Influence of the Dow returns on the intraday Spanish stock market behavior

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Influence of the Dow returns on the intraday Spanish stock market behavior"

Transcription

1 Influence of he Dow reurns on he inraday Spanish sock marke behavior José Luis Miralles Marcelo, José Luis Miralles Quirós, María del Mar Miralles Quirós Deparmen of Financial Economics, Universiy of Exremadura Av. Elvas s/n Badajoz (Spain) Absrac In recen years differen sudies have analyzed he influence of he greaer equiy markes on oher markes as well as he inegraion of emerging markes or he price and volailiy spillovers beween advanced markes. This kind of sudies has been improved wih he exisence of inraday rading daa which have made feasible he sudy of inraday price behavior. This work focuses on he main objecive of analyzing he influence of he DOW on he IBEX. We expand he daabase in such a way ha 5-min inerval quoes of he IBEX hroughou each rading day are used from February, 000 o December 30, 011. Tha fac allows us o analyze a bigger inerval of ime for each hypohesis and for a longer ime. The resuls lead us o sae he exisence of a significan underreacion effec of he previous DOW dayime reurn upon he IBEX inraday dayime reurns during he firs hours of rading which urns ino an overreacion effec during he las hours of rading. Addiionally, we found he opposie o be rue of he effec of he IBEX reurn measures on he IBEX inraday reurns (overreacion a he morning and underreacion a he end of he rading day). JEL Classificaion: G10, G11, G14. Keywords: Inraday daa; Asymmeric models; Informaion Spillovers; Overreacion; Underreacion. Corresponding auhor. Tel.: ; Fax: address: 1

2 Influence of he Dow reurns on he inraday Spanish sock marke behavior 1. Inroducion The analysis of linkages among equiy markes has received grea aenion from researchers following he developmen of he differen ARCH models. There are several sudies in which he influence of he greaer equiy markes on oher markes is analyzed as well as oher sudies in which he inegraion of emerging markes or he price and volailiy spillovers beween advanced markes are invesigaed. Some examples of hose lines of invesigaion are he sudies of Liu and Pan (1997), Chan-Lau and Ivaschenko (003), Lee e al. (004) and more recenly Singh e al. (010). Furhermore, he exisence of inraday rading daa makes feasible he sudy of inraday price behavior. Soll and Whaley (1990) invesigae he srucure of he marke a he opening of he New York Sock Exchange (NYSE) and conclude ha he effec of sock marke srucure on he shor-run volailiy of sock prices is complex. Susmel and Engle (1994) find ha he volailiy spillover beween New York and London equiy markes is minimal and has a duraion which lass only an hour or so. Fabozzi e al. (1995) find ha inraday reversals for socks on he NYSE and he American Sock Exchange (AMEX) during 1989 are relaed o he iniial price change. Gosnell (1995) also documens ha he proporion of reversals is low near he opening of he marke, bu rapidly increases in he firs hour of rading. Baur and Jung (006) analyze he relaionship beween he Dow Jones Indusrial Average (DJIA) and he Deusche Akienindex (DAX) finding ha foreign dayime reurns can significanly influence domesic overnigh reurns and ha here is no evidence of spillovers from he previous dayime reurns in he US o he DAX morning rading. Finally, Harju and Hussain (008) and Harju and Hussain (011) use 5-min daa from differen inernaional equiy markes o analyze he dynamics among hem finding differen conclusions. Harju and Hussain (008) find ha he US sock marke does no cause significan volailiy spillover o he European markes whereas here is significan volailiy spillover in he opposie direcion. On he oher hand, Harju and Hussain (011) consider ha he opening of he US sock marke significanly raises he level of volailiy in Europe. References o similar sudies in he Spanish sock marke are limied because hey focus heir analysis on he response of he Spanish sock marke o bad news from he Dow Jones index, see Blasco e al. (00) or Blasco e al. (005). To our knowledge he sudy of

3 Miralles-Marcelo e al (010) is he only one which analyzes he behavior of he main Spanish sock index, IBEX-35, hereafer IBEX, in is early and final hours of rading and he influence of he main US index, he Dow Jones Indusrial Average, hereafer DOW, upon IBEX rading and invesor behavior. They find low price movemens of he IBEX ill he opening of Wall Sree and he exisence of a quick reacion of he Spanish sock marke plus an overreacion effec in he following en minues afer he opening of he US marke. This work follows he line of Baur and Jung (006) and Miralles-Marcelo e al (010) focusing on he main objecive of analyzing he influence of he DOW on he IBEX. Some improvemens of he previous empirical evidence are proposed: firsly, he vas majoriy of he sudies which use inraday daa employ a small daabase limied o a few years. However, we expand he daabase in such a way ha 5-min inerval quoes of he IBEX hroughou each rading day are used from February, 000 o December 30, 011. Tha fac allows us o analyze a bigger inerval of ime for each hypohesis and for a longer ime. Secondly, we use asymmeric models o avoid anomalies in he conclusions when asymmeries are no aken ino accoun as several auhors sugges. Finally, we add some behavior hypohesis in order o shed some ligh on he dynamics of he Spanish sock marke. There are wo main reasons for focusing our sudy on he Spanish sock marke. Firsly, in recen years i has become a reference for he main European sock markes based on improvemens in he echnical, operaional and organizaional sysems supporing he marke which has enabled i o channel large volumes of invesmen as is repored in he 011 Annual Repor of Bolsas y Mercados Españoles (BME), he operaor of all sock markes and financial sysems in Spain, where i is poined ou ha he invesmen flows channeled hrough he sock exchange in 011 oaled billion euros, up 35.1% from 010. This amoun ranks BME as he 4 h among he world s sock exchanges in erms of company financing. Secondly, a beer knowledge of he inraday behavior of he Spanish sock marke would lead us o a more aracive sock marke, larger amouns of invesmen flows and, herefore, he possibiliy of developing a profiable sraegy. Addiionally, in recen imes Morgan Sanley s ineres rae sraegiss have poined ou he Spain s brighening growh oulook, progress on reforms, valuaions, and he low risk ha he eurocrisis could blow up anew which could lead Spain o become he euro area s nex Germany. In our opinion, hose facs will lead o a higher ineres for he Spanish economy and, herefore, for he Spanish sock marke. The resuls show he imporance of he DOW reurns on he IBEX inraday reurns behavior. Clear evidence is provided ha he Spanish sock marke underreacs o he DOW 3

4 reurns in he firs hours of rading bu overreacs during he las wo hours (afer he opening of he US markes). Addiionally, he resuls also show ha he Spanish sock marke overweighs he mos recen informaion as opposed o he older informaion, ha is he DOW reurns face o he IBEX reurns. The remainder of his paper is organized as follows. Secion describes he mehodology and presens he daa. Secion 3 shows he principal resuls and Secion 4 provides he main conclusions.. Daa and Mehodology In order o analyze he inraday ransmission of sock reurns and volailiy from he DOW o he IBEX we have iniially compiled IBEX-35 index inraday daa for he period from February, 000 o December 30, 011 (a oal of 3010 rading sessions) saring from he opening quoe a 9:00 local ime and a 5-minue inervals unil he end of each session a 17:30. Considering ha here is no a subsanial overlapping period of rading beween he NYSE and he Spanish sock marke, jus wo hours from 3:30 pm o 5:30 pm (CET ime), i is no necessary o use inraday daa from he DOW. For ha reason we jus use opening and closing prices for he DOW which reflec all he relevan informaion we need o analyze he relaionship beween hese wo markes. Using ha daa we calculae hree differen inraday reurns for he IBEX. Inraday overnigh reurns, IBEXIDNR are calculaed saring a he previous closing price of he IBEX and ending a he price of he nex day a 9:05 AM. Subsequenly, he lengh is increased in 5-min inervals unil open-plus-3 hours is reached (reporing 36 differen overnigh reurns). We calculae he inraday dayime reurns, IBEXIDDRA, iniially as he logarihm difference beween he price a 9:05 AM and he opening price. Furher dayime reurns are calculaed by increasing he lengh in 5-min inervals unil 17:30 (a oal of 10 differen dayime reurns) 1. The second inraday dayime reurns, IBEXIDDRB, are calculaed iniially as he difference beween he price a 15:35 and he price a 15:30 and hen increase he lengh in 5-min inervals unil 17:30 (giving us 4 differen dayime reurns). Basic saisics of he inraday overnigh and dayime reurns are shown in Tables 1 o 3. 1 Tha means ha he second dayime reurn is calculaed as he logarihm difference beween he price a 9:10 AM and he opening price and so on. From hese ables unil he end of he paper we show jus some of he reurns or he esimaions we carried ou in order o save space. The res of hem can be provided upon reques. 4

5 Table 1: Descripive saisics for IBEX overnigh reurns (IBEXIDNR, Previous close o he marked hour price) 09:05 09:15 09:30 09:45 10:00 10:15 10:30 10:45 11:00 11:15 11:30 11:45 1:00 Mean Median Maximum Minimum Sd. Dev Skewness Kurosis Jarque-Bera Probabiliy Sum Sum Sq. Dev Observaions

6 Table : Descripive saisics for IBEX dayime reurns (IBEXIDDR, Open o he marked hour price) 09:05 09:15 09:30 10:00 11:00 1:00 13:00 14:00 15:00 15:30 16:00 17:00 17:30 Mean Median Maximum Minimum Sd. Dev Skewness Kurosis Jarque-Bera Probabiliy Sum Sum Sq. Dev Observaions

7 Table 3: Descripive saisics for IBEX dayime reurns (IBEXIDDRB, Price a 15:30 o he marked hour price) 15:35 15:40 15:45 15:50 15:55 16:00 16:10 16:15 16:30 16:45 17:00 17:15 17:30 Mean Median Maximum Minimum Sd. Dev Skewness Kurosis Jarque-Bera Probabiliy Sum Sum Sq. Dev Observaions

8 We observe a common behavior in all cases which is characerized by increasing negaive mean values and volailiies in he course of each ime period. Focusing aenion on he values of he dayime reurns which are repored in Table (IBEXIDDR, from open o he marked hour price) we see ha here is a significan difference in heir mean and volailiy values since boh are much greaer in he laer hours of he rading day coinciding wih he opening and he firs hours of rading in New York. Therefore, we can poin ou he fac ha while he mean dayime reurn in Table a 09:05 AM akes he value of , he same one a 15:30 when he DOW opens is , reaching a minimum of a 17:00, one and a half hours afer he opening of he DOW. A he same hours he sandard deviaions of hose variables are ; and respecively. These resuls lead us o conclude ha he aciviy of he Spanish sock is concenraed in he las hours of rading in order o evaluae and incorporae ino he marke all he informaion generaed by he DOW. The inraday seasonal volailiy paern, defined by he average absolue reurns, is depiced in Figure 1. I displays a ypical U-shaped paern where large posiive mean reurns a he beginning of he rading day are followed by a decreasing rend unil mid-session. From ha momen, i sars a big upward rend unil he end of he rading day. These resuls are consisen wih he findings of Andersen and Bollerslev (1997) and Cai e al (004) among ohers for he US and UK equiy markes. Figure 1: Average Absolue Reurns for he IBEX-35 8

