Impacts Of Ramadan On European Islamic Finance Stock Volatility Based On EGARCH-M Model And Empirical Analysis Of EIIB Stock Luyao Zhu

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Inernaional Conference on Maerials Engineering and Informaion Technology Applicaions (MEITA 2015) Impacs Of Ramadan On European Islamic Finance Sock Volailiy Based On EGARCH-M Model And Empirical Analysis Of EIIB Sock Luyao Zhu No.27, Fuxue Sree, Changping Disric, Beijing, China luyao.z@homail.com Keywords: Islamic finance sock, ramadan EGARCH-M model, volailiy Absrac. The hesis firsly inroduces he feaures of Ramadan and Islamic Finance and GARCH model. Then i analyzes he EIIB sock, he represenaive of Islamic Finance sock via EGARCH-M model, which is applied o daa fiing and forecasing, and illusraes he economics meaning of he model. Finally, i comes o a conclusion ha Ramadan has a posiive influence on he volailiy of EIIB sock as well as a negaive effec on he reurns of i and pu forward suggesions on research and pracice. Inroducion Afer he 2001 "9.11" inciden, he Islamic finance increase rapidly. Today, here are more han 300 financial insiuions and more han 300 rus "in line wih Sharia", which is over 75 Islamic and non-islamic counries. Briain is he firs Wesern counries o issue sovereign sukuk. Meanwhile, he European Islamic Invesmen Bank (EIIB) as he firs in he UK "in line wih Shariah invesmen" owned bank, has represenaive and unique significance in he Islamic finance indusry in Europe. Thus we wan o sar from he sock price volailiy EIIB, o explore he impac of Ramadan o he European Islamic finance-relaed sock price volailiy. Reference Review Efficien marke heory holds ha i is impossible o achieve using he available informaion on marke rends forecas. Bu numerous sudies show ha he volailiy of reurns o some exen can be predicable, volailiy forecass for invesors can deermine marke risk siuaion, hus i is imporan o have effecively asse pricing, develop rading sraegies, consruc porfolio and conrol risk. In recen years, people are keen o use he GARCH model o sudy he sock price, swings and even index fuures sock. Bu also reflecs is effeciveness. Be he firs o volailiy modeling and provide a framework model is ARCH model Engle (1982) raised. Bollerslev (1986) presens a useful exended form, called generalized ARCH model (GARCH). GARCH Models have a reduced number of parameers, he weak condiion o achieve posiive definie advanage. Akgiray relaively use GARCH model and ARCH model o predic he volailiy of US sock early. Brooks and Persand use VaR (value a risk) model o sudy he asymmery index reurns of bad news and good news reacions. Nelson (1991) suggesed EGARCH model, using he assumpions GED disribuion and so on. Subsequen empirical sudy observed yields residuals may also have asymmeric effecs on yields, also known as leverage. When he marke was negaively affeced, condiional variance yields expanded, resuling in more volaile sock prices and yields; on he conrary, when he sock price rises, volailiy is reduced. Shares fell causes he Company's sock value drop, assuming consan corporae deb, he company's financial leverage increased, increase he risk of holding he sock. Therefore, he negaive impac of his effec on he condiional variance is also known as leverage (hp://baike.baidu.com/view/939517.hm?fr=aladdin). Glosen, Jagannahan and Runkel (1993) analyzed and compared various GARCH-M model, poining ou he differen seings will 2015. The auhors - Published by Alanis Press 262

cause ha he condiional variance models have differen posiive or negaive impac on profiabiliy. Volailiy on domesic and foreign research papers are more, using GARCH model is greaer, bu mos are applied o he Shanghai and Shenzhen 300 or SP500 research; a he same ime, a home and abroad, alhough covered on Islamic finance, bu more are ending simple analysis of heoreical exploraion, replicabiliy analogies and empirical daa, and did no focus on Islamic finance-relaed sock price volailiy. Therefore, his aricle will research mehods GARCH Models superioriy and unique perspecive of Islamic finance-relaed sock price volailiy