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1 BANK OF GREECE Economic Research Deparmen Special Sudies Division 21, Ε. Venizelos Avenue GR Ahens Τel: Fax: Prined in Ahens, Greece a he Bank of Greece Prining Works. All righs reserved. Reproducion for educaional and non-commercial purposes is permied provided ha he source is acknowledged. ISSN

2 OIL PRICE SHOCKS AND STOCK MARKET VOLATILITY: EVIDENCE FROM EUROPEAN DATA Savros Degiannakis Bank of Greece George Filis Bournemouh Universiy Renaas Kizys Universiy of Porsmouh ABSTRACT The paper invesigaes he effecs of oil price shocks on sock marke volailiy in Europe by focusing on hree measures of volailiy, i.e. he condiional, he realised and he implied volailiy. The findings sugges ha supply-side shocks and oil specific demand shocks do no affec volailiy, whereas, oil price changes due o aggregae demand shocks lead o a reducion in sock marke volailiy. More specifically, aggregae demand oil price shocks have significan explanaory power on boh curren- and forward-looking volailiies. The resuls are qualiaively similar for aggregae sock marke volailiy and indusrial secors volailiies. Finally, a robusness exercise using shor- and long-run volailiy models suppors he findings. Keywords: Condiional Volailiy, Realised Volailiy, Implied Volailiy, Oil Price Shocks, SVAR JEL classificaion: C13, C32, G10, G15, Q40 Acknowledgemens: We would like o hank Heaher Gibson for her consrucive suggesions which helped us o improve he clariy of he paper. The views expressed are hose of he auhors and should no be inerpreed as hose of heir respecive insiuions. The auhors are solely responsible for any remaining errors and deficiencies. Correspondence: Savros Degiannakis Bank of Greece 21, El. Venizelos Ave Ahens, Greece Tel.: sdegiannakis@bankofgreece.gr

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4 1. Inroducion and brief review of he lieraure There is a consensus among academics and praciioners ha oil and sock markes are ofen inerwined wih global economic aciviy. Asceraining exac naure and sources of he linkage beween oil and sock markes and global economic aciviy has proved o be a promising area for researchers over he las few decades. Research ineres mainly concenraes eiher on he impac of oil prices on sock marke developmens or he effecs of oil prices on he economy. Adding o his lieraure, he main objecive of his paper is o conduc research ino he effecs of hree oil price shocks (namely, supply side shocks, aggregae demand shocks and oil specific demand shocks) on sock marke volailiy, wih paricular reference in he European sock marke. The seminal paper by Jones and Kaul (1996) was among he firs o reveal a negaive relaionship beween oil prices and sock marke reurns. In addiion, Sadorsky (1999) concludes ha oil price changes are imporan deerminans of sock marke reurns. In paricular, he shows ha sock markes respond negaively o a posiive oil price change. Filis (2010), Chen (2009), Miller and Rai (2009), Park and Rai (2008), Driesprong e al. (2008) and Gjerde and Sæem (1999) second hese findings by Sadorsky (1999) and Jones and Kaul (1996). The aforemenioned negaive relaionship does no hold for sock markes operaing in oil-exporing counries. Arouri and Raul (2011) show ha for he oil-exporing counries here is a posiive relaionship beween oil price shocks and sock marke reurns. Oher auhors, hough, do no find any relaionship beween oil price shocks and sock marke reurns (Jammazi and Aloui, 2010; Cong e al., 2008; Haung e al., 1996). Filis e al. (2011) provide an exensive review of he lieraure in he paricular area. Sudies paricularly focused on European sock markes reveal ha posiive oil price changes end o negaively affec sock reurns; neverheless, he exac relaionship depends on he secor. In paricular, oil-relaed sock marke secors end o appreciae in he even of a posiive oil price change, whereas he reverse holds for oil-inensive secors (see, for example, Scholens and Yursever, 2012; Arouri, 2011; Arouri and Nguyen, 2010). 5