9 Addiionally, we show in Figure he average inraday volume which also exhibis a U- shaped paern in accordance wih he findings of Hussain (011). In boh figures we find significan peaks a 14:30 and 15:30 similar o hose found by Harju and Hussain (011). They associae hem wih he scheduled US macroeconomic news announcemens and he opening of he New York Sock Exchange, hereafer he NYSE, a 14:30 and 15:30 respecively. Figure : Mean Inraday Volume We have also calculaed reurns of IBEX, IBEXR, and DOW, DOWR, as he differences in logarihms of wo consecuive closing prices. However, boh of hem can also be calculaed as he sum of overnigh reurns, 3 IBEXNR and DOWNR respecively, and dayime reurns, 4 IBEXDR and DOWDR respecively. From he basic saisics of hose reurns which are repored in Table 4 we can observe he firs insighs ino reurn ransmissions. In ha sense, we deec ha posiive DOW dayime reurn is accompanied by a posiive IBEX overnigh reurn and, conversely, a negaive DOW overnigh reurn is followed by a negaive IBEX dayime reurn. 3 4 Overnigh reurns are calculaed as he difference in logarihms beween he previous closing and he opening prices of each sock marke. In his case dayime reurns are calculaed as he difference in logarihms beween he opening and he closing prices of each sock marke. 9

10 Table 4: Descripive saisics of daily, overnigh and dayime reurns IBEXR IBEXNR IBEXDR DOWR DOWNR DOWDR Mean Median Maximum Minimum Sd. Dev Skewness Kurosis Jarque-Bera Probabiliy Sum Sum Sq. Dev Observaions The ime line of he marke rading hours of he IBEX and he DOW is shown in Figure 3. From is scruiny, various ineracions can be consruced wih he aim of asceraining he naure of conemporaneous and lead-lag relaionships beween he markes. Firsly, we can consider ha overnigh reurns from he DOW (defined as DOWNR ) can influence hose inraday reurns of he IBEX we have defined as IBEXIDDRB. 5 Secondly, we observe ha dayime reurns of he DOW on he previous day (DOWDR -1 ) and one-day lagged reurns of he DOW (DOWR -1 ) 6 can impac on he overnigh reurns of he IBEX he following day (IBEXNR ), bu also on he inraday reurns of he IBEX (IBEXDR ). Wih respec o he influence of he IBEX on he DOW we find some relaionship opions. In ha sense, DOW dayime reurns (DOWDR) can be influenced by he IBEX dayime reurn from 9:00 o 15:30, he IBEX dayime reurn (from open o close, IBEXDR) and he IBEX reurn (from previous close o close, IBEXR ). Likewise, here could be a conemporaneous influence of he IBEX reurns (IBEXR ) over he DOW reurns (DOWR ). 5 6 Those reurns from he opening of he DOW a 15:30 CET ime ill he end of he rading session in he Spanish sock marke a 17:30. Calculaed as he difference in logarihms beween wo consecuive closing prices, bu also he sum of overnigh and day reurns. 10

11 Figure 3: Time line of he marke rading hours of he IBEX and he DOW CET Time IBEX IBEXNR IBEXDR IBEXNR IBEXDR IBEXNR 9:00 17:30 9:00 17:30 DOW DOWNR DOWDR DOWNR DOWDR 15:30 :00 15:30 :00 OVERLAPPING PERIOD 15:30-17:30 OVERLAPPING PERIOD 15:30-17:30 11

12 Following Lee e al. (004) or Kim (005) among ohers, we have performed Granger causaliy ess in order o assess hose informaion flows beween he IBEX and he DOW. From he resuls of hose causaliy ess, which are shown in Table 5, we find ha here is a clear unidirecional reurns ransmission from he DOW o he IBEX. In all cases we rejec he null ha he differen DOW s reurns do no cause IBEX s reurns. However, ha null canno be rejeced when IBEX reurns causaliies over he DOW are esed. Table 5: Granger causaliy ess DOW causes IBEX F-sa Probabiliy IBEX causes DOW F-sa Probabiliy DOWNR IBEXIDDRB IBEXDR (15:30) DOWDR RDOW -1 IBEXNR IBEXDR DOWDR RDOW -1 IBEXDR RIBEX DOWDR DOWDR -1 IBEXNR RIBEX RDOW DOWDR -1 IBEXDR Noe: IBEXIDDRB and IBEXDR (15:30) represen he dayime reurn from 15:30 o Close and he dayime reurn from Open o 15:30 respecively. The sandard frameworks in he empirical evidence o analyze he reurn and volailiy ransmission beween wo or more markes are based in he GARCH model due o is abiliy o ake ino accoun he condiional heeroskedasiciy inheren in financial ime series. 7 However, several auhors sugges ha hese volailiy models could be erroneous if we do no ake ino accoun asymmeries in variance. In his sense, Black (1976) and Chrisie (198) demonsraed he exisence of asymmeric effecs, also known as leverage effecs, on he condiional variance whereby negaive equiy reurns are usually followed by larger increases in volailiy han is he case wih equally large posiive reurns. In order o accommodae his asymmeric response we adap he aggregae-shock model proposed by Lin e al. (1994), which was also used by Baur and Jung (006), o a Threshold GARCH (TGARCH) aggregae model The TGARCH model, proposed by Glosen e al (1993) and Zakoian (1994), bu also used by Chan-Lau and Ivaschenko (003), Hughes e al (007), Jaleel and Samarakoon 7 See French e al. (1987), Akgiray (1989), Conolly (1989), Baillie and DeGennaro (1990), Bollerslev e al. (199), Kyriacou and Sarno (1999), Gonzalez e al. (003), Franses e al. (004), Baur and Jung (006) and Miralles e al (010) among ohers, who applied he GARCH models o sock indexes showing ha hey are useful in modeling he dynamic behavior of sock reurns. 1

13 (009), Haniff and Pok (010) and Sabiruzzaman e al (010) among ohers, 8 is specified as follows: h r αε μ ε βh γε where o allow for asymmery in volailiy he sandard GARCH model is augmened by including a dummy variable, I -1, which akes he value of 1 if ε -1 is negaive and 0 (zero) oherwise. In his model, good news, ε -1 >0, and bad news, ε -1 <0, have differenial effecs in condiional variance. Good news has an impac of α while bad news has an impac of α+γ. In his model we say ha here is a leverage effec if γ>0 and is saisically significan. Taking ino consideraion no only he unidirecional reurns ransmission we found previously, bu also he ime line of he marke rading hours of he IBEX and he DOW, we propose he analysis of five differen hypoheses: Hypohesis 1: I (1) IBEXIDNR h αε μ 0 μ IBEXDR βh 1 γε I -1 μ DOWDR θdowdr -1 () The firs one analyzes he impac of he previous dayime reurns of he DOW and IBEX (DOWDR -1 and IBEXDR -1 respecively) on he inraday overnigh reurns of he Spanish sock index (IBEXIDNR ) during he firs 3 hours of rading, which means ha 36 esimaions were calculaed. Addiionally, we analyze he influence of he DOW dayime volailiy by including is squared reurn lagged one period in he variance equaion. This analysis, where he DOW index is used insead of any Asian index, makes sense from he poin of view ha using NYSE Arca i is possible o ener and execue orders from 10 AM CET o 3:30 PM CET. Therefore, here is a coninuous flow of informaion coming from he US marke ha neuralizes any news coming from he Asian markes which close a 7 AM CET approximaely. 8 There is anoher opion o capure asymmery which is he use of he Exponenial GARCH (EGARCH) model. However, Engle and Ng (1993) find ha he variabiliy of he condiional variance implied by he EGARCH model is oo high. Addiionally, beyond o he fac of he GARCH models being incapable of 13

14 Hypohesis : IBEXIDDRA h αε μ 0 βh μ IBEXNR 1 γε I μ DOWNR θdownr (3) The second hypohesis focuses on he behavior of he inraday dayime reurns of he IBEX during he las wo hours of rading. In his case, we analyze wheher he DOW and IBEX overnigh reurns (DOWNR and IBEXNR respecively) influence he IBEX inraday dayime reurns from Open-o-15:30 (IBEXIDDRA ) and he following ones unil he end of he rading session a 17:30. We also analyze wheher DOW overnigh volailiy, characerized by he squared overnigh reurns, conains any relevan informaion for hose dayime reurns. Hypohesis 3: IBEXIDDRB h μ 0 αε μ IBEXIDDR 1 βh γε OPEN TO15:30 I μ θdownr DOWNR (4) Hypoheses 1 and are he same as he firs wo proposed by Miralles-Marcelo e al (010). The hird one is also similar bu changing he mehodology of calculaing he endogenous variable. We boh use he 15:30 CET o close reurn, however, while Miralles- Marcelo e al (010) calculae he reurns by mainaining he closing price fixed and hen using prices a 15:30 plus en-minues ahead (wih icks of one minue), we fix he price a 15:30 CET and change he oher reference beginning by he price a 15:35 CET wih icks of 5-minues ill he end of he rading session a 17:30. Tha difference allows us o mainly analyze he effec of he DOW overnigh reurn over he cumulaive reurn of he IBEX from he opening of he US marke. Consequenly, in he hird hypohesis we consider as he endogenous variable he second inraday dayime reurn (IBEXIDDRB ) while he exogenous variables of he reurn model are he DOW overnigh (DOWNR ) reurns and he inraday dayime reurns of he Spanish index (IBEXIDDR OPEN TO 15:30 ) from Open-o-3:30 pm. Furhermore, he DOW overnigh squared reurns lagged one period are included in he volailiy equaion in order o capure he volailiy spillover from he American marke ino he Spanish marke. separaing ou he asymmeric informaion, Sabiruzzaman e al (010) provide evidence ha he TGARCH specificaion is superior o GARCH specificaion. 14

15 In addiion o hese hypoheses, we sugges wo more in order o analyze in deph he behavior of he Spanish sock marke. Hypohesis 4: IBEXIDDRA h μ 0 αε μ IBEXIDDR 1 βh γε I OPEN TO15:30 μ θdownr DOWNR (5) The fourh hypohesis shares wih he second hypohesis he exogenous variable relaive o he DOW (he overnigh reurns, DOWNR ) and parially he endogenous variable (because in his case he firs variable o be analyzed is he inraday dayime reurns from open o 15:35) 9. However, in conras wih he second hypohesis, we include he inraday dayime reurn of he IBEX from Open o 15:30 as an exogenous variable. This change will allow us o examine he behavior of he IBEX during he las wo hours of he rading session faced wih he conemporaneous news generaed by he IBEX and he DOW unil he opening of he laer. As well as in he second hypohesis we add he squared DOW overnigh reurn in he volailiy equaion as an exogenous variable. We also find suppor for using he DOW overnigh reurn as an exogenous variable in hypoheses o 4 from Figures 1 and. In boh cases, we find a significan increase a 15:30 CET. Following he evidence repored by Harju and Hussain (011) and Hussain (011), ha behavior could be associaed wih he opening of he New York Sock Exchange and, herefore, i mus be considered. Hypohesis 5: IBEXIDDRA h αε μ 0 βh μ IBEXR 1 γε I -1 μ DOWR θdowr -1-1 (6) The las hypohesis proposed in his paper measures in he mean equaion he effecs of he previous daily reurns of he IBEX and DOW indexes (IBEXR -1 and DOWR -1 respecively) on he inraday dayime reurn of he following day (IBEXIDDRA ). Meanwhile, in he volailiy equaion we add as an exogenous variable he squared daily reurn of he DOW lagged one period in order o analyze is effec on he condiional volailiy of he IBEX. In his case we analyze he behavior of he IBEX hrough he whole rading session which leads us o esimae 10 regressions. 9 The followers are he dayime reurns from Open o 15:40 and so on increasing he lengh in 5 min inervals. The fac ha he exogenous variable is he dayime reurn from Open o 15:30 leads us o esimae 4 regressions. 15

