θ F, θ F > 0 c( θ F ) = 0, θ F = 0 (1) κ θ F, θ F < 0. The inervenion cos assumed above is inended o capure several characerisics of a firm's inervenion behavior. Firs, he cos o inervene prevens he firm from rading is own shares a all imes. Insead, i inervenes only when price deviaions caused by he liquidiy shock is sufficienly large. Second, he hreshold and he srengh of he inervenion may boh depend on he firm's abiliy o adjus is financial posiion. In he 11 These marke makers are needed o se he price under normal circumsances when he firm is no inervening. 1 I may seem arificial o assume ha he firm has zero shares of is own sock. Oher han simpliciy, he moivaion for such an assumpion is as follows. A firm's inervenion in he marke is an aciviy separae from is usual business operaions. Thus, i may rea i separaely when considering is meri, in paricular, is risk-reurn rade-off. Our resuls do no depend on his simplifying assumpion. 9

11 case of share repurchase, for example, he firm's abiliy o inervene in he marke clearly depends on how consrained i is in amassing he funds needed. In he case of seasoned equiy issues, is abiliy depends on he cos o issue new equiy. The linear form of he cos funcion makes he cos dependen on he size of he inervenion. The proporionaliy coefficiens, κ+ and κ, reflec he firm's abiliy o inervene. Moreover, he cos coefficien is in general differen beween share repurchases and sales, reflecing he fac ha consrains and coss can be asymmeric beween hese wo operaions. In paricular, we will assume ha κ > κ +. Tha is, oher hings equal, i is easier for he firm o repurchase is shares from he marke han issuing new shares. In he remainder of he paper, we will furher assume haκ =. Thus, he firm's inervenion only akes he form of share repurchase. Also, we seτ F =, i.e., he firm is risk neural. These wo assumpions help o simplify he analysis, bu are no criical o he resuls. To simplify noaion, we le κ = κ+.. Equilibrium and Price Behavior We now consider he marke equilibrium in he simple model described above and he resuling sock price. Le p~ denoe he sock price a, afer payoff v ~, = 0, 1, (wih v ~0 = 0 ). No arbirage insures ha he sock price a = is simply 0, i.e., ~ p = 0. A = 1, a liquidiy shock x~ occurs. Boh he marke makers and he firm will aemp o accommodae he liquidiy shock. Their desire o provide liquidiy depends on hree facors: he curren price of he sock, he payoff when hey unload he posiion in he fuure, and heir risk olerance. By assuming ha he payoff nex period is ~v, we are effecively assuming ha he liquidiy providers can unload heir posiions a ~v. The uncerainy in ~v reflecs he risk hey have o bear o make he marke. Theorem 1: A = 1, he equilibrium sock price is ~ ~ * p = σ min x x v τ, () ( ) ( ) 1 M, where x = ( τ / σ ) κ 0. A = 0, he equilibrium sock price is given by M v 10

12 p 0 0 ~ ~ / / [ ~ p1 p1 p e ] Ε [ e ] = Ε (3) 1 0 where Ε [ ] denoes he expecaion a ime 0. From he soluion o he equilibrium, we 0 observe he following. In absence of any liquidiy shock, he sock price a = 1 is also zero, which reflecs he fundamenal value of he sock. Noe ha he expeced payoff of he sock is assumed o be zero. Alhough he realized payoff is risky, marke makers and he firm bear no risk in absence of any liquidiy shocks since heir iniial holdings are zero. Consequenly, he price of he sock is also zero. When here is a liquidiy shock x~, however, marke makers and he firm have o bear he risk of he sock if hey accommodae he shock. Naurally, he price has o adjus o compensae hem for he risk. The price adjusmen depends on he risk of he sock σ v, he size of he shock ~ x and he overall risk olerance of he marke. 13 When he liquidiy shock x ~ is smaller han x, he firm does no inervene and he liquidiy shock is fully absorbed by marke makers. The price is deermined by heir risk olerance. Alhough he sock price deviaes from is fundamenal, he size of he deviaion, given by ( σ / τ ) ~ x, is no large enough o rigger he firm o inervene. v M When he liquidiy shock x ~ is larger han x, however, he price deviaion becomes sufficienly large for he firm o sep in. Given ha he firm is assumed o be risk neural, i will absorb he liquidiy shock alone and he deviaion of he sock price from is fundamenal is limied a he hreshold level ( σ / τ v M ) x. The maximum deviaion is deermined by κ, he firm's inervenion cos. From he equilibrium price process, we obain several properies of he sock's reurns. For simpliciy, we consider he dollar reurns on he sock: ~ r v~ + ~ p ~ p, (4) 1 13 Please see, among ohers, Campbell, Grossman and Wang (1993) and Grossman and Miller (1988) for a more elaborae analysis of his. 11

