1 Journal of Emprcal Fnance 16 (2009) Contents lsts avalable at ScenceDrect Journal of Emprcal Fnance journal homepage: Costly trade, manageral myopa, and long-term nvestment Crag W. Holden a,1, Leonard L. Lundstrum b, a Kelley School of Busness, Indana Unversty, Bloomngton, IN , Unted States b Department of Fnance, College of Busness, Northern Illnos Unversty, DeKalb, IL 60115, Unted States artcle nfo abstract Artcle hstory: Receved 16 July 2007 Receved n revsed form 28 Aprl 2008 Accepted 20 May 2008 Avalable onlne 27 May 2008 JEL classfcaton: G14 G31 Keywords: Investng polcy LEAPS Myopa The costly trade theory predcts that t s much more dffcult to explot long-term prvate nformaton than short-term. Thus, there s less long-term nformaton mpounded n prces. The manageral myopa theory predcts that a varety of short-term pressures, ncludng nadequate nformaton on long-term projects, cause asymmetrcally-nformed corporate managers to undernvest n long-term projects. The ntroducton of long-term optons called LEAPS provdes a natural experment to jontly test both theores, whch are otherwse dffcult to test. We conduct an event study around the ntroducton of LEAPS for a gven stock and test whether corporate nvestment n long-term R&D/sales ncreases n the years followng the ntroducton. We fnd that over a two year perod of tme LEAPS frms ncrease ther R&D/sales between 23% and 28% ($125 $152 mllon annually) compared to matchng non-leaps frms. The dfference depends on the matchng technque used. Two other proxes for long-term nvestment fnd smlar ncreases. We fnd that the ncrease s postvely related to LEAPS volume. We also fnd that the ncrease s larger n frms where R&D plays a larger and more strategc role. We test f a frm becomes less lkely to beat analyst's quarterly earnngs forecasts after LEAPS are ntroduced and fnd support for the hypothess. These results provde both statstcally and economcally sgnfcant support for the costly trade and manageral myopa theores Elsever B.V. All rghts reserved. 1. Introducton Shlefer and Vshny (1990) develop a Costly Trade theory that predcts that t s more dffcult to explot nformaton whose publc resoluton s long-term rather than short-term. They develop a model of asymmetrc nformaton about the tradng ablty of an nformed trader, whch causes captal provders to raton captal avalablty to nformed traders and charge a hgh cost of captal. Ths hgh cost of captal makes t especally dffcult to explot long-term prvate nformaton rather short-term prvate nformaton. Wth endogenous nformaton acquston, ths dffculty n explotng long-term prvate nformaton causes stocks to mpound less long-term nformaton than short-term. 2 Sten (1988) develops a Manageral Myopa theory under whch managers have an ncentve to focus on short-run actons to prop up the current stock prce n order to reduce the lkelhood of a takeover and ths leads them to undernvest n long-term projects. A wde varety of short-term pressures have been suggested as contrbutors to manageral myopa, ncludng short-term tradng by nsttutonal traders, the short-term focus of securty analysts, and the ssue we consder, very lttle nformaton beng mpounded nto securty prces about long-run projects. 3 We use the ntroducton of long-term optons called LEAPS as a natural experment to jontly test both theores, whch are otherwse dffcult to test. Correspondng author. Tel.: E-mal addresses: (C.W. Holden), (L.L. Lundstrum). 1 Tel.: Holden and Subrahmanyam (1996) develop a complementary verson of the Costly Trade theory. In ther model, long-term prvate nformaton s more rsky to explot than short-term nformaton. For hgh enough values of rsk averson, ths causes rsk averse nformed traders to choose to acqure short-term nformaton only. That s, they forego tradng n long-term nformaton, because the utlty cost s too hgh. 3 The extensve lterature on manageral myopa ncludes Narayanan (1985, 1996), Sten (1988, 1989), Thakor (1980), Bzjak, Brckley, and Coles (1993), Bebchuk and Stole (1993), Chemla (2004, 2005), among others /$ see front matter 2008 Elsever B.V. All rghts reserved. do: /j.jempfn
2 C.W. Holden, L.L. Lundstrum / Journal of Emprcal Fnance 16 (2009) It s dffcult to emprcally test the Costly Trade and Manageral Myopa theores because t s dffcult to separate long-term nformatonal events and long-term management actons from short-term events and short-term management actons. An opportunty to make ths separaton s presented by the Chcago Board Optons Exchange (CBOE) ntroducton of long-term optons. They are called Long Term Equty Apprecaton Securtes (LEAPS). LEAPS are Amercan-style, standardzed, exchange-lsted optons on ndvdual stocks. They are smlar n every way to short-term optons except that ther maxmum tme to maturty (39 months) s nearly four tmes greater than short-terms optons. LEAPS lower the cost of tradng on long-term nformaton because of the mplct leverage n optons compared to the underlyng stocks. That s, an nvestment n LEAPS allows one to make a much larger long-term bet than the same dollar nvestment n the underlyng stocks. In theory, a lower cost of long-term tradng should lead to more longterm nformatonal effcency and thus ncrease the ncentve for management to nvest n long-term projects. Ths paper tests ths theoretcal predcton by performng an event study around the ntroducton of LEAPS tradng on a gven stock. We look at three proxes for long-term nvestment: (1) R&D expendtures as a percentage of sales, (2) R&D as percent of assets, and (3) the rato of net property, plant and equpment dvded by current assets (hereafter PP&E/CA). Under the null hypothess, there would be no ncrease n the three proxes n the years followng the ntroducton of LEAPS. Under the alternatve hypothess, there would be an ncrease n the three proxes followng the ntroducton. The CBOE exercses sole dscreton over the selecton of frms upon whch to ntroduce LEAPS. The frms themselves have no nfluence over ths selecton process. We use matchng samples formed n a varety of ways. Our results are robust to the alternatve matchng technques we use. We fnd that over a two year perod of tme LEAPS frms ncrease ther R&D/sales between 23% and 28% (annual R&D spendng ncreases by a total of $125 $152 mllon) compared to matchng non-leaps frms. Smlarly, LEAPS frms ncrease ther R&D/assets between 20% and 22% compared to matchng non-leaps frms. Also, LEAPS frms ncrease ther PP&E/CA between 27% and 35% compared to matchng non-leaps frms. The range of results depends upon the matchng technque used. Our results are statstcally sgnfcant n rejectng the null hypothess and supportng the alternatve. We fnd both statstcally and economcally sgnfcant support for the Costly Trade and Manageral Myopa theores. For the