5 Furhermore, a srand of he lieraure disinguishes he effecs of oil price shocks on sock marke aciviy according o heir origin. Hamilon (2009a,b) and Kilian (2007a,b), in paricular, sugges ha differen shocks in he oil marke have differen effecs on sock markes. Kilian (2009) provide evidence ha he response of aggregae sock reurns differs depending on he cause of he oil price shock. Hamilon (2009a,b) disaggregaes oil price shocks ino wo componens, namely, demand-side oil price shocks (which are caused by increased aggregae demand, e.g. due o he indusrialisaion of China) and supply-side oil prices shocks (which are caused by aleraion in he world oil producion). In addiion, Kilian (2009) idenifies a hird origin, precauionary demand shocks or oil specific demand shocks. These are oil price shocks ha are relaed o he uncerainy of he fuure availabiliy of oil. Baumeiser and Peersman (2012), Basher e al. (2012), Kilian and Lewis (2011), Filis e al. (2011), Lippi and Nobili (2009), Kilian and Park (2009), Apergis and Miller (2009), Lescaroux and Mignon (2008), Kilian (2008) and Barsky and Kilian (2004) also illusrae he imporance of aking ino consideraion he origins of he oil price shock in his area of ineres. For example, Hamilon (2009a,b) mainain ha oil price shocks have mainly been demand driven in he las decades and hus supply-side evens do no exercise significan effecs in oil prices. A similar picure is pained by Baumeiser and Peersman (2009). Lippi and Nobili (2009) argue ha supply-side oil price shocks have a negaive effec in he economy, whereas he opposie is observed for demand-side oil price shocks. In addiion, Kilian and Park (2009) demonsrae ha supply-side oil price shocks have no effecs on sock marke reurns, whereas sock markes end o reac negaively o oil specific demand shocks. On he oher hand, hey find ha aggregae demand oil price shocks rigger a posiive response from sock markes. Along he same line of reasoning, Filis e al. (2011) find evidence ha supply-side shocks do no seem o impac on sock marke reurns, whereas he reverse holds for demand-side shocks. Similarly, Basher e al. (2012) show ha supply-side oil price shocks do no exercise an impac on emerging sock marke reurns, whereas aggregae demand oil price shocks seem o have a posiive effec. Finally, hey find evidence ha oil specific demand shocks pu downward pressure on sock reurns. 6

6 Despie he fac ha evidence proposes ha he origin of he oil price shock riggers differen responses from he sock markes, he majoriy of he lieraure does no consider origin when examining is effecs (see, iner alia, Arouri and Raul, 2011; Arouri and Khuong, 2010; Bjornland, 2009; Chen, 2009; Park and Rai, 2008). As aforemenioned, he aim of his paper is o direc he aenion of he research o he effecs of he oil price shocks on sock marke volailiy. Sudies in he early 80s and 90s (see, for example, Pindyck, 1991 and Bernanke, 1983, among ohers) reveal ha increased energy prices generae uncerainy for firms, resuling in a delay in invesmen decisions. Furhermore, some auhors opine ha oil price innovaions exercise an impac on aggregae uncerainy and hey have significan negaive effecs on invesmens (see, iner alia, Rai e al., 2011; Rahman and Serleis, 2011; Elder and Serleis, 2010). In addiion, Bloom (2009) documens ha sock marke uncerainy increases afer major shocks, such as he 2001 erroris aack in US, OPEC oil supply disrupions, ec. Neverheless, hese sudies have no considered he origins of he oil price shocks. We argue, hough, ha Bloom s choice of major shocks coincides wih evens ha rigger cerain oil price shocks, as hese have been idenified by Hamilon (2009a,b) and Kilian (2009, 2007a,b). For example, he 2001 erroris aack in US riggered an oil specific demand shock, whereas OPEC oil supply disrupions cause supply-side oil price shocks. Thus, disenangling oil price shocks is of imporance in undersanding beer sock marke uncerainy. In addiion, he lieraure has well esablished ha he aforemenioned firm s uncerainy and aggregae uncerainy can be represened by individual sock price volailiy and sock marke volailiy, respecively (see, for example, Baum e al., 2010 and Bloom, 2009). Even hough he characerisics of sock marke volailiy have been sudied exensively in he pas 1, he lieraure remains silen on he effecs of he differen oil price shocks on sock marke volailiy. Raher, a plehora of research oupu cenres is aenion solely on spillover effecs beween he oil price volailiy and sock marke 1 See, among ohers, Xekalaki and Degiannakis (2010), Becker e al. (2007), Andersen e al. (2005), Andersen e al. (2001) and Bollerslev e al. (1992). 7

7 reurns and volailiy or he relaionship beween oil price volailiy and firm invesmens 2. This paper comes o fill his void. More specifically, he conribuion of he paper is hreefold. Firs, i conribues o he lieraure ha sudies he effecs of hree differen oil price shocks an oil supply shock, an aggregae demand shock and an oil specific demand shock 3 on he sock marke. Unlike previous sudies ha examine he response of sock reurns on oil price shocks, we invesigae he response of sock marke volailiy, as a measure of uncerainy of sock marke invesmens, using a Srucural VAR model. Second, we provide evidence from boh aggregae sock marke indices and indusrial secor indices, as according o Arouri e al. (2012, p.2) "he use of equiy secor indices is, in our opinions, advanageous because marke aggregaion may mask he characerisics of various secors". Third, in conras o sudies ha mainly focus on he responses of sock marke reurns in individual counries in Europe or in he US (Arouri 2011, Arouri and Nguyen 2010, and Scholens and Yursever 2012 are noable excepions), he emphasis of his research is on he pan-european sock marke. In ligh of empirical evidence ha underlines he relaive imporance of demanddriven oil price shocks, we expec sock marke volailiy in Europe o be more sensiive o an aggregae demand shock and an oil specific demand shock han o a supply-side shock. Three volailiy measures are uilised; condiional volailiy, realised volailiy and implied volailiy. The use of hree differen volailiy esimaes is moivaed by he fac ha par of he lieraure illusraes ha implied volailiy (a forward-looking measure) is more informaional efficien compared o oher volailiy esimaes, which represen he curren-looking measures of volailiy 4. Thus, i is imporan o idenify any differences in heir responses o oil price shocks. Koopman e al. (2005) propose ha boh implied volailiy and realised volailiy are informaionally accurae. Conversely, auhors such as Becker e al. (2007) and Corrado and Truong (2007) sugges ha implied volailiy indices do no provide any incremenal informaion compared o oher volailiy indices. 2 See, iner alia, Arouri e al. (2012), Henriques and Sadorsky (2011), Sadorsky (2011), Arouri e al. (2011), Vo (2011), Malik and Ewing (2009), Chiou and Lee (2009). 3 Definiions of hese shocks can be found in Kilian and Park (2009). 4 See for example Blair e al. (2001), Chrisensen and Prabhala (1998), Fleming (1998) and Day and Lewis (1992). 8