13 n where = 1,. Le σ ( ) denoe he sock reurn variance over n periods, where n = 1,. Thus, we have 1) [ ~ ] [ ~ σ = Var r = Var r ] and σ ) = Var[ ~ r + ~ r ] ( v ( 1 ( 1 have σ ) = σ, where σ v gives he variance of he fundamenal, and. We hen σ (1) = σ + Var[ ~ ] (5) v p where Var ~ p ] denoes he shor-run price variaion due o liquidiy shocks. In general, [ Var[ ~ p ] depends on he variance of liquidiy shocks σ x, he variance of he fundamenal σ v, he risk olerance of marke makers τ M, and more imporanly he firm s cos of inervenion κ. In paricular, we have he following resul: Proposiion 1: Shor-horizon reurn variance is greaer han long-horizon or fundamenal variance. Conrolling for long-horizon or fundamenal variance, shorhorizon reurn variance increases wih he cos of inervenion κ (i.e. financing consrain), i.e., σ (1) κ > 0. Firms wih lower inervenion cos are likely o paricipae in he marke o suppor is share price. As a resul, we will see less deviaion in is sock price from is fundamenals in response o liquidiy shocks and he shor-horizon sock reurns will exhibi less variance holding fixed fundamenal variance. Given he documened persisence of financing consrains, our empirical analysis uilizes cross-secional firm variaion in he cos of inervenion. The dependen variable is naurally a firm s shor horizon variance and he independen variables are fundamenal variance and he various proxies for a firm s financing consrains. We also include oher conrols, which we deail below. The prediced relaionship from Proposiion 1 is ha all else equal, he higher a firm s financing consrain, he higher is shor-horizon variance conrolling for fundamenal variance. Since he price effecs arise from firms being able o legally execue repurchases in he firs place, in periods or regimes in which repurchases are difficul or illegal, a 1

14 firm s financing consrain under-esimaes he rue cos of inervenion and hence he relaion beween financing consrain measures and firm reurn variances will be weaker during hese periods. Hence our heory predics: Proposiion : The cross-secional relaionship beween financing consrains and reurn variances (conrolling for fundamenal variance) ough o be sronger in he period or regime in which he legal cos of doing repurchases is cheaper. As we deail below, we will es Proposiion using wo sources of exogenous variaion: legal reforms in he Unied Saes hrough ime and cross-secional variaion in legal regimes across an inernaional sample. 3. Daa Our daa on U.S. firms come from he Cener for Research in Securiy Prices (CRSP) and COMPUSTAT. From CRSP, we obain daily and monhly sock reurns, closing sock prices, shares ousanding, and share rading volume for NYSE, AMEX and NASDAQ socks. From COMPUSTAT, we obain annual informaion on a variey of accouning variables. To be included in our sample, a firm mus firs have he requisie financial daa on CRSP and COMPUSTAT. We include only common socks (CRSP iem SHRCD=10 or 11) lised on NYSE / AMEX / NASDAQ. We follow oher sudies of he U.S. marke using marke-o-book raios in excluding firms wih book value less han en million and firms wih one-digi SIC codes of 6, which are in he financialservices indusry. We will calculae long-horizon reurn variances using six-year windows and exclude socks wih less han seveny-wo monhly reurn observaions in he six-year window. Our daa on firms for he oher nine counries come from he COMPUSTAT GLOBAL daabase, which begins in From his daabase, we obain monhly closing prices, dividends, shares ousanding and rading volume, which only allow us o calculae variables such as reurn variances a monhly or lower frequencies. Moreover, we are only able o obain a subse of he accouning variables ha are available in he U.S. Namely, his daabase does no have informaion on sock repurchases nor are we 13