subset of frms wth hgh pror R&D spendng (N3% of sales), we fnd that hgher LEAPS volume n the year of ntroducton leads to greater ncreases n R&D/sales ntensty down the road. Ths supports the theory that a hgher volume of longterm optons should lead to more long-term nformaton beng mpounded nto the prce, whch should lead to a greater ncrease n R&D ntensty. We also fnd that frms wth hgh pror R&D spendng (N3% of sales) have a larger subsequent ncrease n R&D spendng than frms wth low pror R&D spendng (b3% of sales). Ths supports the dea that LEAPS have a greater mpact on frms where R&D plays a larger and more strategc role than they do on frms where R&D s smaller and more perpheral. Graham et al. (2005) documents addtonal myopc behavor. They fnd that a large fracton of managers focus myopcally upon beatng the analyst's quarterly earnngs forecasts. In other words, some managers are wllng to sacrfce long-term payoffs to beat short-term earnngs forecasts. We test the hypothess that a frm becomes less lkely to beat analyst's quarterly earnngs forecasts after LEAPS are ntroduced and fnd support for the hypothess. Our fndngs have mportant mplcatons for boards, opton exchanges, nvestors, and polcy makers. Boards mght encourage optons exchanges to ntroduce long-term optons. Optons exchanges can use the results of ths paper to better understand exstng long-term optons and to help desgn new dervatve securtes. Investors should update ther securty valuatons based on the trade mbalance (buys mnus sells) n LEAPS. Polcymakers should consder that polcy changes that encourage/dscourage LEAPS ntroductons wll have a correspondng mpact on long-term corporate nvestment. The exstng emprcal lterature on the ntroducton of opton tradng nvestgates whether the ntroducton of opton trade ncreases the frm's share prce effcency by ncreasng ncentves to collect prvate nformaton and trade on t. Jennngs and Starks (1986) fnd that market prces adjust more rapdly to new nformaton for frms that have exchange-lsted optons than for those frms wthout opton trade. Damodaran and Lm (1991) fnd that prces adjust more rapdly to new nformaton after optons are lsted. Sknner (1989) fnds that the reacton to earnngs reports s smaller after optons are lsted. Manaster and Rendleman (1982) suggest that the benefts of tradng optons nclude leverage, lower transactons costs, and fewer short-sale restrctons. They tested the hypothess that the nformed trader prefers tradng optons on stocks to tradng stocks. They found that opton prce changes help predct stock prce changes, consstent wth the hypothess that arbtrageurs force the frm's stock prce to adjust to nformaton n opton prces. Ther results mply that the ntroducton of a long-term opton would be assocated wth an ncrease n the quantty and precson of long-term nformaton mpounded nto current share prce. All of these fndngs are consstent wth the hypothess that opton trade ncreases the ncentve to nvest n nformaton about the frm. We contrbute by testng the logcal extenson of ths lterature that the ntroducton of trade on a long-term opton should ncrease the effcency of stock prce wth respect to long-term nformaton. The extant emprcal lterature on manageral myopa nvestgates whether manageral myopa results n managers choosng to meet earnngs forecasts at the cost of value-maxmzng R&D spendng. Graham et al. (2005) report that ther analyss of ther survey of fnancal executves fnds that the majorty of managers would avod a postve NPV project f t meant mssng the current quarter's consensus earnngs forecast, and furthermore, three-quarters would gve up economc value n exchange for smooth earnngs. Bhojraj and Lbby (2005) test whether, n an expermental settng, experenced managers exhbt sgns of myopa when captal market pressure ncreases. They conclude that when choosng between projects where there exsts a conflct between near-term earnngs and total cash flow, experenced managers wll often sub-optmally choose projects that maxmze short-term earnngs at the cost of value maxmzaton. Usng frm-level data Dechow and Sloan (1991) and Baber et al. (1991) fnd results consstent wth manageral myopa n the case of CEO's near retrement, and n the case of money-losng frms, respectvely. Furthermore, Roychowdhury (2006) reports
3 128 C.W. Holden, L.L. Lundstrum / Journal of Emprcal Fnance 16 (2009) evdence of earnngs management by examnng real actvtes (ncludng a reducton of dscretonary expendtures) to meet analyst's earnngs forecasts. Bushee (1998) fnds myopa exacerbated n those frms held by transent nsttutonal nvestors. Cheng et al. (2005) test whether the evdence that managers wll forgo value-maxmzng projects to meet earnngs targets, as reported n Graham et al.'s survey analyss, and corroborated by Bhojraj and Lbby n an expermental settng, are supported by frm-level hstorcal earnngs and R&D data. Cheng et al. examne the frequency wth whch frm's offer earnngs gudance, and fnd that frms that offer more frequent earnngs gudance also spend less on R&D and they also meet analyst consensus more frequently. They conclude that results are consstent wth more frequent earnngs gudance beng assocated wth myopc R&D spendng. In other words, they conclude that the hstorcal emprcal evdence s consstent wth the contenton that managers myopcally forgo value-maxmzng projects n favor of meetng short-term earnngs targets. The extant emprcal lterature on manageral myopa fnds that manageral myopa results n managers choosng to meet earnngs forecasts at the cost of value-maxmzng R&D spendng. We contrbute by testng the logcal extenson of ths lterature, that less manageral myopa s observed as a result of the reducton n captal market pressures that result from LEAPS ntroducton. We do ths by testng whether less manageral myopa s observed subsequent to LEAPS ntroducton by examnng both R&D spendng and the frequency wth whch LEAPS frms meet analyst earnngs forecasts. The paper proceeds as follows. Secton 2 dscusses the ntroducton of LEAPS. Secton 3 presents the emprcal specfcaton. Secton 4 presents the sample and descrptve statstcs. Secton 5 presents the man results. Secton 6 examnes the relaton between LEAPS volume and changes n R&D ntensty. Secton 7 presents an addtonal robustness check. Secton 8 examnes changes assocated wth LEAPS ntroducton n the frm's propensty to meet earnngs forecasts. Secton 9 concludes. 2. The ntroducton of LEAPS Pror to 1973, optons could only be traded n the over the counter market. In 1973, the Chcago Board Optons Exchange (CBOE) became the frst exchange to lst and trade short-term optons wth a maxmum of 12 months maturty. Today, short-term optons are lsted on sx U.S. exchanges and dozens of exchanges around the world. In 1990, the CBOE ntroduced long-term optons (LEAPS) wth a maxmum of 39 months expry. The CBOE stated ratonal was that LEAPS would result n lower trade costs because of the leverage that they offer. It was also suggested that LEAPS would appeal to nvestors wth longer horzons. 