8 Engle (2002), hough, argues ha here is no a simple answer as o which volailiy measure is he mos accurae, as i depends upon he saisical approach adoped for he evaluaion of forecass. We provide evidence ha supply-side shocks and oil specific demand shocks do no affec sock marke volailiy, whereas, oil price changes due o aggregae demand shocks lead o a reducion in sock marke volailiy. The resuls hold for he indusrial secors volailiies, as well. Prominen among our resuls is he finding ha oil price shocks have a qualiaively similar impac for boh he curren-looking volailiy measures and implied volailiy, which is a forward-looking measure. The res of he paper is organised as follows: Secion 2 presens he volailiy measures and he model used, Secion 3 describes he daase, Secion 4 presens he empirical findings of he research and Secion 5 concludes he sudy. 2. Mehodology In he nex secion hree measures of volailiy are defined, i.e. condiional volailiy, realised volailiy and implied volailiy, whereas in secion 2.2 he Srucural VAR model is presened Volailiy esimaes According o he lieraure here are hree main frameworks for measuring volailiy. The firs wo correspond o he curren marke volailiy measures, whereas he hird is a forward-looking measure of volailiy. In his paper we examine all hree volailiy esimaes. The condiional volailiy is he condiional sandard deviaion of he asse reurns given he mos recenly available informaion. The condiional variance process of y can be defined as 2 V y, for I 1 denoing he informaion se I 1 V 1 y invesors know when hey make heir invesmen decisions a ime 1. The realised volailiy is based on he idea of using high frequency daa o compue measures of volailiy a a lower frequency, i.e. using hourly log-reurns o 9

9 generae a measure of daily volailiy. By he erm monhly realized volailiy we imply he esimaion of a monhly variance using daily daa. Implied volailiy is he insananeous sandard deviaion of he reurn on he underlying asse, which would have o be inpu ino a heoreical pricing model in order o yield a heoreical value idenical o he price of he opion in he markeplace, assuming all oher inpus are known Condiional volailiy The condiional variance of he daily log-reurns process, y, is esimaed wih Ding's e al. (1993) APARCH model. The APARCH model has an appealing feaure ha i allows nesing ess of differen ypes of asymmery and funcional forms (Henschel, 1995). For insance, Lauren (2004) argues ha he APARCH model ness a leas seven GARCH specificaions. The asymmeric power ARCH, or APARCH model is esimaed assuming ha he demeaned daily log-reurns are condiionally Suden- disribued 5 : f a 0 z; a z 1 y c i. i. d. ~ z 1 1 T 0,1; v b z , (1) where a 0 0, 0, b 0, a 0 and 1 1, The APARCH model wih Suden- disribued sandardized innovaions accouns for i) volailiy clusering, ii) power ransformaion of he condiional variance, iii) asymmeric and lepokuric uncondiional disribuion of log-reurns, and iv) asymmeric condiional disribuion of log-reurns. Therefore, i is considered as he mos successfully applied model in esimaing condiional volailiy. For echnical deails, he reader is referred o Xekalaki and Degiannakis (2010). 5 The incorporaion of a firs-order auoregressive erm, AR(1), in he condiional mean, provides qualiaive similar resuls. 10