15 able o obain firm age. Forunaely, we do have enough daa o consruc various versions of he Kaplan-Zingales index of financing consrains. A. Reurn Variance Measures For each year, we begin in he U.S. sock marke by calculaing for each sock is cash flow variance (CVAR) according o Cohen, Polk and Vuoleenaho (006) using sixyear windows. Cash flow is measured by he logarihm of ROE - raio of clean-surplus gross earnings ( BE BE 1 + D ) o beginning-of-he-period book equiy ( BE 1 ). 14 Dividend gross D is from COMPUSTAT daa iem 1. Firm i s cash flow variance in year is calculaed using six annual daa from year o +5. This variable is denoed by CVAR i.. We hen calculae for each sock he variance of 3-year log reurns using overlapping six-year windows. For insance, firm i s 3-year reurn variance in 1963 (he firs year for his variable) is calculaed using annual daa from 1963 o Using wo hree-year non-overlapping reurns (i.e. he log reurn from he beginning of 1963 o he end of 1965, he reurn from he beginning of 1966 o he end of 1968), we calculae his 3-year reurn variance and annualize i by dividing i by hree. This variable is denoed by TVAR i. Firm i s 3-year reurn variance in 1964 is calculaed wih he same procedure using daa from 1964 o 1969, and so forh for all he oher years in our sample. The las year ha we can calculae TVAR is 000 since our daase ends in 005. For each observaion of CVAR and TVAR, we hen calculae he corresponding shorer horizon reurn variances. For insance, for firm i in 1963, we calculae he variance of daily reurns (denoed by DVAR i ), weekly reurns (denoed by WVAR i ), monhly reurns (MVAR i ), and quarerly reurns (denoed by QVAR i ), using daa from 1963 o all hese variances are calculaed using non-overlapping reurns and are 14 Book equiy BE is defined as sockholders equiy (COMPUSTAT daa iem 16) plus balance shee deferred axes (COMPUSTAT daa iem 74) and invesmen ax credi (daa iem 08) (if available), plus pos-reiremen benefi liabiliies (daa iem 330) (if available) minus he book value of preferred sock. Depending on availabiliy, we use redempion (daa iem 56), liquidaion (daa iem 10), or par value (daa iem 130) (in ha order) for he book value of preferred sock. If sockholders equiy is unavailable from COMPUSTAT, we measure sockholders equiy as common equiy (daa iem 60) plus he book value of preferred sock. If common equiy is no available, we compue sockholders equiy as he book value of asses (daa iem 6) minus oal liabiliies (daa iem 181), all from COMPUSTAT. 14

16 annualized. We repea he same procedure for 1964 using daa from 1964 o 1969 and so forh for all he oher years in he sample. For he oher nine markes during he period of , we calculae he same individual sock reurn variance measures, excep ha we are unable o calculae any daily or weekly numbers. B. Financing Consrain Proxies Our financial consrain proxies for U.S. companies are he following. The firs financing consrain proxy is REPO/VOLUME, a firm s repurchases (COMPUSTAT Iem 115 minus preferred sock reducion divided by daily dollar volume. Preferred sock reducion is from he firs difference of COMPUSTAT iem 10. We will also consider REPO/MKT, a firm s repurchases divided by marke capializaion. These wo measures follow nicely from our heory since he abiliy of a firm o sabilize is sock price depends boh on how much resources i has relaive o how many shares i migh have o sabilize. Dollar volume and marke capializaion capure he poenial size of liquidiy shocks hiing a firm. We winsorized REPO/VOLUME and REPO/MKT a 1% and 99% level. The resuls are similar when he raw REPO/VOLUME and REPO/MKT are used. Firm AGE is defined as he year ha we are considering minus he firs year ha ha firm has price daa in CRSP monhly reurns file, which sars in 195. Our hird financing consrain proxy is he KZ index. Following Lamon, Polk and Saa-Requejo (001) and Baker, Sein and Wurgler (003), we consruc he fivevariable KZ index for each firm-year as he following linear combinaion: KZ i = CF i /A i DIV i /A i C i /A i BLEV i Q i (6) where CF i /A i-1 is cash flow (Iem 14+Iem 18) over lagged asses (Iem 6); DIV i /A i-1 is cash dividends (Iem 1+Iem 19) over asses; C i /A i-1 is cash balances (Iem 1) over sar-of-he-year book asses (Iem 6); book leverage, denoed by BLEV i, which is oal deb divided by he sum of oal deb and book equiy ((Iem 9+Iem 34)/(Iem 9+Iem 34+Iem 16))---his is measured a fiscal year-end; and Tobin s Q is he marke value of equiy (price imes shares ousanding from CRSP) plus asses minus he book value of 15