conac, exploring he impac on Ramadan o he share price volailiy. Ramadan, Islamic Finance Overview Ramadan. Ramadan is one of Islam's five major religions of worship course. In Ramadan, he Arab counries are generally adjus working hours, mos of he UAE's working hours are 8:00 am o 2:00 pm, Saudi provisions 10:00 am beginning o work. Lower operaional efficiency of governmen agencies, bu also a corresponding reducion in he aciviies of businessmen, Arab business aciviies carried ou in he evenings. People during Ramadan due o he low efficiency of he Gulf Arab saes during he day, ofen canno find people, so for business visis and business negoiaions, hey usually ry o avoid Ramadan o visi. Islamic Finance. The main principles of Islamic Finance: (1) prohibiing he collecion and paymen of ineres. (2) prohibiing he rading of uncerainy. (3) profi and loss assessmen. (4) prohibiing speculaion. (5) in a lease way o have a profi. (6) "Hosni raha sysem" (meaning "mark-up"). (7) fee sysem. Because of characerisic of heir risk-sharing, speculaion-prohibiing, sress spiri of he conrac, Islamic finance-relaed socks in he sock marke has a more sable and considerable appeal. Especially since he US subprime morgage crisis riggered by he financial crisis spread, causing widespread concerns abou he global economic downurn, many invesors believe ha "Sharia compliance of financial operaions" is more reliable han he radiional financial secor. EGARCH-M model building Daa Acquisiion. This paper seleced EIIB closing price on May 17, 2006 o Ocober 31, 2014, a oal of 2197 observaions. We esablish he sequence {p}, and hen build is number of reurn series {r}, esablish condiional heeroskedasiciy models for he sequence {r}, and o sudy he volailiy of is earnings. [Daa from Yahoo finance!] Here, he logarihmic rae of reurn expressed as: P r = ln P 1 Among hem, is closing price, is he previous day's closing price. Afer he uni roo es, logarihmic yields sequence {r} proves sabiliy. ARCH Effec Tes. Logarihmically wih Eviews7.2 sequence {r} reurn auocorrelaion and parial auocorrelaion analysis o deermine is lag order is 1. Therefore, he esablishmen of AR (1) model is as follows. r = 0.295607r 1 + a Among hem, is year logarihm reurns, is one-year lag ha is he number of he previous year o yield, is Residuals. Sric ARCH-LM es, he resuls shows he exisence of a sequence of squared residuals order auocorrelaion, ha model error sequence is presen auoregressive condiional heeroskedasiciy, i.e. ARCH effecs. Thus in he applicabiliy of he model, i is suiable for using GARCH Models. 263

EGARCH-M Modeling Basic Srucure Of The Model. Since EIIB sock logarihmic reurn series {r} is no normal, so in rying o esablish he GARCH model of he process, he selecion of he GED disribuion assumpions. Esablish EGARCH-M model wih Eviews7.2, resuls are as follows: 5 2 r = 2.73 10 0.000741r 1 + 0.011449σ 0. 001388µ + a a 2 1 a 1 2 ln( σ ) = 5.012066 + 1.052616 0.093410 + 0.170065( σ 1 ) + 3.264591u σ 1 σ 1 0.93410 r = = 0.088740813, a = σ ε 1.052616 0, doesn' belong o Ramadan u = 1, Ramadan Among hem, is on behalf of he number of shares on he dae of reurn; is on behalf of sock from he previous day he logarihmic rae of reurn; represens he number of shares he day before he sock o reurn residuals; represens he number of shares on he dae of reurn volailiy, he variance; is he auhor added, "dummy variables"; represens he leverage effec of, he resul is negaive, in line wih our requiremens in he pracical applicaion. Model Inerpreaion. The model is acually a combinaion of EGARCH, GARCH-M, AR model and he "dummy". Firs, he model characerisics have EGARCH model, reflecing leverage on he number of reurn series. Obviously, he condiional variance equaion can be seen, he negaive effec of he disurbance caused by he flucuaion conribuion o exceed he posiive conribuion of he disurbance caused by he effec of flucuaion, and he whole idea ha economics is consisen confidence. Then, he model has he characerisics of GARCH-M model, so in line wih he financial secor depends in par on he yield volailiy (i.e. risk) of he heoreical framework. The heoreical