SWISS FOREIGN TRADE INDICES USERS GUIDE

Size: px
Start display at page:

Download "SWISS FOREIGN TRADE INDICES USERS GUIDE"

Transcription

1 SWSS FOREGN TRADE NDCES USERS GUDE Ma 26 Federal Cusoms Admnsraon (FCA) Secon Dssemnaon and analyses The resen documen s he reference gude for Swss foregn rade ndces and s nended for all s users. Through examles, reveals and exlans se-by-se he mehodology used o calculae he ndces. ncludes n arcular: he avalable ndces, he mehod used o calculae hem and her ossble uses. The ueson of un values and he rocedures used o guaranee ha he resuls are reresenave and relable are analysed n deal. Fnally, he mos raccal asecs of he ndces (dssemnaon, erodcy) are ndcaed.

2 CONTENTS 1 FOREGN TRADE NDCES: OVERVEW UNT VALUES PROBLEM AND SOLUTONS APPLED Un value and rce Soluons chosen n relaon o he roblem of un values Mehod aled n relaon o arff headngs Mehods aled n relaon o mean values Connual chec of he relably of un values and ndces CALCULATNG THE NDCES Calculaons on a movng base for grous by naure of goods Un value ndex a he lowes level of subgrous by naure of goods Nomnal ndex a he lowes level of subgrous by naure of goods Real ndex for he lowes level of subgrous by naure of goods Calculaon on a movng base for he grous by broad economc caegores Channg and year-on-year comarson Channg Year-on-year comarson WORKNG DAYS AND SEASONAL ADJUSTMENTS Why are hese adusmens necessary? Mehod Resuls PERODCTES DSSEMNATON POSSBLE USES FOR THE NDCES CONTACT

3 1 FOREGN TRADE NDCES: OVERVEW Swss foregn rade sascs rovde he general ublc no only wh absolue rade fgures (value n Swss francs, uany n lograms) bu also ndces whch brea down he nomnal rend no wo elemens, namely rce and volume. Ths reveals he real rend n rade. The followng ndces are avalable o he ublc: nomnal ndex (or value ndex) un value ndex (or rce ndex) real ndex (or volume ndex) The nomnal ndex s calculaed from sascal values and ndcaes he varaon n value beween wo erods of me. The un value ndex measures he rend n rces on he bass of un values. The real ndex ndcaes he real rend (or removed from rce effecs) n foregn rade. Ths s a resdual value resulng from he nomnal ndex and he un value ndex. These ndces are comled for oal rade as well as for grous of goods accordng o her naure (breadown by branches) or her broad economcs caegores (breadown by basc caegores of he naonal accoun). n conras, no ndex by counry or by arff headng s avalable. 2 UNT VALUES PROBLEM AND SOLUTONS APPLED An undersandng of he basc characerscs of un values enables users o roerly nerre he esmaed varaon n rces usng foregn rade ndces. n hs secon we resen he conce of un value and he uesons ha arse from. Subseuenly, we descrbe he soluons aled o guaranee he ualy and relably of he ublshed nformaon. 2.1 Un value and rce The rce of mored and exored goods s no recorded by he cusoms auhores. The cusoms declaraon does, however, nclude he ye of merchandse, he uany and he value. Varaons n mor and exor rces are esmaed for each arff headng 1 on he bass of un values, whch are defned as he rao beween he value and he uany. The un value s herefore no a real rce, bu an average rce er logram for each arff headng. For a arff headng ha s ermed homogeneous, conanng for examle only one sngle roduc, un values vary n drec rooron o rces. n general, varaons n rces and un values are closely lned emrcally over he long erm. n he shor erm, here may be a degree of dvergence. 1 Caegory of merchandse 3

4 The use of un values n relaon o foregn rade offers he followng advanages n arcular: No addonal recordng The un values are calculaed from cusoms nformaon. Unle rces, hey do no have o be secfcally noed by dfferen comanes. The advanages are hus obvous for boh exorng and morng frms (no exra burden) and our sascs secon (n erms of cos). Comrehensve summary of rade The un values are calculaed for all cusoms ransacons ha are ncluded n foregn rade sascs. Usng un values as a bass can nvolve he followng dsadvanages: Hgher volaly Un values are generally much more volale han rces. Varaons arsng from facors oher han rce. The un value of a arff headng may change even f he rce of he arcle n ueson remans consan. Un values are n fac nfluenced by many facors aar from rce, rncally he followng: changes n he range of goods whn a heerogeneous arff headng,.e. ncludng dfferen roducs (see box below); mnaursaon: hans o echnologcal rogress roducs are beng manufacured n smaller and lgher versons whou he characerscs or he funcon of he roduc beng mroved. The rce er logram (mean value) of hese roducs ends herefore o gradually rse; acagng modfcaon: snce he un value deends on he wegh, s affeced by he acagng (o a greaer or lesser exen); ualy modfcaon: hs facor s a roblem n relaon no only o he relably of an un value ndex bu also o a classcal rce ndex. BOX Change n he range of roducs and un value Un values are more volale han rces and do no necessarly reflec he real varaon n rce. n exreme cases, un values may aear o vary whle rces reman sable over he erod n ueson. Le us consder a heorecal arff headng ha ncludes hree roducs (A, B and C) for whch we have nown uanes and values as well as, for our uroses, rces: PEROD 1 PEROD 2 g CHF/g CHF g CHF/g CHF Produc A 3 3 9, 1 3 3, Produc B 2 2 4, 2 2 4, Produc C 1 2 2, 1 2 2, Toal for he arff headng 6-15, 4-9, There aears o be no varaon n rce among he roducs. The mored uanes of roducs B and C have no changed. Only sales of roduc A have slumed. Now le us calculae he un values for he headng: - Over erod 1, he headng shows a value of CHF 15, for a uany of 6 g un value: CHF 25.-/g (= 15,.- / 6 g) - Over erod 2, he value of he headng s CHF 9, and he uany n ueson s 4 g un value: CHF 22.5/g 4

5 Beween erods 1 and 2 he un value of he arff headng has fallen from Fr. 25 o 22.5,.e. a dro of 1%. whou nowng he real rces one would assume ha hey had fallen by 1% whle n fac here has been no change n rce. n hs examle he un value has changed followng a modfcaon n he comoson of he arff headng. 2.2 Soluons chosen n relaon o he roblem of un values n order o omse he use of un values he chosen mehod s aled a hree comlemenary levels: selecon of reresenave ems, rocessng of un values and safey ne (connual chec of he relably of he un values and ndces) Mehod aled n relaon o arff headngs To guaranee he ualy and relably of he ndces for un values he 8, or so arff headngs are sl no wo grous: reresenave ems: he un values for hese arff headngs are suffcenly sable and her varaon s lely o corresond o ha of rces. The un value ndex s based solely on hese ems. n Ocober 25 hs grou ncluded 69% of mored ems for 93% of he value; on he exor sde, hs grou reresened 49% of goods for 92% of value. non-reresenave ems: he un values of hese ems generally resen an exreme volaly and can be lned wh he evoluon of rces. Ths caegory can also nclude ems ha are raded very lle. n Ocober 25, whle hs grou comrsed 31% of mored ems, reresened only 7% of he oal value of mors. On he exor sde, ncluded 51% of ems mored and 8% of he value. The dvson of arff headngs no hese wo caegores s based rmarly on a dealed examnaon ha s generally carred ou once a year. Ths comrses an (auomaed) sysemac dscrmnan analyss amed a erodcally revsng he exen o whch un values are reresenave for each arff headng. Dfferen ualy ndcaors for each em are aen no accoun: he coeffcen of varaon before and afer oulers have been correced, he number of erods whou any flow, he relave morance (whn he merchandse grou) and absolue morance (n relaon o oal rade) of he em, ec. n concree erms, he mehod s used o assess he robably of an em belongng o one grou or he oher. Ths rae of robably s hen used o draw u roosed classfcaons. A fnal chec of he resuls, ogeher wh an n-deh sudy for ceran arff headngs, wll hen confrm or nvaldae he roosals resulng from he dscrmnan analyss Mehods aled n relaon o mean values n order o elmnae devan un values ha do no relae o he real rend n rces, he orgnal seres of un values are rocessed every monh before he ndces are calculaed. Ths rocedure may be carred ou n any of he followng ways: oulers correcon, exernal rces, medan, orgnal daa. 5

6 Oulers correcon Ths s he sandard mehod for rocessng seres of un values. n Ocober 25 hs mehod was used on 99.6% and 99.9% of reresenave mored and exored ems resecvely. The mehod for rocessng un values s fully auomaed and consss of denfyng oulers and relacng hem wh lausble values. The basc ool s he AUTOBOX rogramme 2 devsed by Davd P. Relly (USA) secfcally for analysng me seres. A verson has also been develoed ha s secally adaed o our reuremens. For each seres of un values (monhly seres coverng he revous 6 years and he curren year) he rogramme denfes he ARMA model whch bes descrbes he daa evoluon. Ths model aes no accoun n arcular any level shfs, seasonal facors, changes n he rend and changes n varance. The rogramme hen deecs any oulers defned as values ousde he confdence nerval se by he model. Once hey have been denfed, oulers are relaced by a lausble esmaon ha conforms o he model. Ths mehodology allows he varably of he un values o be consderably reduced, hus mang hem more reresenave, whch means ha a larger number of arff headngs can be used o calculae he un value ndex. Whle hs mehod rovdes relable resuls for he large maory of ems, may nvolve nadeuae correcons, deendng on he characerscs of he seres of orgnal daa. n such cases, oulers are no correced auomacally and one of he hree oher mehods s used. Exernal rces The oon of exernal rces allows un values for a arff headng o be relaced by values for an exernal seres of rces. Ths seres may be rovded by an exernal source no relaed o foregn rade sascs. For raccal reasons and n vew of he avalably of nformaon, an nernal soluon s generally referred. Ths mehod s secfcally for arff headngs wh a huge radng value bu for whch he un values are no arcularly sgnfcan and are so varable ha no model can be found and oulers canno be deeced. A resen, he oon of exernal rces s used only o rocess ems relang o arcraf. These arff headngs cover flucual rade n new arcraf (exremely hgh mean value) and second-hand arcraf and sare ars whose un values are very volale. Medan The un value of a arff headng can also be relaced by he medan, whch s defned as he cenral value (rce er g) of all he shmens relang o ha em over one monh. By defnon, he medan s he value whch dvdes all he shmens no wo grous of he same sze: 5% of he shmens are a a rce er g above he medan and 5% a a rce er g below he medan. Ths oon s suable for ems of morance wh exremely varable mean values, where exreme values gve oally ncorrec resuls. Ths oon s rarely used