17 equiy (Iem 60+Iem 74) all over asses. We winsorize he ingrediens of he index before consrucing i. We will also use a modified version of he KZ index ha differs from he original score in ha i excludes a measure of leverage and Tobin s Q: KZ3 i = CF i /A i DIV i /A i C i /A i-1 (7) KZ3 makes more sense han KZ for our purposes because highly levered firms may have higher shor-horizon volailiy for a given fundamenal volailiy if leverage raios change in a paricular manner over ime and Q may proxy for boh invesmen opporuniies and mis-pricing. To he exen ha we wan o rule ou alernaive explanaions relaed o mechanical leverage effecs and mis-pricing, we will drop leverage and Q from he KZ index. 15 I urns ou ha here is lile difference in our resuls beween using KZ3 or KZ. So we will feaure KZ3 in he main resuls and provide he resuls relaing o KZ in he robusness secion. We view he use of hese proxies as simply an effor o resric ourselves o hese previously nominaed variables, so as o avoid daa mining. The sample period is for REPO/MKT and REPO/VOLUME and is for oher US variables. For inernaional companies, he corresponding daa iem numbers from COMPUSTAT GLOBAL are he following. CF i /A i-1 is cash flow (Iem 11+Iem 3) over lagged asses (Iem 89); DIV i /A i-1 is cash dividends (Iem 36+Iem 35) over asses; C i /A i-1 is cash balances (Iem 60) over sar-of-he-year book asses (Iem 89); book leverage, denoed by BLEV i, is (Iem 106+Iem 94)/(Iem 106+Iem 94+Iem 135); and Tobin s Q is he average marke cap plus asses minus he book value of equiy (Iem 146+Iem 105) all over asses. C. Oher Variables 15 A word of warning regarding cash and leverage as proxies for financing consrains is ha consrained firms should endogenously ry o save more cash (see Almeida, Campello and Weisbach (004)) and perhaps save some deb capaciy for he fuure (hus having lower leverage). Almeida, Campello and Weisbach (004) show ha he KZ index, which loads heavily on cash and leverage, migh sor firms crosssecionally in an uninuiive way. Hence, we wan o also rely on oher, perhaps more exogenous, proxies such as firm age o make inferences. 16

18 The oher variables ha we use are very familiar and do no meri much discussion. LOGSIZE i is he log of firm i s sock-marke capializaion a he end of year. TURNOVER i is he average monhly share urnover in sock i defined as shares raded divided by shares ousanding over year. RET i is he average monhly reurn on sock i, also measured over he 1-monh period. LOGMB i is he log of firm i s marke cap a he end of year divided by is book value in year. We also use marke leverage which is denoed by MLEV i, which is he same as BLEV excep ha we replace Iem 16 wih a firm s marke capializaion a he end of ha calendar year. We can calculae hese variables for U.S. and inernaional companies. We also use exchange dummies downloaded from CRSP. D. Summary Saisics The summary saisics for he variables used in he financing consrains relaed regressions are presened in Table 1. We repor he ime series average of cross-secional means and sandard deviaions. We sar wih he saisics for he U.S. sock marke and hen repor he analogous numbers for he oher counries in urn. We firs presen he saisics for annualized reurn variances a differen horizons. The summary saisics for he oher counries are similar in magniude. We hen presen he summary saisics for our financing consrain proxies. We have checked ha hese saisics are similar o hose found in oher sudies such as Baker, Sein and Wurgler (003). Finally, we presen he summary saisics for he oher variables. 4. Empirical Resuls A. Correlaedness of Financing Consrain Proxies and Likelihood of Iniiaing Repurchase Programs We analyze he relaion beween our financing consrain proxies in Table and heir abiliy o predic repurchases. In Panel A, we calculae he conemporaneous correlaion beween he various proxies in a given year. We find ha older firms and firms wih lower values of KZ s (less consrained) are more likely o have high REPO/VOLUME or REPO/MKT values and older firms are more likely o have lower KZ scores. In oher words, hese financing consrain proxies are correlaed. Mos of 17