16 In all cases we run several regressions using differen proxies of he inraday IBEX overnigh and dayime reurns by saring from he reference quoe in each case and exending he ime span on a 5 min basis. The main objecive of hese procedures is o analyze he behavior of he Spanish marke as more and more real-ime informaion is available. In all he regressions, maximum likelihood esimaion are obained from he Bernd-Hall-Hall- Hausman algorihm. 3. Empirical Resuls Table 6 repors he regression resuls for he firs hypohesis. The firs hree rows show he coefficiens relaive o he mean equaion which measures he impac of IBEX s and DOW s previous open-o-close reurns (IBEXDLDR -1 and DOWDLDR -1 respecively) on he inraday overnigh reurns of he Spanish sock index (IBEXIDNR ). In his case, if IBEX inraday overnigh reurns conain any informaion from DOW or IBEX and heir previous dayime reurns, hese coefficiens should be significan. The following five rows show he coefficiens relaive o he volailiy equaion where we focus our aenion on he las wo, γ and θ, which represen he coefficiens relaive o he asymmery and he DOW volailiy respecively. Some ineresing resuls emerge from he firs hree rows of coefficiens. Firsly, all of hem are significan which means ha here are significan ransmissions of informaion from he previous dayime reurns of he IBEX and he DOW o he IBEX inraday overnigh reurns, which is consisen wih he resuls of he previous empirical evidence. Secondly, he negaive values of he coefficiens relaed o he IBEX previous dayime reurns show evidence of an overreacion effec. While he posiive values of hose relaed o he DOW previous dayime reurns show evidence of an underreacion effec. Moreover, his underreacion effec is in keeping wih he firs evidence of informaion ransmission beween hese markes found in he descripive saisics where a posiive DOW dayime reurn coincides wih a posiive IBEX overnigh reurn. I is also ineresing o poin ou ha he coefficiens relaive o he previous IBEX dayime reurns are lower in absolue erms han hose relaive o he DOW. In our opinion, ha fac means ha he Spanish sock marke overweighs he informaion coming from he US marke in he firs hours of rading. Tha circumsance makes sense from he poin of view ha he informaion coming from he US marke is closer and, herefore, more valuable han he Spanish one. 16

17 Table 6: Reurn and volailiy spillovers from Hypohesis 1 09:05 09:15 09:30 09:45 10:00 10:15 10:30 10:45 11:00 11:15 11:30 11:45 1:00 Mean Equaion μ (-0.619) μ *** ( ) μ *** (7.951) (0.405) *** ( ) *** (6.96) (-0.361) *** (-1.886) *** (4.668) (-0.609) *** (-13.98) *** (3.139) (-1.01) *** (-1.95) 0.36 *** (1.473) (-1.014) *** ( ) (-1.54) *** ( ) (-1.114) (-1.35) *** *** (-11.05) (-11.09) 0.3 *** (0.390) 0.31 *** (19.944) 0.3 *** (0.13) 0.37 *** (0.185) Variance Equaion (-1.540) *** ( ) 0.3 *** (19.491) * (-1.763) *** (-9.686) 0.31 *** (18.85) * (-1.658) *** (-9.341) *** (18.95) * (-1.645) *** (-8.907) 0.31 *** (17.667) ω *** (.744) α *** (3.18) β *** (5.1) γ 0.10 *** (4.898) θ 0.07 *** (9.975) *** (3.419) *** (3.38) *** (63.710) *** (5.748) 0.0 *** (8.44) *** (3.941) *** (.801) *** (69.631) 0.10 *** (6.696) 0.03 *** (8.07) *** (4.8) *** (.81) *** (66.559) *** (9.10) 0.0 *** (7.053) *** (4.191) *** (3.077) *** (65.899) 0.13 *** (8.485) 0.0 *** (6.309) *** (3.881) 0.08 ** (.369) *** (74.7) *** (7.770) 0.00 *** (5.766) *** (3.777) 0.07 ** (.37) *** (75.545) 0.11 *** (8.409) 0.03 *** (5.869) Saisics *** (3.817) *** (3.736) 0.03 *** ** (.599) (.469) *** *** (8.016) (75.779) *** *** (77.63) (8.176) 0.01 *** 0.0 *** (5.60) (5.77) *** (3.713) 0.07 ** (.54) *** (78.766) 0.11 *** (8.74) *** (5.01) *** (5.499) 0.03 * (1.946) *** (74.939) *** (8.400) 0.0 *** (6.1) *** (4.998) * (1.73) *** (8.569) 0.11 *** (8.579) 0.0 *** (6.11) *** (5.143) (1.478) *** (75.170) 0.11 *** (8.541) 0.06 *** (6.466) LL LB(15) 5.1 *** *** ** * LBS(15) * Noes: This able shows he resuls for he TGARCH model IBEXIDNR μ 0 μ 1 IBEXDR -1 μ DOWDR -1 h αε 1 βh 1 γε 1 I 1 θdowdr 1 T-saisics in parenheses. LL is he Log-likelihood saisic. LB(15) and LBS(15) are he Ljung-Box saisics for he sandardized residuals and squared residuals, respecively, wih 15 lagged values included. Significan coefficiens are denoed by ***, ** and * for 1%, 5% and 10% significance levels, respecively. 17

18 Relaive o he second par of Table 6 where he coefficiens of he volailiy equaion are shown, we deec a significan volailiy spillover effec from he DOW o he IBEX, which remains consan hroughou he differen esimaions. Furhermore, he posiive and significan value of he γ coefficien in all cases indicaes ha here is a leverage effec where bad news increases volailiy. Finally, he analysis of he Ljung-Box saisics for he sandardized and squared sandardized residuals shows, in mos of he cases, he inexisence of serial correlaion in he mean equaions or remaining ARCH effecs in he variance equaions. Shown in Table 7 are he resuls of he esimaions relaive o he second hypohesis where we analyze he influence of he DOW and IBEX overnigh reurns upon he IBEX inraday dayime reurns from Open-o-15:30 and he following ones unil he end of he rading session a 17:30. We find significan conemporaneous reurn spillovers form he DOW overnigh reurns o he IBEX inraday dayime reurns. However, in conras wih he resuls obained by Miralles e al (010), we find significan conemporaneous spillovers from he IBEX overnigh reurns o he IBEX inraday dayime reurns basically due o he fac ha hey use a sample of jus years while we use a sample of 1 years where spillovers among markes can change enormously. As well as in he firs hypohesis resuls, we find evidence of overreacion and underreacion effecs as a consequence of he negaive and posiive values of he IBEX and DOW coefficiens in he mean equaion. Once again, he DOW coefficiens are higher han he IBEX coefficiens and heir value decreases hroughou he rading session, bu in his case hey become no saisically significan from 17:00 onwards. In our opinion, his is evidence of he exisence of a significan Opening DOW effec in he Spanish sock marke which akes ino accoun all he informaion coming from he DOW opening and disappears gradually once he informaion is analyzed by he markes. However, besides hese iniial ineresing resuls, we also find ha even hough he asymmery coefficiens of he volailiy equaion are all significan, herefore indicaing he exisence of a leverage effec, mos of he volailiy coefficiens associaed wih he DOW overnigh volailiy are no significan. This fac, ogeher wih he significan values of he Ljung-Box saisics for he squared sandardized residuals in mos of he esimaions, leads us o consider his model as inappropriae. Table 8 repors he analysis of he spillover effecs from he DOW overnigh reurns and IBEX inraday dayime reurns from Open o 15:30 on he IBEX inraday dayime reurn from he opening of he DOW a 15:30 unil he end of he rading session. 18

19 μ * (-1.654) μ *** (-3.568) μ *** (3.559) ω *** (6.657) α *** (3.865) β *** (9.347) γ *** (7.846) θ (1.15) Table 7: Reurn and volailiy spillovers from Hypohesis 15:30 15:35 15:40 15:45 15:50 16:00 16:10 16:15 16:30 16:45 17:00 17:15 17: (-1.639) *** (-3.785) *** (3.496) *** (6.415) 0.04 *** (3.594) 0.89 *** (93.310) *** (8.79) 0.03 (0.956) * (-1.738) *** (-3.888) *** (3.85) *** (6.61) 0.05 *** (4.139) *** (90.883) *** (6.966) 0.04 (1.93) * (-1.8) *** (-3.79) 0.86 *** (3.007) *** (6.85) *** (3.960) 0.89 *** ( ) *** (6.948) (1.505) ** (-.134) *** (-3.89) 0.95 *** (3.048) *** (6.18) *** (3.355) *** ( ) *** (7.955) ** (.199) ** (-.176) *** (-4.471) 0.59 *** (.66) *** (6.74) 0.09 *** (.805) 0.90 *** (104.85) *** (9.603) * (1.853) Mean Equaion ** (-.16) *** (-4.46) 0.19 ** (.77) Variance Equaion *** (5.976) 0.04 *** (.658) 0.91 *** (119.99) *** (10.566) (0.596) Saisics ** (-.40) *** (-4.513) 0.3 ** (.80) *** (5.948) 0.01 ** (.43) *** (16.931) *** (11.351) (0.510) * (-1.80) *** (-3.953) 0.00 * (1.946) *** (5.73) *** (3.445) *** ( ) *** (9.419) 0.00 (0.657) * (-1.693) *** (-3.895) * (1.654) *** (5.971) ** (.495) *** ( ) *** (11.067) (0.61) ** (-1.993) *** (-3.316) (1.98) *** (6.575) (1.396) 0.9 *** (144.34) 0.10 *** (1.388) (-0.177) * (-1.790) *** (-.998) 0.11 (1.043) *** (6.96) * (1.79) *** (135.95) 0.17 *** (1.868) (-0.00) (0.5) (-1.336) (1.134) *** (7.494) LL (0.901) *** ( ) *** (13.685) LB(15) LBS(15) ** ** 5.94 ** 3.90 *.747 * *** *** ** ** Noes: This able shows he resuls for he TGARCH model IBEXIDDRA μ 0 μ 1 IBEXNR μ DOWNR h αε 1 βh 1 γε 1 I 1 θdownr T-saisics in parenheses. LL is he Log-likelihood saisic. LB(15) and LBS(15) are he Ljung-Box saisics for he sandardized residuals and squared residuals, respecively, wih 15 lagged values included. Significan coefficiens are denoed by ***, ** and * for 1%, 5% and 10% significance levels, respecively (0.05) 19