4 Long-term optons can be replcated wth a complex combnaton of short-term optons and money-market securtes, but Choe and Novomestky (1989) fnd that replcaton s expensve n terms of transacton costs. To date, LEAPS have only been ntroduced on frms upon whch exchange-lsted short-term optons are currently tradng. The decson to ntroduce LEAPS trade on a partcular stock s made by the CBOE. It may be thought of as largely an exogenous shock. Km and Young (1991) note that the decson to ntroduce ether a short-term opton or LEAPS on the exchange s not made by the manager of the frm on whch the opton trades and thus cannot be a sgnal. Furthermore, Jennngs and Starks (1986) note that the ntroducton of opton trade s not random, but rather the decson to ntroduce short-term opton trade depends upon nvestor nterest, stock tradng actvty and stock prce volatlty. Km and Young (1991) and Holland and Wngender (1997) fnd zero abnormal announcement return on short-term opton and LEAPS ntroductons, respectvely. Ths s not surprsng snce the crtera and the data that the CBOE uses to decde on the ntroducton of short-term opton and LEAPS ntroductons s publcly avalable. Whle t has always been possble to buy over-the-counter, long-term optons on ndvdual stocks, trade n standardzed exchangelsted LEAPS should be less costly than tradng a smlar, prvate contract. For LEAPS to ncrease the effcency of stock prce of frms wth long-term cash flows, they need only reduce the trade cost dfferental between short- and long-term nformaton enough so that the nformed trader can realze an ncrease n ther profts by tradng long-term nformaton. By reducng the costs of nformed trade on long-term nformaton, LEAPS should result n postve externaltes for the frm. Specfcally, the Costly Trade and Manageral Myopa theores mply an ncrease n nvestment n long-term projects when LEAPS are ntroduced. The null hypothess follows. H1. The frm's nvestment n projects wth long-term cash flows does not ncrease when LEAPS are ntroduced on the frm's shares. 3. Emprcal specfcaton Followng the ntal ntroducton of LEAPS trade on a lmted number of stocks n 1990, LEAPS were ntroduced on addtonal stocks n the followng years. A sample of frms upon whch LEAPS were ntroduced s collected and referred to as the Introducton Sample. The percent change n the frm's annual nvestments n projects wth long-term cash flows s examned around the year n whch LEAPS trade was ntroduced. Research and Development expense s used as the emprcal proxy for nvestment n long-term projects for three reasons. Frst, theoretcal work on corporate long-term nvestment by Sten (1989), Noe and Rebello (1997) and Bebchuk and Stole (1993) explctly suggests the use of Research and Development expense to measure nvestment n long-term projects. Second, the pror emprcal work of Meulbroek and Mtchell (1990), Knoeber (1986), Bushee (1998) and Dechow and Sloan (1991) use of Research and Development expenses to examne corporate nvestment n long-term projects. Thrd, the long-term tme lag between the nvestment decson and the assocated returns for Research and Development expendtures makes t a good proxy for nvestment n long-term projects. The percentage change n the frm's annual R&D s dvded by sales to control for sze effects. R&D/sales s referred to as the R&D Intensty n what follows. The year n whch the LEAPS trade s ntroduced s referred to as year zero. A ( 1,1) wndow s used to 4 The Fnancal Tmes, September 12, 1990, p.31.
4 C.W. Holden, L.L. Lundstrum / Journal of Emprcal Fnance 16 (2009) measure the change n R&D ntensty from 1 year pror to the ntroducton to the year followng the ntroducton to examne the percentage change n R&D ntensty. As frms may be slow to adjust R&D n response to an ntroducton, an alternatve ( 1,2) wndow s used. Ths measures the change n R&D ntensty from the year precedng the ntroducton to the second year followng the ntroducton. The hypothess, H1, that R&D ntensty does not ncrease when LEAPS trade s ntroduced on the frm's shares s tested usng a one-taled T-test. A set of control frms s used to control for other sources of varaton n the frm's R&D ntensty. The control frms are dentfed by matchng the sample frms on: (1) ndustry, (2) market-to-book equty, and (3) cash dvded by assets. Market-to-book proxes for the level of growth opportuntes faced by the frm. Cash dvded by assets proxes for the ablty of the frm to make R&D nvestments wthout accessng the captal market. A frm wth greater nvestment opportuntes and/or more cash may, all else equal, ncrease R&D for reasons unrelated to the LEAPS ntroducton. Data on fnancal statement tems ncludng market-to-book equty, cash, assets, and SIC code are obtaned from the Compustat annual fles. Each LEAPS frm s matched wth a control frm n year 1. Therefore the match occurs pror to the LEAPS ntroducton. The matchng technology employed by Huang and Stoll (1996) s utlzed to select a match frm. Each frm n the LEAPS ntroducton sample s matched wth all potental match frms n the same 4-dgt SIC code. For each matched par, the followng match score S s calculated as 0 S MtB LEAPS MtB LEAPS MtB NoLEAPS þ MtB NoLEAPS 1 2 A þ =2! 2 Cash=Assets LEAPS Cash=Assets NoLEAPS ; ð1þ Cash=Assets LEAPS þ Cash=Assets NoLEAPS =2 where MtB s market-to-book equty, LEAPS refers to a frm n the LEAPS sample, ndexes LEAPS sample frms and NoLEAPS refers to a matchng frm n the same SIC code. The matchng frm wth the smallest matchng score s chosen. As a robustness check, an alternatve control set s constructed by matchng on ndustry as defned at a 3-dgt SIC code level. The S score matchng procedure s repeated at the 3-dgt SIC code level. The percentage change n R&D ntensty net of the match frm s calculated for both SIC code levels. In addton to examnng the percentage change n R&D spendng net of a match frm, we examne the percentage change net of that of a portfolo of match frms. Control portfolos are dentfed at both the 4-dgt and 3-dgt SIC code levels. The control portfolo s defned as all frms n the frm's SIC code, for whch ether market-to-book or cash/total assets are wthn 20% of the value of ether varable for the LEAPS frm. 4. Sample and descrptve statstcs The sample of LEAPS ntroductons s drawn from the perod that begns wth the frst ntroducton of LEAPS, n October 1990, and ends n We begn wth a sample of 378 frms upon whch the Chcago Board Optons Exchange has ntroduced these long-term optons. The date for each LEAPS ntroducton s located on ether