7 Orgnal seres may haen ha orgnal seres aear o be more realsc ha hose obaned usng sandard correcon. n such cases he sandard correcon s no carred ou Connual chec of he relably of un values and ndces Gven he rad changes n reresenavy and he delcae as of correcng oulers n ceran cases, decsons regardng annual classfcaon may ucly become nvald. s for hs reason ha, as well as beng revsed annually, arff headngs are subeced o a monhly ualy chec whch consss of searchng ou unrealsc un values (defned by a varaon n rce beween wo erods eual o or over 1) before he erodcal ublcaon of new daa. f necessary, roblemac headngs are elmnaed mmedaely from he reresenave ems and he ndex s recalculaed ang no accoun he modfcaons. The nroducon of hs monhly safey ne means ha an acve (as oosed o a reacve) olcy can be followed wh regard o he ualy and he relably of he ndces. 7

8 3 CALCULATNG THE NDCES The nomnal and real ndces are based on all he arff headngs, whereas only he reresenave ems are used o calculae he un value ndex. ndces are avalable down o he lowes level of subgrous accordng o he naure of goods (breadown by branches) or he broad economcs caegores (breadown by basc caegores of he naonal accoun). They are frs calculaed for hese grous. The resuls obaned are hen aggregaed o gve daa for subgrous a hgher levels, hen for he man grous and fnally for oal rade. The ndces are calculaed on he bass of orgnal values or of oulers correced daa. n any case, only he second are ublshed. Snce rade n recous meals, recous sones, gemsones, wors of ar and anues s unceran and unredcable, such goods are no ncluded n he calculaons for he ndces (.e. accordng o oal 1). 3.1 Calculaons on a movng base for grous by naure of goods The mehodology and formulae used for calculang nomnal, real and un value ndces are ndcaed se-by-se. To mae hs more comrehensble, he varous rocedures and calculaons are llusraed wh a smle examle. For he un value ndex he basc elemens are frs ndcaed for he deal case,.e. for a grou accordng o he naure of goods made u solely of reresenave ems. We shall hen focus on he general case of a grou ha also ncludes non-reresenave ems. BOX Advanages of a movng base as oosed o a fxed base The comoson of oal mors and exors s consanly changng and from one erod of me o anoher and varaons can be consderable. f he ndex s calculaed on a movng base he weghng s deermned by he curren base of goods exchanged. s herefore no necessary o revse he conens of he base a regular nervals snce wll auomacally change from one erod o he nex. Ths mehod serves o mnmse he recurren roblems of rce ndces when he ualy of he roducs changes. f a fxed base s used he conens of he base reman he same over me and changes n ualy beween he nal erod and he curren erod may gve a false dea of rces Un value ndex a he lowes level of subgrous by naure of goods Grous by naure of goods made u solely of ndex ems Foregn rade ndces are calculaed on he bass of nformaon obaned from cusoms declaraons. n arcular, he uany and he value consue he man daa for he calculaons. Based on rovsonal fgures for he monh of June 25, he subgrou Socs, socngs, ghs ( ), whch s ar of he man grou exles, clohng, foowear (3) s used as an examle. BOX The examle n bref The subgrou socs, socngs, ghs ncludes 1 arff headngs ha can be dsngushed by he ualy of he fbre used (such as synhec fbre, coon or vegeable fbre). Ths grou ncludes only reresenave ems. 8

9 Naure Tarff headng curren erod (e.g. June 25) value a uany (orgnal or correced) a un value a Toal s no he value a he same erod he revous year, bu he value for an average erod durng he revous year (erod ). uany (orgnal or correced) a un value a f Q (1) where Q = oal uany for he revous year f P Q (2) where P Q = oal value for he revous year where f x 12 for he monhly daa for heuarerly daa for hecumulaed daa (e.g. x 8 for he erod January oaugus) BOX Orgnal and oulers correced uanes The correcon of exreme values s aen no accoun when he ndex s calculaed by usng and. For each reresenave arff headng he uanes are adaed o oban a oseror he adused un value ndcaed by he model. Ths mehod guaranees ha each em s correced n a neural way, based on he defnon uany mes rce. The correced ndex s based on correced uanes, whle he orgnal ndex s calculaed from orgnal uanes. The Laseyres ndex Snce foregn rade ndces are calculaed from a movng base, and relae o he recedng year as a whole. The frs sage s o oban un values for and for roduc ( and ). n order o do hs he value for he curren erod and ha for he recedng year (e.g. average monhly value for 24) are dvded by her 9

10 resecve uany e (e.g. he average monhly uany for 24). By defnon, he value/uany uoens reresen he un values. For he frs arff headng of he grou ( ), he followng s hus obaned: (3) = (4) = Naure Tarff headng Toal Usng esmaed rces and uanes s ossble o reconsruc he values for he desred erods. n arcular, he (hyohecal) value of he nal base a curren rces can be exressed. Ths value s necessary for he Laseyres ndex o be calculaed. Naure Tarff headng Laseyres Toal The Laseyres ndex can be calculaed usng he followng formula: where P Q P Q Laseyres (5) P Q = he value of base a erod 1

11 P Q = he hyohecal value of he base a erod exressed n curren rces (erod ). BOX The Laseyres ndex The formula for he Laseyres ndex was devsed over 13 years ago by Erns Lous Eenne Laseyres ( ). He used frs hs formula for he rce of goods n he or of Hamburg. The hnng behnd hs formula s easly undersood hrough he followng smlfed examle: ae a counry ha mors only wne and bananas. Over a gven year hs counry has mored 2 lres of wne a Fr. 4 er lre and 3 g of bananas a Fr. 2 er g. A year laer he wne coss Fr. 5 er lre and he bananas Fr. 3 er g. Wha s he average ercenage ncrease n he rce of he mored goods? Laseyres The Laseyres rce ndex shows he rae of varaon n rces f he base for he reference erod remans he same unl he resen erod. n our examle he rce of he mored goods rose on average by 27%. The Laseyres ndex s a weghed arhmec mean of rce raos. The weghng s defned here by he rao of he value of em o he oal value for he reference erod (erod ) : where g Relacng m 1 Laseyres m g 1 he weghng of em based on erod g by s exresson n he ndex formula, we ge he shorened Laseyres formula: Laseyres m g 1 m 1 1 m Ths s hus he exresson (5) of he calculaon of he un value ndex. should be noed ha he shor formula for he ndex mlcly uses he weghng of he basc formula. The ndex The ndex s calculaed alongsde he Laseyres ndex. For he former, he (hyohecal) value of curren base a rces for erod s calculaed frs, noed as. Ths value s obaned smly by mullyng he rce by he uany as defned revously. g m 1 m 1 11

12 Naure Tarff headng Toal The ndex s obaned for each naure-based grou usng he followng formula: P Q (6) P Q BOX The ndex The ndex, as devsed by Hermann ( ), shows he relave rce of a base for he curren erod comared wh wha he same base coss for he reference erod. n he case of hs ndex he weghng vares from one erod o he nex. f, n our smlfed examle, we noe ha no only has he rce of he goods ncreased, bu ha he uanes of wne and bananas mored have rsen o 3 lres and 15 g resecvely, he ndex can be calculaed as follows: The rce ndex accordng o hus shows he varaon n rces f he base for he curren erod were also vald for he reference erod. n our examle he rce of he mored goods has rsen on average by 3%. The ndex s a harmonc weghed mean of rce raos. The weghng s defned here as he rao of he value of em o he oal value for he curren erod (erod ): where g m 1 m 1 weghng of em based on erod f g s relaced by s exresson n he ndex formula, one obans he shorened formula: g 1 12

13 m 1 g 1 m m 1 1 g 1 Ths s hus he exresson (6) of he formula for calculang he un value ndex. should be noed ha he shor formula for he ndex mlcly uses he weghng of he basc formula. m 1 m 1 The Fsher ndex The ublshed un value ndex s calculaed usng Fsher s formula, defned as he geomercal means of he Laseyres and ndces. s based on he followng formula: Fsher Laseyres = (7) BOX The Fsher ndex The Fsher ndex was devsed by rvng Fsher ( ) as a comromse soluon beween he Laseyres and he ndces. s generally referred o he wo ohers for he followng reasons: - s an deal ndex: f, on average rces double and uanes rle whn a gven erod of me he number obaned mus be mulled by sx. Ou of he hree ndces consdered here, only he Fsher ndex resecs hs axom; - s an nermedae alernave beween he Laseyres and he ndces: from a raccal on of vew: he Fsher ndex comensaes for he endency of he Laseyres ndex o overesmae he varaon of rces and ha of he ndex o underesmae. from a heorecal on of vew: as neher he Laseyres nor he ndex has he favour, seems reasonable o loo a an nermedae soluon; - unle he oher wo ndces, he Fsher ndex resecs he desred roery of reversbly. Accordng o hs rncle he ndex for he erod n relaon o s he nverse of he ndex for he erod n relaon o Grous by naure of goods wh non-ndex ems A he lowes level of classfcaon by naure, mos of he subgrous nclude ems ha are no reresenave. Gven ha such ems do no rovde any vald nformaon abou rce, he varaon n rce of he grou o whch hey belong s aled o hem oo (on condon ha he grou ncludes a leas one ndex em). Ths measure guaranees ha he non-reresenave ems do no have any effec on he un value ndex for her grou. To llusrae hs on, he calculaons are aled o he grou Tes ( ), whch ncludes 5 ems of whch one s non-reresenave (P = no). 13