10 The monhly condiional volailiy is compued by summing he daily condiional variances. Therefore, he annualized condiional volailiy of monh, or (m) CV, is compued as he square roo of he sum of he condiional variances from he 16 h of he previous monh up o and including he 15 h of he curren monh 6 : ( m) 2 CV , (2) 2 where denoes he daily condiional variance for he j 1,..., rading days of monh. j Realised volailiy j1 Meron (1980) was he firs o sugges he idea of using high frequency daa o compue measures of volailiy a a lower frequency. The concep of he realised volailiy 2IV 2 is based on he inegraed volailiy, a, b d. The financial lieraure assumes ha he insananeous logarihmic price, process, d log p dw, where is he volailiy of he insananeous logreurns process and b a j log p, of a financial asse follows a diffusion W is he sandard Wiener process. The heory of quadraic variaion of semi-maringales provides a consisen esimae of he inegraed volailiy by he realised variance, RV log P j log P a, b j1 j1 2, assuming ha he ime inerval a, b is pariioned in equidisan poins in ime; see Andersen e al. (2003) and Barndorff-Nielsen and Shephard (2002). For he purposes of he presen sudy, we measure he monhly realised volailiy, pariioning he monhly ime inerval ino daily equidisan poins in ime, for denoing he number of rading days. Therefore, he annualized realised volailiy of monh, or RV m, is compued as he square roo of he sum of he squared daily log-reurns from he 16h of he previous monh up o he 15h of he curren monh: 6 The use of he daily observaions from he 16 h of he previous monh up o he 15 h of he curren monh is jusified by he availabiliy of he monhly daa on he 15 h of each monh. 11

11 m log P j log P RV. (3) j1 We esimae monhly volailiy by summing daily volailiy. However, his measure would be biased by he number of rading days in he monh. Tha is, volailiy in monh wih more rading days would be greaer han volailiy in any oher monh, even if he volailiy did no change. In order o check he robusness of he resuls, we also esimae m j 1 RV by scaling each monh s volailiy wih 2 22, assuming an equal number of rading days for each monh. The resuls remain qualiaively similar Implied volailiy index - VSTOXX Sudies, see i.e. Blair e al. (2001), characerize implied volailiy measures as less informaive han volailiy esimaed from asse reurns, because hey induce biases and conain mis-specificaion problems. In 1993, he Chicago Board of Opions Exchange published he firs implied volailiy index. The compuaion of implied volailiy indices akes ino accoun he laes advances in financial heory, eliminaing measuremen errors ha characerized he implied volailiy measures. Marke paricipans consider he implied volailiy index as an imporan ool for measuring invesors senimen. Invesors and risk managers refer o volailiy indices as fear indices or an invesor fear gauge. The VSTOXX Volailiy Index (which is he volailiy index for he Eurosoxx 50 Index, also named as EURO STOXX 50 Volailiy Index) measures he implied variance across all opions of a given ime o expiry. The main index is designed as a rolling index a a fixed 30 days o expiry. This is achieved using linear inerpolaion of he wo neares of he eigh available sub-indices. The index is calculaed based on eigh expiry monhs wih a maximum ime o expiry of wo years. The annualized implied volailiy of monh, or VSTOXX average of he daily curren monh: m, is compued as he VSTOXX from he 16 h of he previous monh up o he 15 h of he j 1 m 2 VSTOXX VSTOXX, (4) j1 j 12

12 where VSTOXX denoes he daily implied volailiy for he j j 1,..., rading days of monh. VSTOXX index is based on opion prices and i is consruced by STOXX limied Srucural VAR model Using a Srucural VAR framework, we examine he effecs of hree oil price shocks on sock marke volailiy (VOL). Namely, he oil price shocks are he supply-side shocks, he aggregae demand shocks and he oil specific demand shocks, as hese are idenified from changes in world oil producion (PROD), global economic aciviy (GEA) and changes in oil prices (OP), respecively. VOL is he generic name of he volailiy series. For each SVAR model he volailiy variable will be named afer he mehod of esimaion (i.e. condiional, realised or implied volailiy) and he name of he index (eiher aggregae or indusrial) 8. The srucural represenaion of he VAR model of order p akes he following general form: where, A p y c Aiy i ε (5) 0 0 i1 y is a [4 1] vecor of endogenous variables, i.e. PROD, GEA, OP, VOL y, A represens he [4x4] conemporaneous marix, A are [4x4] auoregressive coefficien 0 marices, ε is a [4 1] vecor of srucural disurbances, assumed o have zero covariance and be serially uncorrelaed. The covariance marix of he srucural disurbances akes i he following form [ ]. In order o ge he reduce form [ ] of our srucural model (1) we muliply boh sides wih A 1 0, such as ha: 7 The ineresed reader can find all he necessary informaion abou volailiy index in he following link: hp:// 8 For example he realised volailiy of he indusrial secor will be named RV_INDUSTRIAL. 13