Lexus-Nexus or Dow Jones Interactve. Table 1 presents the sample. We start wth 378 LEAPS ntroductons from 1990 to The LEAPS sample excludes frms that do not report R&D expendtures durng the years mmedately adjacent to the ntroducton year. There s suffcent data to examne 94 of the ntroductons. Data losses nclude 72 ntroductons for whch no ntroducton date s avalable and 187 ntroductons on frms for whch suffcent data are not avalable on Compustat to complete the analyss and 25 for whch data s not yet avalable on COMPUSTAT for the end of the second year subsequent to ntroducton. Panel A of Table 1 presents the dstrbuton of ntroductons over tme. The dstrbuton of LEAPS ntroductons s: 9 n 1990, 4 n 1991, 10 n 1992, 11 n 1993, 17 n 1995, 5 n 1996, 12 n 1997, 4 n 1998, 21 n 2001 and 1 n Panel B presents the LEAPS volume compared to Total Equty Opton Volume. LEAPS volume and total equty opton volume are gathered manually from the Annual Market Statstc books publshed by the Chcago Board Optons Exchange. The volume proxy s LEAPS annualzed LEAPS volume as a percentage to total equty opton volume. Volume s annualzed by multplyng the average daly volume calculated by a standard number of tradng days per year, 252. Durng the ntroducton year, year 0, the average daly volume s calculated only over those trade days from the date of ntroducton to year end. For any level of LEAPS annualzed volume, the LEAPS volume may be more mportant to the resoluton of nformaton problems for a frm that has a lower level of equty opton trade than to a frm wth hgher levels of ordnary opton trade. The LEAPS volume percentage attempts to control for the LEAPS volume relatve to total equty opton volume. Each of the proxes s collected for years 0, 1 and 2. The average LEAPS securty trades 10,554 contracts a year n year 0, 24,890 contracts n year 1 and 31,607 contracts n year 2. As a percentage of annual equty opton volume, annualzed LEAPS volume makes up 4.2% of equty opton volume n year 0, 13.0% n year 1 and 8.6% n year 2. Panel C of Table 1 presents the year 1 parameters on whch LEAPS frms are matched wth the control frms. The control sample s matched on cash/assets and market-to-book. A varety of percentle values for the match varables are presented here. We fnd that the ntroducton of LEAPS s concentrated n three ndustres: 20 n Chemcals and Alled Products (SIC 28), 19 n Electronc and other electrcal equpment, except computer equpment (SIC 36), and 14 n Busness Servces (SIC 73). Apparent ndustry concentraton suggests that an ndustry control may be mportant n examnng LEAPS affects. The medan number of frms operatng n the frm's ndustry defned by ts 4-dgt SIC code s 43. The average matchng score calculated at the 3-dgt levels s smaller than the average matchng score calculated at the 4-dgt level. Whle the 4-dgt matchng frm may not have the smallest score, t may be n a lne of busness that s more smlar than s the 3-dgt match frm.
5 130 C.W. Holden, L.L. Lundstrum / Journal of Emprcal Fnance 16 (2009) Table 1 Descrptve statstcs Panel A: Sample ntroductons by year. The annual number of sample LEAPS ntroductons by calendar year. Year Total Introductons Panel B: LEAPS volume compared wth total equty optons volume. Annual volume s the annualzed volume for the LEAPS frms. Total equty optons annual volume (contracts) s the total of annualzed LEAPS and ordnary equty opton trade volume. Annualzed volume s the average daly volume for all the days durng the year of ntroducton, tmes 252 standardzed tradng days per year. LEAPS/total equty optons s the annualzed LEAPS volume dvded by total equty optons volume. Varables Year 0 Year +1 Year +2 LEAPS annual volume (contracts) 10,554 24,890 31,607 Total equty optons annual volume (contracts) 441, , ,936 LEAPS/total equty optons 4.2% 13.0% 8.6% Panel C: Comparson of LEAPS sample and control frms n year 1. Descrptve statstcs are for the year before the ntroducton year (year 1) for the 94 sample frms on whch Long-term Equty Apprecaton Securtes (LEAPS) were ntroduced durng the perod, and for whch data s avalable to analyze the change n R&D n the subsequent years. Income statement, balance sheet and market value data are for the year end mmedately precedng the date on whch LEAPS were ntroduced. Annual share trade volume s for the fscal year end mmedately precedng the date on whch LEAPS were ntroduced. Market-to-book equty s market value of equty dvded by book value of equty. Cash/total assets s cash dvded by total assets. LEAPS frms are the sample of frms on whch LEAPS were ntroduced. Control frms are matched on ndustry, market-to-book equty and cash/total assets. Best match frms are dentfed by matchng on Market-to-book equty and cash/total assets. Varables 10th Percentle 25th 50th Percentle 75th Percentle 90th Percentle Market-to-book equty LEAPS sample Control frms: Best match n 4-dgt ndustry Portfolo n 4-dgt ndustry Best match n 3-dgt ndustry Portfolo n 3-dgt ndustry Cash/total assets LEAPS sample Control frms: Best match n 4-dgt ndustry Portfolo n 4-dgt ndustry Best match n 3-dgt ndustry Portfolo n 3-dgt ndustry The ndustry concentraton of LEAPS ntroductons dscussed above suggests that ndustry controls may be mportant when solatng the effects of LEAPS. 5. Man results 5.1. Dollars of R&D We examne dollar change n R&D over two wndows surroundng year 0. The two wndows are denoted as ( 1,1) and ( 1,2). The ( 1,1) wndow measures the dollar change n the frm's annual R&D from the fscal year pror to the ntroducton to the fscal year mmedately subsequent to the fscal year durng whch the ntroducton occurred. The ( 1,2) wndow s defned analogously and ends n year 2. Table 2, Panel A, presents the mean dollar change n R&D. For the LEAPS frm R&D ncrease $ mllon and $ mllon over the ( 1,1) and ( 1,2) wndows, respectvely. The mean dollar changes for the control frms for ( 1,1) are an order of magntude lower than the LEAPS frms, and range from $9.38 mllon to $43.34 mllon. The same pattern holds for the medans, but a somewhat lower level than the means. Medan growth n dollars of R&D are $36.89 and $42.35 mllon over the two wndows. The medan dollar changes for the control frms are also an order of magntude lower than the LEAPS frms, rangng from $1.83 mllon to $13.33 mllon. Consderng both the mean and medan results, the strong dfference between LEAPS and controls frms holds across the board R&D/sales Next, we examne the percent change n R&D/sales. Results are presented n Panel A, the mean percent change n R&D/sales for LEAPS frms s 22.32% over ( 1,1) and 21.19% over ( 1,2). The mean percent change for the control frms are all negatve, rangng from 6.25% to 2.38%. The same pattern holds for the medans, but at a lower level.