20 μ (-0.307) μ *** (4.730) μ (-0.57) ω *** (3.905) α *** (15.480) β 0.91 *** (4.48) γ *** (4.104) θ ** (.344) Table 8: Reurn and volailiy spillovers from Hypohesis 3 15:35 15:40 15:45 15:50 15:55 16:00 16:10 16:15 16:30 16:45 17:00 17:15 17: (-1.3) (-0.07) (-0.886) *** (5.100) *** (8.537) 0.98 *** (10.46) *** (4.78) * (1.715) (-1.608) *** (-.686) * (-1.759) *** (3.88) *** (8.590) *** (180.05) *** (5.715) *** (3.083) *** (-3.077) *** (-.84) ** (-.100) *** (3.110) *** (9.647) 0.99 *** (38.895) *** (4.709) *** (3.660) *** (-3.0) *** (-5.07) ** (-.543) *** (4.505) *** (6.601) 0.93 *** (48.797) *** (3.618) ** (.013) *** (-.865) *** (-4.958) * (-1.880) *** (4.537) *** (8.415) 0.9 *** (4.094) *** (3.03) * (1.788) Mean Equaion ** (-.01) *** (-3.557) ** (-.404) Variance Equaion *** (3.181) *** (8.381) 0.93 *** ( ) *** (3.570) (1.113) Saisics ** (-.019) *** (-3.515) ** (-.186) *** (3.41) 0.05 *** (7.904) 0.96 *** (0.77) *** (4.57) * (1.87) (-1.15) * (-1.661) ** (-.348) *** (3.807) *** (6.901) 0.98 *** ( ) *** (4.786) *** (.901) (-0.557) (-0.714) ** (-.013) *** (4.19) *** (5.59) *** (19.875) 0.06 *** (7.99) *** (.91) ** (.057) * (1.799) *** (-3.635) *** (11.91) *** (1.114) *** (90.183) ** (.64) *** ( ) (-0.910) 0.01 (1.314) ** (-.08) *** (5.3) *** (4.5) 0.96 *** ( ) *** (6.343) (1.359) ** (.444) *** (3.703) ** (-.78) *** (5.576) 0.09 *** (3.660) 0.91 *** (14.60) *** (7.94) LL LB(15) * LBS(15) Noes: This able shows he resuls for he TGARCH model IBEXIDDRB μ 0 μ 1 IBEXIDDR OPEN TO15:30 μ DOWNR h αε 1 βh 1 γε 1 I 1 θdownr The exogenous variable IBEXIDDR represens in his hypohesis he dayime reurn from Open o 15:30. T-saisics in parenheses. LL is he Log-likelihood saisic. LB(15) and LBS(15) are he Ljung-Box saisics for he sandardized residuals and squared residuals, respecively, wih 15 lagged values included. Significan coefficiens are denoed by ***, ** and * for 1%, 5% and 10% significance levels, respecively (0.887) 0

21 Based on he value of he IBEX coefficiens, we find hree differen phases. The firs one, which akes he firs esimaion, shows evidence of a weak underreacion effec which urns ino an overreacion effec, second phase, during he following hour of rading approximaely (unil 16:30). Finally, we find a hird phase where we again observe a weak underreacion effec. We do no find a significan influence of he DOW overnigh reurn on he IBEX inraday dayime reurns unil 15:45, when an overreacion effec appears once he marke has evaluaed he informaion coming from he US. The increasing values of he coefficiens associaed wih he DOW overnigh reurns, as well as heir larger values when compared in absolue erms wih hose relaive o he IBEX reurns, show he imporance of he DOW on he IBEX developmen. Focusing on he volailiy coefficiens, we again find evidence of he exisence of a leverage effec and a significan bu weak volailiy spillover form he DOW overnigh reurn o he IBEX inraday dayime reurn from 15:35 o he end of he session. Finally, he analysis of he Ljung-Box saisics for he sandardized and squared sandardized residuals shows he adequacy of he model. The resuls of he fourh hypohesis are shown in Table 9. This hypohesis solves he problems we found in he second hypohesis relaive o he adequacy of he model for describing he condiional heeroskedasiciy of he daa. In his case, we consider ha in he mean equaion of he model i is more appropriae o relae he IBEX inraday dayime reurns during he las hours of rading wih he IBEX inraday dayime reurn from Open o 15:30 han wih he IBEX overnigh reurn. This is mainly because here is much more informaion o be considered for he Spanish sock marke a 15:30 in he former han in he laer. As prediced, he resuls for he μ 1 coefficiens associaed wih he spillover effecs from he IBEX inraday dayime reurns are all significan and much higher in absolue erms han he μ coefficiens relaed wih he DOW overnigh reurns spillovers, which are also mosly significan. This means ha he IBEX inraday dayime reurns are basically driven by he previous behavior of he Spanish marke during he session and in a minor way by he DOW s behavior. Furhermore, he signs of boh coefficiens show ha he IBEX underreacs o is previous reurns and overreacs o he DOW overnigh reurns, which is in accordance wih he resuls of he previous hypohesis. I is also ineresing o poin ou ha boh effecs increase as he rading day finishes and as more and more updaed informaion abou he markes goes o he IBEX. 1

22 μ (0.11) μ *** ( ) μ (-0.301) ω *** (4.561) α *** (14.890) β *** (184.88) γ *** (3.360) θ *** (3.000) Table 9: Reurn and volailiy spillovers from Hypohesis 4 15:35 15:40 15:45 15:50 15:55 16:00 16:10 16:15 16:30 16:45 17:00 17:15 17: (-0.690) 0.99 *** ( ) (-0.73) *** (5.318) *** (10.867) *** (131.87) (0.680) *** (3.858) (-1.066) *** ( ) (-1.460) *** (4.433) *** (11.355) *** (156.35) ** (1.97) *** (4.85) *** (-.87) 0.98 *** (31.195) * (-1.791) *** (3.44) *** (15.378) 0.90 *** (51.834) (1.193) *** (4.789) *** (-.89) *** (97.787) ** (-.190) *** (4.710) *** (11.013) *** (196.60) 0.03 ** (1.980) *** (.736) *** (-.63) *** (51.586) * (-1.94) *** (4.468) *** (11.703) *** (01.487) ** (1.981) ** (.535) Mean Equaion * (-1.89) *** ( ) ** (-.443) Variance Equaion *** (3.95) *** (8.143) 0.93 *** ( ) *** (3.394) * (1.803) Saisics * (-1.831) *** ( ) ** (-.347) *** (3.401) *** (7.519) 0.94 *** ( ) 0.04 *** (3.848) ** (.147) (-1.051) *** (145.04) *** (-.63) *** (3.671) *** (6.943) 0.97 *** (193.84) *** (4.531) *** (.81) (-0.478) *** ( ) ** (-.15) *** (4.19) *** (5.187) *** (15.85) *** (7.38) *** (.850) (-0.956) *** (18.953) ** (-.353) *** (4.796) *** (4.38) 0.98 *** ( ) *** (6.760) (1.088) (-0.776) *** (110.07) ** (-.185) *** (5.175) *** (4.456) 0.94 *** ( ) *** (6.440) (1.119) (.576) *** (96.195) ** (-.317) *** (5.553) 0.09 *** (3.830) 0.9 *** ( ) *** (7.955) LL LB(15) * LBS(15) * Noes: This able shows he resuls for he TGARCH model IBEXIDDRA μ 0 μ 1 IBEXIDDR OPEN TO15:30 μ DOWNR h αε 1 βh 1 γε 1 I 1 θdownr The endogenous variable IBEXIDDRA represens in his hypohesis he dayime reurn from Open o 15:35 and followers while he exogenous variable IBEXIDDR OPEN TO 15:30 represens in his hypohesis he dayime reurn from Open o 15:30. T-saisics in parenheses. LL is he Log-likelihood saisic. LB(15) and LBS(15) are he Ljung-Box saisics for he sandardized residuals and squared residuals, respecively, wih 15 lagged values included. Significan coefficiens are denoed by ***, ** and * for 1%, 5% and 10% significance levels, respecively (0.688)

23 Wih respec o he resuls of he coefficiens relaive o he asymmery, we observe ha mos of hem are posiive and significan. This concurs wih he resuls obained in he previous hypoheses, as well as he θ coefficiens, associaed wih he volailiy ransmission from he DOW, which are also posiive and significan in mos of he cases. Finally, we make wo more observaions, when he resuls of he Log-likelihood, and Ljung-Box saisics for he sandardized and squared sandardized residuals are compared wih hose obained in he second hypohesis (Table 7). Firsly, ha he log-likelihood sas are much higher in his case, which means ha he model is beer suied. Secondly, all of he Ljung-Box sas are no significan (wih he excepion of wo a he end of he session). Therefore his TGARCH model is clearly adequae for describing he condiional heeroskedasiciy of he daa. Table 10, while showing he resuls of he fifh hypohesis, also provides us wih a general vision of he behavior of he IBEX inraday dayime reurns hroughou he whole session. Firsly, we observe ha a 09:05 AM here are iniial overreacion and underreaion effecs in he IBEX inraday dayime reurns caused by he informaion coming from he previous daily reurns in he IBEX and DOW respecively. Secondly, here are no significan coefficiens in he mean equaion relaed wih he μ 1 and he μ erms unil 1:00 which indicaes ha afer he opening of he Spanish marke here is a period of relaive calm which is broken as he marke begins o ge ready for he opening of he DOW and he arrival of news from he US. This leads us o he hird par of he day when he IBEX inraday dayime reurns underreac o he IBEX previous reurns, which is in accordance wih he fourh hypohesis, and overreac o he DOW reurns (which is also in accordance wih he hird and fourh hypoheses). We find no differences wih respec o he previous resuls of he asymmery and volailiy coefficiens in his case since boh of hem are posiive and significan, which in reference o he asymmery coefficiens indicaes he exisence of a leverage effec. Finally, he Ljung-Box saisics show ha he serial dependence of he condiional mean and variance dependence were well capured by he proposed model. Therefore, he analysis of hese five hypoheses leads us, firsly, o confirm he exisence of reurn and volailiy spillovers from he DOW over he IBEX. Secondly, o sae ha he DOW reurns cause an underreacion effec in he IBEX firs hours of rading (from 09:05 o 1:00) and an overreacion effec in he laer hours (from 15:30 o he end of he rading day). 3

24 Table 10: Reurn and volailiy spillovers from Hypohesis 5 09:05 09:15 09:30 10:00 11:00 1:00 13:00 14:00 15:00 15:30 16:00 17:00 17:30 Mean Equaion μ *** ** ** *** *** *** *** ** * ** ** (-3.339) (-0.763) (-1.97) (-.304) (-.585) (-.67) (-3.337) (-3.19) (-.331) (-1.855) (-.357) (-.107) (0.9) μ *** * 0.0 * 0.01 * 0.07 ** ** ** ** ** (-4.654) (-0.739) (0.414) (-1.545) (0.589) (1.74) (1.836) (1.747) (1.974) (.08) (.410) (.159) (.064) μ 0.01 ** ** ** *** *** *** *** *** *** (.538) (-0.315) (-1.466) (-1.545) (-1.638) (-.397) (-.081) (-.777) (-4.345) (-4.799) (-4.916) (-4.48) (-3.63) Variance Equaion ω *** *** *** *** *** *** *** *** *** *** *** *** *** (7.930) (7.607) (4.578) (4.93) (4.767) (5.983) (5.569) (4.733) (4.678) (4.69) (4.763) (5.587) (6.843) α *** *** *** 0.09 *** *** *** *** *** *** *** 0.09 *** (6.515) (4.303) (8.896) (6.640) (11.168) (9.76) (10.397) (6.583) (3.19) (3.14) (.76) (1.539) (0.99) β *** *** *** *** 0.8 *** 0.83 *** *** 0.88 *** *** *** *** *** *** (59.981) (93.48) (65.993) (63.773) (67.57) (66.610) (60.751) (71.951) (84.67) (76.838) (85.88) ( ) ( ) γ *** *** *** 0.07 *** 0.06 *** ** *** *** 0.13 *** 0.16 *** 0.13 *** *** (-0.144) (6.149) (6.419) (6.33) (4.370) (3.377) (.355) (3.689) (6.760) (7.743) (9.157) (11.10) (1.468) θ 0.00 *** *** *** *** *** 0.00 *** 0.03 *** 0.09 *** 0.0 *** 0.03 *** *** *** *** (8.405) (9.147) (13.444) (6.870) (6.40) (7.598) (11.070) (8.738) (6.894) (6.193) (5.47) (.905) (.745) LL LB(15) *** LBS(15) *** 3.67 * Noes: This able shows he resuls for he TGARCH model IBEXIDDRA μ 0 μ 1 IBEXR -1 μ DOWR -1 Saisics h αε 1 βh 1 γε 1 I 1 θdowr -1 T-saisics in parenheses. LL is he Log-likelihood saisic. LB(15) and LBS(15) are he Ljung-Box saisics for he sandardized residuals and squared residuals, respecively, wih 15 lagged values included. Significan coefficiens are denoed by ***, ** and * for 1%, 5% and 10% significance levels, respecively. 4