13 y a p B y e 0 i i (6) i where, a0 A0 c0, Bi A0 Ai, and e A0 ε, i.e. ε A0e. The reduced form errors e are linear combinaions of he srucural errors ε, wih a covariance marix of he form ' 1 1' e e A DA E. 0 0 The srucural disurbances can be derived by imposing suiable resricions on A 0. The following shor-run resricions are imposed in he model: SS 1, 2, 3, VS 4, ADS OSS a a a a a a a a a e1, 0 e 0 e a44 e PROD GEA 2, OP 3, VOL 4, where, SS=supply-side shocks, ADS=aggregae demand shock, OSS=oil specific demand shock and VS=volailiy shock. The resricions in he model are explained as follows. Oil producion does no respond conemporaneously o an increase/decrease in oil demand, caused by higher/lower economic aciviy, due o adjusmen coss in oil producion. However, oil supply disrupion (a supply-side shock) can influence global economic aciviy, he price of oil and sock marke volailiy, wihin he same monh. Global economic aciviy is no conemporaneously influenced by oil prices due o he ime ha is required for he world economy o reac. On he conrary, an aggregae demand shock will have an immediae impac on oil prices and sock marke volailiy, considering he reacion ime of he commodiies and financial markes. Turning o he oil price innovaion, any increase in he price can be driven by supply-side evens, aggregae demand-side evens, as well as, oil specific demand evens. Thus, oil producion shocks, as well as, aggregae demand shocks can conemporaneously rigger responses from he oil prices. In highly liquid markes such as he European marke, he sock marke volailiy reacs conemporaneously o all aforemenioned oil price shocks. To proceed o he esimaion of he reduced form of model (1), i is firs necessary o esablish he saionariy of he variables. The ADF and PP uni roo ess sugges ha 14

14 all variables are I(0). The lag lengh of he VAR model was idenified using he Akaike Informaion Crierion (AIC). The AIC selecs a VAR model wih four lags Daa descripion In order o esimae he volailiy figures we use daily daa from January 1999 o December 2010 on aggregae European sock marke indices. In paricular, he sock marke index used is he Eurosoxx 50, which is Europe s leading blue chips sock marke index and he daa have been exraced from Daasream. In addiion, we consider he following indusrial secors indices, which have been consruced by Dow Jones: Financials, Oil&Gas, Reail, Consumpion Goods, Healh, Indusrial, Basic Maerials, Technology, Telecommunicaions and Uiliies. The indusrial secor indices daa have been exraced from Daasream. For consisency purposes we also considered he pan- European sock marke index consruced by Dow Jones. As menioned in secion 2.1, once he daily volailiy figures have been esimaed, we hen conver hem ino monhly figures. Furhermore, we use monhly daa for he same ime period for oil producion, oil prices and global economic aciviy. Bren crude oil is chosen, as a proxy for he world oil price, due o he fac ha his ype of oil represens 60% of he world oil daily consumpion (Maghyereh, 2004). We use oil producion daa, as a proxy for oil supply. Boh Bren crude oil price and oil producion daa have been exraced from he Energy Informaion Adminisraion. Finally, we adop Kilian s (2009) measuremen of he global economic aciviy based on dry cargo freigh raes 10. Prices are expressed in dollar erms and are ransformed in log-reurns. Figure 1 presens he volailiy measures for he Eurosoxx50 index (realised volailiy-rv_stoxx50, condiional volailiy-cv_stoxx50 and implied volailiy- 9 Resuls are available upon reques. The SVAR models do no suffer from auocorrelaion and no inverse roos of he characerisic polynomial lie ouside he uni circle. Thus, we conclude ha he SVAR models saisfy he sabiliy condiion. 10 The daa can be found in Luz Kilian personal websie (hp://www-personal.umich.edu/~lkilian/) 15

15 VSTOXX), he growh rae of world oil producion, global economic aciviy and oil price reurns 11. [FIGURE 1 HERE] I is immediaely apparen ha volailiy (in all hree expressions) reaches a peak near he end of 2008 and again in May These periods coincide wih he world financial crisis and he Greek deb crisis, respecively. Similar paerns are observed in he volailiy measures of he pan-european sock marke index by Dow Jones and of all indusrial secors indices (no presened visually here, hough). During 2008, we also observe a rough in global economic aciviy and exreme negaive reurns for he oil prices. This period has been also characerised by demand driven oil price shocks. These preliminary findings may sugges ha sock marke volailiy responds heavily o demand driven oil price shocks. Neverheless, he impulse responses from he SVAR model will provide us wih a clearer picure. Furhermore, Table 1 presens some descripive saisics for he volailiy measures of he Eurosoxx 50 index and he hree oil variables. The mean values of he realised volailiy and condiional volailiy are very close, whereas he VSTOXX mean value is higher. In addiion, all volailiy measures exhibi significan variaion over ime which is eviden from he minimum, maximum and sandard deviaion saisics. Naurally, he volailiy measures are posiively skewed and lepokuric. [TABLE 1 HERE] As far as he oil variables are concerned, he global economic aciviy is he mos volaile, followed by oil price reurns. Boh variables are posiively skewed, whereas oil producion growh raes are negaively skewed. The skewness measures sugges ha here are more negaive oil log-reurns and changes in he global economic aciviy, whereas he oil producion exhibis more posiive reurns. 11 The volailiy graphs for he pan-european sock marke index and he indusrial secors indices are available upon reques. 16