19 hese correlaions are saisically significan. The resuls are largely he same regardless of hese differen measures, so we plan o feaure REPO/VOLUME and leave REPO/MKT for he robusness checks. In Panel B, we focus on wha deermines (predics) wheher a firm execues repurchases. While his issue has been covered in previous papers, we jus wan o poin ou ha one can predic repurchases using pas repurchases, firm age and he KZ indices. To his end, we gaher addiional daa on which firms iniiae a sock buy-back program in a given year from he SDC Daabase, which repors for each year he firms ha have obained auhorizaion from heir board o iniiae repurchases. The SDC daa spans he period of The variable REPINITIATE i, equals one if a firm i iniiaes a repurchase program in year and zero oherwise. Abou 14.3% of firms in a given year iniiae a new repurchase program. Imporanly, we find in column (1) of Panel B ha firms wih higher values of REPO/VOLUME in year -1 are more likely o iniiae repurchase programs in year. The coefficien in fron of REPO/VOLUME is wih a -saisic of 7.7. This means ha a wo-sandard increase in REPO/VOLUME leads o an increase in he likelihood of repurchase nex year by abou 0.15 (0.0035xx1.6). Compared o he uncondiional mean probabiliy of iniiaion (which is 0.143), his is a subsanial increase in he probabiliy of iniiaion (over wice as likely). Similarly, in column (), we find ha older firms (AGE) are more likely o iniiae a repurchase program and as are lower KZ3 index value firms (less consrained) (see column (3)). These effecs are also economically sizeable (and of similar magniudes) and saisically significan. In column (4), we do a horse race beween each of hese consrain proxies and find ha each has incremenal forecasing power for repurchases nex year. Indeed, he coefficiens in fron of each of hese hree proxies are fairly similar o wha we obained when we considered each one of hem separaely (in columns (1)-(3)), excep ha he coefficien on AGE is aenuaed (now bu sill saisically significan). In Panel C, raher han using he REPINITIATE as he dependen variable, we use REPO/VOLUME. The resuls are similar. So he resuls in Panels B and C clearly show ha hese financing consrain proxies do predic he likelihood of fuure repurchases and hence verifies he premise of our empirical work. Moreover, we have also separaely 18

20 checked ha hese resuls do indeed hold for he year of 87 crash, which was a paricularly relevan source of anecdoal moivaion for our work. In sum, hese findings are consisen wih he idea ha financially consrained firms are less likely o execue repurchases. B. Reurn Variance and Financing Consrains, U.S. Sock Marke We begin by looking a wheher financially consrained firms have a higher shorhorizon reurn variance conrolling for fundamenal variance (Proposiion 1). To his end, we will implemen he following cross-secional regression specificaion: STVAR i = a 0 + a 1 *CONSTRAINT i-1 + a *CVAR i + a 3 LOGSIZE i-1 + a 4 *MLEV i-1 + a 5 *LOGMB i-1 + a 6 *RET i-1 + a 7 *TURNOVER i-1 + INDUSTRYDUMMIES i-1 + EXCHANGEDUMMIES i-1 + ε i, i=1,,n (8) where STVAR i is shor-horizon reurn variance (including DVAR, WVAR, MVAR, QVAR), and CONSTRAINT is a proxy for he degree o which a firm is financing consrained (including REPO/VOLUME, AGE, and KZ3). CVAR, he variance of reurn on equiy, is a noisy measure of fundamenals. This is an imporan cavea when i comes o inerpreing our findings. We ry o deal wih his using long-horizon reurn variance bu his is no a perfec soluion eiher as we discuss below. Here, ε i sands for a generic error erm ha is uncorrelaed wih all oher independen variables. The coefficien of ineres is a 1, which capures he relaion beween financing consrains and shor-horizon reurn variance conrolling for he firm s fundamenal variance and a hos of oher firm characerisics (LOGSIZE, MLEV, LOGMB, RET, TURNOVER, INDUSTRYDUMMIES and EXCHANGEDUMMIES). 16 We hen ake he esimaes from hese annual regressions and follow Fama and MacBeh (1973) in aking heir ime series means and sandard deviaions o form our overall esimaes of he effecs of financing consrains on he shor-horizon reurn variance The indusry dummies use he Fama and French (1997) 48 indusry classificaion. 17 Insead of having TVAR on he righ hand side, one could have one of he shor-erm variances, e.g. look a how he raio of DVAR (daily variance) o WVAR (weekly variance) varies wih financing consrains. We do no expec o find much since his raio is close o one o begin wih and firms do no inervene a 19