framework is consisen wih he CAPM. While ha he coefficien is posiive is a proof of he benefis and risks of a posiive correlaion beween heoreical ideas. In addiion, he model has he characerisics of AR model. Model number reflecs he day o yield no only by he dae of he impac of new informaion, bu also by he number of he previous day on yields. In addiion, he "dummy variable" is a variable we se manually when building he model. When he ime when he agreemen is locaed in he holy monh of Ramadan, X, when ime is no locaed wihin he monh of Ramadan, Y. A he same ime, from he model mean equaion can be seen, when in he monh of Ramadan, he log will yield, he negaive impac from he condiional variance equaion can be seen, when he ime in he monh of Ramadan, will yield volailiy bring posiive impac. Tha is, when he ime is locaed in Ramadan, he logarihmic sock reurns will be reduced, while he volailiy of he sock price increases. Assessmen of Model s Finess. All models have passed he confidence coefficien of 1% of he z es, so fiing of he model is very srong. From he predicion model can be seen from Figure 1, he model is well refleced in he volailiy and "seasonal" effec on he number of he yield curve, and is bounded flucuaions. In addiion, ARCH-LM es for new model residuals shows ha he 264

new model doesn have auoregressive condiional heeroskedasiciy, which mees he previous saisical assumpions. 1.2 0.8 0.4 0.0-0.4-0.8-1.2 06 07 08 09 10 11 12 13 14 Forecas: RF Acual: R Forecas sample: 5/17/2006 10/31/2014 Adjused sample: 5/18/2006 10/30/2014 Included observaions: 2195 Roo Mean Squared Error 0.047330 Mean Absolue Error 0.024421 Mean Abs. Percen Error 58.84071 Theil Inequaliy Coefficien 0.985698 Bias Proporion 0.000355 Variance Proporion 0.971068 Covariance Proporion 0.028577 RF?2 S.E..4.3.2.1.0 06 07 08 09 10 11 12 13 14 Forecas of Variance Figure 1 Forecas of he Model Meaning Of The Model. As can be seen from he model, Ramadan is no only affeced he number of sock reurns, bu also affec he volailiy of he sock. And his effec is of pracical significance from mahemaical logic and meaning from he perspecive of economics. According o he auhor of he analysis, Ramadan will come roughly from shareholders, managemen and cusomers have an impac yields and volailiy of he bank. Consider he shareholder level. Afer verificaion of he European Islamic Invesmen Bank shareholder srucure, he bank's main shareholder is he Gulf counry's financial insiuions and individuals, in paricular sugges ha hese people are mainly relaed o Islamic financial insiuions and individuals, and hese are he Islamic Gulf counries. Therefore, i is considered a componen of shareholders EIIB bank inside a large proporion of Muslims. Since he bank is sric compliance wih he Shariah provision, so all ransacions, which performs producion aciviies are in line wih Islamic ransacion, which is ha i aracs a large number of Muslims handle he relevan business, he reason o buy is sock. From he foregoing descripion of he aciviies of Muslims in Ramadan characerisics shows ha he aciviies of hese shareholders in he monh of Ramadan will have impac on he bank equiies, he usual appearance will decline in rading volume. From he perspecive of managemen and saff, EIIB has special Shariah direcors, and he appoinmen of managers a all levels is also sricly abided by he eachings of Islam. A he same ime, here are more saff members as Muslims. So Ramadan aciviies will affec he daily work of hese groups, which affecs he amoun of he company's daily business. From he cusomer level, he bank's cusomer is a large proporion of Muslim populaion. Since is operaion operaes in line wih he eachings of Islam, while oher banks financial services canno mee he needs of Muslims. So, Ramadan aciviies will affec he business aciviies of Muslim cusomers, while also affecing he business volume of he bank. Because he amoun of banking will affec banks hus affecing he inrinsic value and is sock 265