16 4. Esimaion resuls The purpose of he SVAR model is o examine he dynamic adjusmens of each of he variables o exogenous sochasic srucural shocks (see, iner alia, Bjornland and Leiemo, 2009; Kilian and Park, 2009). Thus, nex we presen he SVAR model findings for he volailiy indices of he Eurosoxx50 and he indusrial secors in erms of he impulse response funcions (IRF) and he variance decomposiion 12. Secion 4.1 describes he esimaion resuls based on curren-looking measures of sock marke volailiy (condiional and realised volailiies). The resuls for he aggregae sock marke and indusrial secor indices are summarised in Secions and 4.1.2, respecively. Secion 4.2 describes he esimaion resuls based on he forward-looking measure of sock marke volailiy (implied volailiy) Curren-looking volailiy measures Aggregae European sock marke indices The impulse responses (Figure 2) depic ha he reacion of he volailiy measures of he Eurosoxx50 index o he hree oil shocks differ quie subsanially. [FIGURE 2 HERE] Changes in world oil producion do no exercise any significan impac on sock marke volailiy. The argumen ha OPEC s decisions on oil producion levels do no impac sock markes nowadays, finds suppor here. Thus, his finding does no come as a surprise. Furhermore, he fac ha sock marke volailiy does no reac o supply-side oil prices shocks complemens he evidence provided by Basher e al. (2012), Filis e al. (2011) and Kilian and Park (2009), who argue ha changes in oil producion do no affec sock price reurns. A similar observaion can be made for he oil specific demand shock, as is effec is no significan on any volailiy measure. A plausible explanaion of his resul lies in he naure of firms responses o oil price changes. We argue ha firms, nowadays, engage in effecive hedging sraegies which reduce he effecs of adverse oil price movemens (Arouri, 2011), mainly caused by idiosyncraic oil price shocks (or oil 12 The SVAR resuls for he pan-european sock marke index consruced by Dow Jones are qualiaively similar and hus hey are no presened here. They are available upon reques. 17

17 specific demand shocks). On he conrary, increases in world aggregae demand, which implies increased economic aciviy, end o reduce sock marke volailiy, as expeced. A posiive aggregae demand shock can be regarded as good news for he sock marke. In he even of a posiive aggregae demand shock, uncerainy abou fuure cash flows decreases, driving down sock marke volailiy. One can also argue posiive news abou global economic aciviy is associaed wih a more sable business environmen, which, in urn, reduces uncerainy in he marke. From an opposie angle, Bloom (2009) has shown ha negaive news abou he global economic aciviy, such as hose during he Asian crisis in 1997 and he credi crunch in 2008, end o increase sock marke volailiy. In general, sock markes end o respond favourably when world economic developmens are posiive. The preliminary findings had already provided an iniial idea abou he inverse link beween aggregae demand oil price shocks and sock marke volailiy. Overall, he response is significan for abou 6 monhs and dynamic convergence is achieved afer 12 monhs afer he shock, for boh volailiy measures. Wih regard o he variance decomposiion (Table 2), we observe ha he effecs of he supply-side and oil specific demand shocks are very small and i furher suggess ha hese shocks do no exercise an impac on sock marke volailiy. Furhermore, he effecs of he aggregae demand shocks are small in he shor-run; however heir explanaory power exhibis an increasing paern as he forecasing window increases. This is suggesive of he fac ha aggregae demand shocks have a very imporan role in he European sock marke volailiy. [TABLE 2 HERE] In more deail, abou 9%-18% (depending on he volailiy measure) of he variaion in he volailiy of he Eurosoxx50 index is associaed wih he oil price shocks, during he firs few monhs. In a period of 24 monhs a oal of 24%-38% of he variabiliy of he volailiy is explained by he oil price shocks. The main conribuor o his variabiliy for boh volailiy measures is he aggregae demand oil price shock. Linking hese findings wih he evidence on sock marke reurns (see, for example, Kilian and Park, 2009; Hamilon, 2009a,b) suggess ha supply-side shocks do no seem o influence any of he sock markes characerisics (i.e. reurns and volailiies), whereas demand-side shocks and in paricular he aggregae demand oil price shocks do. 18

18 Overall, he resuls sugges ha increases in oil prices due o increased global economic aciviy (aggregae demand shock) reduce sock marke volailiy, as global economic aciviy is regarded as posiive informaion by he sock markes European indusrial secors Having analysed he effecs of he hree oil shocks on he aggregae sock marke volailiy, we proceed o he analysis of hese effecs on he indusrial secors 13. The impulse responses (Figure 3 and 4) sugges ha he reacion of he volailiy measures for he indusrial secors on he hree oil shocks is similar o hose of he Eurosoxx50 volailiy measures. More specifically, he aggregae demand shock exercises a significan negaive effec on indusrial secors volailiy (he same resul holds for boh he realised volailiy and he condiional volailiy). The supply-side oil price shocks and he oil specific demand shocks do no seem o influence any of he secors realised or condiional volailiies. [FIGURE 3 HERE] [FIGURE 4 HERE] The only exempion is he Oil&Gas secor. Boh he realised and condiional volailiy of he Oil&Gas secor respond negaively o he wo demand-side shocks (i.e. aggregae demand shock and oil specific demand shock). This finding is expeced since any increase in oil price is received as posiive news for he companies lised in he Oil&Gas secor. The effecs remain significan for abou 3-4 monhs and hey are fully absorbed afer 8 o10 monhs. I could be argued ha supply-side shocks should also benefi he Oil&Gas secor; neverheless, we canno find such evidence in his sudy. Overall, he findings sugges ha disrupions or increases in world oil producion do no provide any informaion for he volailiy of any secor, even he Oil&Gas one. The opposie holds for he aggregae demand oil price shocks. The variance decomposiion analysis (Table 3 and 4) illusraes ha he hree oil price shocks exercise he highes influence on he RV_OIL&GAS and CV_OIL&GAS (abou 53%), as expeced, and i is followed by he RV_CONSUMPTION and 13 The descripive saisics and figures of he indusrial secors volailiy measures are available upon reques. 19