6 C.W. Holden, L.L. Lundstrum / Journal of Emprcal Fnance 16 (2009) Table 2 Alternatve measures of long-term nvestment for LEAPS sample and control frms The ( 1,1) wndow measures the change n the varable from the fscal year pror to the ntroducton of LEAPS to the fscal year mmedately subsequent to the fscal year durng whch the ntroducton occurred. The ( 1,2) wndow s defned analogously. R&D s Research and Development expense, PP&E s the net property plant and equpment dvded bycurrent assets. Balancesheetvalues arefromyearend, andsales and R&Dare annual. Fordollaramountof R&D thechangesnmllons of dollars, fortheothervarables the change s the percentage change n the rato. p-values are for the two-taled test of the null hypothess that the change n the varable s equal to zero. LEAPS sample s the sample of 94 LEAPS frms from Best match n 4-dgt (3-dgt) ndustry s the sngle frm that matches the closest and the portfolo n 4-dgt (3- dgt) ndustry s a portfoloofcontrolfrms wthn a bracket of the LEAPS frm. Sample sze s 94 on RD dollars, R&D/sales, R&D/assets and 88 on PP&E/CA. Panel A Varables Mean ( 1,1) T-test Mean ( 1,2) T-test Medan ( 1,1) sgn-rank Medan ( 1,2) sgn-rank Dollar change n R&D LEAPS sample $ (0.0001) $ (0.0002) $36.89 (0.0001) $42.35 (0.0001) Control frms Best match n 4-dgt ndustry $10.17 (0.1128) $22.98 (0.0433) $1.83 (0.0001) $9.27 (0.0001) Portfolo n 4-dgt ndustry $14.84 (0.0512) $9.95 (0.1739) $6.52 (0.0001) $2.32 (0.0001) Best match n 3-dgt ndustry $9.38 (0.1232) $43.34 (0.0870) $1.88 (0.0001) $2.63 (0.0001) Portfolo n 3-dgt ndustry $13.37 (0.0153) $23.08 (0.0007) $5.36 (0.0001) $13.33 (0.0001) % Change n R&D/sales LEAPS sample (0.0037) (0.0044) 7.33 (0.0031) 5.14 (0.0141) Control frms Best match n 4-dgt ndustry 2.78 (0.5510) 2.38 (0.5493) 0.56 (0.7948) 0.16 (0.9181) Portfolo n 4-dgt ndustry 3.25 (0.1534) 4.44 (0.0787) 6.22 (0.1840) 7.89 (0.0002) Best match n 3-dgt ndustry 2.86 (0.4736) 6.61 (0.0794) 1.61 (0.5038) 6.50 (0.0523) Portfolo n 3-dgt ndustry 4.53 (0.0159) 6.25 (0.0035) 3.92 (0.0212) 8.30 (0.0001) % Change n R&D/assets LEAPS sample (0.0101) (0.0329) 4.35 (0.0785) (0.2452) Control frms: Best match n 4-dgt ndustry 2.13 (0.6093) 6.19 (0.1116) 0.18 (0.4990) 5.32 (0.1204) Portfolo n 4-dgt ndustry 0.25 (0.9053) 4.13 (0.0667) 1.28 (0.9389) 4.58 (0.1241) Best match n 3-dgt ndustry 6.75 (0.0950) 5.80 (0.1245) 4.30 (0.0969) 4.86 (0.0533) Portfolo n 3-dgt ndustry 0.58 (0.7417) 5.65 (0.0038) 0.03 (0.9717) 4.21 (0.0015) % Change n PP&E/current assets LEAPS sample (0.0045) (0.0087) 2.37 (0.1233) 3.35 (0.3009) Control frms Best match n 4-dgt ndustry 0.91 (0.8413) 2.46 (0.6092) 0.21 (0.6677) 5.65 (0.4773) Portfolo n 4-dgt ndustry 2.64 (0.1816) 5.40 (0.0274) 0.32 (0.1361) (0.0125) Best match n 3-dgt ndustry 0.68 (0.8802) 3.27 (0.4750) 0.64 (0.7227) 1.08 (0.8527) Portfolo n 3-dgt ndustry 2.70 (0.1080) 5.05 (0.0153) 0.67 (0.1005) 4.71 (0.0004) Panel B: Dfferences n percent change of alternatve measures of long-term nvestment. Dfference n % change s the dfference between the LEAPS frm's percentage change and the best match frm's percentage change. The dfference s defned analogously for LEAPS Portfolo n 4-dgt ndustry, wth the average value of the portfolo of control frms for each LEAPS frm replacng the best match frm n the prevous defnton. Sample sze s 94 on R&D/sales and R&D/assets and 88 observatons on PPE/CA. p-values are for the two-taled test of the hypothess that the dfference n % change s equal to zero. Varables Mean ( 1,1) T-test Mean ( 1,2) T-test Medan ( 1,1) sgn-rank Medan ( 1,2) sgn-rank Dfference n % change n R&D/sales LEAPS Best match n 4-dgt ndustry (0.0062) (0.0040) 5.07 (0.0613) 4.87 (0.0319) LEAPS Portfolo n 4-dgt ndustry (0.0010) (0.0004) (0.0007) (0.0002) LEAPS Best match n 3-dgt ndustry (0.0033) (0.0009) (0.0195) (0.0020) LEAPS Portfolo n 3-dgt ndustry (0.0007) (0.0003) (0.0002) (0.0001) Dfference n % change n R&D/assets LEAPS Best match n 4-dgt ndustry (0.0957) (0.0116) 1.04 (0.3938) 9.81 (0.0106) LEAPS Portfolo n 4-dgt ndustry (0.0128) (0.0088) 5.63 (0.0740) 6.57 (0.0138) LEAPS Best match n 3-dgt ndustry (0.0015) (0.0054) 9.61 (0.0091) (0.0171) LEAPS Portfolo n 3-dgt ndustry (0.0103) (0.0045) 3.73 (0.0778) 7.13 (0.0062) Dfference n % change n PP&E/CA LEAPS Best match n 4-dgt ndustry (0.0089) (0.0145) 4.58 (0.0263) 8.22 (0.0213) LEAPS Portfolo n 4-dgt ndustry (0.0014) (0.0030) 2.05 (0.0345) 7.60 (0.0391) LEAPS Best match n 3-dgt ndustry (0.0060) (0.0255) 3.29 (0.0375) 5.38 (0.2395) LEAPS Portfolo n 3-dgt ndustry (0.0014) (0.0030) 3.48 (0.0179) 7.06 (0.0541) Panel B reports the dfferences n percent changes of alternatve measures of long-term nvestment. For ( 1,1), the dfference n percent change of R&D/sales net of the 4-dgt control frm s 25.10% (p-valueb0.0062), and 25.57% (p-valueb0.0010) net of the 4-dgt portfolo. Results net of the 3-dgt control frm and control portfolo are qualtatvely smlar.