14 Naure P Tarff headng Laseyres yes yes yes yes Fsher Toal no Toal Toal grou As before he Laseyres, and Fsher ndces are calculaed solely from reresenave ems (P = yes). Tang he grou whch s made u of n ndex ems and m non-ndex ems : Grou ndex ems 1 2 Non-ndex ems 1 2 m n P Q Laseyres (8) P Q P Q (9) P Q Fsher Laseyres (1) These ndces are hen used o calculae ems : e for he non-reresenave Laseyres (11)

15 96 78 (12) Once and are nown for he non-ndex ems oo, s ossble o deermne he value of hese hyohecal bases for he whole of he naure grou: P Q (13) P Q (14) The ndces can fnally be recalculaed for he grou, hs me ncluded he non-ndex ems. P Q Laseyres (15) P Q P Q (16) P Q One can chec ha he Laseyres and ndces wh and whou non-ndex ems are srcly dencal, snce hese ems are nally alloed he values of he ndces for her grou Nomnal ndex a he lowes level of subgrous by naure of goods The nomnal ndex (or value ndex) of he grou, nom, ndcaes he varaon n value beween wo erods. s calculaed usng he formula: P Q nom (17) P Q Once he ndces are avalable for he 271 grous accordng o he naure of goods he daa are aggregaed o calculae he nomnal ndex for oal mors or exors Real ndex for he lowes level of subgrous by naure of goods The real ndex (or volume ndex) for grou, real, shows he real or removed from nflaon rend for foregn rade. Ths s a resdual value ha s obaned from he rao of he value ndex o he un value ndex. 15

16 nom real (18) Fsher Aggregaon The ndces for he uer levels are calculaed by aggregang he daa for all her resecve subgrous. From he aggregaed values, he Laseyres, and Fsher ndces can be calculaed usng he same formulae as before. Ths rocedure s hen reeaed for each level of he herarchy u o he oal ndex. Le us ae he grou Underwear (3.2.2), whch s made u of 4 subgrous: Grdles, corses, braces, ec. ( ) Socs, socngs, ghs ( ) Oher ems of hosery underwear such as yamas, T-shrs, brefs ( ) Oher ems of fabrc underwear such as yamas, bah-robes, brefs ( ) Naure P P Q P Q PQ P Q Laseyres Fsher nom real yes yes yes yes Snce all he subgrous of hs grou comrse a leas one reresenave em (P = yes), he dfferen ndces can be obaned drecly as follows: P Q P Q Laseyres (19) P Q P Q P Q P Q (2) P Q P Q Fsher Laseyres (21) P Q P Q nom (22) P Q P Q

17 nom real (23) 96.3 Fsher f a subgrou ncludes no reresenave ems, s omed when he un value ndces (Laseyres, e Fsher) for he grou are calculaed. Ths subgrou s hen alloed he values of he un value ndces for he uer grou o whch belongs, so ha hey are comlee: P Q P Q 1 Laseyres (24) P Q P Q 1 (25) The resuls are obaned for he uer levels of aggregaon usng he same rncle. 3.2 Calculaon on a movng base for he grous by broad economc caegores Whle here s a slgh dfference n how he daa s rocessed for he ndex by broad economc caegores and he ndex by naure of goods, he way he ndex er se s calculaed s absoluely dencal o ha for he grous by naure. Accordngly, we shall no exlan he mehod n deal (see Secon 3.1). Wh resec o he calculaon of he grous by broad economc caegores a he lowes level here s a sngle dfference ha should be noed: he rocessng of nonreresenave ems. To reca, hese ems are alloed he Laseyres and ndces for her resecve naure-based grou n order o calculae he hyohecal values of he corresondng bases (see formulae 11 and 12). When he broad economc caegores-based grous are calculaed hese ems manan her hyohecal values, so ha all he arff headngs can hen be consdered as ndex ems n he broad economc caegores-based grous. Ths rc guaranees ha he resuls are eual afer aggregaon accordng o he wo nomenclaures. 3.3 Channg and year-on-year comarson All he ndces for he dfferen caegores of goods and for he oal are calculaed on a movng base. On he bass of hese resuls he ndces are hen ransformed no bases ha are easer o use and nerre (chan ndex and revous year=1 ndex) Channg Foregn rade ndces are ublshed n he form of chan ndces. The movng base resuls are hus lned n a mullcave fashon wh he revous year resul, whch 17

18 s lned o ha for he year before, ec has been aen as he bass for he ndex. n order o allow comarsons o be made beween he varous erods, he dfferen movng base ndces movng base 97 movng base, 98, 99 movng base are hen made no a chan,.e. exressed n relaon o a common bass (1997), usng he followng formula:,... chan movng base 1 chan revous year (26) chan chan chan movng base where un value) ( value) ( volume) 1 ( ( un value) chan ( un value) movng base ( un value) 1 chan revous year (27) ( value) ( volume) chan chan ( value) ( volume) movng base ( value) 1 movng base ( volume) 1 chan revous year chan revous year (28) (29) Ths oeraon s called channg and allows varaons over wo dsnc erods of me o be lned o gve he varaon for he oal erod. Channg for annual daa The channg rocess s llusraed usng oal exors as an examle: Movng base ndex Chan ndex: 1997=1 Year Perod Nomnal Un value Real Nomnal Un value Real ( value) chan 24 movng base chan ( value) 24 ( value) (3) 1 1 The chan ndex s nerreed as follows: exors have rsen n value by 34.8% n relaon o

19 ( un value) ( volume) chan 24 chan 24 movng base chan ( un value) 24 ( un value) (31) 1 1 movng base chan ( volume) 24 ( volume) (32) 1 1 should be noed ha, by defnon, he laer can also be deduced from he wo formulae above: chan chan ( value) 24 ( volume) chan (33) ( un value) Channg for oher erods The monhly and uarerly seres are no chaned wh he chan ndex for he same erod n he recedng year bu wh ha for he recedng year (annual resul). Ths rocedure s usfed from a echncal on of vew. By defnon, he movng base corresonds o he average erod for he revous year (see formulae 1 and 2). Ths rao mus hen be lned wh he comarson of he mean erod for he revous year n relaon o 1997, n oher words he chan ndex of he revous year. Here s an examle for he monhly resuls regardng exors: Movng base Chan ndex: 1997=1 Year Perod Nomnal Un value Real Nomnal Un value Real 25 Augus ( value) chan Augus 25 movng base chan ( value) Augus 25 ( value) (34) The chan ndex for 24 (134.8) s gven n he recedng examle Year-on-year comarson The year-on-year comarson s calculaed from he chan ndces for he wo erods. Snce he chan ndex for each erod shows he varaon beween ha erod and he mean erod of 1997, he varaon beween erod of year and erod of year -1 s nohng oher han he rao beween he wo chan ndces: yearon year comarson chan chan 1 1 (35) 19

20 To undersand hs, le us reurn o our revous examle: Movng base Chan ndex: 1997=1 Year Perod Nomnal Un value Real Nomnal Un value Real 24 Augus Augus ( value) chan yearon year comarson Augus 25 Augus 25 chan Augus (36) The nerreaon s as follows: n Augus 25 nomnal exors were 1.1% hgher han n Augus 24. 2

21 4 WORKNG DAYS AND SEASONAL ADJUSTMENTS 4.1 Why are hese adusmens necessary? n general economc acvy vares wh me. Over a year acvy ends o be concenraed n ceran erods, wh monhs of low acvy n beween. Vacaon erods and holdays also lay an moran role. Seres of daa for economc acvy are smlar and reflec hese seasonal comonens among oher hngs. s herefore no easy o nerre hese seres n he shor erm: does a dro n exors n Augus comared wh July ndcae an economc slum or s merely a seasonal flucuaon? The am of seasonal adusmen s o elmnae hs mechancal and regular seasonal varaon. Subseuenly, seres can be roerly comared over me and resuls can be duly nerreed, arcularly wh regard o shor-erm rends. Snce mors and exors are he core of economc exchange beween dfferen counres hey are auomacally subec o seasonal varaon. For hs reason seasonally adused ndces are ublshed n addon o he ndces menoned above. 4.2 Mehod The seasonally adused ndces for Swss foregn rade are drawn u n collaboraon wh he Cenre for Economc Research (KOF) 3 a he Zurch Federal nsue of Technology (ETHZ). The aled mehod s he mos common one, whch was develoed n he Uned Saes by he US Bureau of Census (verson X12-ARMA) 4. The X12-ARMA mehod s based on he same hlosohy as he X11-ARMA and X11 versons. The dfferen comonens of a seres, such as he rend-cycle and he seasonal and rregular comonens, are successvely esmaed usng an algorhm based on arorae movng averages. These movng averages allow he seres o be smoohed and he dfferen comonens o be denfed. n order o reduce he nsably of he revson of seasonally adused daa for recen erods, he nal seres s exended by forecass esmaed by an ARMA model. The algorhm menoned above uses he exended seres o esmae he comonens. 4.3 Resuls The nomnal and real ndces and he un value ndces are avalable from 1997 n he form of monhly or uarerly seres. As he basc ndex, he seasonally adused ndex s based on classfcaon of goods by naure and broad economc caegores. Ths rocedure s aled only o he mos moran grous of merchandse. Three seres are drawn u from he foregn rade ndces (oulers correced chan ndex): he worng days adused ndex, by whch he resuls refer o a consan number of worng days. Such an ndex means ha one monh (or one uarer) can be comared wh anoher monh (or uarer) whn he same year or he same erod of he revous year;