19 CV_CONSUMPTION (abou 40%). The laer is expeced o be influenced heavily from he oil price shocks considering ha Europe is mainly an oil imporing region. Regarding he remaining indusrial indices, he hree oil price shocks explain abou 10%-20% of he variabiliy of heir volailiy. The lowes influenced is observed in he realised and condiional volailiy of he Financials secor (abou 10%), suggesing ha he Financials secor s volailiy is mainly influenced by oher variables, raher han he oil price shocks. The main conribuor of his influence, in all cases, is he aggregae demand shock, a similar finding wih he aggregae European sock marke volailiy. [TABLE 3 HERE] [TABLE 4 HERE] 4.2. Forward-looking volailiy measure The impulse responses (Figure 5) of he Eurosoxx50 implied volailiy (VSTOXX) measure is essenial he same as hose produced by he condiional and realised volailiies. [FIGURE 5 HERE] Again, boh supply-side oil price shocks and oil specific demand shocks do no exercise any significan impac on implied volailiy, whereas posiive aggregae demand oil price shocks rigger a negaive response. In erms of he variance decomposiion (Table 5), we observe ha he explanaory power of he hree oil price shocks for implied volailiy exhibis a peak in he mediumerm and sars o decline hereafer unil i reaches a sable level afer 24 monhs. [TABLE 5 HERE] More specifically, in he firs monh abou 9% of he variaion in he implied volailiy is associaed wih he oil price shocks, whereas in a period of 6-12 monhs his figure increases o an average of 22%. The main conribuor o his variabiliy is he aggregae demand oil price shock, as also suggesed by he condiional and realised volailiies. Comparing he resuls among he hree volailiy measures, we observe ha hese measures provide qualiaively and quaniaively similar informaion. Hence, he implied volailiy index (a forward-looking volailiy measure) does no provide addiional 20

20 informaion compared o he condiional and realised volailiy measures, which esimae he marke volailiy a he curren ime. This is a very ineresing finding considering ha several aforemenioned sudies have concluded ha implied volailiy indices provide superior informaion (see Xekalaki and Degiannakis, 2010; Becker e al., 2007; Andersen e al., 2005; Andersen e al., 2001 and Bollerslev e al., 1992). Despie he fac ha his resul may come as a surprise, i is no inexplicable. I is worh noing ha his resul does no conradic he forward-looking feaure of he implied volailiy measure. The impulse responses of he curren-looking volailiy measures sugges ha he effecs of he aggregae demand oil price shocks do no fade immediaely, bu raher hey require abou 12 monhs o be fully absorbed. This means ha he impac remains for he fuure monhs and his is wha i is capured by he implied volailiy response o he aggregae demand oil price shocks. The uncharacerisically prolonged response of he implied volailiy is also an arifac of is long memory, semming from he esimae of equaions 7 and 8 in Secion Robusness checks In order o es for he robusness of our resuls a baery of alernaive approaches has been employed. More specifically, we esimae wo volailiy models (one wih shor memory and one wih long memory) and we examine wheher he aggregae demand oil price shock series has explanaory power for sock marke volailiy. The choice of he aggregae demand oil price shock series is jusified by he fac ha i was he only oil price shock ha had a significan effec on sock marke volailiy, based on he impulse response funcions. Because sock marke volailiy is found o be invarian o he supplyside shock and he oil specific demand shock, we deliberaely discard hese wo shocks from our robusness exercise. Firs, we consruc he aggregae demand oil price shock series (ADS). In order o achieve ha we proceed o a hisorical decomposiion of he effecs of all hree oil price shocks on he oil price reurns See Burbidge and Harrison (1985) and Kilian and Park (2009) for a deailed descripion of he hisorical decomposiion. 21