DOES TRADING VOLUME INFLUENCE GARCH EFFECTS? SOME EVIDENCE FROM THE GREEK MARKET WITH SPECIAL REFERENCE TO BANKING SECTOR

DOES TRADING VOLUME INFLUENCE GARCH EFFECTS? SOME EVIDENCE FROM THE GREEK MARKET WITH SPECIAL REFERENCE TO BANKING SECTOR Invesmen Managemen and Financial Innovaions, Volume 4, Issue 3, 7 33 DOES TRADING VOLUME INFLUENCE GARCH EFFECTS? SOME EVIDENCE FROM THE GREEK MARKET WITH SPECIAL REFERENCE TO BANKING SECTOR Ahanasios

More information

THE NEW MARKET EFFECT ON RETURN AND VOLATILITY OF SPANISH STOCK SECTOR INDEXES

THE NEW MARKET EFFECT ON RETURN AND VOLATILITY OF SPANISH STOCK SECTOR INDEXES THE NEW MARKET EFFECT ON RETURN AND VOLATILITY OF SPANISH STOCK SECTOR INDEXES Juan Ángel Lafuene Universidad Jaume I Unidad Predeparamenal de Finanzas y Conabilidad Campus del Riu Sec. 1080, Casellón

More information

Chapter 8: Regression with Lagged Explanatory Variables

Chapter 8: Regression with Lagged Explanatory Variables Chaper 8: Regression wih Lagged Explanaory Variables Time series daa: Y for =1,..,T End goal: Regression model relaing a dependen variable o explanaory variables. Wih ime series new issues arise: 1. One

More information

Revisions to Nonfarm Payroll Employment: 1964 to 2011

Revisions to Nonfarm Payroll Employment: 1964 to 2011 Revisions o Nonfarm Payroll Employmen: 1964 o 2011 Tom Sark December 2011 Summary Over recen monhs, he Bureau of Labor Saisics (BLS) has revised upward is iniial esimaes of he monhly change in nonfarm

More information

Market Liquidity and the Impacts of the Computerized Trading System: Evidence from the Stock Exchange of Thailand

Market Liquidity and the Impacts of the Computerized Trading System: Evidence from the Stock Exchange of Thailand 36 Invesmen Managemen and Financial Innovaions, 4/4 Marke Liquidiy and he Impacs of he Compuerized Trading Sysem: Evidence from he Sock Exchange of Thailand Sorasar Sukcharoensin 1, Pariyada Srisopisawa,

More information

GOOD NEWS, BAD NEWS AND GARCH EFFECTS IN STOCK RETURN DATA

GOOD NEWS, BAD NEWS AND GARCH EFFECTS IN STOCK RETURN DATA Journal of Applied Economics, Vol. IV, No. (Nov 001), 313-37 GOOD NEWS, BAD NEWS AND GARCH EFFECTS 313 GOOD NEWS, BAD NEWS AND GARCH EFFECTS IN STOCK RETURN DATA CRAIG A. DEPKEN II * The Universiy of Texas

More information

Why Did the Demand for Cash Decrease Recently in Korea?

Why Did the Demand for Cash Decrease Recently in Korea? Why Did he Demand for Cash Decrease Recenly in Korea? Byoung Hark Yoo Bank of Korea 26. 5 Absrac We explores why cash demand have decreased recenly in Korea. The raio of cash o consumpion fell o 4.7% in

More information

The Relationship between Stock Return Volatility and. Trading Volume: The case of The Philippines*

The Relationship between Stock Return Volatility and. Trading Volume: The case of The Philippines* The Relaionship beween Sock Reurn Volailiy and Trading Volume: The case of The Philippines* Manabu Asai Faculy of Economics Soka Universiy Angelo Unie Economics Deparmen De La Salle Universiy Manila May

More information

Contrarian insider trading and earnings management around seasoned equity offerings; SEOs

Contrarian insider trading and earnings management around seasoned equity offerings; SEOs Journal of Finance and Accounancy Conrarian insider rading and earnings managemen around seasoned equiy offerings; SEOs ABSTRACT Lorea Baryeh Towson Universiy This sudy aemps o resolve he differences in

More information

Market Efficiency or Not? The Behaviour of China s Stock Prices in Response to the Announcement of Bonus Issues

Market Efficiency or Not? The Behaviour of China s Stock Prices in Response to the Announcement of Bonus Issues Discussion Paper No. 0120 Marke Efficiency or No? The Behaviour of China s Sock Prices in Response o he Announcemen of Bonus Issues Michelle L. Barnes and Shiguang Ma May 2001 Adelaide Universiy SA 5005,

More information

Measuring the Downside Risk of the Exchange-Traded Funds: Do the Volatility Estimators Matter?

Measuring the Downside Risk of the Exchange-Traded Funds: Do the Volatility Estimators Matter? Proceedings of he Firs European Academic Research Conference on Global Business, Economics, Finance and Social Sciences (EAR5Ialy Conference) ISBN: 978--6345-028-6 Milan-Ialy, June 30-July -2, 205, Paper

More information

Morningstar Investor Return

Morningstar Investor Return Morningsar Invesor Reurn Morningsar Mehodology Paper Augus 31, 2010 2010 Morningsar, Inc. All righs reserved. The informaion in his documen is he propery of Morningsar, Inc. Reproducion or ranscripion

More information

CALENDAR ANOMALIES IN EMERGING BALKAN EQUITY MARKETS

CALENDAR ANOMALIES IN EMERGING BALKAN EQUITY MARKETS INTERNATIONAL ECONOMICS & FINANCE JOURNAL Vol. 6, No. 1, January-June (2011) : 67-82 CALENDAR ANOMALIES IN EMERGING BALKAN EQUITY MARKETS Andreas G. Georganopoulos *, Dimiris F. Kenourgios ** and Anasasios

More information

Price elasticity of demand for crude oil: estimates for 23 countries

Price elasticity of demand for crude oil: estimates for 23 countries Price elasiciy of demand for crude oil: esimaes for 23 counries John C.B. Cooper Absrac This paper uses a muliple regression model derived from an adapaion of Nerlove s parial adjusmen model o esimae boh

More information

THE EFFECTS OF INTERNATIONAL ACCOUNTING STANDARDS ON STOCK MARKET VOLATILITY: THE CASE OF GREECE

THE EFFECTS OF INTERNATIONAL ACCOUNTING STANDARDS ON STOCK MARKET VOLATILITY: THE CASE OF GREECE Invesmen Managemen and Financial Innovaions, Volume 4, Issue 1, 007 61 THE EFFECTS OF INTERNATIONAL ACCOUNTING STANDARDS ON STOCK MARKET VOLATILITY: THE CASE OF GREECE Chrisos Floros * Absrac The adopion

More information

The Influence of Positive Feedback Trading on Return Autocorrelation: Evidence for the German Stock Market

The Influence of Positive Feedback Trading on Return Autocorrelation: Evidence for the German Stock Market The Influence of Posiive Feedback Trading on Reurn Auocorrelaion: Evidence for he German Sock Marke Absrac: In his paper we provide empirical findings on he significance of posiive feedback rading for

More information

Journal Of Business & Economics Research September 2005 Volume 3, Number 9

Journal Of Business & Economics Research September 2005 Volume 3, Number 9 Opion Pricing And Mone Carlo Simulaions George M. Jabbour, (Email: jabbour@gwu.edu), George Washingon Universiy Yi-Kang Liu, (yikang@gwu.edu), George Washingon Universiy ABSTRACT The advanage of Mone Carlo

More information

SPEC model selection algorithm for ARCH models: an options pricing evaluation framework

SPEC model selection algorithm for ARCH models: an options pricing evaluation framework Applied Financial Economics Leers, 2008, 4, 419 423 SEC model selecion algorihm for ARCH models: an opions pricing evaluaion framework Savros Degiannakis a, * and Evdokia Xekalaki a,b a Deparmen of Saisics,

More information

Supplementary Appendix for Depression Babies: Do Macroeconomic Experiences Affect Risk-Taking?

Supplementary Appendix for Depression Babies: Do Macroeconomic Experiences Affect Risk-Taking? Supplemenary Appendix for Depression Babies: Do Macroeconomic Experiences Affec Risk-Taking? Ulrike Malmendier UC Berkeley and NBER Sefan Nagel Sanford Universiy and NBER Sepember 2009 A. Deails on SCF

More information

Investor sentiment of lottery stock evidence from the Taiwan stock market

Investor sentiment of lottery stock evidence from the Taiwan stock market Invesmen Managemen and Financial Innovaions Volume 9 Issue 1 Yu-Min Wang (Taiwan) Chun-An Li (Taiwan) Chia-Fei Lin (Taiwan) Invesor senimen of loery sock evidence from he Taiwan sock marke Absrac This

More information

Estimating Time-Varying Equity Risk Premium The Japanese Stock Market 1980-2012

Estimating Time-Varying Equity Risk Premium The Japanese Stock Market 1980-2012 Norhfield Asia Research Seminar Hong Kong, November 19, 2013 Esimaing Time-Varying Equiy Risk Premium The Japanese Sock Marke 1980-2012 Ibboson Associaes Japan Presiden Kasunari Yamaguchi, PhD/CFA/CMA

More information

Small and Large Trades Around Earnings Announcements: Does Trading Behavior Explain Post-Earnings-Announcement Drift?

Small and Large Trades Around Earnings Announcements: Does Trading Behavior Explain Post-Earnings-Announcement Drift? Small and Large Trades Around Earnings Announcemens: Does Trading Behavior Explain Pos-Earnings-Announcemen Drif? Devin Shanhikumar * Firs Draf: Ocober, 2002 This Version: Augus 19, 2004 Absrac This paper

More information

Term Structure of Prices of Asian Options

Term Structure of Prices of Asian Options Term Srucure of Prices of Asian Opions Jirô Akahori, Tsuomu Mikami, Kenji Yasuomi and Teruo Yokoa Dep. of Mahemaical Sciences, Risumeikan Universiy 1-1-1 Nojihigashi, Kusasu, Shiga 525-8577, Japan E-mail:

More information

Can Individual Investors Use Technical Trading Rules to Beat the Asian Markets?