7 132 C.W. Holden, L.L. Lundstrum / Journal of Emprcal Fnance 16 (2009) For ( 1,2), the dfference n percent change of R&D/sales net of the 4-dgt control frm s 23.57% (p-valueb0.0040), and 25.63% (p-valueb0.0004) net of the 4-dgt control portfolo. Results net of the 3-dgt control frm and control portfolo are qualtatvely smlar. The results of examnng medan dfferences n percent changes are qualtatvely the same although of smaller magntude and nearly all are sgnfcant at the 5% level n the sgned-rank test. Overall, these results reject H1 and provde strong support of the jont theores of Costly Trade and Manageral Myopa. We conclude that the ncrease for LEAPS s sgnfcantly and robustly greater than the control frms, however defned R&D/assets For addtonal robustness, we examne R&D scaled by assets rather than by sales. In Panel A, the mean percent change n R&D/ assets for LEAPS frms s 12.59% over ( 1,1) and 16.28% over ( 1,2). The mean percent change for the control frms are nearly all negatve, rangng from 6.75% to 2.13%. The same pattern holds for the medans, but at a lower level. Panel B reports the dfferences n percent changes of alternatve measures of long-term nvestment. For ( 1,1), the dfference n percent change of R&D/sales net of the 4-dgt control frm s 10.46% (p-valueb0.0957), and 12.84% (p-valueb0.0128) net of the 4-dgt portfolo. For ( 1,2), the dfferences are 22.47% (p-valueb0.0116), and 20.41% (p-valueb0.0088), respectvely. Results net of the 3-dgt control frm and control portfolo are qualtatvely smlar. The results of examnng medan dfferences n percent changes are qualtatvely the same although of smaller magntude and nearly all are sgnfcant at the 5% level usng the sgned-rank test. Overall, these results provde robust confrmaton of rejectng H1 and supportng the jont theores of Costly Trade and Manageral Myopa PP&E/CA We construct another proxy for the frm's relatve choce of long-term nvestment to short-term nvestment usng the rato of net property, plant and equpment dvded by current assets (hereafter PP&E/CA). If subsequent to LEAPS ntroducton frms shft ther assets more towards the long-term, we expect to see ths rato ncrease. We examne the change n ths rato around LEAPS ntroducton. For ( 1,1), the dfference n percent change of PP&E/CA net of the 4-dgt control frm s 21.31% (p-value b0.0089), and 23.04% (p-value b0.0014) net of the 4-dgt portfolo. For ( 1,2), the dfferences are 32.44% (p-value b0.0145), and ncreases 35.39% (p-valueb0.0030), respectvely. Results for the 3-dgt control frm and control portfolo are qualtatvely smlar. Tests of medan changes are qualtatvely smlar but of smaller magntude. Overall, these results provde addtonal robust confrmaton of rejectng H1 and supportng the jont theores of Costly Trade and Manageral Myopa. 6. The relatonshp between R&D ntensty changes and LEAPS volume Theoretcally, greater volume of long-term optons should lead to more long-term nformaton beng mpounded nto the prce, whch should lead to a greater ncrease n R&D ntensty. We test ths theoretcal predcton by analyzng the cross-sectonal relatonshp between the longness of opton volume and the change n R&D ntensty. Our proxy for the longness of opton volume s annualzed LEAPS volume n year 0 as a percentage of total equty opton volume n year 0. Prevous research on manageral myopa, usng R&D, has often screened out frms wth lower levels of R&D to focus on those wth a more economcally sgnfcant level of R&D spendng. It s possble that LEAPS volume s related to the change n R&D ntensty for those frms for whch the level of R&D s more economcally sgnfcant. Dechow and Sloan (1991) and Lundstrum (2002) both examne changes n R&D/sales to test theores of manageral myopa and both requre that R&D/sales meet some ndustry mnmum levels of R&D ntensty. Dechow and Sloan mplement a 5% R&D/sales mnmum whle Lundstrum uses a 3% mnmum. Dechow and Sloan use the mnmum ntensty to dentfy ndustres n whch large Research and Development expendtures are common. Lundstrum argues for the 3% mnmum to be sure that the level of R&D expendtures are sgnfcant n the ndustry-year. A mnmum R&D ntensty screen s an approprate screen here as any potental ms-prcng assocated wth R&D spendng s more lkely to be more mportant to the manager when the level of spendng exceeds some economcally sgnfcant level. We examne the relatonshp between the change n R&D ntensty and LEAPS volume after controllng for year effects and the level of R&D ntensty n year 1. R&D ntensty n year 1 of 3% corresponds to approxmately the twenteth sample percentle of R&D ntensty. Screenng out those observatons for whch year 1 R&D/sales does not exceed 3% of sales leaves a sample of 70 observatons. We estmate the followng regresson ncludng only those frms for whch R&D/sales exceeds 3%. ΔR&D=salesð 1; 1Þ ;t ¼ α þ γ 1 Lvolume þ γ 2 R&D=sales 1 þ e ;t ; ð2þ 0: :0110 0: :7554 0:0232 0:0001 where ΔR&D/sales( 1,1) s the LEAPS change n R&D ntensty, Lvolume s the LEAPS annualzed volume percentage n year 0, R&D/ sales 1 s the frm's R&D ntensty n year negatve 1. Year ndcator varables are also ncluded n the estmaton but are not shown. The coeffcent estmates are presented beneath the parameters wth p-values for the two-taled T-test of the hypothess that the coeffcent s equal to zero dsplayed n parenthess beneath the coeffcent estmate.