22 he seasonally adused ndex, where varaons due o he dfference n he number of worng days and recurrng seasonal varaons have been elmnaed; he rend comonen, whch shows he rend afer he elmnaon of he seasonal, rregular (all he random elemens ha canno be nerreed) and cyclcal comonens. BOX Varaon n seasonally adused daa and rend n oal exors NOMNAL NDEX : SEASONAL ADJUSTMENT (chan ndex 1997=1) oulers correced seasonally adused rend comonen JFMAMJ JASONDJFMAMJJASONDJFMAMJ JASONDJFMAMJJASONDJFMAMJ JASONDJFMAMJ JASONDJFMAMJJASONDJFMAMJ JASONDJFMAMJ JA The seasonally adused ndex shows he rend-cycle of a me seres afer elmnaon of he shorerm and seasonal varaons. The correced seres can herefore be used for analysng hsorcal values as well as for forecasng. The rend comonen reflecs he long-erm evoluon (rend) and reveals he defned busness cycle effecs as movemens around hs general rend. BOX Worng days adusmen s dffcul o nerre he resuls regardng foregn rade owng o calendar effecs. n general economc acvy reacs osvely o he number of worng days and negavely o he number of holdays. The worng days adused ndex (WDA) shows he resuls for foregn rade based on he mean number of days n a gven monh of he year. Thans o hs correcon, he comarson and nerreaon of he daa s much more ernen. Conrary o wha one mgh hn, he correcon of he dfference n he number of worng days does no nvolve a drec comarson of he number of worng days durng a gven erod wh ha for he same erod n he recedng year, bu wh ha for he mean erod n he curren year. For examle, he mean number of worng days er monh n 25 s 21.17, snce 25 has a oal of 254 worng days ( ). The worng days adused chan ndex can be calculaed as follows: WDA nowda n N f J 22

23 where n = number of worng days durng erod, N J = number of worng days n year J (of whch s a ar), f = 12 f he erod aen s one monh, 4 f he erod aen s a uarer. Ths ndex s he chan ndex ha would aly for he erod f he number of worng days corresonded o he monhly mean for he year. Examle: he monh of Augus 25 had 22 worng days, whch was.8 worng days more han he monhly mean for 25 ( 21.17). For hs reason, he resuls for Augus need o be correced downwards so ha hey can be comared wh he oher monhs n 25 or wh he same monh of he recedng year. Nomnal chan ndex for Augus 25 = Nomnal chan ndex WDA: The year-on-year comarson can be calculaed agan as he rao beween wo chan ndces: ( year on year comarson) WDA nowda nowda 1 n n 1 N N f J J 1 f nowda nowda 1 n 1 n N N J J 1 Ths formula shows ha he year-on-year comarson s nohng else ha o adus he no worng days adused comarson wh a coeffcen relang o he number of worng days n he monhs n ueson as well as wh a coeffcen relang o he number of worng days n he years n ueson. Conrary o wha one mgh hn a ror, he ndces for he number of worng days, uncorreced and correced are no necessarly eual f he monhs have he same number of worng days. n order for hem o be eual, he years n ueson mus have he same number of worng days. The worng days adusmens should correc erods of less han a full year bu have no effec on annual resuls. A he end of he year he correced daa are hus adused so ha he sum of he monhly chan ndces are euvalen wh and whou he number of worng days beng correced: ( defnve ) 12 WDA WDA 1 12 Below s he examle for oal mors for 24 (nomnal ndex) : 1 nowda WDA No WDA WDA CWD and correced January February March Arl May June July Augus Seember Ocober November December Toal

24 12 WDA WDA 1 ( defnve ) March March 12 1 nowda WDA PERODCTES ndces are avalable for he followng erods (number of erods) : year (1) semeser (2) rmeser (4) monh (12) cumulaed monhs: for examle January o Arl (8) n all, here s a choce of 27 dfferen erods durng he year. 6 DSSEMNATON Foregn rade ndces are comled for oal rade as well as for grous of goods by naure or by broad economc caegores. n conras, no ndces are avalable by counry or by arff headng. The foregn rade ndces are avalable o he ublc n he followng forms: he ables wh he man grous of goods can be consuled on our webse under foregn rade ndces, all he resuls concernng he ndex from 1997 on can also be consuled n SWSS-mex (daabase for Swss foregn rade) on he nerne (more nformaon under our headng roducs), he ndex CD-ROM conans he ndces for value, un value and volume for all erods from 1997 on. should be oned ou ha only he oulers correced ndces are ublshed. These resuls are rovsonal for he curren year and he revous year (unl he fnal closure n May of he followng year) and are revsed every monh. Resuls for earler years are defnve. Please noe ha seasonally adused ndces are never defnve, neher for he curren year nor for earler years. 7 POSSBLE USES FOR THE NDCES Foregn rade ndces are an essenal ool for any economc analyses of exors and mors and allow growh n rade for a gven secor or roduc grou or for all rade 24

25 o be roerly nerreed, be n nomnal or real erms. The ndces can also be used as a bass for esmang rends n rces of mored or exored goods. For a gven secor or roduc grou, foregn rade ndces can be used noably o: measure rce ncreases; deflae seres: foregn rade sascs always corresond o curren rces (nomnal ndex). Daa a consan rces (real ndex) are ofen more arorae for a long-erm analyss, however. Un value ndces can be used o deflae seres,.e. o elmnae rce varaons; analyse real rends n nernaonal mares; analyse comevy n nernaonal mares; analyse rce elascy of mors or exors,.e. deermne how urchases or sales abroad reac o a varaon n rce. The greaer he reacon, he more sensve urchases or sales are o varaons n rce. For he economy n general, foregn rade ndces can be used n arcular o: measure nflaon: he rce of mored goods may lay an moran role n relaon o he level of rces whn a counry. A rse n he rce of mored goods generally leads o a rse n domesc rces, albe wh a slgh delay; ancae nflaon: he delay beween he movemen of rces of mors and domesc rces means ha he laer can be foreseen on he bass of he former; deflae seres: foregn rade sascs always corresond o curren rces (nomnal ndex). Daa for consan rces (real ndex) are ofen more arorae for a long-erm analyss, however. Mean value ndces can be used o deflae seres,.e. o elmnae rce varaons; analyse real develomen of a counry on nernaonal mares; analyse he economc rend n foregn rade; analyse he comevy of a counry on he nernaonal mares; analyse rce elascy of mors or exors,.e. o deermne how urchases or sales abroad reac o a varaon n rce. The greaer he reacon, he more sensve urchases or sales are o varaons n rce; analyse he erms of rade. BOX Calculaon and nerreaon of erms of rade Terms of rade ndcae varaons n condons of comevy beween he domesc and he foregn mare. They consue an ndex of relave rces and ndcae he rce of exors n relaon o he rce of mors. Terms of rade are sad o deerorae f he rao falls, wh he conseuence ha a counry mus exor more o manan he same level of mors. The oose s an mrovemen n erms of rade. The un value ndex s he ey ool for calculang erms of rade usng he formula: erms of rade ( un value ( un value for ex ors) for mors) yearon year comarson yearon year comarson 1 Examle : 25

26 SWSS TERMS OF TRADE, from 1997 o Augus JFMAMJ JASONDJFMAMJJASONDJFMAMJ JASONDJFMAMJJASONDJFMAMJ JASONDJFMAMJ JASONDJFMAMJJASONDJFMAMJ JASONDJFMAMJ JA nerreaon of erms of rade The erceon of erms of rade s more easly undersood usng he followng smlfed examle. A counry mors only a raw maeral and exors only a fnshed roduc. f he rce of he raw maeral rses by 5% on he world mare (over one year) and he rce of he exored fnshed roduc remans unchanged, he erms of rade deerorae by around 5% ( 1 15). Ths means ha he counry mus exor more o be able o connue morng he same uany of he raw maeral. 8 CONTACT f you have any uesons or commens you can conac us easly va our webse ( message o accreded exer, heme ndex ). You can also conac us by e-mal a he followng address: ozd.ahs.dffuson@ezv.admn.ch. 26

12/7/2011. Procedures to be Covered. Time Series Analysis Using Statgraphics Centurion. Time Series Analysis. Example #1 U.S.

12/7/2011. Procedures to be Covered. Time Series Analysis Using Statgraphics Centurion. Time Series Analysis. Example #1 U.S. Tme Seres Analyss Usng Sagraphcs Cenuron Nel W. Polhemus, CTO, SaPon Technologes, Inc. Procedures o be Covered Descrpve Mehods (me sequence plos, auocorrelaon funcons, perodograms) Smoohng Seasonal Decomposon

More information

Methodology of the CBOE S&P 500 PutWrite Index (PUT SM ) (with supplemental information regarding the CBOE S&P 500 PutWrite T-W Index (PWT SM ))

Methodology of the CBOE S&P 500 PutWrite Index (PUT SM ) (with supplemental information regarding the CBOE S&P 500 PutWrite T-W Index (PWT SM )) ehodology of he CBOE S&P 500 PuWre Index (PUT S ) (wh supplemenal nformaon regardng he CBOE S&P 500 PuWre T-W Index (PWT S )) The CBOE S&P 500 PuWre Index (cker symbol PUT ) racks he value of a passve

More information

Analyzing Energy Use with Decomposition Methods

Analyzing Energy Use with Decomposition Methods nalyzng nergy Use wh Decomposon Mehods eve HNN nergy Technology Polcy Dvson eve.henen@ea.org nergy Tranng Week Pars 1 h prl 213 OCD/ 213 Dscusson nergy consumpon and energy effcency? How can energy consumpon

More information

Effects of Terms of Trade Gains and Tariff Changes on the Measurement of U.S. Productivity Growth *

Effects of Terms of Trade Gains and Tariff Changes on the Measurement of U.S. Productivity Growth * Effecs of Terms of Trade Gans and Tarff Changes on he Measuremen of U.S. Producvy Growh * Rober C. Feensra Unversy of Calforna-Davs and NBER Benjamn R. Mandel Federal Reserve Bank of New York Marshall

More information

GUIDANCE STATEMENT ON CALCULATION METHODOLOGY

GUIDANCE STATEMENT ON CALCULATION METHODOLOGY GUIDANCE STATEMENT ON CALCULATION METHODOLOGY Adopon Dae: 9/28/0 Effecve Dae: //20 Reroacve Applcaon: No Requred www.gpssandards.org 204 CFA Insue Gudance Saemen on Calculaon Mehodology GIPS GUIDANCE STATEMENT

More information

Spline. Computer Graphics. B-splines. B-Splines (for basis splines) Generating a curve. Basis Functions. Lecture 14 Curves and Surfaces II