Can Individual Investors Use Technical Trading Rules to Beat the Asian Markets? Can Individual Invesors Use Technical Trading Rules o Bea he Asian Markes? INTRODUCTION In radiional ess of he weak-form of he Efficien Markes Hypohesis, price reurn differences are found o be insufficien

More information

Usefulness of the Forward Curve in Forecasting Oil Prices

Usefulness of the Forward Curve in Forecasting Oil Prices Usefulness of he Forward Curve in Forecasing Oil Prices Akira Yanagisawa Leader Energy Demand, Supply and Forecas Analysis Group The Energy Daa and Modelling Cener Summary When people analyse oil prices,

More information

Does informed trading occur in the options market? Some revealing clues

Does informed trading occur in the options market? Some revealing clues Does informed rading occur in he opions marke? Some revealing clues Blasco N.(1), Corredor P.(2) and Sanamaría R. (2) (1) Universiy of Zaragoza (2) Public Universiy of Navarre Absrac This paper analyses

More information

How Fast Do Tokyo and New York Stock Exchanges. Respond to Each Other?: An Analysis with. High-Frequency Data

How Fast Do Tokyo and New York Stock Exchanges. Respond to Each Other?: An Analysis with. High-Frequency Data Discussion Paper No.10 How Fas Do Tokyo and New York Sock Exchanges Respond o Each Oher?: An Analysis wih High-Frequency Daa Yoshiro Tsusui and Kenjiro Hirayama Ocober 2008 GCOE Secrearia Graduae School

More information

Measuring macroeconomic volatility Applications to export revenue data, 1970-2005

Measuring macroeconomic volatility Applications to export revenue data, 1970-2005 FONDATION POUR LES ETUDES ET RERS LE DEVELOPPEMENT INTERNATIONAL Measuring macroeconomic volailiy Applicaions o expor revenue daa, 1970-005 by Joël Cariolle Policy brief no. 47 March 01 The FERDI is a

More information

Duration and Convexity ( ) 20 = Bond B has a maturity of 5 years and also has a required rate of return of 10%. Its price is $613.

Duration and Convexity ( ) 20 = Bond B has a maturity of 5 years and also has a required rate of return of 10%. Its price is $613. Graduae School of Business Adminisraion Universiy of Virginia UVA-F-38 Duraion and Convexiy he price of a bond is a funcion of he promised paymens and he marke required rae of reurn. Since he promised

More information

The Behavior of China s Stock Prices in Response to the Proposal and Approval of Bonus Issues

The Behavior of China s Stock Prices in Response to the Proposal and Approval of Bonus Issues The Behavior of China s Sock Prices in Response o he Proposal and Approval of Bonus Issues Michelle L. Barnes a* and Shiguang Ma b a Federal Reserve Bank of Boson Research, T-8 600 Alanic Avenue Boson,

More information

The Greek financial crisis: growing imbalances and sovereign spreads. Heather D. Gibson, Stephan G. Hall and George S. Tavlas

The Greek financial crisis: growing imbalances and sovereign spreads. Heather D. Gibson, Stephan G. Hall and George S. Tavlas The Greek financial crisis: growing imbalances and sovereign spreads Heaher D. Gibson, Sephan G. Hall and George S. Tavlas The enry The enry of Greece ino he Eurozone in 2001 produced a dividend in he

More information

The Transmission of Pricing Information of Dually-Listed Stocks

The Transmission of Pricing Information of Dually-Listed Stocks Journal of Business Finance & Accouning, 26(5) & (6), June/July 1999, 0306-686X The Transmission of Pricing Informaion of Dually-Lised Sks Kee-Hong Bae, Baekin Cha and Yan-Leung Cheung* 1. INTRODUCTION

More information

expressed here and the approaches suggested are of the author and not necessarily of NSEIL.

expressed here and the approaches suggested are of the author and not necessarily of NSEIL. I. Inroducion Do Fuures and Opions rading increase sock marke volailiy Dr. Premalaa Shenbagaraman * In he las decade, many emerging and ransiion economies have sared inroducing derivaive conracs. As was

More information

AN INVESTIGATION INTO THE LINKAGES BETWEEN EURO AND STERLING SWAP SPREADS. Somnath Chatterjee* Department of Economics University of Glasgow

AN INVESTIGATION INTO THE LINKAGES BETWEEN EURO AND STERLING SWAP SPREADS. Somnath Chatterjee* Department of Economics University of Glasgow AN INVESTIGATION INTO THE LINKAGES BETWEEN EURO AND STERLING SWAP SPREADS Somnah Chaerjee* Deparmen of Economics Universiy of Glasgow January, 2005 Absrac This paper examines he causal relaionship beween

More information

How Useful are the Various Volatility Estimators for Improving GARCH-based Volatility Forecasts? Evidence from the Nasdaq-100 Stock Index

How Useful are the Various Volatility Estimators for Improving GARCH-based Volatility Forecasts? Evidence from the Nasdaq-100 Stock Index Inernaional Journal of Economics and Financial Issues Vol. 4, No. 3, 04, pp.65-656 ISSN: 46-438 www.econjournals.com How Useful are he Various Volailiy Esimaors for Improving GARCH-based Volailiy Forecass?

More information

NATIONAL BANK OF POLAND WORKING PAPER No. 120

NATIONAL BANK OF POLAND WORKING PAPER No. 120 NATIONAL BANK OF POLAND WORKING PAPER No. 120 Large capial inflows and sock reurns in a hin marke Janusz Brzeszczyński, Marin T. Bohl, Dobromił Serwa Warsaw 2012 Acknowledgemens: We would like o hank Ludwig

More information

11/6/2013. Chapter 14: Dynamic AD-AS. Introduction. Introduction. Keeping track of time. The model s elements

11/6/2013. Chapter 14: Dynamic AD-AS. Introduction. Introduction. Keeping track of time. The model s elements Inroducion Chaper 14: Dynamic D-S dynamic model of aggregae and aggregae supply gives us more insigh ino how he economy works in he shor run. I is a simplified version of a DSGE model, used in cuing-edge

More information

Does Option Trading Have a Pervasive Impact on Underlying Stock Prices? *

Does Option Trading Have a Pervasive Impact on Underlying Stock Prices? * Does Opion Trading Have a Pervasive Impac on Underlying Sock Prices? * Neil D. Pearson Universiy of Illinois a Urbana-Champaign Allen M. Poeshman Universiy of Illinois a Urbana-Champaign Joshua Whie Universiy

More information

Ownership structure, liquidity, and trade informativeness

Ownership structure, liquidity, and trade informativeness Journal of Finance and Accounancy ABSTRACT Ownership srucure, liquidiy, and rade informaiveness Dan Zhou California Sae Universiy a Bakersfield In his paper, we examine he relaionship beween ownership

More information

The predictive power of volatility models: evidence from the ETF market

The predictive power of volatility models: evidence from the ETF market Invesmen Managemen and Financial Innovaions, Volume, Issue, 4 Chang-Wen Duan (Taiwan), Jung-Chu Lin (Taiwan) The predicive power of volailiy models: evidence from he ETF marke Absrac This sudy uses exchange-raded

More information

Do Investors Overreact or Underreact to Accruals? A Reexamination of the Accrual Anomaly

Do Investors Overreact or Underreact to Accruals? A Reexamination of the Accrual Anomaly Do Invesors Overreac or Underreac o Accruals? A Reexaminaion of he Accrual Anomaly Yong Yu* Smeal College of Business Pennsylvania Sae Universiy This draf: December 30, 2005 Absrac Sloan (996) finds ha

More information

Asymmetric Information, Perceived Risk and Trading Patterns: The Options Market

Asymmetric Information, Perceived Risk and Trading Patterns: The Options Market Asymmeric Informaion, Perceived Risk and Trading Paerns: The Opions Marke Guy Kaplanski * Haim Levy** March 01 * Bar-Ilan Universiy, Israel, Tel: 97 50 696, Fax: 97 153 50 696, email: guykap@biu.ac.il.

More information

The Information Content of Implied Skewness and Kurtosis Changes Prior to Earnings Announcements for Stock and Option Returns

The Information Content of Implied Skewness and Kurtosis Changes Prior to Earnings Announcements for Stock and Option Returns The Informaion Conen of Implied kewness and urosis Changes Prior o Earnings Announcemens for ock and Opion Reurns Dean Diavaopoulos Deparmen of Finance Villanova Universiy James. Doran Bank of America

More information

Oil Price Fluctuations and Firm Performance in an Emerging Market: Assessing Volatility and Asymmetric Effect

Oil Price Fluctuations and Firm Performance in an Emerging Market: Assessing Volatility and Asymmetric Effect Journal of Economics, Business and Managemen, Vol., No. 4, November 203 Oil Price Flucuaions and Firm Performance in an Emerging Marke: Assessing Volailiy and Asymmeric Effec Hawai Janor, Aisyah Abdul-Rahman,

More information

SAMUELSON S HYPOTHESIS IN GREEK STOCK INDEX FUTURES MARKET

SAMUELSON S HYPOTHESIS IN GREEK STOCK INDEX FUTURES MARKET 154 Invesmen Managemen and Financial Innovaions, Volume 3, Issue 2, 2006 SAMUELSON S HYPOTHESIS IN GREEK STOCK INDEX FUTURES MARKET Chrisos Floros, Dimirios V. Vougas Absrac Samuelson (1965) argues ha

More information

Does Option Trading Have a Pervasive Impact on Underlying Stock Prices? *

Does Option Trading Have a Pervasive Impact on Underlying Stock Prices? * Does Opion Trading Have a Pervasive Impac on Underlying Soc Prices? * Neil D. Pearson Universiy of Illinois a Urbana-Champaign Allen M. Poeshman Universiy of Illinois a Urbana-Champaign Joshua Whie Universiy

More information

Why does the correlation between stock and bond returns vary over time?

Why does the correlation between stock and bond returns vary over time? Why does he correlaion beween sock and bond reurns vary over ime? Magnus Andersson a,*, Elizavea Krylova b,**, Sami Vähämaa c,*** a European Cenral Bank, Capial Markes and Financial Srucure Division b

More information

VIX, Gold, Silver, and Oil: How do Commodities React to Financial Market Volatility?

VIX, Gold, Silver, and Oil: How do Commodities React to Financial Market Volatility? VIX, Gold, Silver, and Oil: How do Commodiies Reac o Financial Marke Volailiy? Daniel Jubinski Sain Joseph s Universiy Amy F. Lipon Sain Joseph s Universiy We examine how implied and conemporaneous equiy

More information

Journal of Financial and Strategic Decisions Volume 12 Number 1 Spring 1999

Journal of Financial and Strategic Decisions Volume 12 Number 1 Spring 1999 Journal of Financial and Sraegic Decisions Volume 12 Number 1 Spring 1999 THE LEAD-LAG RELATIONSHIP BETWEEN THE OPTION AND STOCK MARKETS PRIOR TO SUBSTANTIAL EARNINGS SURPRISES AND THE EFFECT OF SECURITIES

More information

Information Leadership in Advanced Asia-Pacific Stock Markets: Returns. and Volatility Spillover and the role of public information from the U.S.