price flucuaions, bu also affec he sale of operaions shareholders flucuaions in sock prices. Thus from an economic poin of view o explain he significance of he model is o have relevance. Conclusions Model resuls shows ha Ramadan will have a negaive direcion influence on EIIB sock logarihm reurns, and would have a posiive direcion influence on volailiy of sock price. Tha is, in he monh of Ramadan, he logarihmic yields EIIB significanly reduced, and he sock price volailiy is significanly larger. This effec is more inense, causing sock prices have a "seasonal" flucuaions. In addiion o a glimpse of he volailiy of he sock price of Len cusoms aciviies on his special, we can also see he posiive marke disurbances and perurbaions negaive effec on he sock price volailiy is differen. This is consisen wih he "leverage effec" seing. Sock reurns no only by he influence of Len, while also subjec o he yield on he impac and influence of he curren volailiy. Especially he laer, reflecing he risk and reurn was a posiive correlaion, bu also mee he heoreical framework of he CAPM. Also can be seen, for Islamic finance-relaed sock marke, i also can accuraely reflec he marke informaion. For he above conclusions, we can have he following recommendaions: Firs, because Ramadan is one of hree major fesivals of Islam, wih a long and sric cusoms consrain, hus affecing Ramadan Islamic finance-relaed shares will be "seasonal" and appears o be sable. In view of his siuaion, in he sudy of volailiy and he yield of Islamic finance-relaed shares, we should no ignore his pariculariy. I is also for he invesors who end o inves in he field of Islamic finance o have brough a more cauious and argeed suggesive. Secondly, because in he Islamic financial equiy markes, risk and reurn are posiively relaed, and empirical sudies have proved more effecive in his marke. Thus in erms of invesmen in Islamic financial socks, we should consider he effeciveness of is own operaions and he soundness of he marke. If you choose o speculaive invesmen seems o be raher irraional. Finally, in he direcion of invesmen wih he Islamic finance-relaed socks, we have o be vigilan Len brings is "leverage." When he negaive marke disurbances produce, share price decline, causing he sock decline in value. In he amoun of deb he same premise, he company's leverage increases, which makes venure capial becomes higher. References [1] Moin Siddiqi: Islamic Banking, Middle Eas, November 2008, p.36. [2] Islamic Finance: Global Trends and Challenges, NBR ANALYSIS, Volume 18, Number 4, March 2008, p.3. [3] Moin Siddiqi: Islamic Banking, Middle Eas, November 2008, p.35. [4]Shuangqing Chen: "Islamic finance indusry and is developmen characerisics" [J], "Inernaional daa and informaion", 2009 (06) [5]Quan jiang, Meng Liu: "HS300 index reurn volailiy and VaR Merics" [J], "financial economy", 2008 (08): 87-89 [6]Dehua Chen, Jianmin Shi: "China's sock marke volailiy risk predicion: A Comparaive Sudy on he Shanghai and Shenzhen 300 Index" [J], "produciviy sudies", 2009 (4): 36-38 [7]Ping-Tsung Wu, Shwu Jane Shieh: Value - a - Risk analysis for long - erm ineres rae fuures: Fa- ail and long memory in reurn innovaions [J].Journal of Empirical Finance, 2007,14: p.248-259. [8]Xiao Liu, Yimin Li: "GARCH family model in he sock marke: The Shenzhen Componen 266

Index on volailiy " [J], "Technology Economics and Managemen Research", 2005 (05): 36-38 [9]Liping An, Bo Wang, Xidong Shen : "GARCH family model based on he Shanghai and Shenzhen sock VaR measure" [J], "Mahemaical Theory and Applicaions", 2014 (02): 94-102 [10]Jinwen Zhao: "Simulaion of GARCH Models SSE 180 Index on: indirec empirical modeling of he Shanghai 300 Index Analysis" [J], "Finance and Economics Research", 2008 (03): 48-54 [11]Rui Gong, Dongrui Yang: "GARCH Family Model Chinese Sock Marke Value a Risk: A Comparaive Sudy and Review VaR risk" [J], "Quaniaive and Technical Economics Research", 2005 (07): 68-81 [12] Libing Fang, Bingkun Guo,Yong Zeng : "abiliy o predic he GARCH model is relaively a semi-parameric mehod" [J], "Quaniaive and Technical Economics Research", 2010 (04): 148-160 [13]Xuhui Ding,Xinyu Gao, Kaikai Yang: "The inernaional gold price volailiy and Risk Prevenion Research: An Empirical Analysis of he GARCH model" [J], 2014 (07): 72-74 267