Spline. Computer Graphics. B-splines. B-Splines (for basis splines) Generating a curve. Basis Functions. Lecture 14 Curves and Surfaces II Lecure 4 Curves and Surfaces II Splne A long flexble srps of meal used by drafspersons o lay ou he surfaces of arplanes, cars and shps Ducks weghs aached o he splnes were used o pull he splne n dfferen

More information

A binary powering Schur algorithm for computing primary matrix roots

A binary powering Schur algorithm for computing primary matrix roots Numercal Algorhms manuscr No. (wll be nsered by he edor) A bnary owerng Schur algorhm for comung rmary marx roos Federco Greco Bruno Iannazzo Receved: dae / Acceed: dae Absrac An algorhm for comung rmary

More information

Capacity Planning. Operations Planning

Capacity Planning. Operations Planning Operaons Plannng Capacy Plannng Sales and Operaons Plannng Forecasng Capacy plannng Invenory opmzaon How much capacy assgned o each producon un? Realsc capacy esmaes Sraegc level Moderaely long me horzon

More information

MORE ON TVM, "SIX FUNCTIONS OF A DOLLAR", FINANCIAL MECHANICS. Copyright 2004, S. Malpezzi

MORE ON TVM, SIX FUNCTIONS OF A DOLLAR, FINANCIAL MECHANICS. Copyright 2004, S. Malpezzi MORE ON VM, "SIX FUNCIONS OF A DOLLAR", FINANCIAL MECHANICS Copyrgh 2004, S. Malpezz I wan everyone o be very clear on boh he "rees" (our basc fnancal funcons) and he "fores" (he dea of he cash flow model).

More information

Trading volume and stock market volatility: evidence from emerging stock markets

Trading volume and stock market volatility: evidence from emerging stock markets Invesmen Managemen and Fnancal Innovaons, Volume 5, Issue 4, 008 Guner Gursoy (Turkey), Asl Yuksel (Turkey), Aydn Yuksel (Turkey) Tradng volume and sock marke volaly: evdence from emergng sock markes Absrac

More information

How To Calculate Backup From A Backup From An Oal To A Daa

How To Calculate Backup From A Backup From An Oal To A Daa 6 IJCSNS Inernaonal Journal of Compuer Scence and Nework Secury, VOL.4 No.7, July 04 Mahemacal Model of Daa Backup and Recovery Karel Burda The Faculy of Elecrcal Engneerng and Communcaon Brno Unversy

More information

Estimating intrinsic currency values

Estimating intrinsic currency values Cung edge Foregn exchange Esmang nrnsc currency values Forex marke praconers consanly alk abou he srenghenng or weakenng of ndvdual currences. In hs arcle, Jan Chen and Paul Dous presen a new mehodology

More information

Ground rules. Guide to the calculation methods of the FTSE Actuaries UK Gilts Index Series v1.9

Ground rules. Guide to the calculation methods of the FTSE Actuaries UK Gilts Index Series v1.9 Ground rules Gude o he calculaon mehods of he FTSE Acuares UK Gls Index Seres v1.9 fserussell.com Ocober 2015 Conens 1.0 Inroducon... 4 1.1 Scope... 4 1.2 FTSE Russell... 5 1.3 Overvew of he calculaons...

More information

The Rules of the Settlement Guarantee Fund. 1. These Rules, hereinafter referred to as "the Rules", define the procedures for the formation

The Rules of the Settlement Guarantee Fund. 1. These Rules, hereinafter referred to as the Rules, define the procedures for the formation Vald as of May 31, 2010 The Rules of he Selemen Guaranee Fund 1 1. These Rules, herenafer referred o as "he Rules", defne he procedures for he formaon and use of he Selemen Guaranee Fund, as defned n Arcle

More information

Lecture 40 Induction. Review Inductors Self-induction RL circuits Energy stored in a Magnetic Field

Lecture 40 Induction. Review Inductors Self-induction RL circuits Energy stored in a Magnetic Field ecure 4 nducon evew nducors Self-nducon crcus nergy sored n a Magnec Feld 1 evew nducon end nergy Transfers mf Bv Mechancal energy ransform n elecrc and hen n hermal energy P Fv B v evew eformulaon of

More information

Guidelines and Specification for the Construction and Maintenance of the. NASDAQ OMX Credit SEK Indexes

Guidelines and Specification for the Construction and Maintenance of the. NASDAQ OMX Credit SEK Indexes Gudelnes and Specfcaon for he Consrucon and Manenance of he NASDAQ OMX Cred SEK Indexes Verson as of Aprl 7h 2014 Conens Rules for he Consrucon and Manenance of he NASDAQ OMX Cred SEK Index seres... 3

More information

Expiration-day effects, settlement mechanism, and market structure: an empirical examination of Taiwan futures exchange

Expiration-day effects, settlement mechanism, and market structure: an empirical examination of Taiwan futures exchange Invesmen Managemen and Fnancal Innovaons, Volume 8, Issue 1, 2011 Cha-Cheng Chen (Tawan), Su-Wen Kuo (Tawan), Chn-Sheng Huang (Tawan) Expraon-day effecs, selemen mechansm, and marke srucure: an emprcal

More information

Insurance. By Mark Dorfman, Alexander Kling, and Jochen Russ. Abstract

Insurance. By Mark Dorfman, Alexander Kling, and Jochen Russ. Abstract he Impac Of Deflaon On Insurance Companes Offerng Parcpang fe Insurance y Mar Dorfman, lexander Klng, and Jochen Russ bsrac We presen a smple model n whch he mpac of a deflaonary economy on lfe nsurers

More information

Index Mathematics Methodology

Index Mathematics Methodology Index Mahemacs Mehodology S&P Dow Jones Indces: Index Mehodology Ocober 2015 Table of Conens Inroducon 4 Dfferen Varees of Indces 4 The Index Dvsor 5 Capalzaon Weghed Indces 6 Defnon 6 Adjusmens o Share

More information

Selected Financial Formulae. Basic Time Value Formulae PV A FV A. FV Ad

Selected Financial Formulae. Basic Time Value Formulae PV A FV A. FV Ad Basc Tme Value e Fuure Value of a Sngle Sum PV( + Presen Value of a Sngle Sum PV ------------------ ( + Solve for for a Sngle Sum ln ------ PV -------------------- ln( + Solve for for a Sngle Sum ------

More information

Fixed Income Attribution. Remco van Eeuwijk, Managing Director Wilshire Associates Incorporated 15 February 2006

Fixed Income Attribution. Remco van Eeuwijk, Managing Director Wilshire Associates Incorporated 15 February 2006 Fxed Incoe Arbuon eco van Eeuwk Managng Drecor Wlshre Assocaes Incorporaed 5 February 2006 Agenda Inroducon Goal of Perforance Arbuon Invesen Processes and Arbuon Mehodologes Facor-based Perforance Arbuon

More information

[ ] Econ4415 International trade. Trade with monopolistic competition and transportation costs

[ ] Econ4415 International trade. Trade with monopolistic competition and transportation costs Econ445 Inernaonal rade Trade wh monopolsc compeon and ransporaon coss We have nroduced some basc feaures of he Dx-Sglz modellng approach. We shall now also nroduce rade coss n he Dx-Sglz framework. I

More information

RISK MONITORING OF FIXED INCOME PORTFOLIOS

RISK MONITORING OF FIXED INCOME PORTFOLIOS UNIVERSITÉ PARIS I PANTHÉON-SORBONNE M Ingénere du Rsque Sécalé Professonnelle - Fnance Shela ROSEMBERG RISK MONITORING OF FIXED INCOME PORTFOLIOS Analyss of Wlshre Axom Facor Model Dae: 6 h, Seember 008

More information

No. 32-2009. David Büttner and Bernd Hayo. Determinants of European Stock Market Integration

No. 32-2009. David Büttner and Bernd Hayo. Determinants of European Stock Market Integration MAGKS Aachen Segen Marburg Geßen Göngen Kassel Jon Dscusson Paper Seres n Economcs by he Unverses of Aachen Geßen Göngen Kassel Marburg Segen ISSN 1867-3678 No. 32-2009 Davd Büner and Bernd Hayo Deermnans

More information

THE USE IN BANKS OF VALUE AT RISK METHOD IN MARKET RISK MANAGEMENT. Ioan TRENCA *

THE USE IN BANKS OF VALUE AT RISK METHOD IN MARKET RISK MANAGEMENT. Ioan TRENCA * ANALELE ŞTIINłIFICE ALE UNIVERSITĂłII ALEXANDRU IOAN CUZA DIN IAŞI Tomul LVI ŞnŃe Economce 009 THE USE IN BANKS OF VALUE AT RISK METHOD IN MARKET RISK MANAGEMENT Ioan TRENCA * Absrac In sophscaed marke

More information

Testing techniques and forecasting ability of FX Options Implied Risk Neutral Densities. Oren Tapiero

Testing techniques and forecasting ability of FX Options Implied Risk Neutral Densities. Oren Tapiero Tesng echnques and forecasng ably of FX Opons Impled Rsk Neural Denses Oren Tapero 1 Table of Conens Absrac 3 Inroducon 4 I. The Daa 7 1. Opon Selecon Crerons 7. Use of mpled spo raes nsead of quoed spo

More information

Multiple Periodic Preventive Maintenance for Used Equipment under Lease

Multiple Periodic Preventive Maintenance for Used Equipment under Lease Mulle Perodc Prevenve Manenance or Used Equmen under ease Paarasaya Boonyaha, Jarumon Jauronnaee, Member, IAENG Absrac Ugradng acon revenve manenance are alernaves o reduce he used equmen alures rae whch

More information

A Model for Time Series Analysis

A Model for Time Series Analysis Aled Mahemaal Senes, Vol. 6, 0, no. 5, 5735-5748 A Model for Tme Seres Analyss me A. H. Poo Sunway Unversy Busness Shool Sunway Unversy Bandar Sunway, Malaysa ahhn@sunway.edu.my Absra Consder a me seres

More information

What influences the growth of household debt?