Information Leadership in Advanced Asia-Pacific Stock Markets: Returns. and Volatility Spillover and the role of public information from the U.S. Informaion Leadership in Advanced Asia-Pacific Sock Markes: Reurns and Volailiy Spillover and he role of public informaion from he U.S. and Japan Suk-Joong Kim School of Banking and Finance The Universiy

More information

Appendix D Flexibility Factor/Margin of Choice Desktop Research

Appendix D Flexibility Factor/Margin of Choice Desktop Research Appendix D Flexibiliy Facor/Margin of Choice Deskop Research Cheshire Eas Council Cheshire Eas Employmen Land Review Conens D1 Flexibiliy Facor/Margin of Choice Deskop Research 2 Final Ocober 2012 \\GLOBAL.ARUP.COM\EUROPE\MANCHESTER\JOBS\200000\223489-00\4

More information

Bid-ask Spread and Order Size in the Foreign Exchange Market: An Empirical Investigation

Bid-ask Spread and Order Size in the Foreign Exchange Market: An Empirical Investigation Bid-ask Spread and Order Size in he Foreign Exchange Marke: An Empirical Invesigaion Liang Ding* Deparmen of Economics, Macaleser College, 1600 Grand Avenue, S. Paul, MN55105, U.S.A. Shor Tile: Bid-ask

More information

Available online www.bmdynamics.com ISSN: 2047-7031. Society for Business and Management Dynamics

Available online www.bmdynamics.com ISSN: 2047-7031. Society for Business and Management Dynamics Unexpeced Volailiy Shifs and Efficiency of Emerging Sock Marke: The Case of Malaysia Elgilani Elahir Elshareif 1, Hui-Boon Tan 2 and Mei-Foong Wong 3 Absrac This paper analyzed he behavior of Malaysian

More information

Relationship between Stock Returns and Trading Volume: Domestic and Cross-Country Evidence in Asian Stock Markets

Relationship between Stock Returns and Trading Volume: Domestic and Cross-Country Evidence in Asian Stock Markets Proceedings of he 2013 Inernaional Conference on Economics and Business Adminisraion Relaionship beween Sock Reurns and Trading olume: Domesic and Cross-Counry Evidence in Asian Sock Markes Ki-Hong Choi

More information

Applied Econometrics and International Development Vol.7-1 (2007)

Applied Econometrics and International Development Vol.7-1 (2007) Applied Economerics and Inernaional Developmen Vol.7- (7) THE INFLUENCE OF INTERNATIONAL STOCK MARKETS AND MACROECONOMIC VARIABLES ON THE THAI STOCK MARKET CHANCHARAT, Surachai *, VALADKHANI, Abbas HAVIE,

More information

On Overnight Return Premiums of International Stock Markets

On Overnight Return Premiums of International Stock Markets On Overnigh Reurn Premiums of Inernaional Sock Markes Mei Qiu and Tao Cai Deparmen of Economics and Finance (Albany), Massey Universiy Absrac We sudy he daily close-o-opening overnigh reurns of sock indices

More information

THE UNIVERSITY OF TEXAS AT SAN ANTONIO, COLLEGE OF BUSINESS Working Paper SERIES

THE UNIVERSITY OF TEXAS AT SAN ANTONIO, COLLEGE OF BUSINESS Working Paper SERIES THE UNIVERSITY OF TEXAS AT SAN ANTONIO, COLLEGE OF BUSINESS Working Paper SERIES March 11 h, 2009 Wp# 0063FIN-257-2009 Where does Volailiy and Reurn Come From? The Case of Asian ETFs Yiuman Tse Deparmen

More information

Journal Of Business & Economics Research Volume 1, Number 11

Journal Of Business & Economics Research Volume 1, Number 11 Profis From Buying Losers And Selling Winners In The London Sock Exchange Anonios Anoniou (E-mail: anonios.anoniou@durham.ac.ak), Universiy of Durham, UK Emilios C. Galariois (E-mail: emilios.galariois@dirham.ac.uk),

More information

Price, Volume and Volatility Spillovers among New York, Tokyo and London Stock Markets

Price, Volume and Volatility Spillovers among New York, Tokyo and London Stock Markets INTERNATIONAL JOURNAL OF BUSINESS, 4(), 999 ISSN: 083-4346 Price, Volume and Volailiy Spillovers among New York, Tokyo and London Sock Markes Sangphill Kim and Meng Rui The dynamic relaionship among he

More information

An asymmetric process between initial margin requirements and volatility: New evidence from Japanese stock market

An asymmetric process between initial margin requirements and volatility: New evidence from Japanese stock market African Journal of Business Managemen Vol.6 (9), pp. 870-8736, 5 July, 0 Available online a hp://www.academicjournals.org/ajbm DOI: 0.5897/AJBM.88 ISSN 993-833 0 Academic Journals Full Lengh Research Paper

More information

Vector Autoregressions (VARs): Operational Perspectives

Vector Autoregressions (VARs): Operational Perspectives Vecor Auoregressions (VARs): Operaional Perspecives Primary Source: Sock, James H., and Mark W. Wason, Vecor Auoregressions, Journal of Economic Perspecives, Vol. 15 No. 4 (Fall 2001), 101-115. Macroeconomericians

More information

MACROECONOMIC FORECASTS AT THE MOF A LOOK INTO THE REAR VIEW MIRROR

MACROECONOMIC FORECASTS AT THE MOF A LOOK INTO THE REAR VIEW MIRROR MACROECONOMIC FORECASTS AT THE MOF A LOOK INTO THE REAR VIEW MIRROR The firs experimenal publicaion, which summarised pas and expeced fuure developmen of basic economic indicaors, was published by he Minisry

More information

SURVEYING THE RELATIONSHIP BETWEEN STOCK MARKET MAKER AND LIQUIDITY IN TEHRAN STOCK EXCHANGE COMPANIES

SURVEYING THE RELATIONSHIP BETWEEN STOCK MARKET MAKER AND LIQUIDITY IN TEHRAN STOCK EXCHANGE COMPANIES Inernaional Journal of Accouning Research Vol., No. 7, 4 SURVEYING THE RELATIONSHIP BETWEEN STOCK MARKET MAKER AND LIQUIDITY IN TEHRAN STOCK EXCHANGE COMPANIES Mohammad Ebrahimi Erdi, Dr. Azim Aslani,

More information

DO FUNDS FOLLOW POST-EARNINGS ANNOUNCEMENT DRIFT? RACT. Abstract

DO FUNDS FOLLOW POST-EARNINGS ANNOUNCEMENT DRIFT? RACT. Abstract DO FUNDS FOLLOW POST-EARNINGS ANNOUNCEMENT DRIFT? Ali Coskun Bogazici Universiy Umi G. Gurun Universiy of Texas a Dallas RACT Ocober 2011 Absrac We show ha acively managed U.S. hedge funds, on average,

More information

Volatility in Returns of Islamic and Commercial Banks in Pakistan

Volatility in Returns of Islamic and Commercial Banks in Pakistan Volailiy in Reurns of Islamic and Commercial Banks in Pakisan Muhammad Iqbal Non-Linear Time Series Analysis Prof. Rober Kuns Deparmen of Economic, Universiy of Vienna, Vienna, Ausria Inroducion Islamic

More information

PROFIT TEST MODELLING IN LIFE ASSURANCE USING SPREADSHEETS PART ONE

PROFIT TEST MODELLING IN LIFE ASSURANCE USING SPREADSHEETS PART ONE Profi Tes Modelling in Life Assurance Using Spreadshees PROFIT TEST MODELLING IN LIFE ASSURANCE USING SPREADSHEETS PART ONE Erik Alm Peer Millingon 2004 Profi Tes Modelling in Life Assurance Using Spreadshees

More information

Central Bank Communication and Exchange Rate Volatility: A GARCH Analysis

Central Bank Communication and Exchange Rate Volatility: A GARCH Analysis Cenral Bank Communicaion and Exchange Rae Volailiy: A GARCH Analysis Radovan Fišer Insiue of Economic Sudies, Charles Universiy, Prague Roman Horváh* Czech Naional Bank and Insiue of Economic Sudies, Charles

More information

Do news announcements affect volatility spillovers? Evidence from implied volatilities *

Do news announcements affect volatility spillovers? Evidence from implied volatilities * o news announcemens affec volailiy spillovers? Evidence from implied volailiies * George J. Jiang a, Eirini Konsaninidi b, and George kiadopoulos c This draf: epember 29, 2010 Paper No: 10/05 bsrac This

More information

Commission Costs, Illiquidity and Stock Returns

Commission Costs, Illiquidity and Stock Returns Commission Coss, Illiquidiy and Sock Reurns Jinliang Li* College of Business Adminisraion, Norheasern Universiy 413 Hayden Hall, Boson, MA 02115 Telephone: 617.373.4707 Email: jin.li@neu.edu Rober Mooradian

More information

An Econometric Analysis of Market Anomaly - Day of the Week Effect on a Small Emerging Market

An Econometric Analysis of Market Anomaly - Day of the Week Effect on a Small Emerging Market Inernaional Journal of Academic Research in Accouning, Finance and Managemen Sciences Vol., No., January 0, pp. 4 ISSN: 5-89 0 HRMARS www.hrmars.com An Economeric Analysis of Marke Anomaly - Day of he

More information

William E. Simon Graduate School of Business Administration. IPO Market Cycles: Bubbles or Sequential Learning?

William E. Simon Graduate School of Business Administration. IPO Market Cycles: Bubbles or Sequential Learning? Universiy of Rocheser William E. Simon Graduae School of Business Adminisraion The Bradley Policy Research Cener Financial Research and Policy Working Paper No. FR 00-21 January 2000 Revised: June 2001

More information

Chapter 7. Response of First-Order RL and RC Circuits

Chapter 7. Response of First-Order RL and RC Circuits Chaper 7. esponse of Firs-Order L and C Circuis 7.1. The Naural esponse of an L Circui 7.2. The Naural esponse of an C Circui 7.3. The ep esponse of L and C Circuis 7.4. A General oluion for ep and Naural

More information

Single-machine Scheduling with Periodic Maintenance and both Preemptive and. Non-preemptive jobs in Remanufacturing System 1

Single-machine Scheduling with Periodic Maintenance and both Preemptive and. Non-preemptive jobs in Remanufacturing System 1 Absrac number: 05-0407 Single-machine Scheduling wih Periodic Mainenance and boh Preempive and Non-preempive jobs in Remanufacuring Sysem Liu Biyu hen Weida (School of Economics and Managemen Souheas Universiy

More information

Causal Relationship between Macro-Economic Indicators and Stock Market in India

Causal Relationship between Macro-Economic Indicators and Stock Market in India Asian Journal of Finance & Accouning Causal Relaionship beween Macro-Economic Indicaors and Sock Marke in India Dr. Naliniprava ripahy Associae Professor (Finance), Indian Insiue of Managemen Shillong

More information

A DCC Analysis of Two Stock Market Returns Volatility with an Oil Price Factor: An Evidence Study of Singapore and Thailand s Stock Markets

A DCC Analysis of Two Stock Market Returns Volatility with an Oil Price Factor: An Evidence Study of Singapore and Thailand s Stock Markets Journal of Convergence Informaion Technology Volume 4, Number 1, March 9 A DCC Analysis of Two Sock Marke Reurns Volailiy wih an Oil Price Facor: An Evidence Sudy of Singapore and Thailand s Sock Markes

More information

TEMPORAL PATTERN IDENTIFICATION OF TIME SERIES DATA USING PATTERN WAVELETS AND GENETIC ALGORITHMS

TEMPORAL PATTERN IDENTIFICATION OF TIME SERIES DATA USING PATTERN WAVELETS AND GENETIC ALGORITHMS TEMPORAL PATTERN IDENTIFICATION OF TIME SERIES DATA USING PATTERN WAVELETS AND GENETIC ALGORITHMS RICHARD J. POVINELLI AND XIN FENG Deparmen of Elecrical and Compuer Engineering Marquee Universiy, P.O.