8 C.W. Holden, L.L. Lundstrum / Journal of Emprcal Fnance 16 (2009) Table 3 Regressons of R&D/sales ( 1,1) ntensty change on LEAPS volume for frms wth R&D/salesN3% Dependent varable Independent varable: LEAPS volume n year 0 as a percentage of total equty opton volume % Change n R&D/sales Regresson coeffcent p-value LEAPS Best match n 4-dgt ndustry (0.0279) LEAPS Portfolo n 4-dgt ndustry (0.0153) LEAPS Best match n 3-dgt ndustry (0.0602) LEAPS Portfolo n 3-dgt ndustry (0.0170) Coeffcent estmates and p-values for the two-taled test of the null hypothess that the coeffcent s equal to zero. Coeffcents estmated usng Ordnary Least Squares. The R&D Intensty change proxy s the dependent varable n the regresson, and proxes are as descrbed prevously. The Independent varable n year 0 s the annualzed LEAPS volume as a percentage of total annual equty opton volume. Annualzed volume s the average daly volume (computed from all the days durng the year of ntroducton), tmes 252 tradng days per year. Total annual equty opton volume s the sum of annualzed LEAPS volume plus the ordnary annual opton volume. Coeffcents are also estmated on R&D/sales n year 1 and year dummes, but not reported here. p-values are for the two-taled test of the hypothess that the coeffcent s equal to zero, and are dsplayed n parenthess. Sample ncludes only those frms for whch R&D/sales n year 1 exceeds 3%, a sample of 70 observatons. Results appear n Table 3. The p-value for the test of model sgnfcance for ths sample s less than 5%, n each of the regressons. The coeffcent estmate on LEAPS volume percentage s postve and sgnfcant at (p-valueb0.0232) and the coeffcent on year 1 R&D ntensty s (p-valueb0.0001). Results are not substantvely dfferent f the change n LEAPS R&D/sales ntensty s replaced wth the LEAPS less best match or less a portfolo of match frms. Usng the full sample we examne whether there s some mnmum level of LEAPS volume for whch LEAPS volume s sgnfcantly related to the change n R&D ntensty. We use the full sample to re-estmate Eq. (2) and fnd that the coeffcent on the LEAPS volume percentage s not sgnfcantly dfferent from zero (results not reported). We conclude that for those frms that have an economcally sgnfcant level of R&D ntensty, the change n R&D ntensty around LEAPS ntroducton s ncreasng n LEAPS volume n the precedng year. Results are consstent wth the theores, and consstent wth the hypothess that the change n R&D ntensty s postvely related to the LEAPS volume n the pror year. 7. An addtonal robustness check We examne the evdence on whether the change n R&D ntensty s greater for those frms that have hgher level of R&D ntensty before LEAPS are ntroduced. The dea s that R&D may have a more central and strategc role for hgh R&D ntensty frms. Whereas, t may play be more of a perpheral role for low R&D ntensty frms. Hence, LEAPS may have a greater mpact on hgh R&D ntensty frms than on low frms. We agan partton the sample nto low ntensty frms, defned here as those frms wth R&D/sales less than 3%, and hgh R&D ntensty frms, those frms wth R&D/sales of 3% or greater. Table 4 reports the mean dfference n the percentage change n R&D/sales net of control frm(s) separately for low ntensty frms (19 frms) and hgh ntensty frms (75 frms). For ( 1,1), the dfference n % change for LEAPS net of the best match frm n 4-dgt ndustry s 21.65%, but s not statstcally sgnfcant (p-valueb0.2338) for low ntensty frms. Ths nsgnfcance s lkely due to the very small sample sze (19). For hgh Table 4 Mean dfferences n % change n R&D/sales for low and hgh R&D ntensty frms R&D/sales b3% R&D/sales N=3% Dfference n % change n R&D/sales Wndow ( 1,1) T-test Wndow ( 1,1) T-test LEAPS Best match n 4-dgt ndustry (0.2338) (0.0145) LEAPS Portfolo n 4-dgt ndustry (0.2216) (0.0025) LEAPS Best match n 3-dgt ndustry (0.1898) (0.0091) LEAPS Portfolo n 3-dgt ndustry (0.1629) (0.0021) R&D/sales b3% R&D/salesN=3% Dfference n % change n R&D/sales Wndow ( 1,2) T-test Wndow ( 1,2) T-test LEAPS Best match n 4 dgt ndustry (0.3522) (0.0064) LEAPS Portfolo n 4 dgt ndustry (0.5022) (0.0003) LEAPS Best match n 3 dgt ndustry (0.3362) (0.0015) LEAPS Portfolo n 3 dgt ndustry (0.2910) (0.0005) Dfference n % change n R&D/sales s the dfference between the LEAPS frm's percentage change and the best match frm's percentage change. Results have been pooled across frm-years. Wndow ( 1,1) s the sample average percentage change net of the best match frm. R&D/sales b3% s for the sample for whch R&D/sales s less than 3% n year 1. At year 1, there are 19 frms wth R&D/sales less than 3% and 75 frms wth R&D/sales of at least 3%. p-value s for the two-taled T-test of the hypothess that the percentage change net of the match frm s equal to zero.
9 134 C.W. Holden, L.L. Lundstrum / Journal of Emprcal Fnance 16 (2009) Table 5 Proporton of quarterly earnngs that beat or meet the mean analyst forecast Year ( 1, 1) Year ( 1, 2) Sample Year -1 Year 1 Year 1 Year 1 LEAPS Control Year 2 Year 2 Year 1 LEAPS Control LEAPS (0.5309) (0.5774) 4-dgt match (0.0013) (0.0057) (0.0482) 9.71 (0.2709) 3-dgt match (0.7130) 1.35 (0.8810) (0.8805) 2.20 (0.6967) 4-dgt portfolo (0.0570) (0.1120) (0.0162) 8.94 (0.2830) 3-dgt portfolo (0.2184) 9.59 (0.2047) (0.0883) 4.94 (0.5134) Observatons The proporton of frm-quarter earnngs that beat or meet analyst forecast durng the pre-leaps and Post-LEAPS perods. To dentfy a set of quarterly earnngs for a perod correspondng to the ( 1,1) nterval, quarters endng from day 547 to day 183 become year 1. Quarters endng from day 182 to day +182 become year 0. Quarters endng from day +183 to day +547 become year 1, and quarters endng from day 548 to day 912 become year 2. For each LEAPS frm and for each control frm, the four quarters whch end durng each of the years 1, 1 and 2 are examned. A sample s dentfed whch ncludes only those frm-quarters for whch analyst errors are avalable for both the LEAP frm and at least one control frm n the same four-dgt ndustry. Beatng or meetng analyst forecast s defned here as when actual earnngs per share n quarter t s greater than or equal to the mean of analyst forecasts made n quarter t 1 about earnngs per share n quarter t. ntensty frms, the dfference s 25.97% and statstcally sgnfcant (p-valueb0.0145). Results are smlar for the ( 1,2) wndow and 3-dgt match frm and net of portfolos. Whle the sample sze for low ntensty frms s small, t appears that the hgh ntensty frms experence an ncrease n ntensty of greater magntude than do the low ntensty frms. 8. Beatng analyst's earnngs forecasts We examne an