What influences the growth of household debt? Wha nfluences he growh of household deb? Dag Hennng Jacobsen, economs n he Secures Markes Deparmen, and Bjørn E. Naug, senor economs n he Research Deparmen 1 Household deb has ncreased by 10 11 per cen

More information

Financial Time Series Forecasting: Comparison of Neural Networks and ARCH Models

Financial Time Series Forecasting: Comparison of Neural Networks and ARCH Models Inernaonal Research Journal of Fnance and Economcs ISSN 450-887 Issue 49 (00) EuroJournals Publshng, Inc. 00 h://www.eurojournals.com/fnance.hm Fnancal Tme Seres Forecasng: Comarson of Neural Neworks and

More information

Kalman filtering as a performance monitoring technique for a propensity scorecard

Kalman filtering as a performance monitoring technique for a propensity scorecard Kalman flerng as a performance monorng echnque for a propensy scorecard Kaarzyna Bjak * Unversy of Souhampon, Souhampon, UK, and Buro Informacj Kredyowej S.A., Warsaw, Poland Absrac Propensy scorecards

More information

The Cost of Equity in Canada: An International Comparison

The Cost of Equity in Canada: An International Comparison Workng Paper/Documen de raval 2008-21 The Cos of Equy n Canada: An Inernaonal Comparson by Jonahan Wmer www.bank-banque-canada.ca Bank of Canada Workng Paper 2008-21 July 2008 The Cos of Equy n Canada:

More information

YÖNET M VE EKONOM Y l:2005 Cilt:12 Say :1 Celal Bayar Üniversitesi..B.F. MAN SA

YÖNET M VE EKONOM Y l:2005 Cilt:12 Say :1 Celal Bayar Üniversitesi..B.F. MAN SA YÖNET M VE EKONOM Y l:2005 Cl:12 Say :1 Celal Bayar Ünverses..B.F. MAN SA Exchange Rae Pass-Through Elasces n Fnal and Inermedae Goods: The Case of Turkey Dr. Kemal TÜRKCAN Osmangaz Ünverses, BF, ksa Bölümü,

More information

Applying the Theta Model to Short-Term Forecasts in Monthly Time Series

Applying the Theta Model to Short-Term Forecasts in Monthly Time Series Applyng he Thea Model o Shor-Term Forecass n Monhly Tme Seres Glson Adamczuk Olvera *, Marcelo Gonçalves Trenn +, Anselmo Chaves Neo ** * Deparmen of Mechancal Engneerng, Federal Technologcal Unversy of

More information

APPLICATION OF CHAOS THEORY TO ANALYSIS OF COMPUTER NETWORK TRAFFIC Liudvikas Kaklauskas, Leonidas Sakalauskas

APPLICATION OF CHAOS THEORY TO ANALYSIS OF COMPUTER NETWORK TRAFFIC Liudvikas Kaklauskas, Leonidas Sakalauskas The XIII Inernaonal Conference Appled Sochasc Models and Daa Analyss (ASMDA-2009) June 30-July 3 2009 Vlnus LITHUANIA ISBN 978-9955-28-463-5 L. Sakalauskas C. Skadas and E. K. Zavadskas (Eds.): ASMDA-2009

More information

The Feedback from Stock Prices to Credit Spreads

The Feedback from Stock Prices to Credit Spreads Appled Fnance Projec Ka Fa Law (Keh) The Feedback from Sock Prces o Cred Spreads Maser n Fnancal Engneerng Program BA 3N Appled Fnance Projec Ka Fa Law (Keh) Appled Fnance Projec Ka Fa Law (Keh). Inroducon

More information

Linear Extension Cube Attack on Stream Ciphers Abstract: Keywords: 1. Introduction

Linear Extension Cube Attack on Stream Ciphers Abstract: Keywords: 1. Introduction Lnear Exenson Cube Aack on Sream Cphers Lren Dng Yongjuan Wang Zhufeng L (Language Engneerng Deparmen, Luo yang Unversy for Foregn Language, Luo yang cy, He nan Provnce, 47003, P. R. Chna) Absrac: Basng

More information

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Journal of Appled Mahemacs and Compuaonal Mechancs 3, (), 45-5 HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Sansław Kukla, Urszula Sedlecka Insue of Mahemacs,

More information

Revision: June 12, 2010 215 E Main Suite D Pullman, WA 99163 (509) 334 6306 Voice and Fax

Revision: June 12, 2010 215 E Main Suite D Pullman, WA 99163 (509) 334 6306 Voice and Fax .3: Inucors Reson: June, 5 E Man Sue D Pullman, WA 9963 59 334 636 Voce an Fax Oerew We connue our suy of energy sorage elemens wh a scusson of nucors. Inucors, lke ressors an capacors, are passe wo-ermnal

More information

The Japan-U.S. Exchange Rate, Productivity, and the Competitiveness of Japanese Industries*

The Japan-U.S. Exchange Rate, Productivity, and the Competitiveness of Japanese Industries* 1 The apan-u.s. Exchange Rae Producvy and he Compeveness of apanese Indusres* March 2009 Rober Dekle Deparmen of Economcs USC and Kyoj Fukao Insue of Economc Research Hosubash Unversy Wh he Asssance of

More information

Information-based trading, price impact of trades, and trade autocorrelation

Information-based trading, price impact of trades, and trade autocorrelation Informaon-based radng, prce mpac of rades, and rade auocorrelaon Kee H. Chung a,, Mngsheng L b, Thomas H. McInsh c a Sae Unversy of New York (SUNY) a Buffalo, Buffalo, NY 426, USA b Unversy of Lousana

More information

Return Persistence, Risk Dynamics and Momentum Exposures of Equity and Bond Mutual Funds

Return Persistence, Risk Dynamics and Momentum Exposures of Equity and Bond Mutual Funds Reurn Perssence, Rsk Dynamcs and Momenum Exposures of Equy and Bond Muual Funds Joop Hu, Marn Marens, and Therry Pos Ths Verson: 22-2-2008 Absrac To analyze perssence n muual fund performance, s common

More information

Both human traders and algorithmic

Both human traders and algorithmic Shuhao Chen s a Ph.D. canddae n sascs a Rugers Unversy n Pscaaway, NJ. bhmchen@sa.rugers.edu Rong Chen s a professor of Rugers Unversy n Pscaaway, NJ and Peng Unversy, n Bejng, Chna. rongchen@sa.rugers.edu

More information

Template-Based Reconstruction of Surface Mesh Animation from Point Cloud Animation

Template-Based Reconstruction of Surface Mesh Animation from Point Cloud Animation Temlae-Based Reconsrucon of Surface Mesh Anmaon from Pon Cloud Anmaon Sang Il Park and Seong-Jae Lm In hs aer, we resen a mehod for reconsrucng a surface mesh anmaon sequence from on cloud anmaon daa.

More information

Attribution Strategies and Return on Keyword Investment in Paid Search Advertising

Attribution Strategies and Return on Keyword Investment in Paid Search Advertising Arbuon Sraeges and Reurn on Keyword Invesmen n Pad Search Adversng by Hongshuang (Alce) L, P. K. Kannan, Sva Vswanahan and Abhshek Pan * December 15, 2015 * Honshuang (Alce) L s Asssan Professor of Markeng,

More information

CALCULATION OF OMX TALLINN

CALCULATION OF OMX TALLINN CALCULATION OF OMX TALLINN CALCULATION OF OMX TALLINN 1. OMX Tallinn index...3 2. Terms in use...3 3. Comuaion rules of OMX Tallinn...3 3.1. Oening, real-ime and closing value of he Index...3 3.2. Index

More information

A STUDY ON THE CAUSAL RELATIONSHIP BETWEEN RELATIVE EQUITY PERFORMANCE AND THE EXCHANGE RATE

A STUDY ON THE CAUSAL RELATIONSHIP BETWEEN RELATIVE EQUITY PERFORMANCE AND THE EXCHANGE RATE A STUDY ON THE CAUSAL RELATIONSHIP BETWEEN RELATIVE EQUITY PERFORMANCE AND THE EXCHANGE RATE The Swedsh Case Phlp Barsk* and Magnus Cederlöf Maser s Thess n Inernaonal Economcs Sockholm School of Economcs

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

Fundamental Analysis of Receivables and Bad Debt Reserves

Fundamental Analysis of Receivables and Bad Debt Reserves Fundamenal Analyss of Recevables and Bad Deb Reserves Mchael Calegar Assocae Professor Deparmen of Accounng Sana Clara Unversy e-mal: mcalegar@scu.edu February 21 2005 Fundamenal Analyss of Recevables

More information

The Joint Cross Section of Stocks and Options *

The Joint Cross Section of Stocks and Options * The Jon Cross Secon of Socks and Opons * Andrew Ang Columba Unversy and NBER Turan G. Bal Baruch College, CUNY Nusre Cakc Fordham Unversy Ths Verson: 1 March 2010 Keywords: mpled volaly, rsk premums, reurn

More information

The impact of unsecured debt on financial distress among British households

The impact of unsecured debt on financial distress among British households The mpac of unsecured deb on fnancal dsress among Brsh households Ana Del-Río* and Garr Young** Workng Paper no. 262 * Banco de España. Alcalá, 50. 28014 Madrd, Span Emal: adelro@bde.es ** Fnancal Sabl,

More information

Linear methods for regression and classification with functional data

Linear methods for regression and classification with functional data Lnear mehods for regresson and classfcaon wh funconal daa Glber Sapora Chare de Sasue Appluée & CEDRIC Conservaore Naonal des Ars e Méers 9 rue San Marn, case 44 754 Pars cedex 3, France sapora@cnam.fr

More information

INTERNATIONAL JOURNAL OF STRATEGIC MANAGEMENT

INTERNATIONAL JOURNAL OF STRATEGIC MANAGEMENT IJSM, Volume, Number, 0 ISSN: 555-4 INTERNATIONAL JOURNAL OF STRATEGIC MANAGEMENT SPONSORED BY: Angelo Sae Unversy San Angelo, Texas, USA www.angelo.edu Managng Edors: Professor Alan S. Khade, Ph.D. Calforna

More information

Network Effects on Standard Software Markets: A Simulation Model to examine Pricing Strategies

Network Effects on Standard Software Markets: A Simulation Model to examine Pricing Strategies Nework Effecs on Sandard Sofware Markes Page Nework Effecs on Sandard Sofware Markes: A Smulaon Model o examne Prcng Sraeges Peer Buxmann Absrac Ths paper examnes sraeges of sandard sofware vendors, n

More information

THE IMPACT OF UNSECURED DEBT ON FINANCIAL DISTRESS AMONG BRITISH HOUSEHOLDS. Ana del Río and Garry Young. Documentos de Trabajo N.