More information

Time Series Modeling for Risk of Stock. Price with Value at Risk Computation

Time Series Modeling for Risk of Stock. Price with Value at Risk Computation Applied Mahemaical Sciences, Vol 9, 015, no 56, 779-787 HIKARI Ld, wwwm-hikaricom hp://dxdoiorg/101988/ams0155144 Time Series Modeling for Risk of Sock Price wih Value a Risk Compuaion Dodi Deviano, Maiyasri

More information

MALAYSIAN FOREIGN DIRECT INVESTMENT AND GROWTH: DOES STABILITY MATTER? Jarita Duasa 1

MALAYSIAN FOREIGN DIRECT INVESTMENT AND GROWTH: DOES STABILITY MATTER? Jarita Duasa 1 Journal of Economic Cooperaion, 8, (007), 83-98 MALAYSIAN FOREIGN DIRECT INVESTMENT AND GROWTH: DOES STABILITY MATTER? Jaria Duasa 1 The objecive of he paper is wofold. Firs, is o examine causal relaionship

More information

MODELING SPILLOVERS BETWEEN STOCK MARKET AND MONEY MARKET IN NIGERIA

MODELING SPILLOVERS BETWEEN STOCK MARKET AND MONEY MARKET IN NIGERIA Working Paper Series: 16 Jan/2015 MODELING SPILLOVERS BETWEEN STOCK MARKET AND MONEY MARKET IN NIGERIA Afees A. Salisu and Kazeem O. Isah MODELING SPILLOVERS BETWEEN STOCK MARKET AND MONEY MARKET IN NIGERIA

More information

BALANCE OF PAYMENTS. First quarter 2008. Balance of payments

BALANCE OF PAYMENTS. First quarter 2008. Balance of payments BALANCE OF PAYMENTS DATE: 2008-05-30 PUBLISHER: Balance of Paymens and Financial Markes (BFM) Lena Finn + 46 8 506 944 09, lena.finn@scb.se Camilla Bergeling +46 8 506 942 06, camilla.bergeling@scb.se

More information

The impact of the trading systems development on bid-ask spreads

The impact of the trading systems development on bid-ask spreads Chun-An Li (Taiwan), Hung-Cheng Lai (Taiwan)* The impac of he rading sysems developmen on bid-ask spreads Absrac Following he closure, on 30 June 2005, of he open oucry sysem on he Singapore Exchange (SGX),

More information

Resiliency, the Neglected Dimension of Market Liquidity: Empirical Evidence from the New York Stock Exchange

Resiliency, the Neglected Dimension of Market Liquidity: Empirical Evidence from the New York Stock Exchange Resiliency, he Negleced Dimension of Marke Liquidiy: Empirical Evidence from he New York Sock Exchange Jiwei Dong 1 Lancaser Universiy, U.K. Alexander Kempf Universiä zu Köln, Germany Pradeep K. Yadav

More information

Predicting Stock Market Index Trading Signals Using Neural Networks

Predicting Stock Market Index Trading Signals Using Neural Networks Predicing Sock Marke Index Trading Using Neural Neworks C. D. Tilakarane, S. A. Morris, M. A. Mammadov, C. P. Hurs Cenre for Informaics and Applied Opimizaion School of Informaion Technology and Mahemaical

More information

The Transport Equation

The Transport Equation The Transpor Equaion Consider a fluid, flowing wih velociy, V, in a hin sraigh ube whose cross secion will be denoed by A. Suppose he fluid conains a conaminan whose concenraion a posiion a ime will be

More information

Predicting Stock Volatility Using After-Hours Information: Evidence. from the NASDAQ Actively Traded Stocks

Predicting Stock Volatility Using After-Hours Information: Evidence. from the NASDAQ Actively Traded Stocks Predicing Sock Volailiy Using Afer-Hours Informaion: Evidence from he NASDAQ Acively Traded Socks Chun-Hung Chen 1 Office of he Comproller of he Currency Wei-Choun Yu 2 Winona Sae Universiy Eric Zivo 3

More information

The Economic Value of Volatility Transmission between the Stock and Bond Markets

The Economic Value of Volatility Transmission between the Stock and Bond Markets The Economic Value of Volailiy Transmission beween he Sock and Bond Markes Helena Chuliá * Hipòli Torró Sepember 006 Keywords: Volailiy Spillovers, GARCH, Trading Rules JEL Classificaion: C3, C53, G11

More information

Fifth Quantitative Impact Study of Solvency II (QIS 5) National guidance on valuation of technical provisions for German SLT health insurance

Fifth Quantitative Impact Study of Solvency II (QIS 5) National guidance on valuation of technical provisions for German SLT health insurance Fifh Quaniaive Impac Sudy of Solvency II (QIS 5) Naional guidance on valuaion of echnical provisions for German SLT healh insurance Conens 1 Inroducion... 2 2 Calculaion of bes-esimae provisions... 3 2.1

More information

The Sensitivity of Corporate Bond Volatility to Macroeconomic Announcements. by Nikolay Kosturov* and Duane Stock**

The Sensitivity of Corporate Bond Volatility to Macroeconomic Announcements. by Nikolay Kosturov* and Duane Stock** The Sensiiviy of Corporae Bond Volailiy o Macroeconomic nnouncemens by Nikolay Kosurov* and Duane Sock** * Michael F.Price College of Business, Universiy of Oklahoma, 307 Wes Brooks, H 205, Norman, OK

More information

The Effectiveness of Reputation as a Disciplinary Mechanism in Sell-side Research

The Effectiveness of Reputation as a Disciplinary Mechanism in Sell-side Research The Effeciveness of Repuaion as a Disciplinary Mechanism in Sell-side Research Lily Fang INSEAD Ayako Yasuda The Wharon School, Universiy of Pennsylvania We hank Franklin Allen, Gary Goron, Pierre Hillion,

More information

THE IMPACT OF SHORT SALE RESTRICTIONS ON STOCK VOLATILITY: EVIDENCE FROM TAIWAN

THE IMPACT OF SHORT SALE RESTRICTIONS ON STOCK VOLATILITY: EVIDENCE FROM TAIWAN The Inernaional Journal of Business and Finance Research Volume 5 Number 4 2011 THE IMPACT OF SHORT SALE RESTRICTIONS ON STOCK VOLATILITY: EVIDENCE FROM TAIWAN Shih Yung Wei, Universiy of Science and Technology,

More information

A Note on the Impact of Options on Stock Return Volatility. Nicolas P.B. Bollen

A Note on the Impact of Options on Stock Return Volatility. Nicolas P.B. Bollen A Noe on he Impac of Opions on Sock Reurn Volailiy Nicolas P.B. Bollen ABSTRACT This paper measures he impac of opion inroducions on he reurn variance of underlying socks. Pas research generally finds

More information

Price Discovery in the Absence of Trading: A Look at the Malta Stock Exchange Pre-opening Period

Price Discovery in the Absence of Trading: A Look at the Malta Stock Exchange Pre-opening Period Price Discovery in he Absence of rading: A Look a he Mala Sock Exchange Pre-opening Period Michael Bowe Suar Hyde Ike Johnson Absrac his paper sudies he conribuion of he pre-opening period o he daily price

More information

INTEREST RATE FUTURES AND THEIR OPTIONS: SOME PRICING APPROACHES

INTEREST RATE FUTURES AND THEIR OPTIONS: SOME PRICING APPROACHES INTEREST RATE FUTURES AND THEIR OPTIONS: SOME PRICING APPROACHES OPENGAMMA QUANTITATIVE RESEARCH Absrac. Exchange-raded ineres rae fuures and heir opions are described. The fuure opions include hose paying

More information

Stock market returns and volatility in the BRVM

Stock market returns and volatility in the BRVM African Journal of Business Managemen Vol. (5) pp. 07-, Augus 007 Available online hp://www.academicjournals.org/ajbm ISSN 993-833 007 Academic Journals Full Lengh esearch Paper Sock marke reurns and volailiy

More information

THE BEHAVIOR OF OPTION S IMPLIED VOLATILITY INDEX: A CASE OF INDIA VIX

THE BEHAVIOR OF OPTION S IMPLIED VOLATILITY INDEX: A CASE OF INDIA VIX Verslas: Teorija ir prakika / Business: Theory and Pracice Issn 1648-0627 / eissn 1822-4202 hp://www.bp.vgu.l 2015 16(2): 149 158 doi:10.3846/bp.2015.463 THE BEHAVIOR OF OPTION S IMPLIED VOLATILITY INDEX:

More information

Modelling and Forecasting Volatility of Gold Price with Other Precious Metals Prices by Univariate GARCH Models

Modelling and Forecasting Volatility of Gold Price with Other Precious Metals Prices by Univariate GARCH Models Deparmen of Saisics Maser's Thesis Modelling and Forecasing Volailiy of Gold Price wih Oher Precious Meals Prices by Univariae GARCH Models Yuchen Du 1 Supervisor: Lars Forsberg 1 Yuchen.Du.84@suden.uu.se

More information

Chapter 6: Business Valuation (Income Approach)

Chapter 6: Business Valuation (Income Approach) Chaper 6: Business Valuaion (Income Approach) Cash flow deerminaion is one of he mos criical elemens o a business valuaion. Everyhing may be secondary. If cash flow is high, hen he value is high; if he

More information

The naive method discussed in Lecture 1 uses the most recent observations to forecast future values. That is, Y ˆ t + 1

The naive method discussed in Lecture 1 uses the most recent observations to forecast future values. That is, Y ˆ t + 1 Business Condiions & Forecasing Exponenial Smoohing LECTURE 2 MOVING AVERAGES AND EXPONENTIAL SMOOTHING OVERVIEW This lecure inroduces ime-series smoohing forecasing mehods. Various models are discussed,

More information

Default Risk in Equity Returns

Default Risk in Equity Returns Defaul Risk in Equiy Reurns MRI VSSLOU and YUHNG XING * BSTRCT This is he firs sudy ha uses Meron s (1974) opion pricing model o compue defaul measures for individual firms and assess he effec of defaul

More information

The Effect of Monetary Policy on Private Money Market Rates in Jamaica: An Empirical Microstructure Study. Derek Leith

The Effect of Monetary Policy on Private Money Market Rates in Jamaica: An Empirical Microstructure Study. Derek Leith The Effec of Moneary Policy on Privae Money Marke Raes in Jamaica: An Empirical Microsrucure Sudy Derek Leih Research Services Deparmen Research and Economic Programming Division Bank of Jamaica Absrac

More information