addtonal mplcaton of myopa: sacrfcng long-term payoffs to beat (or at least meet) analyst's quarterly earnngs forecasts. Graham et al. (2005) and Bhojraj and Lbby (2005) argue that managers wll myopcally forgo a postve NPV project to beat short-term analyst's earnngs forecasts. Cheng et al. (2005) report that frms that beat analyst's forecasts more frequently also nvest less n R&D. Cheng et al. conclude that these frms beat forecasts by sacrfcng R&D spendng. Ths lterature contends that myopc managers sacrfce R&D spendng to beat earnngs forecasts. We test the logcal extenson of ths argument: f myopa decreases after LEAPS are ntroduced, then the observed propensty for a frm to beat (or meet) forecasts wll decrease subsequent to LEAPS ntroducton. The change n the proporton of LEAPS frm-quarter earnngs that beat/meet analyst forecast, net of the control frm, s examned over two dfferent wndows surroundng LEAPS ntroducton, the ( 1,+1) and the ( 1,+2) wndows. Consstent wth the methodology employed by Cheng et al., beatng or meetng analyst forecast s defned here as when actual earnngs per share n quarter t s greater than or equal to the mean of analyst forecasts made n quarter t 1 about earnngs per share n quarter t. Analyst forecasts and actual quarterly earnngs are from Frst Call. To dentfy a set of quarterly earnngs for a perod correspondng to the ( 1,+1) nterval, quarters endng from day 547 to day 183 become year 1. Quarters endng from day 182 to day +182 became year 0. Quarters endng from day +183 to day +547 become year +1, and quarters endng from day 548 to day 912 become year 2. For each LEAPS frm and for each control frm, the four quarters whch end durng each of the years 1, 1 and +2 are examned. A sample s dentfed whch ncludes only those frmquarters for whch data s avalable for both the LEAP frm and at least one control frm n the same four-dgt ndustry. Meetng ths crtera are a total of 94 frm-quarters n year 1, 145 frm-quarters n year 1, and 158 frm-quarters n year 2. Table 5 reports the proporton of quarterly earnngs that beat or meet analyst's forecasts for LEAPS, 4-dgt match frms, 3-dgt match frms, and for portfolos of match frms dentfed at the 4- and 3-dgt SIC code levels, respectvely. For the ( 1,+1) wndow, the proporton of frm-quarters for whch LEAPS beat/meet forecast decreased from 73.40% to 69.66%, a decrease of 3.74% (p-valueb0.5309). By contrast, the 4-dgt match control frms ncreased 21.10% (p-valueb0.0013). Therefore, the dfference LEAPS Control decreased 24.84% (p-valueb0.0057). Lookng down the column, the LEAPS Control dfference usng 3-dgt match frm, 4-dgt portfolo, and 3-dgt portfolo s qualtatvely smlar. Lookng at the LEAPS Control for the ( 1,+2) wndow, the dfference between LEAPS and the 4-dgt ndustry s 9.71% (p-valueb0.2709). Contnung down the column, three out of four of the LEAPS Control dfferences are negatve. We conclude that the predomnance of the evdence supports the hypothess that the ntroducton of LEAPS s assocated wth a reducton n the frm's lkelhood of beatng the analyst's quarterly earnngs forecasts. In other words, the ntroducton of LEAPS s followed by frms actng less myopcally. 9. Concluson Shlefer and Vshny (1990) develop a model n whch the combnaton of ms-prcng of the shares of a frm whch nvest n projects wth long-term cash flows, combned wth the frm's manager's desre to avod under-prcng of the frm's current stock prce result n under-nvestment n projects wth long-term cash flows. By reducng the cost of trade on long-term nformaton, the ntroducton of exchange-tradng n a long-term stock opton on the frm should result n less ms-prcng of long-term nformaton and a correspondng ncrease of corporate nvestment n projects wth long-term cash flows.
10 C.W. Holden, L.L. Lundstrum / Journal of Emprcal Fnance 16 (2009) Ths paper tests the hypothess that corporate nvestment n long-term projects ncreases around the ntroducton of trade on a long-term stock opton. We fnd an abnormal growth n R&D ntensty rangng from 23% to 28% (annual R&D spendng ncreases by a total of $125 $152 mllon) over the two years subsequent to the ntroducton of LEAPS. Ths s consstent wth the hypothess that captal market mperfectons may play a sgnfcant role n deterrng frms from pursung projects wth long-term cash flows. Ths hghlghts the mportance of the costs of collectng and tradng on long-term nformaton, and suggests that the level of nformaton problems n captal markets have a deterrent effect on long-term nvestment. We fnd that for those frms that have an economcally sgnfcant level of R&D ntensty, the change n R&D ntensty around LEAPS ntroducton s ncreasng n LEAPS volume. Our conclusons are robust to the choce of proxy for long-term nvestment and to the matchng technque used to dentfy control frms or control portfolos. We also fnd that frms wth hgh pror R&D spendng have a larger subsequent ncrease n R&D spendng. Ths supports the dea that LEAPS have a greater mpact on frms where R&D plays a larger and more strategc role. Graham et al. (2005), among others, has documented a myopc focus on beatng short-term earnngs forecasts that fnds that managers are wllng to sacrfce long-term payoffs to beat short-term earnngs forecasts. We test the hypothess that a frm becomes less lkely to beat analyst's quarterly earnngs forecasts after LEAPS are ntroduced and fnd support for the hypothess. The results here suggest that understandng the postve externaltes assocated wth the ntroducton of opton trade s crucal to dentfyng all of the mportant costs and benefts of opton trade. The postve mpact of the ntroducton of these dervatves ncludes reducng barrers to long-term nvestment at the frm level. Ths potentally mples a role for regulatory polcy n nfluencng the level of economy-wde prvate, long-term nvestment. Long-term optons appear to help solve nformaton problems that mpede frm's ablty to nvest n long-term projects. LEAPS trade allows these pent-up R&D projects to be pursued. References Baber, W.R., Farfeld, P.M., Haggard, J.A., The effect of concern about reported ncome on dscretonary spendng decsons the case of research-anddevelopment. The Accountng Revew 66, Bebchuk, L., Stole, L., Do short-term objectves lead to under- or overnvestment n long-term projects. Journal of Fnance 48, Bhojraj, S., Lbby, R., Captal market pressure, dsclosure frequency-nduced earnngs/cash flow conflct, and manageral myopa. The Accountng Revew 80, Bzjak, J., Brckley, J., Coles, J., Stock-based ncentve management and nvestment behavor. 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