THE IMPACT OF UNSECURED DEBT ON FINANCIAL DISTRESS AMONG BRITISH HOUSEHOLDS. Ana del Río and Garry Young. Documentos de Trabajo N. THE IMPACT OF UNSECURED DEBT ON FINANCIAL DISTRESS AMONG BRITISH HOUSEHOLDS 2005 Ana del Río and Garry Young Documenos de Trabajo N.º 0512 THE IMPACT OF UNSECURED DEBT ON FINANCIAL DISTRESS AMONG BRITISH

More information

Proceedings of the 2008 Winter Simulation Conference S. J. Mason, R. R. Hill, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds.

Proceedings of the 2008 Winter Simulation Conference S. J. Mason, R. R. Hill, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds. Proceedngs of he 008 Wner Smulaon Conference S. J. Mason, R. R. Hll, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds. DEMAND FORECAST OF SEMICONDUCTOR PRODUCTS BASED ON TECHNOLOGY DIFFUSION Chen-Fu Chen,

More information

Long Run Underperformance of Seasoned Equity Offerings: Fact or an Illusion?

Long Run Underperformance of Seasoned Equity Offerings: Fact or an Illusion? Long Run Underperformance of Seasoned Equy Offerngs: Fac or an Illuson? 1 2 Allen D.E. and V. Souck 1 Edh Cowan Unversy, 2 Unversy of Wesern Ausrala, E-Mal: d.allen@ecu.edu.au Keywords: Seasoned Equy Issues,

More information

Searching for a Common Factor. in Public and Private Real Estate Returns

Searching for a Common Factor. in Public and Private Real Estate Returns Searchng for a Common Facor n Publc and Prvae Real Esae Reurns Andrew Ang, * Nel Nabar, and Samuel Wald Absrac We nroduce a mehodology o esmae common real esae reurns and cycles across publc and prvae

More information

CONTROLLER PERFORMANCE MONITORING AND DIAGNOSIS. INDUSTRIAL PERSPECTIVE

CONTROLLER PERFORMANCE MONITORING AND DIAGNOSIS. INDUSTRIAL PERSPECTIVE Copyrgh IFAC 5h Trennal World Congress, Barcelona, Span CONTROLLER PERFORMANCE MONITORING AND DIAGNOSIS. INDUSTRIAL PERSPECTIVE Derrck J. Kozub Shell Global Soluons USA Inc. Weshollow Technology Cener,

More information

Performance Measurement for Traditional Investment

Performance Measurement for Traditional Investment E D H E C I S K A N D A S S E T M A N A G E M E N T E S E A C H C E N T E erformance Measuremen for Tradonal Invesmen Leraure Survey January 007 Véronque Le Sourd Senor esearch Engneer a he EDHEC sk and

More information

An Optimisation-based Approach for Integrated Water Resources Management

An Optimisation-based Approach for Integrated Water Resources Management 20 h Euroean Symosum on Comuer Aded Process Engneerng ESCAPE20 S Perucc and G Buzz Ferrars (Edors) 2010 Elsever BV All rghs reserved An Omsaon-based Aroach for Inegraed Waer Resources Managemen Songsong

More information

THOMSON REUTERS/CORECOMMODITY CRB INDEX CALCULATION SUPPLEMENT

THOMSON REUTERS/CORECOMMODITY CRB INDEX CALCULATION SUPPLEMENT THOMSON REUTERS/CORECOMMODITY CRB INDEX CALCULATION SUPPLEMENT SEPTEMBER 2013 Thomson Reuers/CoreCommody CRB Index Calculaon Supplemen Ths supplemen conans he rules for calculang he Thomson Reuers/CoreCommody

More information

Ground rules. FTSE Global Bonds Index Series v1.7

Ground rules. FTSE Global Bonds Index Series v1.7 Ground rules FTSE Global Bonds Index Seres v.7 fserussell.com Ocober 205 Conens.0 Inroducon... 3 2.0 Managemen responsbles... 7 3.0 Elgble of secures... 9 4.0 rce sources... 5.0 erodc Change o he orfolos...

More information

The performance of imbalance-based trading strategy on tender offer announcement day

The performance of imbalance-based trading strategy on tender offer announcement day Invesmen Managemen and Fnancal Innovaons, Volume, Issue 2, 24 Han-Chng Huang (awan), Yong-Chern Su (awan), Y-Chun Lu (awan) he performance of mbalance-based radng sraegy on ender offer announcemen day

More information

OPENING THE INTERREGIONAL TRADE BLACK BOX : THE C-INTEREG DATABASE FOR THE SPANISH ECONOMY (1995-2005)

OPENING THE INTERREGIONAL TRADE BLACK BOX : THE C-INTEREG DATABASE FOR THE SPANISH ECONOMY (1995-2005) OPENING THE INTERREGIONAL TRADE BLACK BOX : THE C-INTEREG DATABASE FOR THE SPANISH ECONOMY (1995-2005) AUTHORS: Carlos Llano Economc Analyss Deparmen. and L.R.Klen Insue-CEPREDE. Faculad de CC.EE y EE.

More information

Anomaly Detection in Network Traffic Using Selected Methods of Time Series Analysis

Anomaly Detection in Network Traffic Using Selected Methods of Time Series Analysis I. J. Compuer Nework and Informaon Secury, 2015, 9, 10-18 Publshed Onlne Augus 2015 n MECS (hp://www.mecs-press.org/) DOI: 10.5815/jcns.2015.09.02 Anomaly Deecon n Nework Traffc Usng Seleced Mehods of

More information

The US Dollar Index Futures Contract

The US Dollar Index Futures Contract The S Dollar Inde uures Conrac I. Inroducon The S Dollar Inde uures Conrac Redfeld (986 and Eyan, Harpaz, and Krull (988 presen descrpons and prcng models for he S dollar nde (SDX fuures conrac. Ths arcle

More information

A GENERALIZED FRAMEWORK FOR CREDIT RISK PORTFOLIO MODELS

A GENERALIZED FRAMEWORK FOR CREDIT RISK PORTFOLIO MODELS A GENERALIZED FRAMEWORK FOR CREDIT RISK PORTFOLIO MODELS H. UGUR KOYLUOGLU ANDREW HICKMAN Olver, Wyman & Company CSFP Capal, Inc. * 666 Ffh Avenue Eleven Madson Avenue New Yor, New Yor 10103 New Yor, New

More information

How Much Life Insurance is Enough?

How Much Life Insurance is Enough? How Much Lfe Insurance s Enough? Uly-Based pproach By LJ Rossouw BSTRCT The paper ams o nvesgae how much lfe nsurance proecon cover a uly maxmsng ndvdual should buy. Ths queson s relevan n he nsurance

More information

FINANCIAL CONSTRAINTS, THE USER COST OF CAPITAL AND CORPORATE INVESTMENT IN AUSTRALIA

FINANCIAL CONSTRAINTS, THE USER COST OF CAPITAL AND CORPORATE INVESTMENT IN AUSTRALIA FINANCIAL CONSTRAINTS THE USER COST OF CAPITAL AND CORPORATE INVESTMENT IN AUSTRALIA Gann La Cava Research Dscusson Paper 2005-2 December 2005 Economc Analyss Reserve Bank of Ausrala The auhor would lke

More information

An Anti-spam Filter Combination Framework for Text-and-Image Emails through Incremental Learning

An Anti-spam Filter Combination Framework for Text-and-Image Emails through Incremental Learning An An-spam Fler Combnaon Framework for Tex-and-Image Emals hrough Incremenal Learnng 1 Byungk Byun, 1 Chn-Hu Lee, 2 Seve Webb, 2 Danesh Iran, and 2 Calon Pu 1 School of Elecrcal & Compuer Engr. Georga

More information

The Performance of Seasoned Equity Issues in a Risk- Adjusted Environment?

The Performance of Seasoned Equity Issues in a Risk- Adjusted Environment? The Performance of Seasoned Equy Issues n a Rsk- Adjused Envronmen? Allen, D.E., and V. Souck 2 Deparmen of Accounng, Fnance and Economcs, Edh Cowan Unversy, W.A. 2 Erdeon Group, Sngapore Emal: d.allen@ecu.edu.au

More information

Finance and Economics Discussion Series Divisions of Research & Statistics and Monetary Affairs Federal Reserve Board, Washington, D.C.