21 Having decomposed he oil price reurns series ino he hree componens (i.e. he hree oil price shocks), he ADS series will represen he cumulaive effec of he aggregae demand shocks on oil price log-reurns. The hisorical decomposiion of he oil-price reurns is depiced in Figure 6. The upper, middle and lower panel depics he cumulaive effec of he supply-side shock, he aggregae demand shock and he oilspecific demand shock on he oil price reurns, respecively. [FIGURE 6 HERE] Nex, we esimae a shor-memory volailiy model, which incorporaes he ADS series as an explanaory variable. The model is as follows: (7) ADS u, where, denoes he monhly volailiy esimae (realised, condiional and implied), ADS is he monhly cumulaive effec of he aggregae demand shock on oil price 2 reurns and N0, u, is he error erm. ~ u The saisical significance of coefficien 2 denoes ha he 22 ADS provides addiional explanaory power over and above he lagged monhly volailiy esimae. Naurally, he 1 is expeced o be saisically significan due o he high auocorrelaion of volailiy. Furhermore, a fracionally inegraed model has also been considered in order o capure he long memory propery of volailiy. This is esimaed as follows: 2 where he error erm N0, defined as L L 0 2ADS u, (8) u, he fracional differencing operaor 1 j0 ~ u j 1 j 1 1 L j, for 0 1 1, and. funcion. The saisical significance of coefficien 2 suggess ha 1 L is is he Gamma ADS provides addiional explanaory power compared o he long memory propery of volailiy (as expressed by he 1 esimae). [TABLE 6 HERE]

22 [TABLE 7 HERE] The esimaion resuls, summarised in Tables 6 and 7, indicae ha he ADS exercises a negaive and significan effec on sock marke volailiy. The resuls are qualiaively similar for he hree volailiy measures and for boh he aggregae sock marke and indusrial secor indices. In paricular, a posiive aggregae demand shock causes a reducion in sock marke volailiy, which confirms he findings of he SVAR model. The resuls are, hus, of paricular imporance as hey could faciliae raders, invesors, researchers or policy makers, should hey need o forecas sock marke volailiy, price derivaives, manage risk and formulae regulaion. 6. Concluding remarks This sudy examines he effecs of hree oil prices shocks (i.e., supply-side shock, aggregae demand shock and oil specific demand shock) on sock marke volailiy using a Srucural VAR framework. We consider wo volailiy measures, namely he condiional volailiy and he realised volailiy, which measure curren sock marke volailiy. We also examine he effecs of oil price shocks on implied volailiy which is a forward-looking volailiy measure. We conclude ha supply-side and oil specific demand shocks do no affec volailiy, whereas, aggregae demand shocks influence volailiy a a significan level. This finding holds for boh he curren-looking volailiy and he implied volailiy measures of aggregae sock marke and indusrial secor indices. Furhermore, he wo volailiy models (shor- and long-memory models) verify he SVAR resuls, suggesing ha he effec of he aggregae demand oil price shocks on volailiy is negaive and significan for all indices and all measures. The findings of he sudy are essenial in pricing financial derivaives, selecing porfolios, measuring and managing invesmen risk. Invesors, risk managers, even policy makers of cenral banks and capial marke commissions will find he oucomes of he sudy useful in handling marke's uncerainy in relaion wih he sae of he oil price shocks. For example, supervisors of financial insiuions mus hold capial based on is inernal model s esimaes of Value-a-Risk. The Value-a-Risk inernal model can ake ino consideraion he inerrelaion beween oil price shocks and sock marke volailiy. The Basel Commiee, in order o srenghen 23

23 bank capial requiremens and inroduce enhanced regulaory requiremens on bank liquidiy, may ake advanage of he abiliy o model he relaionship beween aggregae demand oil price shocks and volailiy of European sock markes. I is essenial ha furher sudies will disinguish such effecs for oil-imporing and oil-exporing counries and condiional correlaion models can be used o idenify he aforemenioned relaionships in a ime-varying environmen. Finally, following Andersen e al. (2005), an ineresing quesion underpinning his research is wheher and, if so, how he beas of European sock marke secors respond o differen oil price shocks. 24

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29 Appendix Figures Figure 1: Volailiy measures of he Eurosoxx 50 index, oil producion growh rae, global economic aciviy and oil price reurns. Volailiy Measures of he Eurosoxx 50 Oil Producion Growh Rae (PROD) Global Economic Aciviy (GEA) Oil Price Reurns (OP) 30

30 Figure 2: Impulse Responses of RV_STOXX50 and CV_STOXX50. Response o Srucural One S.D. Innovaions ± 2 S.E. Response of RV_STOXX50 o Shock1 Response of RV_STOXX50 o Shock2 Response of RV_STOXX50 o Shock3 Response of RV_STOXX50 o Shock4 Response of CV_STOXX50 o Shock1 Response of CV_STOXX50 o Shock2 Response of CV_STOXX50 o Shock3 Response of CV_STOXX50 o Shock4 Noe: Shock 1 refers o he supply-side shock (PROD), Shock 2 refers o he aggregae demand shock (GEA), Shock 3 refers o he oil specific demand shock (OP) and Shock 4 refers o he volailiy shock (VOL). 31