Finance and Economics Discussion Series Divisions of Research & Statistics and Monetary Affairs Federal Reserve Board, Washington, D.C. Fnance and Economcs Dscusson Seres Dvsons of Research & Sascs and Moneary Affars Federal Reserve Board, Washngon, D.C. Prcng Counerpary Rs a he Trade Level and CVA Allocaons Mchael Pyhn and Dan Rosen 200-0

More information

Time Series. A thesis. Submitted to the. Edith Cowan University. Perth, Western Australia. David Sheung Chi Fung. In Fulfillment of the Requirements

Time Series. A thesis. Submitted to the. Edith Cowan University. Perth, Western Australia. David Sheung Chi Fung. In Fulfillment of the Requirements Mehods for he Esmaon of Mssng Values n Tme Seres A hess Submed o he Faculy of Communcaons, ealh and Scence Edh Cowan Unversy Perh, Wesern Ausrala By Davd Sheung Ch Fung In Fulfllmen of he Requremens For

More information

An Ensemble Data Mining and FLANN Combining Short-term Load Forecasting System for Abnormal Days

An Ensemble Data Mining and FLANN Combining Short-term Load Forecasting System for Abnormal Days JOURNAL OF SOFTWARE, VOL. 6, NO. 6, JUNE 0 96 An Ensemble Daa Mnng and FLANN Combnng Shor-erm Load Forecasng Sysem for Abnormal Days Mng L College of Auomaon, Guangdong Unversy of Technology, Guangzhou,

More information

JCER DISCUSSION PAPER

JCER DISCUSSION PAPER JCER DISCUSSION PAPER No.135 Sraegy swchng n he Japanese sock marke Ryuch Yamamoo and Hdeak Hraa February 2012 公 益 社 団 法 人 日 本 経 済 研 究 センター Japan Cener for Economc Research Sraegy swchng n he Japanese

More information

Currency Exchange Rate Forecasting from News Headlines

Currency Exchange Rate Forecasting from News Headlines Currency Exchange Rae Forecasng from News Headlnes Desh Peramunelleke Raymond K. Wong School of Compuer Scence & Engneerng Unversy of New Souh Wales Sydney, NSW 2052, Ausrala deshp@cse.unsw.edu.au wong@cse.unsw.edu.au

More information

Optimal portfolio allocation with Asian hedge funds and Asian REITs

Optimal portfolio allocation with Asian hedge funds and Asian REITs Omal orfolo allocaon wh Asan hedge funds and Asan ehan Höch HVB-Insue for Mahemacal Fnance echnsche Unversä München German E-mal: hoech@ma.um.de ah Hwa Ng Drecor Rsk Managemen Insue Naonal Unvers of ngaore

More information

Pedro M. Castro Iiro Harjunkoski Ignacio E. Grossmann. Lisbon, Portugal Ladenburg, Germany Pittsburgh, USA

Pedro M. Castro Iiro Harjunkoski Ignacio E. Grossmann. Lisbon, Portugal Ladenburg, Germany Pittsburgh, USA Pedro M. Casro Iro Harjunkosk Ignaco E. Grossmann Lsbon Porugal Ladenburg Germany Psburgh USA 1 Process operaons are ofen subjec o energy consrans Heang and coolng ules elecrcal power Avalably Prce Challengng

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

IMES DISCUSSION PAPER SERIES

IMES DISCUSSION PAPER SERIES IMS DISCUSSION PPR SRIS Rsk Managemen for quy Porfolos of Japanese Banks kra ID and Toshkazu OHB Dscusson Paper No. 98--9 INSTITUT FOR MONTRY ND CONOMIC STUDIS BNK OF JPN C.P.O BOX 23 TOKYO 1-863 JPN NOT:

More information

The Virtual Machine Resource Allocation based on Service Features in Cloud Computing Environment

The Virtual Machine Resource Allocation based on Service Features in Cloud Computing Environment Send Orders for Reprns o reprns@benhamscence.ae The Open Cybernecs & Sysemcs Journal, 2015, 9, 639-647 639 Open Access The Vrual Machne Resource Allocaon based on Servce Feaures n Cloud Compung Envronmen

More information

Using the Two-Stage Approach to Price Index Aggregation

Using the Two-Stage Approach to Price Index Aggregation Oaa Grou Meeng, 3 Ung he To-Sage Aroach o Prce Inde Aggregaon Toc: Samlng and Elemenary Aggregae; Aggregaon Aravndan Jayanha and Le Conn Abrac Th aer aee he raccal mlcaon for Naonal Sacal Offce (NSO) of

More information

Swiss National Bank Working Papers

Swiss National Bank Working Papers 01-10 Swss Naonal Bank Workng Papers Global and counry-specfc busness cycle rsk n me-varyng excess reurns on asse markes Thomas Nschka The vews expressed n hs paper are hose of he auhor(s and do no necessarly

More information

RESOLUTION OF THE LINEAR FRACTIONAL GOAL PROGRAMMING PROBLEM

RESOLUTION OF THE LINEAR FRACTIONAL GOAL PROGRAMMING PROBLEM Revsa Elecrónca de Comuncacones y Trabajos de ASEPUMA. Rec@ Volumen Págnas 7 a 40. RESOLUTION OF THE LINEAR FRACTIONAL GOAL PROGRAMMING PROBLEM RAFAEL CABALLERO rafael.caballero@uma.es Unversdad de Málaga

More information

Monopolistic Competition and Macroeconomic Dynamics

Monopolistic Competition and Macroeconomic Dynamics Monopolsc Compeon and Macroeconomc Dynamcs Pasquale Commendaore, Unversà d Napol Federco II Ingrd Kubn, Venna Unversy of Economcs and Busness Admnsraon Absrac Modern macroeconomc models wh a Keynesan flavor

More information

Australian dollar and Yen carry trade regimes and their determinants

Australian dollar and Yen carry trade regimes and their determinants Ausralan dollar and Yen carry rade regmes and her deermnans Suk-Joong Km* Dscplne of Fnance The Unversy of Sydney Busness School The Unversy of Sydney 2006 NSW Ausrala January 2015 Absrac: Ths paper nvesgaes

More information

Price convergence in the European Union and in the New Member States

Price convergence in the European Union and in the New Member States Bank Kredy 4 ( 9 7 6 www.bankkredy.nb.l www.bankandcred.nb.l rce convergence n he uroean Unon and n he ew Meber Saes Joanna Wolszczak-Derlacz* Reber De Blander # Subed: 4 Deceber 8. cceed: rl 9. bsrac

More information

What Explains Superior Retail Performance?

What Explains Superior Retail Performance? Wha Explans Superor Real Performance? Vshal Gaur, Marshall Fsher, Ananh Raman The Wharon School, Unversy of Pennsylvana vshal@grace.wharon.upenn.edu fsher@wharon.upenn.edu Harvard Busness School araman@hbs.edu

More information

Calculation of Sampling Weights

Calculation of Sampling Weights Perre Foy Statstcs Canada 4 Calculaton of Samplng Weghts 4.1 OVERVIEW The basc sample desgn used n TIMSS Populatons 1 and 2 was a two-stage stratfed cluster desgn. 1 The frst stage conssted of a sample

More information

DEPARTMENT OF ECONOMETRICS AND BUSINESS STATISTICS. Exponential Smoothing for Inventory Control: Means and Variances of Lead-Time Demand

DEPARTMENT OF ECONOMETRICS AND BUSINESS STATISTICS. Exponential Smoothing for Inventory Control: Means and Variances of Lead-Time Demand ISSN 440-77X ISBN 0 736 094 X AUSTRALIA DEPARTMENT OF ECONOMETRICS AND BUSINESS STATISTICS Exponenal Smoohng for Invenory Conrol: Means and Varances of Lead-Tme Demand Ralph D. Snyder, Anne B. Koehler,

More information

An Architecture to Support Distributed Data Mining Services in E-Commerce Environments

An Architecture to Support Distributed Data Mining Services in E-Commerce Environments An Archecure o Suppor Dsrbued Daa Mnng Servces n E-Commerce Envronmens S. Krshnaswamy 1, A. Zaslavsky 1, S.W. Loke 2 School of Compuer Scence & Sofware Engneerng, Monash Unversy 1 900 Dandenong Road, Caulfeld

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

Combining Mean Reversion and Momentum Trading Strategies in. Foreign Exchange Markets

Combining Mean Reversion and Momentum Trading Strategies in. Foreign Exchange Markets Combnng Mean Reverson and Momenum Tradng Sraeges n Foregn Exchange Markes Alna F. Serban * Deparmen of Economcs, Wes Vrgna Unversy Morganown WV, 26506 November 2009 Absrac The leraure on equy markes documens

More information

CHAPTER 10 DUMMY VARIABLE REGRESSION MODELS

CHAPTER 10 DUMMY VARIABLE REGRESSION MODELS CHAPTER 10 DUMMY VARIABLE REGRESSION MODELS QUESTIONS 10.1. (a) and (b) These are varables ha canno be quanfed on a cardnal scale. They usually denoe he possesson or nonpossesson of an arbue, such as naonaly,

More information

Handelsbanken Sweden All Bond Tradable Index. Index Rules v2.8 Version as of 28 January 2011

Handelsbanken Sweden All Bond Tradable Index. Index Rules v2.8 Version as of 28 January 2011 Handelsbanken Sweden All Bond Tradable ndex ndex Rules v28 Verson as of 28 January 20 ndex Descrpon Handelsbanken Sweden All Bond Tradable ndex (he ndex ) s a arke value weghed ndex conssng of Swedsh orgage

More information

The Definition and Measurement of Productivity* Mark Rogers

The Definition and Measurement of Productivity* Mark Rogers The Defnon and Measuremen of Producvy* Mark Rogers Melbourne Insue of Appled Economc and Socal Research The Unversy of Melbourne Melbourne Insue Workng Paper No. 9/98 ISSN 1328-4991 ISBN 0 7325 0912 6

More information

Chapter 8 Student Lecture Notes 8-1

Chapter 8 Student Lecture Notes 8-1 Chaper Suden Lecure Noes - Chaper Goals QM: Business Saisics Chaper Analyzing and Forecasing -Series Daa Afer compleing his chaper, you should be able o: Idenify he componens presen in a ime series Develop

More information

A Real-time Adaptive Traffic Monitoring Approach for Multimedia Content Delivery in Wireless Environment *

A Real-time Adaptive Traffic Monitoring Approach for Multimedia Content Delivery in Wireless Environment * A Real-e Adapve Traffc Monorng Approach for Muleda Conen Delvery n Wreless Envronen * Boonl Adpa and DongSong Zhang Inforaon Syses Deparen Unversy of Maryland, Balore Couny Balore, MD, U.S.A. bdpa1@ubc.edu,

More information

FOREIGN AID AND ECONOMIC GROWTH: NEW EVIDENCE FROM PANEL COINTEGRATION

FOREIGN AID AND ECONOMIC GROWTH: NEW EVIDENCE FROM PANEL COINTEGRATION JOURAL OF ECOOMIC DEVELOPME 7 Volume 30, umber, June 005 FOREIG AID AD ECOOMIC GROWH: EW EVIDECE FROM PAEL COIEGRAIO ABDULASSER HAEMI-J AD MAUCHEHR IRADOUS * Unversy of Skövde and Unversy of Örebro he

More information